when a problem solving team includes a closed minded

Klaus Vedfelt/Getty Images

By Vanessa Leikvoll Leaders Staff

Vanessa Leikvoll

Culture and Personal Success Writer

Vanessa Leikvoll is a culture and personal success writer for Leaders Media. Vanessa is a certified Workplace Wellness Specialist and...

Learn about our editorial policy

Jul 6, 2023

Reviewed by Hannah L. Miller

Hannah L. Miller

Senior Editor

Hannah L. Miller, MA, is the senior editor for Leaders Media. Since graduating with her Master of Arts in 2015,...

Signs Someone Is Closed-Minded and 4 Ways to Handle It

What does it mean to be closed-minded, where do a person’s beliefs come from, closed-mindedness in interpersonal relationships, a closed-minded person vs. an open-minded person, 5 signs of a closed-minded person, how to deal with closed-minded people, closed minds have closed vision.

Imagine the company you work for is losing money—and fast. If a solution doesn’t present itself soon, you will all be out of a job. You know that there are new, innovative solutions that would reverse the loss, but upper-level executives are resistant to new processes. So resistant, in fact, that they won’t even hear your ideas out.  

The executives in this scenario are an example of closed-minded people you might encounter, including family, friends, or professional colleagues. Whether it’s upper-level management resistant to change, a business partner reluctant to take risks, or even a defensive spouse with strong views, dealing with closed-minded people can be a challenge. 

Failure to consider new ideas, avoid constructive dialogue, and protect one’s beliefs despite all opposing evidence stunts a person’s growth and hinders others’ ability to connect with them. As a result, studies show that closed-minded people also lead less happy lives.

Discover if someone you know is a closed-minded person by exploring the characteristics of closed-mindedness and strategies for opening the mind to new possibilities.

Key Takeaways

• Closed-mindedness is a byproduct of deep-seated cognitive biases and beliefs.
• Childhood experiences, social environments, media, and formal education are some sources of core beliefs.
• Open-mindedness is associated with greater life satisfaction and coping abilities.
• Research has linked curiosity with higher levels of positive emotions.
• Open-mindedness can be cultivated by practicing self-awareness, empathy, and seeking diverse perspectives.

Being closed-minded means having a rigid or inflexible belief system that resists new ideas, perspectives, or information. It’s characterized by an unwillingness to consider alternative viewpoints, a lack of openness to new experiences, and a tendency to adhere strictly to preconceived notions or biases. 

While an open-minded person will embrace new viewpoints regardless of existing beliefs, closed-minded people will reject evidence that doesn’t support their beliefs . Closed-minded individuals often also exhibit a reluctance to engage in constructive conversation with others, preferring instead to maintain their established viewpoints, regardless of any evidence that challenges them.

As Paul Sloane, author and business consultant, shares to a TEDx audience: “ Everyone thinks they’re open-minded . . . but in fact, we’re all mental prisoners of our beliefs and assumptions. And they construct our mindset. And psychologists tell us we’re not particularly open-minded.”

“Our core beliefs need to be seen for what they are: deeply held assumptions about reality that our particular life circumstances have conditioned us to accept as absolute truth.” Ezra Bayda

Core beliefs are a person’s deeply held assumptions about life, regardless of their truth. These beliefs can be negative, such as believing “the world is an unforgiving place” or “money is hard to make.” They can also be positive, such as believing “I am supported” and “everything is within reach.”

Many factors contribute to the formation of a person’s core beliefs. These factors can include early childhood experiences, social or environmental factors, cultural influences, and personal interpretations of events. 

These are the primary sources of a person’s core beliefs:

• Early Childhood Experiences: The early years of life are crucial in shaping core beliefs. Interactions with parents, caregivers, and family members play a significant role. Children form beliefs about themselves, others, and the world based on how they are treated and the messages they receive during this developmental stage.
• Social Environment: Peers, friends, teachers, and other significant figures in a person’s life contribute to the formation of core beliefs. Social interactions shape their perspectives, values, and attitudes. For example, a person growing up in a supportive and nurturing environment will harbor greater beliefs of their own worthiness and the trustworthiness of others.
• Cultural and Societal Influences: The cultural and societal context in which a person grows up greatly influences their core beliefs. Cultural norms, values, traditions, and societal expectations play a role in shaping perspectives on topics such as family, gender roles, religion, education, and success. 
• Personal Interpretations: People assign meaning to situations based on their own cognitive processes, beliefs, and prior experiences, forming new core beliefs. For example, two people facing the same challenging event may interpret it differently, leading to distinct core beliefs.
• Traumatic Experiences: Traumatic events, such as abuse, neglect, or significant losses, can have a profound impact on core beliefs. Trauma can distort perceptions, create negative self-beliefs, and influence one’s worldview. These core beliefs may persist into adulthood unless reevaluated through therapeutic interventions.
• Education and Learning: Formal education and exposure to different ideas and perspectives can broaden one’s mindset and influence core beliefs. Education encourages critical thinking, challenges existing beliefs, and provides new information that may shape a person’s values and perspectives.
• Media and Technology: Media, including television, movies, books, and the internet, can shape core beliefs by providing information, promoting certain values, and shaping societal narratives. Media exposure can contribute to the formation of beliefs about beauty, relationships, success, and societal issues.

The outcome of events experienced or promoted beliefs will form a deep-seated association that a person will, unless challenged, carry with them throughout their lives. Closed-mindedness is a byproduct of these learned and collected beliefs. Closed-mindedness may be a common human tendency, but it’s fortunately not fixed or permanent. Through self-awareness, cognitive flexibility, and a willingness to challenge one’s own beliefs, individuals can cultivate open-mindedness gradually.

To learn more about unconscious bias, read Scale Up to 70% by Beating These 22 Unconscious Biases.  

Closed-mindedness can hinder effective communication and understanding between individuals. This is because people who are closed-minded may struggle to empathize with others, dismissing differing opinions without giving them due consideration. This can lead to workplace conflict, strained relationships, and a breakdown in collaboration.

As Andrea Mathews, LPC, explains in Psychology Today, “The open-minded person is willing to explore his own mind and even find that he’s been wrong about something and self-correct. The closed-minded person is unwilling to do this. Being wrong is simply not safe . . . for this reason, trying to talk to the closed-minded person out of a closed mind is not likely to succeed.”

“If your only tool is a hammer, all your problems will be nails.” Rolf Dobelli

Spotting a closed-minded person can be relatively easy, but the extent to which they differ from an open-minded person may be less known. While a closed-minded person struggles to understand and consider things outside of their internal belief system, an open-minded person embraces that contrast. Open-minded people possess certain qualities and attitudes that allow them to approach new ideas, perspectives, and experiences, unhindered by rigid limiting beliefs .

Qualities of an Open-Minded Person

• They’re Willing to Consider Alternative Viewpoints: An open-minded person is willing to consider and explore alternative viewpoints, even if they differ from their own. They are receptive to new ideas and actively seek diverse perspectives to broaden their understanding.
• They Embrace Critical Thinking: Open-minded individuals engage in critical thinking, objectively evaluating information and considering evidence from different sources. They are open to questioning their own beliefs and adjusting them based on compelling evidence.
• Intellectual Curiosity Comes Naturally: Open-mindedness is accompanied by intellectual curiosity. Open-minded individuals have a genuine desire to learn, explore, and expand their knowledge. They are open to new experiences and actively seek opportunities for personal and intellectual growth.
• They’re Flexible and Adaptable: Open-minded people demonstrate flexibility and adaptability in their thinking. They are more willing to adjust their beliefs and opinions based on new information or compelling arguments. They embrace change and are open to revising their perspectives as needed.
• They Appreciate Diverse Perspectives: Open-minded individuals appreciate and respect diverse perspectives, recognizing that different viewpoints can enrich their understanding of the world. They actively seek out and value diverse cultural, social, and intellectual experiences.

“Some of it’s a technical problem. People don’t like it when you force them to think at high resolution.” Jordan Peterson

It can be difficult to know if someone is truly closed-minded or if they are just stubborn. To help tell the difference, here are five telltale signs to compare against. 

1. They’re Resistant to New Ideas

A closed-minded person is resistant to new ideas or information that challenge their existing beliefs. They’re less willing to explore alternative viewpoints and may dismiss them without thoughtful consideration.

Example: You present your manager with a new workflow platform to better connect remote employees, but without even reviewing it, they say it won’t work.

Solution: Before presenting new ideas to someone who is closed-minded, ask them to keep an open mind and have strong evidence prepared to support your idea.

2. They Have a Limited Perspective

Closed-minded individuals tend to rely on a narrow set of beliefs or information. They may be less receptive to diverse perspectives, experiences, or cultural differences.

Example: It’s difficult for your parents to understand and support your decision to become a digital nomad solopreneur because they both went to college and work traditional jobs.

Solution: Share examples, evidence, and insights about the new information, like how many solopreneurs there are and examples of some successful ones. 

3. Confirmation Bias Dictates Their Decisions

Closed-minded people selectively seek out information that confirms their existing beliefs and dismiss or ignore contradictory evidence. They may engage in motivated reasoning to justify their preconceived notions.

Example: Your colleague was raised in a strict and structured religious environment. Because of this, their input in casual, social dialogue tends to live in a vacuum, and they’re resistant when you share your thoughts outside of that vacuum. 

Solution: Use behavioral psychology to close the gap between their biased beliefs and yours. This can be done by first finding common ground and identifying a related belief that you both share, which will help inch them closer to understanding your point of view.

4. They Lack Curiosity

Closed-minded people generally exhibit a lack of curiosity and a reluctance to learn or explore new ideas. They may prefer sticking to familiar concepts and avoid venturing into unfamiliar territory.

Example: A new restaurant just opened downtown. It’s getting rave reviews and generating a lot of buzz in the community. You want to check it out, but your friend refuses to go with you because they don’t like that particular cuisine. 

Solution: Ask them what kinds of foods and flavors they do like and highlight a few particular menu items that have them, along with some items that they’ve never tried.

5. Accepting Feedback Is Difficult

Closed-minded people often don’t know how to handle criticism . In fact, they may act defensively when their ideas or beliefs are challenged.

Example: You gently mention to your spouse that they tend to be forgetful with house chores. Instead of acknowledging this, they become angry and deflect, accusing you of being the forgetful one. 

Solution: Rather than becoming upset by this person’s response, calmly present evidence supporting your statement and allow the person to respond uninterruptedly. Listen carefully both to what they say and don’t say

“The hallmark of successful people is that they are always stretching themselves to learn new things.” Carol S. Dweck

Embracing challenges, accepting mistakes, and considering new ideas are all part of what psychologist and author Carol Dweck calls having a growth mindset . In fact, Dweck says that not only are these factors necessary for personal advancement, but they impact one’s mental health and relationships. 

A 2022 study on college students, published in Frontiers in Psychology, supports this, concluding that “individuals with a growth mindset demonstrated better life perception ability than those with a fixed mindset,” and that “ the growth mindset group may have more positive coping strategies, and therefore might have better mental health.” 

Except, not everyone is open-minded in this way, and dealing with a closed-minded person can be challenging. Fortunately, you can follow a few tips to make a closed-minded interaction more effective.

Here are some strategies for dealing with a closed-minded person:

1. Remain Calm Despite Resistance

Remaining calm and composed is important when interacting with a closed-minded individual. Getting emotional or confrontational may escalate the situation and make it harder to find common ground. 

Cultivating self-awareness, a critical component of emotional intelligence , can be a good way of ensuring one’s composure if a conversation with a closed-minded person isn’t going as hoped. 

Things to remember when interacting with a closed-minded person:

• You’re allowed to disagree.
• Some conversations aren’t worth pursuing further.
• It’s better to maintain neutrality by avoiding “you” statements.
• It’s okay to honor your boundaries and uphold your standards.

For a practical tool to aid self-awareness, read Using the Emotion Wheel to Enhance Emotional Intelligence .  

2. Be Curious and Try to Understand Their Perspective

As Todd B. Kashdan says in Curious? Discover the Missing Ingredient to a Fulfilling Life , “When we are open to new possibilites, we find them. Be open and skeptical of everything.”

Engaging in conversations with people from different backgrounds and with different viewpoints is a tremendous way to expand both your perspective and someone else’s. According to the Hult International Business School , the presence of diverse perspectives inspires creativity, drives innovation, improves marketing efforts, and helps teams and individuals be more productive.

A person can facilitate new perspectives by trying to understand why the person holds their beliefs or opinions. Do this by asking them questions, listening carefully, and embracing what they say. This can help open an opportunity for more effective dialogue.

How to better understand their perspective:

• Ask open-ended questions like, “Why do you believe that?”
• Be open and adaptable if what they are saying has merit.
• Invite feedback from them.
• Be willing to implement any sound ideas.

For more tips on improving communication, read How to Practice Effective Interpersonal Communication.

3. Bridge the Gap by Finding Common Ground 

Identifying common ground can be a starting point for building a bridge between differing perspectives and leveling the playing field. If you’re engaging with a closed-minded person, look for areas of agreement or shared values. Doing so could reveal more shared beliefs than previously thought.

Tips for finding common ground:

• Practice active listening . 
• Tell the person you want to find common ground.
• Let them know how you feel about the conflict.
• Ask them if they would also like to find common ground.
• Recognize and accept each other’s different perspectives.
• Ask open-ended questions on topics of mutual interest without judgment.

4. Cultivate Empathy by Sharing Personal Experiences

As author Brené Brown says, “Empathy fuels connection. Sympathy drives disconnection.” Sharing personal stories or experiences that relate to the other person can be a powerful way to cultivate empathy and convey your point of view. It humanizes the discussion and helps the closed-minded person disarm and relate to you on an emotional level. This, in turn, fuels more open-minded dialogue.

Tips for communicating with greater empathy:

• Harness the power of vulnerability by sharing your personal experiences.
• Acknowledge the challenge, conflict, or concern being discussed.
• Validate how the closed-minded person feels about the challenge.
• Communicate your thoughts and stories simply, clearly, and with transparency.

“You begin to fly when you let go of self-limiting beliefs and allow your mind and aspirations to rise to greater heights.” Brian Tracy

When Spanx CEO and founder Sara Blakely imagined appearing on The Oprah Winfrey Show , she knew how powerful the mind is. She kept visualizing this event, knowing that it would be the moment that would change her business and life. With this belief and vision, Blakely didn’t stop until it became a reality. This proves that learning how to manifest something requires a distinct vision and an open mind that considers new pathways, opportunities, and places to pivot.   

Resources for nurturing vision:

• Browse vision board ideas for putting your vision down on paper.
• Read Think Again: The Power of Knowing What You Don’t Know by Adam Grant.
• Read Wise Mind, Open Mind by Ronald Alexander.

Continue embracing new possibilities and achieving transformation by reading 8 Visualization Strategies That Make Your Goals a Reality . 

Leaders Media has established sourcing guidelines and relies on relevant, and credible sources for the data, facts, and expert insights and analysis we reference. You can learn more about our mission, ethics, and how we cite sources in our editorial policy .

• Antinori, Anna. “Seeing It Both Ways: Openness to Experience and Binocular Rivalry Suppression.” Journal of Research in Personality , vol. 68, June 2017, pp. 15–22, https://www.sciencedirect.com/science/article/pii/S0092656617300338 .
• “Are You Open-Minded? Three Ways to Break Thinking Patterns | Paul Sloane | TEDxUniversityofBrighton.” YouTube , 19 Apr. 2016, https://www.youtube.com/watch?v=4vgl3v8rjj8 .
• Andrea Mathews, LPC. “The Closed Mind.” Psychology Today , 1 May 2023, https://www.psychologytoday.com/us/blog/traversing-the-inner-terrain/201907/the-closed-mind .
• Serrano-Ripoll, Maria. “The Influence of Growth Mindset on the Mental Health and Life Events of College Students.” Frontiers , 24 Nov. 2021, https://www.frontiersin.org/articles/10.3389/fpsyg.2022.821206/full .
• Reynolds, Katie. “13 Benefits and Challenges of Cultural Diversity in the Workplace | Hult International Business School.” Hult International Business School , 17 Jan. 2019, https://www.hult.edu/blog/benefits-challenges-cultural-diversity-workplace/ .
• Kashdan, Todd B. “Curiosity and Exploration: Facilitating Positive Subjective Experiences and Personal Growth Opportunities.” Journal of Personality Assessment , vol. 82, no. 3, 2004, https://www.tandfonline.com/doi/abs/10.1207/s15327752jpa8203_05#.Vbu4EWTF8m8 .

Search Leaders.com

Quantum Transformation Lab

Closed Mindset: What it is and How to Overcome It

Closed mindset refers to an individual’s unwillingness to consider new information or perspectives. People with a closed mindset are typically resistant to change and unwilling to develop their beliefs or ideas beyond what they already know. They tend to reject or ignore any input that is contrary to their existing thinking and can become overly defensive or hostile when presented with new facts or alternative perspectives. Those with this mindset may also struggle to engage in meaningful dialogue, as they are unable to accept that there may be more valid approaches than the ones they have adopted thus far.

Table Of Contents

Defining Closed Mindset

A closed mindset is an inflexible outlook on life that involves believing that one’s beliefs and opinions are superior to others. This type of thinking is typically characterized by an unwillingness to consider alternatives or different perspectives, a rigid adherence to predetermined ideas, and a refusal to engage with new information when it conflicts with existing beliefs. Those with a closed mindset exhibit an intolerance for other points of view, ignore evidence that does not fit their belief system, and often become defensive when presented with conflicting facts.

Cognitively speaking, those with a closed mindset have no appetite for learning or considering other perspectives. They assume that they know enough and can thus be uninterested in furthering their knowledge base. To them, there is only one right answer, and any other opinion is wrong. This leads them to reject any new ideas or possibilities without giving them due consideration.

Recognizing Signs of a Closed Mindset

Rejecting new ideas and possibilities.

The hallmark of a closed-minded individual is the rejection of new ideas and possibilities. Those with this mindset may refuse to entertain new concepts even if these are supported by scientific evidence or developed through logic. Instead, they focus exclusively on what they already know while disregarding any novel input in order to maintain a sense of certainty.

On the other hand, those who are open-minded understand that even if they possess extensive knowledge, there is still much more to learn. They accept that novelty exists and can be beneficial, so they are willing to explore unfamiliar concepts or take risks in order to expand their understanding.

Refusing to Consider Different Perspectives

The trademark sign of a closed-minded individual is the lack of interest in looking at things from different angles. Such people often get stuck in their own narrow views on life and completely disregard alternative approaches even when those have been proven effective.

In contrast, an open-minded person recognizes that although their view on the world might be valid, it does not constitute the definitive truth as there could be multiple interpretations depending on different contexts. Therefore, such individuals are willing to look at every situation from multiple angles before making conclusions.

Believing There Is Only One Right Answer

The confirmation bias, meaning paying more attention to information which confirms our existing beliefs while discounting anything else that challenges those beliefs can often feed into this kind of rigidity in thinking styles. Those who are stuck in this loop will not let go of their pre-existing ideas easily nor show willingness towards exploring alternatives.

On the contrary, people with an open mindset inherently accept that nothing is absolute nor fixed; rather that truth can exist in multiple forms simultaneously depending on various external factors. As such, they strive to develop mental flexibility by stepping outside higher level categories and appreciating nuance.

The Advantages of an Open Mindset

Adaptability.

Individuals who are willing to consider different perspectives and view points tend to be more adaptive than those who have a rigid attitude. Those with an open-minded approach have the ability to adjust better in different situations.

People who are open to new ideas and experiences have greater flexibility than those who remain stuck in their ways. Being closed-minded can limit our adaptability in life.

Having an open mind helps us to look at unfamiliar situations objectively. We can pay close attention to different views and opinions, taking them into consideration when making decisions or creating plans.

Innovation is key to overcoming a closed mindset and embracing the power of an open one. To spark creativity and generate new ideas, it’s important to think beyond boundaries and explore what lies in the unknown. Acknowledge different perspectives, challenge beliefs, and learn from diverse cultures to open up your world of possibilities – that’s true innovation!

Problem-Solving Skills

Having a closed mindset can sometimes stifle problem-solving skills. To overcome it, try to adapt an open mindset that promotes curiosity, creativity, and resilience. By recognizing and actively engaging with differing perspectives, you increase your chances of figuring out solutions to complex problems. An open mindset also helps build more trust with others, encourages collaboration, and allows you to be more comfortable taking risks without fear of failure.

Overcoming Challenges to Achieving an Open Mindset

Dealing with fear of change.

One of the biggest challenges to achieving an open mindset is dealing with fear of change. It requires a certain level of courage and mental strength to overcome doubts, accept that things may not go the way you expect, and embrace the unfamiliar. Once you’ve challenged your own beliefs, be prepared to adjust or reject them in favour of more accurate or beneficial perspectives.

Developing strategies for managing fear can be beneficial in keeping an open mind. This could include practising mindfulness meditation, breaking tasks into smaller steps, setting realistic goals and taking constructive feedback as a learning opportunity. By gradually increasing your exposure to different opinions and ideas, you will become less apprehensive when dealing with uncertainty.

Gathering the Willpower to Grow

Having an open mindset means having the willpower to grow. Embracing new experiences can help us develop our knowledge and understanding of different perspectives. To do this effectively, we must take responsibility for our own learning and actively seek out opportunities that provide insight into other cultures and lifestyles.

It’s important to practice self-care while engaging in activities outside your comfort zone. Take timeouts when needed and focus on connecting with yourself by reflecting on what has been learned during these experiences. Make sure to surround yourself with supportive people who will encourage you on this journey towards personal development.

Developing an Open Mindset

Practicing self-reflection.

In order to keep an open mind, it’s important to practice self-reflection regularly. Take some time each day or week to pause and reflect on how your thoughts have evolved over time. Pay attention to any emotions or biases that influence your opinion about certain topics and acknowledge that it is possible for a variety of viewpoints to exist without either being right or wrong.

Self-reflection also involves understanding why certain opinions are held so strongly and looking at issues from multiple angles. Ask yourself constructive questions such as “What evidence do I have to back up my beliefs?” or “How might someone else see this situation differently?” It is only through openness that we are able to gain insight into our own thinking patterns.

Encouraging Diversity

Opening ourselves up to new perspectives requires exposing ourselves to diverse communities, experiences and cultures. Spend time talking with people who think differently than you do – whether online or in person – and learn about their views on various topics. Exchange ideas respectfully while listening intently without judgement.

Foster meaningful conversations rather than just arguing points – look for common ground so that everyone involved can grow in understanding each other’s perspectives. This kind of dialogue will eventually lead to increased acceptance of different opinions without feeling threatened by them.

Exploring Unfamiliar Perspectives

When trying to understand another person’s point of view, avoid jumping quickly into conclusions about what they’re saying – instead, ask further questions about their opinion in order to gain a better understanding. Instead of immediately writing off opposing thoughts, give them honest consideration before making decisions.

At times it may be difficult but try putting aside preconceived notions until all sides are fully explored. By doing this,you can uncover unique insights which would otherwise remain hidden. This approach will lead you down paths that you may never have gone down before, helping broaden your perspective.

A closed mindset can be an obstacle in developing meaningful conversations and relationships , as well as reaching greater understanding. Learning to move past this mindset can help one become more open-minded and embrace the variety of thoughts, ideas, and perspectives out there. It is key to recognize that having a closed mindset may limit our growth and hinder our potential. It helps to look at each new idea or perspective with an open mind and act with respect – rather than react defensively – when presented with something contrary to what we are used to.

Recognizing when you have a closed mindset and striving to overcome it is essential for personal and professional development. This can be a difficult but achievable goal through consistent effort, self-awareness, and open thought. While it can be easy to get stuck in a certain way of thinking, choosing instead to take on a more flexible outlook is beneficial for both yourself and those around you. With time and dedication, a closed mindset is no longer an obstacle but instead a chance for growth .

You may also be interested in reading:

• Discover the Benefits of Mindset Coaching: A Guide to Kickstart Positive Change!
• Transform Your Life: Unlock the Power of Mindset Mastery
• How To Overcome a Toxic Mindset
• Mindset Coaching: Overcome Mental Blocks and Reach Your Goals

• Privacy Overview
• Strictly Necessary Cookies

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

ORIGINAL RESEARCH article

Complex problem solving in teams: the impact of collective orientation on team process demands.

• Business Psychology, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high ( n = 58) or low ( n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies.

Introduction

Complex problems in organizational contexts are seldom solved by individuals. Generally, interdependently working teams of experts deal with complex problems ( Fiore et al., 2010 ), which are characterized by element interactivity/ interconnectedness, dynamic developments, non-transparency and multiple, and/or conflicting goals ( Dörner et al., 1983 ; Brehmer, 1992 ; Funke, 1995 ). Complex problem solving “takes place for reducing the barrier between a given start state and an intended goal state with the help of cognitive activities and behavior. Start state, intended goal state, and barriers prove complexity, change dynamically over time, and can be partially intransparent” ( Funke, 2012 , p. 682). Teams dealing with complex problems in interdependent work contexts, for example in disaster, crisis or accident management, are called High Responsibility Teams. They are named High Responsibility Teams (HRTs; Hagemann, 2011 ; Hagemann et al., 2011 ) due to their dynamic and often unpredictable working conditions and demanding work contexts, in which technical faults and slips have severe consequences for human beings and the environment if they are not identified and resolved within the team immediately ( Kluge et al., 2009 ). HRTs bear responsibility regarding lives of third parties and their own lives based on their actions and consequences.

The context of interdependently working HRTs, dealing with complex problems, is described as follows ( Zsambok, 1997 ): Members of interdependently working teams have to reach ill-defined or competing goals in common in poor structured, non-transparent and dynamically changing situations under the consideration of rules of engagement and based on several cycles of joint action. Some or all goals are critical in terms of time and the consequences of actions result in decision-based outcomes with high importance for the culture (e.g., human life). In HRT contexts, added to the features of the complexity of the problem, is the complexity of relationships, which is called social complexity ( Dörner, 1989/2003 ) or crew coordination complexity ( Kluge, 2014 ), which results from the interconnectedness between multiple agents through coordination requirements. The dynamic control aspect of the continuous process is coupled with the need to coordinate multiple highly interactive processes imposing high coordination demands ( Roth and Woods, 1988 ; Waller et al., 2004 ; Hagemann et al., 2012 ).

Within this article, it is important to us to describe the theoretical background of complex problem solving in teams in depth and to combine different but compatible theoretical approaches, in order to demonstrate their theoretical and practical use in the context of the analysis of complex problem solving in teams. In Industrial and Organizational Psychology, a detailed description of tasks and work contexts that are in the focus of the analysis is essential. The individual or team task is the point of intersection between organization and individual as a “psychologically most relevant part” of the working conditions ( Ulich, 1995 ). Thus, the tasks and the teamwork context of teams that deal with complex problems is of high relevance in the present paper. We will comprehensively describe the context of complex problem solving in teams by introducing a model of an idealized teamwork process that complex problem solving teams pass through and extensively integrate the relevant teamwork skills for these interdependently working teams into the idealized teamwork process model.

Furthermore, we will highlight the episodic aspect concerning complex problem solving in teams and combine the agreed on transition, action, interpersonal and learning processes of teamwork with the idealized teamwork process model. Because we are interested in investigating teamwork competencies and action processes of complex problem solving teams, we will analyze the indirect effect of collective orientation on team performance through the teams' coordination behavior. The focusing of the study will be owed to its validity. Even though that we know that more aspects of the theoretical framework might be of interest and could be analyzed, we will focus on a detail within the laboratory experiment for getting reliable and valid results.

Goal, Task, and Outcome Interdependence in Teamwork

Concerning interdependence, teamwork research focuses on three designated features, which are in accordance with general process models of human action ( Hertel et al., 2004 ). One type is goal interdependence, which refers to the degree to which teams have distinct goals as well as a linkage between individual members and team goals ( Campion et al., 1993 ; Wageman, 1995 ). A second type is task interdependence, which refers to the interaction between team members. The team members depend on each other for work accomplishment, and the actions of one member have strong implications for the work process of all members ( Shea and Guzzo, 1987 ; Campion et al., 1993 ; Hertel et al., 2004 ). The third type is outcome interdependence, which is defined as the extent to which one team member's outcomes depend on the performance of other members ( Wageman, 1995 ). Accordingly, the rewards for each member are based on the total team performance ( Hertel et al., 2004 ). This can occur, for instance, if a team receives a reward based on specific performance criteria. Although interdependence is often the reason why teams are formed in the first place, and it is stated as a defining attribute of teams ( Salas et al., 2008 ), different levels of task interdependence exist ( Van de Ven et al., 1976 ; Arthur et al., 2005 ).

The workflow pattern of teams can be

(1) Independent or pooled (activities are performed separately),

(2) Sequential (activities flow from one member to another in a unidirectional manner),

(3) Reciprocal (activities flow between team members in a back and forth manner) or

(4) Intensive (team members must simultaneously diagnose, problem-solve, and coordinate as a team to accomplish a task).

Teams that deal with complex problems work within intensive interdependence, which requires greater coordination patterns compared to lower levels of interdependence ( Van de Ven et al., 1976 ; Wageman, 1995 ) and necessitates mutual adjustments as well as frequent interaction and information integration within the team ( Gibson, 1999 ; Stajkovic et al., 2009 ).

Thus, in addition to the cognitive requirements related to information processing (e.g., encoding, storage and retrieval processes ( Hinsz et al., 1997 ), simultaneously representing and anticipating the dynamic elements and predicting future states of the problem, balancing contradictory objectives and decide on the right timing for actions to execute) of individual team members, the interconnectedness between the experts in the team imposes high team process demands on the team members. These team process demands follow from the required interdependent actions of all team members for effectively using all resources, such as equipment, money, time, and expertise, to reach high team performance ( Marks et al., 2001 ). Examples for team process demands are the communication for building a shared situation awareness, negotiating conflicting perspectives on how to proceed or coordinating and orchestrating actions of all team members.

A Comprehensive Model of the Idealized Teamwork Process

The cognitive requirements, that complex problem solving teams face, and the team process demands are consolidated within our model of an idealized teamwork process in Figure 1 ( Hagemann, 2011 ; Kluge et al., 2014 ). Individual and team processes converge sequential and in parallel and influencing factors as well as process demands concerning complex problem solving in teams can be extracted. The core elements of the model are situation awareness, information transfer, individual and shared mental models, coordination and leadership, and decision making.

Figure 1 . Relevant teamwork skills (orange color) for interdependently working teams (see Wilson et al., 2010 ) integrated into the model of an idealized teamwork process.

Complex problem solving teams are responsible for finding solutions and reaching specified goals. Based on the overall goals various sub goals will be identified at the beginning of the teamwork process in the course of mission analysis, strategy formulation and planning, all aspects of the transition phase ( Marks et al., 2001 ). The transition phase processes occur during periods of time when teams focus predominantly on evaluation and/or planning activities. The identified and communicated goals within the team represent relevant input variables for each team member in order to build up a Situation Awareness (SA). SA contains three steps and is the foundation for an ideal and goal directed collaboration within a team ( Endsley, 1999 ; Flin et al., 2008 ). The individual SA is the start and end within the idealized teamwork process model. SA means the assessment of a situation which is important for complex problem solving teams, as they work based on the division of labor as well as interdependently and each team member needs to achieve a correct SA and to share it within the team. Each single team member needs to utilize all technical and interpersonal resources in order to collect and interpret up-to-date goal directed information and to share this information with other team members via “closed-loop communication.”

This information transfer focuses on sending and receiving single SA between team members in order to build up a Shared Situation Awareness (SSA). Overlapping cuts of individual SA are synchronized within the team and a bigger picture of the situation is developed. Creating a SSA means sharing a common perspective of the members concerning current events within their environment, their meaning and their future development. This shared perspective enables problem-solving teams to attain high performance standards through corresponding and goal directed actions ( Cannon-Bowers et al., 1993 ).

Expectations of each team member based on briefings, individual mental models and interpositional knowledge influence the SA, the information transfer and the consolidation process. Mental models are internal and cognitive representations of relations and processes (e.g., execution of tactics) between various aspects or elements of a situation. They help team members to describe, explain and predict circumstances ( Mathieu et al., 2000 ). Mental models possess knowledge elements required by team members in order to assess a current situation in terms of SA. Interpositional knowledge refers to an individual understanding concerning the tasks and duties of all team members, in order to develop an understanding about the impact of own actions on the actions of other team members and vice versa. It supports the team in identifying the information needs and the amount of required help of other members and in avoiding team conflicts ( Smith-Jentsch et al., 2001 ). This knowledge is the foundation for anticipating the team members' needs for information and it is important for matching information within the team.

Based on the information matching process within the team, a common understanding of the problem, the goals and the current situation is developed in terms of a Shared Mental Model (SMM), which is important for the subsequent decisions. SMM are commonly shared mental models within a team and refer to the organized knowledge structures of all team members, that are shared with each other and which enable the team to interact goal-oriented ( Mathieu et al., 2000 ). SMM help complex problem solving teams during high workload to adapt fast and efficiently to changing situations ( Waller et al., 2004 ). They also enhance the teams' performance and communication processes ( Cannon-Bowers et al., 1993 ; Mathieu et al., 2000 ). Especially under time pressure and in crucial situations when overt verbal communication and explicit coordination is not applicable, SMM are fundamental in order to coordinate implicitly. This information matching process fosters the building of a shared understanding of the current situation and the required actions. In order to do so teamwork skills (see Wilson et al., 2010 ) such as communication, coordination , and cooperation within the team are vitally important. Figure 1 incorporates the teamwork skills into the model of an idealized teamwork process.

Depending on the shared knowledge and SA within the team, the coordination can be based either on well-known procedures or shared expectations within the team or on explicit communication based on task specific phraseology or closed-loop communication. Cooperation needs mutual performance monitoring within the team, for example, in order to apply task strategies to accurately monitor teammate performance and prevent errors ( Salas et al., 2005 ). Cooperation also needs backup behavior of each team member, for example, and continuous actions in reference to the collective events. The anticipation of other team members' needs under high workload maintains the teams' performance and the well-being of each team member ( Badke-Schaub, 2008 ). A successful pass through the teamwork process model also depends e.g., on the trust and the cohesion within the team and the collective orientation of each team member.

Collective orientation (CO) is defined “as the propensity to work in a collective manner in team settings” ( Driskell et al., 2010 , p. 317). Highly collectively oriented people work with others on a task-activity and team-activity track ( Morgan et al., 1993 ) in a goal-oriented manner, seek others' input, contribute to team outcomes, enjoy team membership, and value cooperativeness more than power ( Driskell et al., 2010 ). Thus, teams with collectively oriented members perform better than teams with non-collectively oriented members ( Driskell and Salas, 1992 ). CO, trust and cohesion as well as other coordination and cooperation skills are so called emergent sates that represent cognitive, affective, and motivational states, and not traits, of teams and team members, and which are influenced, for example, by team experience, so that emergent states can be considered as team inputs but also as team outcomes ( Marks et al., 2001 ).

Based on the information matching process the complex problem solving team or the team leader needs to make decisions in order to execute actions. The task prioritization and distribution is an integrated part of this step ( Waller et al., 2004 ). Depending on the progress of the dynamic, non-transparent and heavily foreseeable situation tasks have to be re-prioritized during episodes of teamwork. Episodes are “temporal cycles of goal-directed activity” in which teams perform ( Marks et al., 2001 , p. 359). Thus, the team acts adaptive and is able to react flexible to situation changes. The team coordinates implicitly when each team member knows what he/she has to do in his/her job, what the others expect from him/her and how he/she interacts with the others. In contrast, when abnormal events occur and they are recognized during SA processes, the team starts coordinating explicitly via communication, for example. Via closed-loop communication and based on interpositional knowledge new strategies are communicated within the team and tasks are re-prioritized.

The result of the decision making and action taking flows back into the individual SA and the as-is state will be compared with the original goals. This model of an idealized teamwork process (Figure 1 ) is a regulator circuit with feedback loops, which enables a team to adapt flexible to changing environments and goals. The foundation of this model is the classic Input-Process-Outcome (IPO) framework ( Hackman, 1987 ) with a strong focus on the process part. IPO models view processes as mechanisms linking variables such as member, team, or organizational features with outcomes such as performance quality and quantity or members' reactions. This mediating mechanism, the team process , can be defined as “members' interdependent acts that convert inputs to outcomes through cognitive, verbal, and behavioral activities directed toward organizing taskwork to achieve collective goals” ( Marks et al., 2001 , p. 357). That means team members interact interdependently with other members as well as with their environment. These cognitive, verbal, and behavioral activities directed toward taskwork and goal attainment are represented as gathering situation awareness, communication, coordination, cooperation, the consolidation of information, and task prioritization within our model of an idealized teamwork process. Within the context of complex problem solving, teams have to face team process demands in addition to cognitive challenges related to individual information processing. That means teamwork processes and taskwork to solve complex problems co-occur, the processes guide the execution of taskwork.

The dynamic nature of teamwork and temporal influences on complex problem solving teams are considered within adapted versions ( Marks et al., 2001 ; Ilgen et al., 2005 ) of the original IPO framework. These adaptations propose that teams experience cycles of joint action, so called episodes, in which teams perform and also receive feedback for further actions. The IPO cycles occur sequentially and simultaneously and are nested in transition and action phases within episodes in which outcomes from initial episodes serve as inputs for the next cycle (see Figure 2 ). These repetitive IPO cycles are a vital element of our idealized teamwork process model, as it incorporates feedback loops in such a way, that the outcomes, e.g., changes within the as-is state, are continuously compared with the original goals. Detected discrepancies within the step of updating SA motivate the team members to consider further actions for goal accomplishment.

Figure 2 . Teamwork episodes with repetitive IPO cycles ( Marks et al., 2001 ).

When applying this episodic framework to complex problem solving teams it becomes obvious that teams handle different types of taskwork at different phases of task accomplishment ( Marks et al., 2001 ). That means episodes consist of two phases, so-called action and transition phases , in which teams are engaged in activities related to goal attainment and in other time in reflecting on past performance and planning for further common actions. The addition of the social complexity to the complexity of the problem within collaborative complex problem solving comes to the fore here. During transition phases teams evaluate their performance, compare the as-is state against goals, reflect on their strategies and plan future activities to guide their goal accomplishment. For example, team members discuss alternative courses of action, if their activities for simulated firefighting, such as splitting team members in order to cover more space of the map, are not successful. During action phases, teams focus directly on the taskwork and are engaged in activities such as exchanging information about the development of the dynamic situation or supporting each other. For example, a team member recognizes high workload of another team member and supports him/her in collecting information or in taking over the required communication with other involved parties.

Transition and Action Phases

The idealized teamwork process model covers these transition and action phases as well as the processes occurring during these two phases of team functioning, which can be clustered into transition, action, and interpersonal processes. That means during complex problem solving the relevant or activated teamwork processes in the transition and action phases change as teams move back and forth between these phases. As this taxonomy of team processes from Marks et al. (2001) states that a team process is multidimensional and teams use different processes simultaneously, some processes can occur either during transition periods or during action periods or during both periods. Transition processes especially occur during transition phases and enable the team to understand their tasks, guide their attention, specify goals and develop courses of action for task accomplishment. Thus, transition processes include (see Marks et al., 2001 ) mission analysis, formulation and planning ( Prince and Salas, 1993 ), e.g., fighting a forest fire, goal specification ( Prussia and Kinicki, 1996 ), e.g., saving as much houses and vegetation as possible, and strategy formulation ( Prince and Salas, 1993 ; Cannon-Bowers et al., 1995 ), e.g., spreading team members into different geographic directions. Action processes predominantly occur during action phases and support the team in conducting activities directly related to goal accomplishment. Thus, action processes are monitoring progress toward goals ( Cannon-Bowers et al., 1995 ), e.g., collecting information how many cells in a firefighting simulation are still burning, systems monitoring ( Fleishman and Zaccaro, 1992 ), e.g., tracking team resources such as water for firefighting, team monitoring and backup behavior ( Stevens and Campion, 1994 ; Salas et al., 2005 ), e.g., helping a team member and completing a task for him/her, and coordination ( Fleishman and Zaccaro, 1992 ; Serfaty et al., 1998 ), e.g., orchestrating the interdependent actions of the team members such as exchanging information during firefighting about positions of team members for meeting at the right time at the right place in order to refill the firefighters water tanks. Especially the coordination process is influenced by the amount of task interdependence as coordination becomes more and more important for effective team functioning when interdependence increases ( Marks et al., 2001 ). Interpersonal processes occur during transition and action phases equally and lay the foundation for the effectiveness of other processes and govern interpersonal activities ( Marks et al., 2001 ). Thus, interpersonal processes include conflict management ( Cannon-Bowers et al., 1995 ), like the development of team rules, motivation and confidence building ( Fleishman and Zaccaro, 1992 ), like encourage team members to perform better, and affect management ( Cannon-Bowers et al., 1995 ), e.g., regulating member emotions during complex problem solving.

Summing up, process demands such as transition processes that complex problem solving teams pass through, are mission analysis, planning, briefing and goal specification, visualized on the left side of the idealized teamwork process model (see Figure 3 ). The results of these IPO cycles lay the foundation for gathering a good SA and initiating activities directed toward taskwork and goal accomplishment and therefore initiating action processes. The effective execution of action processes depends on the communication, coordination, cooperation, matching of information, and task prioritization as well as emergent team cognition variables (SSA and SMM) within the team. The results, like decisions, of these IPO cycles flow back into the next episode and may initiate further transition processes. In addition, interpersonal processes play a crucial role for complex problem solving teams. That means, conflict management, motivating and confidence building, and affect management are permanently important, no matter whether a team runs through transition or action phases and these interpersonal processes frame the whole idealized teamwork process model. Therefore, interpersonal processes are also able to impede successful teamwork at any point as breakdowns in conflict or affect management can lead to coordination breakdowns ( Wilson et al., 2010 ) or problems with monitoring or backing up teammates ( Marks et al., 2001 ). Thus, complex problem solving teams have to face these multidimensional team process demands in addition to cognitive challenges, e.g., information storage or retrieval ( Hinsz et al., 1997 ), related to individual information processing.

Figure 3 . The integration of transition, action, interpersonal, and learning processes into the model of an idealized teamwork process.

Team Learning Opportunities for Handling Complex Problems

In order to support teams in handling complex situations or problems, learning opportunities seem to be very important for successful task accomplishment and for reducing possible negative effects of team process demands. Learning means any kind of relative outlasted changes in potential of human behavior that cannot be traced back to age-related changes ( Bower and Hilgard, 1981 ; Bredenkamp, 1998 ). Therefore, Schmutz et al. (2016) amended the taxonomy of team processes developed by Marks et al. (2001) and added learning processes as a fourth category of processes, which occur during transition and action phases and contribute to overall team effectiveness. Learning processes (see also Edmondson, 1999 ) include observation, e.g., observing own and other team members' actions such as the teammate's positioning of firewalls in order to protect houses in case of firefighting, feedback, like giving a teammate information about the wind direction for effective positioning of firewalls, and reflection, e.g., talking about procedures for firefighting or refilling water tanks, for example, within the team. Learning from success and failure and identifying future problems is crucial for the effectiveness of complex problem solving teams and therefore possibilities for learning based on repetitive cycles of joint action or episodes and reflection of team members' activities during action and transition phases should be used effectively ( Edmondson, 1999 ; Marks et al., 2001 ). The processes of the idealized teamwork model are embedded into these learning processes (see Figure 3 ).

The fulfillment of transition, action, interpersonal and learning processes contribute significantly to successful team performance in complex problem solving. For clustering these processes, transition and action processes could be seen as operational processes and interpersonal and learning process as support processes. When dealing with complex and dynamic situations teams have to face these team process demands more strongly than in non-complex situations. For example, goal specification and prioritization or strategy formulation, both aspects of transition processes, are strongly influenced by multiple goals, interconnectedness or dynamically and constantly changing conditions. The same is true for action processes, such as monitoring progress toward goals, team monitoring and backup behavior or coordination of interdependent actions. Interpersonal processes, such as conflict and affect management or confidence building enhance the demands put on team members compared to individuals working on complex problems. Interpersonal processes are essential for effective teamwork and need to be cultivated during episodes of team working, because breakdowns in confidence building or affect management can lead to coordination breakdowns or problems with monitoring or backing up teammates ( Marks et al., 2001 ). Especially within complex situations aspects such as interdependence, delayed feedback, multiple goals and dynamic changes put high demands on interpersonal processes within teams. Learning processes, supporting interpersonal processes and the result of effective teamwork are e.g., observation of others' as well as own actions and receiving feedback by others or the system and are strongly influenced by situational characteristics such as non-transparency or delayed feedback concerning actions. It is assumed that amongst others team learning happens through repetitive cycles of joint action within the action phases and reflection of team members within the transition phases ( Edmondson, 1999 ; Gabelica et al., 2014 ; Schmutz et al., 2016 ). The repetitive cycles help to generate SMM ( Cannon-Bowers et al., 1993 ; Mathieu et al., 2000 ), SSA ( Endsley and Robertson, 2000 ) or transactive memory systems ( Hollingshead et al., 2012 ) within the team.

Emergent States in Complex Team Work and the Role of Collective Orientation

IPO models propose that input variables and emergent states are able to influence team processes and therefore outcomes such as team performance positively. Emergent states represent team members' attitudes or motivations and are “properties of the team that are typically dynamic in nature and vary as a function of team context, inputs, processes, and outcomes” ( Marks et al., 2001 , p. 357). Both emergent states and interaction processes are relevant for team effectiveness ( Kozlowski and Ilgen, 2006 ).

Emergent states refer to conditions that underlie and dynamically enable effective teamwork ( DeChurch and Mesmer-Magnus, 2010 ) and can be differentiated from team process, which refers to interdependent actions of team members that transform inputs into outcomes based on activities directed toward task accomplishment ( Marks et al., 2001 ). Emergent states mainly support the execution of behavioral processes (e.g., planning, coordination, backup behavior) during the action phase, meaning during episodes when members are engaged in acts that focus on task work and goal accomplishment. Emergent states like trust, cohesion and CO are “products of team experiences (including team processes) and become new inputs to subsequent processes and outcomes” ( Marks et al., 2001 , p. 358). Trust between team members and cohesion within the team are emergent states that develop over time and only while experiencing teamwork in a specific team. CO is an emergent state that a team member brings along with him/her into the teamwork, is assumed to be more persistent than trust and cohesion, and can, but does not have to, be positively and negatively influenced by experiencing teamwork in a specific team for a while or by means of training ( Eby and Dobbins, 1997 ; Driskell et al., 2010 ). Thus, viewing emergent states on a continuum, trust and cohesion are assumed more fluctuating than CO, but CO is much more sensitive to change and direct experience than a stable trait such as a personality trait.

CO of team members is one of the teamwork-relevant competencies that facilitates team processes, such as collecting and sharing information between team members, and positively affects the success of teams, as people who are high in CO work with others in a goal-oriented manner, seek others' input and contribute to team outcomes ( Driskell et al., 2010 ). CO is an emergent state, as it can be an input variable as well as a teamwork outcome. CO is context-dependent, becomes visible in reactions to situations and people, and can be influenced by experience (e.g., individual learning experiences with various types of teamwork) or knowledge or training ( Eby and Dobbins, 1997 ; Bell, 2007 ). CO enhances team performance through activating transition and action processes such as coordination, evaluation and consideration of task inputs from other team members while performing a team task ( Driskell and Salas, 1992 ; Salas et al., 2005 ). Collectively oriented people effectively use available resources in due consideration of the team's goals, participate actively and adapt teamwork processes adequately to the situation.

Driskell et al. (2010) and Hagemann (2017) provide a sound overview of the evidence of discriminant and convergent validity of CO compared to other teamwork-relevant constructs, such as cohesion, also an emergent state, or cooperative interdependence or preference for solitude. Studies analyzing collectively and non-collectively oriented persons' decision-making in an interdependent task demonstrated that teams with non-collectively oriented members performed poorly in problem solving and that members with CO judged inputs from teammates as more valuable and considered these inputs more frequently ( Driskell and Salas, 1992 ). Eby and Dobbins (1997) also showed that CO results in increased coordination among team members, which may enhance team performance through information sharing, goal setting and strategizing ( Salas et al., 2005 ). Driskell et al. (2010) and Hagemann (2017) analyzed CO in relation to team performance and showed that the effect of CO on team performance depends on the task type (see McGrath, 1984 ). Significant positive relationships between team members' CO and performance were found in relation to the task types choosing/decision making and negotiating ( Driskell et al., 2010 ) respectively choosing/decision making ( Hagemann, 2017 ). These kinds of tasks are characterized by much more interdependence than task types such as executing or generating tasks. As research shows that the positive influence of CO on team performance unfolds especially in interdependent teamwork contexts ( Driskell et al., 2010 ), which require more team processes such as coordination patterns ( Van de Ven et al., 1976 ; Wageman, 1995 ) and necessitate mutual adjustments as well as frequent information integration within the team ( Gibson, 1999 ; Stajkovic et al., 2009 ), CO might be vitally important for complex problem solving teams. Thus, CO as an emergent state of single team members might be a valuable resource for enhancing the team's performance when exposed to solving complex problems. Therefore, it will be of interest to analyze the influence of CO on team process demands such as coordination processes and performance within complex problem solving teams. We predict that the positive effect of CO on team performance is an indirect effect through coordination processes within the team, which are vitally important for teams working in intensive interdependent work contexts.

Hypothesis 1: CO leads to a better coordination behavior, which in turn leads to a higher team performance.

As has been shown in team research that emergent states like trust and cohesion (see also Figure 1 ) affect team performance, these two constructs are analyzed in conjunction with CO concerning action processes, such as coordination behavior and team performance. Trust between team members supports information sharing and the willingness to accept feedback, and therefore positively influences teamwork processes ( McAllister, 1995 ; Salas et al., 2005 ). Cohesion within a team facilitates motivational factors and group processes like coordination and enhances team performance ( Beal et al., 2003 ; Kozlowski and Ilgen, 2006 ).

Hypothesis 2: Trust shows a positive relationship with (a) action processes (team coordination) and with (b) team performance.

Hypothesis 3: Cohesion shows a positive relationship with (a) action processes (team coordination) and with (b) team performance.

Materials and Methods

In order to demonstrate the importance of team process demands for complex problem solving in teams, we used a computer-based microworld in a laboratory study. We analyzed the effectiveness of complex problem solving teams while considering the influence of input variables, like collective orientation of team members and trust and cohesion within the team, on action processes within teams, like coordination.

The Microworld for Investigating Teams Process Demands

We used the simulation-based team task C 3 Fire ( Granlund et al., 2001 ; Granlund and Johansson, 2004 ), which is described as an intensive interdependence team task for complex problem solving ( Arthur et al., 2005 ). C 3 Fire is a command, control and communications simulation environment that allows teams' coordination and communication in complex and dynamic environments to be analyzed. C 3 Fire is a microworld, as important characteristics of the real world are transferred to a small and well-controlled simulation system. The task environment in C 3 Fire is complex, dynamic and opaque (see Table 1 ) and therefore similar to the cognitive tasks people usually encounter in real-life settings, in and outside their work place ( Brehmer and Dörner, 1993 ; Funke, 2001 ). Figure 4 demonstrates how the complexity characteristics mentioned in Table 1 are realized in C 3 Fire. The screenshot represents the simulation manager's point of view, who is able to observe all units and actions and the scenario development. For more information about the units and scenarios, please (see the text below and the Supplementary Material). Complexity requires people to consider a number of facts. Because executed actions in C 3 Fire influence the ongoing process, the sequencing of actions is free and not stringent, such as a fixed (if X then Y) or parallel (if X then Y and Z) sequence ( Ormerod et al., 1998 ). This can lead to stressful situations. Taking these characteristics of microworlds into consideration, team processes during complex problem solving can be analyzed within laboratories under controlled conditions. Simulated microworlds such as C 3 Fire allow the gap to be bridged between laboratory studies, which might show deficiencies regarding ecological validity, and field studies, which have been criticized due to their small amount of control (see Brehmer and Dörner, 1993 ).

Table 1 . Overview of complexity characteristics of microworlds in general and in C 3 Fire (cf. Funke, 2001 ).

Figure 4 . Examples for the complexity characteristics in Table 1 represented within a simulation scenario in C 3 Fire.

In C 3 Fire, the teams' task is to coordinate their actions to extinguish a forest fire whilst protecting houses and saving lives. The team members' actions are interdependent. The simulation includes, e.g., forest fires, houses, tents, gas tanks, different kinds of vegetation and computer-simulated agents such as firefighting units ( Granlund, 2003 ). It is possible, for example, that the direction of wind will change during firefighting and the time until different kinds of vegetation are burned down varies between those. In the present study, two simulation scenarios were developed for two-person teams and consisted of two firefighting units, one mobile water tank unit (responsible for re-filling the firefighting units' water tanks that contain a predefined amount of water) and one fire-break unit (a field defended with a fire-break cannot be ignited; the fire spreads around its ends). The two developed scenarios lasted for 15 min maximum. Each team member was responsible for two units in each scenario; person one for firefighting and water tank unit and person two for firefighting and fire-break unit. The user interface was a map system (40 × 40 square grid) with all relevant geographic information and positions of all symbols representing houses, water tank units and so on. All parts of the map with houses and vegetation were visible for the subjects, but not the fire itself or the other units; instead, the subjects were close to them with their own units (restricted visibility field; 3 × 3 square grid). The simulation was run on computers networked in a client-server configuration. The subjects used a chat system for communication that was logged. For each scenario, C 3 Fire creates a detailed log file containing all events that occurred over the course of the simulation. Examples of the C 3 Fire scenarios are provided in the Figures S1–3 and a short introduction into the microworld is given in the video. Detailed information regarding the scenario characteristics are given in Table S1. From scenario one to two, the complexity and interdependence increased.

Participants

The study was conducted from Mai 2014 until March 2015. Undergraduate and graduate students ( N = 116) studying applied cognitive sciences participated in the study (68.1% female). Their mean age was 21.17 years ( SD = 3.11). Participants were assigned to 58 two-person teams, with team assignments being based on the pre-measured CO values (see procedure). They received 2 hourly credits as a trial subject and giveaways such as pencils and non-alcoholic canned drinks. The study was approved by the university's ethics committee in February 2014.

The study was conducted within a laboratory setting at a university department for business psychology. Prior to the experiment, the participants filled in the CO instrument online and gave written informed consent (see Figure 5 ). The median was calculated subsequently ( Md = 3.12; range: 1.69–4.06; scale range: 1–5) relating to the variable CO and two individuals with either high ( n = 58) or low ( n = 58) CO values were randomly matched as teammates. The matching process was random in part, as those two subjects were matched to form a team, whose preferred indicated time for participation in a specific week during data collection were identical. The participants were invited to the experimental study by e-mail 1–2 weeks after filling in the CO instrument. The study began with an introduction to the experimental procedure and the teams' task. The individuals received time to familiarize themselves with the simulation, received 20 min of training and completed two practice trials. After the training, participants answered a questionnaire collecting demographic data. Following this, a simulation scenario started and the participants had a maximum of 15 min to coordinate their actions to extinguish a forest fire whilst protecting houses and saving lives. After that, at measuring time T1, participants answered questionnaires assessing trust and cohesion within the team. Again, the teams worked on the following scenario 2 followed by a last round of questionnaires assessing trust and cohesion at T2.

Figure 5 . Overview about the procedure and measures.

Demographic data such as age, sex, and study course were assessed after the training at the beginning of the experiment.

Collective Orientation was measured at an individual level with 16 items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ) developed by the authors ( Hagemann, 2017 ) based on the work of Driskell et al. (2010) . The factorial structure concerning the German-language CO scale was proven prior to this study (χ 2 = 162.25, df = 92, p = 0.000, χ 2 /df = 1.76, CFI = 0.97, TLI = 0.96, RMSEA = 0.040, CI = 0.030-0.051, SRMR = 0.043) and correlations for testing convergent and discriminant evidence of validity were satisfying. For example, CO correlated r = 0.09 ( p > 0.10) with cohesion, r = 0.34 ( p < 0.01) with cooperative interdependence and r = −0.28 ( p < 0.01) with preference for solitude ( Hagemann, 2017 ). An example item is “ I find working on team projects to be very satisfying ”. Coefficient alpha for this scale was 0.81.

Trust in team members' integrity, trust in members' task abilities and trust in members' work-related attitudes ( Geister et al., 2006 ) was measured with seven items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ). An example item is “ I can trust that I will have no additional demands due to lack of motivation of my team member .” Coefficient alpha for this scale was 0.83 (T1) and 0.87 (T2).

Cohesion was measured with a six-item scale from Riordan and Weatherly (1999) rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ). An example item is “ In this team, there is a lot of team spirit among the members .” Coefficient alpha for this scale was 0.87 (T1) and 0.87 (T2).

Action Process: Coordination

Successful coordination requires mechanisms that serve to manage dependencies between the teams' activities and their resources. Coordination effectiveness was assessed based on the time the firefighting units spent without water in the field in relation to the total scenario time. This measure is an indicator of the effectiveness of resource-oriented coordination, as it reflects an efficient performance regarding the water refill process in C 3 Fire, which requires coordinated actions between the two firefighting units and one water tank unit ( Lafond et al., 2011 ). The underlying assumption is that a more successful coordination process leads to fewer delays in conducting the refill process. Coordination was calculated by a formula and values ranged between 0 and 1, with lower values indicating better coordination in the team (see Jobidon et al., 2012 ).

Team Performance

This measure related to the teams' goals (limiting the number of burned out cells and saving as many houses/buildings as possible) and was quantified as the number of protected houses and the number of protected fields and bushes/trees in relation to the number of houses, fields, and bushes/trees, respectively, which would burn in a worst case scenario. This formula takes into account that teams needing more time for firefighting also have more burning cells and show a less successful performance than teams that are quick in firefighting. To determine the worst case scenario, both 15-min scenarios were run with no firefighting action taken. Thus, the particularities (e.g., how many houses would burn down if no action was taken) of each scenario were considered. Furthermore, the houses, bushes/trees and fields were weighted according to their differing importance, mirroring the teams' goals. Houses should be protected and were most important. Bushes/trees (middle importance) burn faster than fields (lowest importance) and foster the expansion of the fire. Values regarding team performance ranged between 0 and 7.99, with higher values indicating a better overall performance. Team performance was calculated as follows (see Table 2 ):

Table 2 . Explanation of formula for calculating team performance in both scenarios.

Means, standard deviations, internal consistencies, and correlations for all study variables are provided in Table 3 .

Table 3 . Means, standard deviations, internal consistencies, and correlations for all study variables.

Team complex problem solving in scenario 1 correlated significantly negative with time without water in scenario 1, indicating that a high team performance is attended by the coordination behavior (as a team process). The same was true for scenario 2. In addition, time without water as an indicator for team coordination correlated significantly negative with the team members' CO, indicating that team members with high CO values experience less time without water in the microworld than teams with members with low CO values.

In order to analyze the influence of CO on team process demands such as coordination processes and thereby performance within complex problem solving teams we tested whether CO would show an indirect effect on team performance through the teams' coordination processes. To analyze this assumption, indirect effects in simple mediation models were estimated for both scenarios (see Preacher and Hayes, 2004 ). The mean for CO was 3.44 ( SD = 0.32) for teams with high CO values and it was 2.79 ( SD = 0.35) for teams with low CO values. The mean concerning team performance in scenario 1 for teams with high CO values was 6.30 ( SD = 1.64) and with low CO values 5.35 ( SD = 2.30). The mean concerning time without water (coordination behavior) for teams with high CO values was 0.16 ( SD = 0.08) and with low CO values 0.20 ( SD = 0.09). In scenario 2 the mean for team performance was 6.26 ( SD = 2.51) for teams with high CO values and it was 4.36 ( SD = 2.24) for teams with low CO values. The mean concerning time without water for teams with high CO values was 0.18 ( SD = 0.08) and with low CO values 0.25 ( SD = 0.11).

For analyzing indirect effects, CO was the independent variable, time without water the mediator and team performance the dependent variable. The findings indicated that CO has an indirect effect on team performance mediated by time without water for scenario 1 (Table 4 ) and scenario 2 (Table 5 ). In scenario 1, CO had no direct effect on team performance ( b(YX) ), but CO significantly predicted time without water ( b(MX) ). A significant total effect ( b(YX) ) is not an assumption in the assessment of indirect effects, and therefore the non-significance of this relationship does not violate the analysis (see Preacher and Hayes, 2004 , p. 719). Furthermore, time without water significantly predicted team performance when controlling for CO ( b(YM.X) ), whereas the effect of CO on team performance was not significant when controlling for time without water ( b(YX.M) ). The indirect effect was 0.40 and significant when using normal distribution and estimated with the Sobel test ( z = 1.97, p < 0.05). The bootstrap procedure was applied to estimate the effect size not based on the assumption of normal distribution. As displayed in Table 4 , the bootstrapped estimate of the indirect effect was 0.41 and the true indirect effect was estimated to lie between 0.0084 and 0.9215 with a 95% confidence interval. As zero is not in the 95% confidence interval, it can be concluded that the indirect effect is indeed significantly different from zero at p < 0.05 (two-tailed).

Table 4 . Indirect Effect for Coordination and Team Performance in Scenario 1.

Table 5 . Indirect Effect for Coordination and Team Performance in Scenario 2.

Regarding scenario 2, CO had a direct effect on team performance ( b(YX) ) and on time without water ( b(MX) ). Again, time without water significantly predicted team performance when controlling for CO ( b(YM.X) ), whereas the effect of CO on team performance was not significant when controlling for time without water ( b(YX.M) ). This time, the indirect effect was 0.60 (Sobel test, z = 2.31, p < 0.05). As displayed in Table 5 , the bootstrapped estimate of the indirect effect was 0.61 and the true indirect effect was estimated to lie between 0.1876 and 1.1014 with a 95% confidence interval and between 0.0340 and 1.2578 with a 99% confidence interval. Because zero is not in the 99% confidence interval, it can be concluded that the indirect effect is indeed significantly different from zero at p < 0.01 (two-tailed).

The indirect effects for both scenarios are visualized in Figure 6 . Summing up, the results support hypothesis 1 and indicate that CO has an indirect effect on team performance mediated by the teams' coordination behavior, an action process. That means, fulfilling team process demands affect the dynamic decision making quality of teams acting in complex situations and input variables such as CO influence the action processes within teams positively.

Figure 6 . Indirect effect of collective orientation on team performance via coordination within the teams for scenario 1 and 2, * p < 0.05, ** p < 0.01, *** p < 0.001, numbers in italic represent results from scenario 2, non-italic numbers are from scenario 1.

Trust between team members assessed after scenario 1 (T1) and after scenario 2 (T2) did not show any significant correlation with the coordination behavior or with team complex problem solving in scenarios 1 and 2 (Table 3 ). Thus, hypotheses 2a and 2b are not supported. Cohesion at T1 showed no significant relationship with team performance in both scenarios, one significant negative correlation ( r = −0.22, p < 0.05) with the coordination behavior in scenario 1 and no correlation with the coordination behavior in scenario 2. Cohesion at T2 did not show any significant correlation with the coordination behavior or with team performance in both scenarios. Thus, hypotheses 3a and 3b could also not be supported. Furthermore, the results showed no significant relations between CO and trust and cohesion. The correlations between trust and cohesion ranged between r = 0.39 and r = 0.51 ( p < 0.01).

The purpose of our paper was first to give a sound theoretical overview and to combine theoretical approaches about team competencies and team process demands in collaborative complex problem solving and second to demonstrate the importance of selected team competencies and processes on team performance in complex problem solving by means of results from a laboratory study. We introduced the model of an idealized teamwork process that complex problem solving team pass through and integrated the relevant teamwork skills for interdependently working teams into it. Moreover, we highlighted the episodic aspect concerning complex problem solving in teams and combined the well-known transition, action, interpersonal and learning processes of teamwork with the idealized teamwork process model. Finally, we investigated the influence of trust, cohesion, and CO on action processes, such as coordination behavior of complex problem solving teams and on team performance.

Regarding hypothesis 1, studies have indicated that teams whose members have high CO values are more successful in their coordination processes and task accomplishment ( Eby and Dobbins, 1997 ; Driskell et al., 2010 ; Hagemann, 2017 ), which may enhance team performance through considering task inputs from other team members, information sharing and strategizing ( Salas et al., 2005 ). Thus, we had a close look on CO as an emergent state in the present study, because emergent states support the execution of behavioral processes. In order to analyze this indirect effect of CO on team performance via coordination processes, we used the time, which firefighters spent without water in a scenario, as an indicator for high-quality coordination within the team. A small amount of time without water represents sharing information and resources between team members in a reciprocal manner, which are essential qualities of effective coordination ( Ellington and Dierdorff, 2014 ). One of the two team members was in charge of the mobile water tank unit and therefore responsible for filling up the water tanks of his/her own firefighting unit and that of the other team member on time. In order to avoid running out of water for firefighting, the team members had to exchange information about, for example, their firefighting units' current and future positions in the field, their water levels, their strategies for extinguishing one or two fires, and the water tank unit's current and future position in the field. The simple mediation models showed that CO has an indirect effect on team performance mediated by time without water, supporting hypothesis 1. Thus, CO facilitates high-quality coordination within complex problem solving teams and this in turn influences decision-making and team performance positively (cf. Figure 1 ). These results support previous findings concerning the relationships between emergent states, such as CO, and the team process, such as action processes like coordination ( Cannon-Bowers et al., 1995 ; Driskell et al., 2010 ) and between the team process and the team performance ( Stevens and Campion, 1994 ; Dierdorff et al., 2011 ).

Hypotheses 2 and 3 analyzed the relationships between trust and cohesion and coordination and team performance. Because no correlations between trust and cohesion and the coordination behavior and team complex problem solving existed, further analyses, like mediation analyses, were unnecessary. In contrast to other studies ( McAllister, 1995 ; Beal et al., 2003 ; Salas et al., 2005 ; Kozlowski and Ilgen, 2006 ), the present study was not able to detect effects of trust and cohesion on team processes, like action processes, or on team performance. This can be attributed to the restricted sample composition or the rather small sample size. Nevertheless, effect sizes were small to medium, so that they would have become significant with an increased sample sizes. The prerequisite, mentioned by the authors, that interdependence of the teamwork is important for identifying those effects, was given in the present study. Therefore, this aspect could not have been the reason for finding no effects concerning trust and cohesion. Trust and cohesion within the teams developed during working on the simulation scenarios while fighting fires, showed significant correlations with each other, and were unrelated to CO, which showed an effect on the coordination behavior and the team performance indeed. The results seem to implicate, that the influence of CO on action processes and team performance might be much more stronger than those of trust and cohesion. If these results can be replicated should be analyzed in future studies.

As the interdependent complex problem-solving task was a computer-based simulation, the results might have been affected by the participants' attitudes to using a computer. For example, computer affinity seems to be able to minimize potential fear of working with a simulation environment and might therefore, be able to contribute to successful performance in a computer-based team task. Although computers and other electronic devices are pervasive in present-day life, computer aversion has to be considered in future studies within complex problem-solving research when applying computer-based simulation team tasks. As all of the participants were studying applied cognitive science, which is a mix of psychology and computer science, this problem might not have been influenced the present results. However, the specific composition of the sample reduces the external validity of the study and the generalizability of the results. A further limitation is the small sample size, so that moderate to small effects are difficult to detect.

Furthermore, laboratory research of teamwork might have certain limitations. Teamwork as demonstrated in this study fails to account for the fact that teams are not simple, static and isolated entities ( McGrath et al., 2000 ). The validity of the results could be reduced insofar as the complex relationships in teams were not represented, the teamwork context was not considered, not all teammates and teams were comparable, and the characteristic as a dynamic system with a team history and future was not given in the present study. This could be a possible explanation why no effects of trust and cohesion were found in the present study. Maybe, the teams need more time working together on the simulation scenarios in order to show that trust and cohesion influence the coordination with the team and the team performance. Furthermore, Bell (2007) demonstrated in her meta-analysis that the relationship between team members' attitudes and the team's performance was proven more strongly in the field compared to the laboratory. In consideration of this fact, the findings of the present study concerning CO are remarkable and the simulation based microworld C3Fire ( Granlund et al., 2001 ; Granlund, 2003 ) seems to be appropriate for analyzing complex problem solving in interdependently working teams.

An asset of the present study is, that the teams' action processes, the coordination performance, was assessed objectively based on logged data and was not a subjective measure, as is often the case in group and team research studies (cf. Van de Ven et al., 1976 ; Antoni and Hertel, 2009 ; Dierdorff et al., 2011 ; Ellington and Dierdorff, 2014 ). As coordination was the mediator in the analysis, this objective measurement supports the validity of the results.

As no transition processes such as mission analysis, formulation, and planning ( Prince and Salas, 1993 ), goal specification ( Prussia and Kinicki, 1996 ), and strategy formulation ( Prince and Salas, 1993 ; Cannon-Bowers et al., 1995 ) as well as action processes such as monitoring progress toward goals ( Cannon-Bowers et al., 1995 ) and systems monitoring ( Fleishman and Zaccaro, 1992 ) were analyzed within the present study, future studies should collect data concerning these processes in order to show their importance on performance within complex problem solving teams. Because these processes are difficult to observe, subjective measurements are needed, for example asking the participants after each scenario how they have prioritized various tasks, if and when they have changed their strategy concerning protecting houses or fighting fires, and on which data within the scenarios they focused for collecting information for goal and systems monitoring. Another possibility could be using eye-tracking methods in order to collect data about collecting information for monitoring progress toward goals, e.g., collecting information how many cells are still burning, and systems monitoring, e.g., tracking team resources like water for firefighting.

CO is an emergent state and emergent states can be influenced by experience or learning, for example ( Kozlowski and Ilgen, 2006 ). Learning processes ( Edmondson, 1999 ), that Schmutz et al. (2016) added to the taxonomy of team processes developed by Marks et al. (2001) and which occur during transition and action phases and contribute to team effectiveness include e.g., feedback . Feedback can be useful for team learning when team learning is seen as a form of information processing ( Hinsz et al., 1997 ). Because CO supports action processes, such as coordination and it can be influenced by learning, learning opportunities, such as feedback, seem to be important for successful task accomplishment and for supporting teams in handling complex situations or problems. If the team is temporarily and interpersonally unstable, as it is the case for most of the disaster or crisis management teams dealing with complex problems, there might be less opportunities for generating shared mental models by experiencing repetitive cycles of joint action (cf. Figure 2 ) and strategies such as cross training ( Salas et al., 2007 ) or feedback might become more and more important for successful complex problem solving in teams. Thus, for future research it would be of interest to analyze what kind of feedback is able to influence CO positively and therefore is able to enhance coordination and performance within complex problem-solving teams.

Depending on the type of feedback, different main points will be focused during the feedback (see Gabelica et al., 2012 ). Feedback can be differentiated into performance and process feedback. Process feedback can be further divided into task-related and interpersonal feedback. Besides these aspects, feedback can be given on a team-level or an individual-level. Combinations of the various kinds of feedback are possible and are analyzed in research concerning their influence on e.g., self- and team-regulatory processes and team performance ( Prussia and Kinicki, 1996 ; Hinsz et al., 1997 ; Jung and Sosik, 2003 ; Gabelica et al., 2012 ). For future studies it would be relevant to analyze, whether it is possible to positively influence the CO of team members and therefore action processes such as coordination and team performance or not. A focus could be on the learning processes, especially on feedback, and its influence on CO in complex problem solving teams. So far, no studies exist that analyzed the relationship between feedback and a change in CO, even though researchers already discuss the possibility that team-level process feedback shifts attention processes on team actions and team learning ( McLeod et al., 1992 ; Hinsz et al., 1997 ). These results would be very helpful for training programs for fire service or police or medical teams working in complex environments and solving problems collaboratively, in order to support their team working and their performance.

In summary, the idealized teamwork process model is in combination with the transition, action, interpersonal and learning processes a good framework for analyzing the impact of teamwork competencies and teamwork processes in detail on team performance in complex environments. Overall, the framework offers further possibilities for investigating the influence of teamwork competencies on diverse processes and teamwork outcomes in complex problem solving teams than demonstrated here. The results of our study provide evidence of how CO influences complex problem solving teams and their performance. Accordingly, future researchers and practitioners would be well advised to find interventions how to influence CO and support interdependently working teams.

Ethics Statement

This study was carried out in accordance with the recommendations of Ethical guidelines of the German Association of Psychology, Ethics committee of the University of Duisburg-Essen, Department of Computer Science and Applied Cognitive Science with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics committee of the University of Duisburg-Essen, Department of Computer Science and Applied Cognitive Science.

Author Contributions

VH and AK were responsible for the conception of the work and the study design. VH analyzed and interpreted the collected data. VH and AK drafted the manuscript. They approved it for publication and act as guarantors for the overall content.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01730/full#supplementary-material

Antoni, C., and Hertel, G. (2009). Team processes, their antecedents and consequences: implications for different types of teamwork. Eur. J. Work Organ. Psychol. 18, 253–266. doi: 10.1080/13594320802095502

CrossRef Full Text | Google Scholar

Arthur, W., Edwards, B., Bell, S., Villado, A., and Bennet, W. (2005). Team task analysis: identifying tasks and jobs that are team based. Hum. Factors 47, 654–669. doi: 10.1518/001872005774860087

PubMed Abstract | CrossRef Full Text | Google Scholar

Badke-Schaub, P. (2008). Teamarbeit und Teamführung: Erfolgsfaktoren und sicheres Handeln. [Teamwork and Team leadership: Factors of success and reliable action], in Führung und Teamarbeit in kritischen Situationen [Leadership and teamwork in critical situations] eds C. Buerschaper and S. Starke (Frankfurt: Verlag für Polizeiwissenschaft), 3–19.

Beal, D. J., Cohen, R. R., Burke, M. J., and McLendon, C. L. (2003). Cohesion and performance in groups: a meta-analytic clarification of construct relations. J. Appl. Psychol. 88, 989–1004. doi: 10.1037/0021-9010.88.6.989

Bell, S. T. (2007). Deep-level composition variables as predictors of team performance: a meta-analysis. J. Appl. Psychol. 92, 595–615. doi: 10.1037/0021-9010.92.3.595

Bower, G. H., and Hilgard, E. R. (1981). Theories of Learning . Englewood Cliffs, NJ: Prentice-Hall.

Google Scholar

Bredenkamp, J. (1998). Lernen, Erinnern, Vergessen [Learning, Remembering, Forgetting]. München: C.H. Beck.

Brehmer, B. (1992). Dynamic decision-making: human control of complex systems. Acta Psychol. 81, 211–241. doi: 10.1016/0001-6918(92)90019-A

Brehmer, B., and Dörner, D. (1993). Experiments with computer-simulated microworlds: escaping both the narrow straits of the laboratory and the deep blue sea of the field study. Comput. Hum. Behav. 9, 171–184. doi: 10.1016/0747-5632(93)90005-D

Campion, M. A., Medsker, G. J., and Higgs, C. (1993). Relations between work group characteristics and effectiveness: implications for designing effective work groups. Pers. Psychol. 46, 823–850. doi: 10.1111/j.1744-6570.1993.tb01571.x

Cannon-Bowers, J. A., Salas, E., and Converse, S. (1993). “Shared mental models in expert team decision making,” in Individual and Group Decision Making , ed N. J. Castellan (Hillsdale, NJ: Lawrence Erlbaum Associates), 221–246.

Cannon-Bowers, J. A., Tannenbaum, S. I., Salas, E., and Volpe, C. E. (1995). “Defining competencies and establishing team training requirements,” in Team Effectiveness and Decision Making in Organizations , eds R. A. Guzzo and E. Salas and Associates (San Francisco, CA: Jossey-Bass), 333–380.

DeChurch, L. A., and Mesmer-Magnus, J. R. (2010). The cognitive underpinnings of effective teamwork: a meta-analysis. J. Appl. Psychol. 95, 32–53. doi: 10.1037/a0017328

Dierdorff, E. C., Bell, S. T., and Belohlav, J. A. (2011). The “power of we”: effects of psychological collectivism on team performance over time. J. Appl. Psychol. 96, 247–262. doi: 10.1037/a0020929

CrossRef Full Text

Dörner, D. (1989/2003). Die Logik des Misslingens. Strategisches Denken in komplexen Situationen [The logic of failure. Strategic thinking in complex situations] 11th Edn . Reinbeck: rororo.

Dörner, D., Kreuzig, H. W., Reither, F., and Stäudel, T. (1983). Lohhausen. Vom Umgang mit Unbestimmtheit und Komplexität. Bern; Stuttgart; Wien: Verlag Hans Huber.

Driskell, J. E., and Salas, E. (1992). Collective behavior and team performance. Hum. Factors 34, 277–288. doi: 10.1177/001872089203400303

Driskell, J., Salas, E., and Hughes, S. (2010). Collective orientation and team performance: development of an individual differences measure. Hum. Factors 52, 316–328. doi: 10.1177/0018720809359522

Eby, L. T., and Dobbins, G. H. (1997). Collectivistic orientation in teams: an individual and group-level analysis. J. Organ. Behav. 18, 275–295. doi: 10.1002/(SICI)1099-1379(199705)18:3<275::AID-JOB796>3.0.CO;2-C

Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Adm. Sci. Q. 44, 350–383. doi: 10.2307/2666999

Ellington, J. K., and Dierdorff, E. C. (2014). Individual learning in team training: self-regulation and team context effects. Small Group Res. 45, 37–67. doi: 10.1177/1046496413511670

Endsley, M. R. (1999). “Situation Awareness in Aviation Systems,” in Handbook of Aviation Human Factors , eds D. J. Garland, J. A. Wise, and V. D. Hopkin (Mahwah, NJ: Lawrence Erlbaum Associates Publishers), 257–276.

Endsley, M. R., and Robertson, M. M. (2000). “Training for Situation Awareness in Individuals and Teams,” in Situation awareness Analysis and Measurement , eds M. R. Endsley and D. J. Garland (Mahwah, NJ: Lawrence Erlbaum Associates Publishers), 349–365.

Fiore, S. M., Rosen, M. A., Smith-Jentsch, K. A., Salas, E., Letsky, M., and Warner, N. (2010). Toward an understanding of macrocognition in teams: predicting processes in complex collaborative contexts. Hum. Factors 52, 203–224. doi: 10.1177/0018720810369807

Fleishman, E. A., and Zaccaro, S. J. (1992). “Toward a taxonomy of team performance funtions,” in Teams: Their Training and Performance , eds R. W. Swezey and E. Salas (Norwood, NJ: Ables), 31–56.

Flin, R., O'Connor, P., and Crichton, M. (2008). Safety at the Sharp End. Aldershot: Ashgate.

Funke, J. (1995). “Experimental research on complex problem solving,” in Complex Problem Solving: The European Perspective eds P. A. Frensch and J. Funke (Hillsdale, NJ: Lawrence Erlbaum Associates), 243–268.

Funke, J. (2001). Daynamic systems as tools for analysing human judgement. Think. Reason. 7, 69–89. doi: 10.1080/13546780042000046

Funke, J. (2012). “Complex Problem Solving,” in Encyclopedia of the Sciences of Learning ed N. M. Seel (Heidelberg: Springer), 682–685.

Gabelica, C., van den Bossche, P., de Maeyer, S., Segers, M., and Gijselaers, W. (2014). The effect of team feedback and guided reflexivity on team performance change. Learn. Instruct. 34, 86–96. doi: 10.1016/j.learninstruc.2014.09.001

Gabelica, C., Van den Bossche, P., Segers, M., and Gijselaers, W. (2012). Feedback, a powerful lever in teams: a review. Educ. Res. Rev. 7, 123–144. doi: 10.1016/j.edurev.2011.11.003

Geister, S., Konradt, U., and Hertel, G. (2006). Effects of process feedback on motivation, satisfaction, and performance in virtual teams. Small Group Res. 37, 459–489. doi: 10.1177/1046496406292337

Gibson, C. B. (1999). Do they do what they believe they can? group efficacy and group effectiveness across tasks and cultures. Acad. Manag. J. 42, 138–152. doi: 10.2307/257089

Granlund, R. (2003). Monitoring experiences from command and control research with the C 3 Fire microworld. Cogn. Technol. Work 5, 183–190. doi: 10.1007/s10111-003-0129-8

Granlund, R., and Johansson, B. (2004). “Monitoring distributed collaboration in the C 3 Fire Microworld,” in Scaled Worlds: Development, Validation and Applications , eds G. Schiflett, L. R. Elliot, E. Salas, and M. D. Coovert (Aldershot: Ashgate), 37–48.

Granlund, R., Johansson, B., and Persson, M. (2001). “C3Fire a micro-world for collaboration training and investigations in the ROLF environment,” in Proceedings of 42nd Conference on Simulation and Modeling: Simulation in Theory and Practice (Porsgrunn).

Hackman, J. R. (1987). “The design of work teams,” in Handbook of Organizational Behavior ed J. W. Lorsch (Englewood Cliffs, NJ: Prentice-Hall), 315–342.

Hagemann, V. (2011). Trainingsentwicklung für High Responsibility Teams [Training development for High Responsibility Teams] . Lengerich: Pabst Verlag.

Hagemann, V. (2017). Development of a German-language questionnaire to measure collective orientation as an individual attitude. Swiss J. Psychol. 76, 91–105. doi: 10.1024/1421-0185/a000198

Hagemann, V., Kluge, A., and Ritzmann, S. (2011). High responsibility teams - Eine systematische Analyse von Teamarbeitskontexten für einen effektiven Kompetenzerwerb [A systematic analysis of teamwork contexts for effective competence acquisition]. Psychologie des Alltagshandelns 4, 22–42. Available online at: http://www.allgemeine-psychologie.info/cms/images/stories/allgpsy_journal/Vol%204%20No%201/hagemann_kluge_ritzmann.pdf

Hagemann, V., Kluge, A., and Ritzmann, S. (2012). Flexibility under complexity: work contexts, task profiles and team processes of high responsibility teams. Empl. Relat. 34, 322–338. doi: 10.1108/01425451211217734

Hertel, G., Konradt, U., and Orlikowski, B. (2004). Managing distance by interdependence: goal setting, task interdependence, and team-based rewards in virtual teams. Euro. J. Work Organ. Psychol. 13, 1–28. doi: 10.1080/13594320344000228

Hinsz, V., Tindale, R., and Vollrath, D. (1997). The emerging concept of groups as information processors. Psychol. Bull. 121, 43–64. doi: 10.1037/0033-2909.121.1.43

Hollingshead, A. B., Gupta, N., Yoon, K., and Brandon, D. (2012). “Transactive memory theory and teams: past, present, and future,” in Theories of Team Cognition , eds E. Salas, S. M. Fiore and M. Letsky (New York, NY: Routledge Taylor & Francis Group), 421–455.

Ilgen, D. R., Hollenbeck, J. R., Johnson, M., and Jundt, D. (2005). Teams in organizations: from input-process-output models to IMOI models. Annu. Rev. Psychol. 56, 517–543. doi: 10.1146/annurev.psych.56.091103.070250

Jobidon, M.-E., Muller-Gass, A., Duncan, M., and Blais, A.-R. (2012). The enhance of mental models and its impact on teamwork. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 56, 1703–1707. doi: 10.1177/1071181312561341

Jung, D. I., and Sosik, J. J. (2003). Group potency and collective efficacy. Group Organ. Manage. 28, 366–391. doi: 10.1177/1059601102250821

Kluge, A. (2014). The Acquisition of Knowledge and Skills for Taskwork and Teamwork to Control Complex Technical Systems : A Cognitive and Macroergonomics Perspective . Dordrecht: Springer.

Kluge, A., Hagemann, V., and Ritzmann, S. (2014). “Military crew resource management – Das Streben nach der bestmöglichen Teamarbeit [Striving for the best of teamwork],” in Psychologie für Einsatz und Notfall [Psychology for mission and emergency] , eds G. Kreim, S. Bruns and B. Völker (Bonn: Bernard & Graefe in der Mönch Verlagsgesellschaft mbH), 141–152.

Kluge, A., Sauer, J., Schüler, K., and Burkolter, D. (2009). Designing training for process control simulators: a review of empirical findings and current practices, theoretical issues in ergonomics Science 10, 489–509. doi: 10.1080/14639220902982192

Kozlowski, S. W. J., and Ilgen, D. R. (2006). Enhancing the effectiveness of work groups and teams. Psychol. Sci. Public Interest 7, 77–124. doi: 10.1111/j.1529-1006.2006.00030.x

Lafond, D., Jobidon, M.-E., Aubé, C., and Tremblay, S. (2011). Evidence of structure- specific teamwork requirements and implications for team design. Small Group Res. 42, 507–535. doi: 10.1177/1046496410397617

Marks, M. A., Mathieu, J. E., and Zaccaro, S. J. (2001). A temporally based framework and taxonomy of team processes. Acad. Manag. Rev. 26, 356–376. doi: 10.2307/259182

Mathieu, J. E., Heffner, T. S., Goodwin, G. F., Salas, E., and Cannon-Bowers, J. A. (2000). The influence of shared mental models on team process and performance. J. Appl. Psychol. 85, 273–283. doi: 10.1037/0021-9010.85.2.273

McAllister, D. J. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Acad. Manag. J. 38, 24–59. doi: 10.2307/256727

McGrath, J. E. (1984). Groups: Interaction and Performance . Englewood Cliffs, NJ: Prentice-Hall.

McGrath, J. E., Arrow, H., and Berdahl, J. L. (2000). The study of groups: past, present, and future. Pers. Soc. Psychol. Rev. 4, 95–105. doi: 10.1207/S15327957PSPR0401_8

McLeod, P. L., Liker, J. K., and Lobel, S. A. (1992). Process feedback in task groups: an application of goal setting. J. Appl. Behav. Sci. 28, 15–41. doi: 10.1177/0021886392281003

Morgan, B. B., Salas, E., and Glickman, A. S. (1993). An analysis of team evolution and maturation. J. Gen. Psychol. 120, 277–291. doi: 10.1080/00221309.1993.9711148

Ormerod, T. C., Richardson, J., and Shepherd, A. (1998). Enhancing the usability of a task analysis method: a notation and environment for requirements specification. Ergonomics 41, 1642–1663. doi: 10.1080/001401398186117

Preacher, K., and Hayes, A. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav. Res. Methods Instrum. Comput. 36, 717–731. doi: 10.3758/BF03206553

Prince, C., and Salas, E. (1993). “Training and research for teamwork in the military aircrew,” in Cockpit Resource Management , eds E. L. Wiener, B. G. Kanki, and R. L. Helmreich (San Diego, CA: Academic Press), 337–366.

Prussia, G. E., and Kinicki, A. J. (1996). A motivation investigation of group effectiveness using social-cognitive theory. J. Appl. Psychol. 81, 187–198. doi: 10.1037/0021-9010.81.2.187

Riordan, C. M., and Weatherly, E. W. (1999). Defining and measuring employees‘identification with their work groups. Educ. Psychol. Meas. 59, 310–324. doi: 10.1177/00131649921969866

Roth, E. M., and Woods, D. D. (1988). Aiding human performance i: cognitive analysis. Trav. Hum. 51, 39–64.

Salas, E., Cooke, N. J., and Rosen, M. A. (2008). On teams, teamwork, and team performance: discoveries and developments. Hum. Factors 50, 540–547. doi: 10.1518/001872008X288457

Salas, E., Nichols, D. R., and Driskell, J. E. (2007). Testing three team training strategies in intact teams. Small Group Res. 38, 471–488. doi: 10.1177/1046496407304332

Salas, E., Sims, D., and Burke, S. (2005). Is there a “big five” in teamwork? Small Group Res. 36, 555–599. doi: 10.1177/1046496405277134

Schmutz, J., Welp, A., and Kolbe, M. (2016). “Teamwork in healtcare organizations,” in Management Innovations for Health Care Organizations , eds A. Örtenblad, C. A. Löfström and R. Sheaff (New York, NY: Routledge Taylor & Francis), 359–377.

Serfaty, D., Entin, E. E., and Johnston, J. H. (1998). “Team coordination training,” in Making Decisions Under Stress , eds J. A. Cannon-Bowers and E. Salas (Washington, DC: American Psychological Association), 221–246.

Shea, G. P., and Guzzo, R. A. (1987). Group effectiveness: what really matters? Sloan Manage. Rev. 28, 25–31.

Smith-Jentsch, K. A., Baker, D. P., Salas, E., and Cannon-Bowers, J. A. (2001). “Uncovering differences in team competency requirements: The case of air traffic control teams,” in Improving Teamwork in Organizations. Applications of Resource Management Training , eds E. Salas, C. A. Bowers, and E. Edens (Mahwah, NJ: Lawrence Erlbaum Associates Publishers), 31–54.

Stajkovic, A. D., Lee, D., and Nyberg, A. J. (2009). Collective efficacy, group potency, and group performance: meta-analyses of their relationships, and test of a mediation model. J. Appl. Psychol. 94, 814–828. doi: 10.1037/a0015659

Stevens, M. J., and Campion, M. A. (1994). The knowledge, skill, and ability requirements for teamwork: implications for human resource management. J. Manage. 20, 503–530. doi: 10.1177/014920639402000210

Ulich, E. (1995). “Gestaltung von Arbeitstätigkeiten [Designing job tasks],” in Lehrbuch Organisationspsychologie [Schoolbook Organizational Psychology] , ed H. Schuler (Bern: Huber), 189–208.

Van de Ven, A. H., Delbecq, A. L., and Koenig, R. (1976). Determinants of coordination modes with organizations. Am. Sociol. Rev. 41, 322–338. doi: 10.2307/2094477

Wageman, R. (1995). Interdependence and group effectiveness. Adm. Sci. Q. 40, 145–180. doi: 10.2307/2393703

Waller, M. J., Gupta, N., and Giambatista, R. C. (2004). Effects of adaptive behaviors and shared mental models on control crew performance. Manage. Sci. 50, 1534–1544. doi: 10.1287/mnsc.1040.0210

Wilson, K. A., Salas, E., and Andrews, D. H. (2010). “Preventing errors in the heat of the battle: formal and informal learning strategies to prevent teamwork breakdowns,” in Human Factors Issues in Combat Identification , eds D. H. Andrews, R. P. Herz, and M. B. Wolf (Aldershot: Ashgate), 1–28.

Zsambok, C. E. (1997). “Naturalistic decision making: where are we now?,” in Naturalistic Decision Making , eds C. E. Zsambok and G. Klein (New York, NY: Routledge), 3–16.

Keywords: interdependence, team processes, complex problem solving, collective orientation, trust, cohesion, C3Fire, microworld

Citation: Hagemann V and Kluge A (2017) Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands. Front. Psychol . 8:1730. doi: 10.3389/fpsyg.2017.01730

Received: 04 May 2017; Accepted: 19 September 2017; Published: 29 September 2017.

Reviewed by:

Copyright © 2017 Hagemann and Kluge. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Vera Hagemann, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Lead an Effective Problem-Solving Meeting

There’s nothing worse than getting a group of smart people together to solve a problem and having the discussion devolve into chaos. This usually happens when people are at different stages of the problem-solving process. To get everyone on the same page, take a methodical approach and conquer one step at a time. First, ask: […]

There’s nothing worse than getting a group of smart people together to solve a problem and having the discussion devolve into chaos. This usually happens when people are at different stages of the problem-solving process. To get everyone on the same page, take a methodical approach and conquer one step at a time. First, ask: Does the team genuinely understand the problem it’s trying to solve? If you can’t clearly articulate it, draft a succinct problem statement. If the group understands the problem, but hasn’t yet produced a set of potential solutions, concentrate on generating as many quality options as possible. If you already have solutions, assess their strengths and weaknesses, and develop a list of pros and cons. Then you can use your time together to do the often difficult work of choosing a solution — and make sure that the final decision is in writing. The last stage, once you’ve selected the solution, is to develop an implementation plan. While conquering just one problem-solving stage at a time may feel a bit underwhelming at first, this methodical approach will often help the group leapfrog ahead, sometimes to the end of the problem-solving cycle.

Source: This tip is adapted from “Why Groups Struggle to Solve Problems Together,” by Al Pittampalli

Partner Center

How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

Want to subscribe to The McKinsey Podcast ?

Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

Would you like to learn more about our Strategy & Corporate Finance Practice ?

Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

Want better strategies? Become a bulletproof problem solver

Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

Explore a career with us

Related articles.

Strategy to beat the odds

Five routes to more innovative problem solving

4 The Psychology of Groups

From the noba project by  donelson r. forsyth, university of richmond.

PDF Download

Key topics:

• Group decision making
• Need to belong
• Self-esteem
• Social facilitation
• Social loafing

Learning Objectives

• Review the evidence that suggests humans have a fundamental need to belong to groups.
• Compare the sociometer model of self-esteem to a more traditional view of self-esteem.
• Use theories of social facilitation to predict when a group will perform tasks slowly or quickly (e.g., students eating a meal as a group, workers on an assembly line, or a study group).
• Summarize the methods used by Latané, Williams, and Harkins to identify the relative impact of social loafing and coordination problems on group performance.
• Describe how groups change over time.
• Apply the theory of groupthink to a well-known decision-making group, such as the group of advisors responsible for planning the Bay of Pigs operation.
• List and discuss the factors that facilitate and impede group performance and decision making.
• Develop a list of recommendations that, if followed, would minimize the possibility of groupthink developing in a group.

The Psychology of Groups

A thorough understanding of people requires a thorough understanding of groups. Each of us is an autonomous individual seeking our own objectives, yet we are also members of groups—groups that constrain us, guide us, and sustain us. Just as each of us influences the group and the people in the group, so, too, do groups change each one of us. Joining groups satisfies our need to belong , gain information and understanding through social comparison , define our sense of self and social identity , and achieve goals that might elude us if we worked alone . Groups are also practically significant, for much of the world’s work is done by groups rather than by individuals. Success sometimes eludes our groups, but when group members learn to work together as a cohesive team their success becomes more certain. People also turn to groups when important decisions must be made, and this choice is justified as long as groups avoid such problems as group polarization and groupthink.

Nearly all human activities—working, learning, worshiping, relaxing, playing, and even sleeping—occur in groups. The lone individual who is cut off from all groups is a rarity. Most of us live out our lives in groups, and these groups have a profound impact on our thoughts, feelings, and actions. Many psychologists focus their attention on single individuals, but social psychologists expand their analysis to include groups, organizations, communities, and even cultures.

To examine the psychology of groups and group membership, we begin with a basic question: What is the psychological significance of groups? People are, undeniably, more often in groups rather than alone. What accounts for this marked gregariousness and what does it say about our psychological makeup? The chapter reviews some of the key findings from studies of groups. Researchers have asked many questions about people and groups: Do people work as hard as they can when they are in groups? Are groups more cautious than individuals? Do groups make wiser decisions than single individuals? In many cases the answers are not what common sense and folk wisdom might suggest.

The Psychological Significance of Groups

Many people loudly proclaim their autonomy and independence. Like Ralph Waldo Emerson, they avow, “I must be myself. I will not hide my tastes or aversions . . . . I will seek my own” (1903/2004, p. 127). Even though people are capable of living separate and apart from others, they join with others because groups meet their psychological and social needs.

The Need to Belong

Across individuals, societies, and even eras, humans consistently seek inclusion over exclusion, membership over isolation, and acceptance over rejection. As Roy Baumeister and Mark Leary (1995) conclude, humans have a  need to belong:  “a pervasive drive to form and maintain at least a minimum quantity of lasting, positive, and impactful interpersonal relationships” (p. 497). And most of us satisfy this need by joining groups. When surveyed, 87.3% of Americans reported that they lived with other people, including family members, partners, and roommates (Davis & Smith, 2007). The majority, ranging from 50% to 80%, reported regularly doing things in groups, such as attending a sports event together, visiting one another for the evening, sharing a meal together, or going out as a group to see a movie (Putnam, 2000).

People respond negatively when their need to belong is unfulfilled. People who are accepted members of a group tend to feel happier and more satisfied. But should they be rejected by a group, they feel unhappy, helpless, and depressed. Studies of  ostracism —the deliberate exclusion from groups—indicate this experience is highly stressful and can lead to depression, confused thinking, and even aggression (Williams, 2007). When researchers used a functional magnetic resonance imaging scanner to track neural responses to exclusion, they found that people who were left out of a group activity displayed heightened cortical activity in two specific areas of the brain—the dorsal anterior cingulate cortex and the anterior insula. These areas of the brain are associated with the experience of physical pain sensations (Eisenberger et al., 2003). It hurts, quite literally, to be left out of a group.

Affiliation in Groups

Groups not only satisfy the need to belong, they also provide members with information, assistance, and social support. Leon Festinger’s theory of  social comparison  (1950, 1954) suggested that in many cases people join with others to evaluate the accuracy of their personal beliefs and attitudes. Stanley Schachter (1959) explored this process by putting individuals in ambiguous, stressful situations and asking them if they wished to wait alone or with others. He found that people  affiliate  in such situations—they seek the company of others.

Although any kind of companionship is appreciated, we prefer those who provide us with reassurance and support as well as accurate information. In some cases, we also prefer to join with others who are even worse off than we are. Imagine, for example, how you would respond when the teacher hands back the test and yours is marked 85%. Do you want to affiliate with a friend who got a 95% or a friend who got a 78%? To maintain a sense of self-worth, people seek out and compare themselves to the less fortunate. This process is known as  downward social comparison .

Identity and Membership

Groups are not only founts of information during times of ambiguity, they also help us answer the existentially significant question, “Who am I?” People are defined not only by their traits, preferences, interests, likes, and dislikes, but also by their friendships, social roles, family connections, and group memberships. The self is not just a “me,” but also a “we.”

Even demographic qualities such as sex or age can influence us if we categorize ourselves based on these qualities.  Social identity theory, for example, assumes that we don’t just classify  other  people into such social categories as man, woman, Anglo, elderly, or college student, but we also categorize ourselves. According to Tajfel and Turner (1986), social identities are directed by our memberships in particular groups. or social categories. If we strongly identify with these categories, then we will ascribe the characteristics of the typical member of these groups to ourselves, and so stereotype ourselves. If, for example, we believe that college students are intellectual, then we will assume we, too, are intellectual if we identify with that group (Hogg, 2001).

Groups also provide a variety of means for maintaining and enhancing a sense of self-worth, as our assessment of the quality of groups we belong to influences our  collective self-esteem  (Crocker & Luhtanen, 1990). If our self-esteem is shaken by a personal setback, we can focus on our group’s success and prestige. In addition, by comparing our group to other groups, we frequently discover that we are members of the better group, and so can take pride in our superiority. By denigrating other groups, we elevate both our personal and our collective self-esteem (Crocker & Major, 1989).

Mark Leary’s sociometer model even suggests that “self-esteem is part of a sociometer that monitors peoples’ relational value in other people’s eyes” (2007, p. 328). He maintains self-esteem is not just an index of one’s sense of personal value , but also an indicator of acceptance into groups . Lowered feelings of self-worth, then, prompt us to search for and correct characteristics and qualities that put us at risk of social exclusion. Self-esteem is not just high self-regard, but the self-approbation that we feel when included in groups (Leary & Baumeister, 2000).

Evolutionary Advantages of Group Living

Groups may be humans’ most useful invention, for they provide us with the means to reach goals that would elude us if we remained alone. Individuals in groups can secure advantages and avoid disadvantages that would plague the lone individuals. In his theory of social integration, Moreland concludes that groups tend to form whenever “people become dependent on one another for the satisfaction of their needs” (1987, p. 104). The advantages of group life may be so great that humans are biologically prepared to seek membership and avoid isolation. From an evolutionary psychology perspective, because groups have increased humans’ overall fitness for countless generations, individuals who carried genes that promoted solitude-seeking were less likely to survive and procreate compared to those with genes that prompted them to join groups (Darwin, 1859/1963). This process of natural selection culminated in the creation of a modern human who seeks out membership in groups instinctively, for most of us are descendants of “joiners” rather than “loners.”

Motivation and Performance

Social facilitation in groups.

Do people perform more effectively when alone or when part of a group? Norman Triplett (1898) examined this issue in one of the first empirical studies in psychology. While watching bicycle races, Triplett noticed that cyclists were faster when they competed against other racers than when they raced alone against the clock. To determine if the presence of others leads to the psychological stimulation that enhances performance, he arranged for 40 children to play a game that involved turning a small reel as quickly as possible (see Figure 1). When he measured how quickly they turned the reel, he confirmed that children performed slightly better when they played the game in pairs compared to when they played alone (see Stroebe, 2012; Strube, 2005).

Triplett succeeded in sparking interest in a phenomenon now known as  social facilitation : the enhancement of an individual’s performance when that person works in the presence of other people. However, it remained for Robert Zajonc (1965) to specify when social facilitation does and does not occur. After reviewing prior research, Zajonc noted that the facilitating effects of an audience usually only occur when the task requires the person to perform dominant responses (i.e., ones that are well-learned or based on instinctive behaviors). If the task requires nondominant responses (i.e., novel, complicated, or untried behaviors that the organism has never performed before or has performed only infrequently) then the presence of others inhibits performance. Hence, students write poorer quality essays on complex philosophical questions when they labor in a group rather than alone (Allport, 1924), but they make fewer mistakes in solving simple, low-level multiplication problems with an audience or a coactor than when they work in isolation (Dashiell, 1930). Social facilitation, then, depends on the task: other people facilitate performance when the task is so simple that it requires only dominant responses, but others interfere when the task requires nondominant responses.

Social Loafing

Groups usually outperform individuals. A single student, working alone on a paper, will get less done in an hour than will four students working on a group project. One person playing a tug-of-war game against a group will lose. A crew of movers can pack up and transport your household belongings faster than you can by yourself. As the saying goes, “Many hands make light the work” (Littlepage, 1991; Steiner, 1972).

Exploration Activity It is axiomatic (self-evidence, hard to disprove) that “many hands make light work.” What are three tasks where many hands (hearts, minds, etc.) make work easier? What are three tasks where having more people involved might make the work more difficult?

Groups, though, tend to be underachievers. Studies of social facilitation confirmed the positive motivational benefits of working with other people on well-practiced tasks in which each member’s contribution to the collective enterprise can be identified and evaluated. But what happens when tasks require a truly collective effort? First, when people work together they must coordinate their individual activities and contributions to reach the maximum level of efficiency—but they rarely do (Diehl & Stroebe, 1987). Three people in a tug-of-war competition, for example, invariably pull and pause at slightly different times, so their efforts are uncoordinated. The result is  coordination loss : the three-person group is stronger than a single person, but not three times as strong. Second, people just don’t exert as much effort when working on a collective endeavor, nor do they expend as much cognitive effort trying to solve problems, as they do when working alone. They display social loafing (Latané, 1981).

Latané, Williams, and Harkins (1979) examined both coordination losses and social loafing by arranging for students to cheer or clap either alone or in groups of varying sizes. The students cheered alone or in 2- or 6-person groups, or they were lead to believe they were in 2- or 6-person groups (those in the “pseudo-groups” wore blindfolds and headsets that played masking sound). As Figure 2 indicates, groups generated more noise than solitary subjects, but the productivity dropped as the groups became larger in size. In dyads, each subject worked at only 66% of capacity, and in 6-person groups at 36%. Productivity also dropped when subjects merely believed they were in groups. With noise cancelling headphones on, if subjects thought that one other person was shouting with them, they shouted 82% as intensely, and if they thought five other people were shouting, they reached only 74% of their capacity. These loses in productivity were not due to coordination problems; this decline in production could be attributed only to a reduction in effort—to social loafing (Latané et al., 1979, Experiment 2).

Social loafing is not a rare phenomenon. When sales personnel work in groups with shared goals, they tend to “take it easy” if another salesperson is nearby who can do their work (George, 1992). People who are trying to generate new, creative ideas in group brainstorming sessions usually put in less effort and are thus less productive than people who are generating new ideas individually (Paulus & Brown, 2007). Students assigned group projects often complain of inequity in the quality and quantity of each member’s contributions: Some people just don’t work as much as they should to help the group reach its learning goals (Neu, 2012). People carrying out all sorts of physical and mental tasks expend less effort when working in groups, and the larger the group, the more they loaf (Karau & Williams, 1993).

Groups can, however, overcome this impediment to performance through  teamwork . A group may include many talented individuals, but they must learn how to pool their individual abilities and energies to maximize the team’s performance. Team goals must be set, work patterns structured, and a sense of group identity developed. Individual members must learn how to coordinate their actions, and any strains and stresses in interpersonal relations need to be identified and resolved (Salas et al., 2009).

Researchers have identified two key ingredients to effective teamwork: a shared mental representation of the task and group unity. Teams improve their performance over time as they develop a shared understanding of the team and the tasks they are attempting. Some semblance of this  shared mental model is present nearly from its inception, but as the team practices, differences among the members in terms of their understanding of their situation and their team diminish as a consensus becomes implicitly accepted (Tindale et al., 2008). Effective teams are also, in most cases, cohesive groups (Dion, 2000).  Group cohesion is the integrity, solidarity, social integration, or unity of a group. In most cases, members of cohesive groups like each other and the group and they also are united in their pursuit of collective, group-level goals. Members tend to enjoy their groups more when they are cohesive, and cohesive groups usually outperform ones that lack cohesion. This cohesion-performance relationship, however, is a complex one. Meta-analytic studies suggest that cohesion improves teamwork among members, but that performance quality influences cohesion more than cohesion influences performance (Mullen & Copper, 1994; Mullen et al., 1998; see Figure 3). Cohesive groups also can be spectacularly unproductive if the group’s norms stress low productivity rather than high productivity (Seashore, 1954).

Group Development

In most cases groups do not become smooth-functioning teams overnight. As Bruce Tuckman’s (1965) theory of group development suggests, groups usually pass through several stages of development as they change from a newly formed group into an effective team. As noted in Focus Topic 1, in the  forming  phase, the members become oriented toward one another. In the  storming  phase, the group members find themselves in conflict, and some solution is sought to improve the group environment. In the  norming ,  phase standards for behavior and roles develop that regulate behavior. In the  performing ,  phase the group has reached a point where it can work as a unit to achieve desired goals, and the  adjourning  phase ends the sequence of development; the group disbands. Throughout these stages groups tend to oscillate between the task-oriented issues and the relationship issues, with members sometimes working hard but at other times strengthening their interpersonal bonds (Tuckman & Jensen, 1977).

Focus Topic 1: Group Development Stages and Characteristics

Stage 1 – “Forming”. Members expose information about themselves in polite but tentative interactions. They explore the purposes of the group and gather information about each other’s interests, skills, and personal tendencies.

Stage 2 – “Storming”. Disagreements about procedures and purposes surface, so criticism and conflict increase. Much of the conflict stems from challenges between members who are seeking to increase their status and control in the group.

Stage 3 – “Norming”. Once the group agrees on its goals, procedures, and leadership, norms, roles, and social relationships develop that increase the group’s stability and cohesiveness.

Stage 4 – “Performing”. The group focuses its energies and attention on its goals, displaying higher rates of task-orientation, decision-making, and problem-solving.

Stage 5 – “Adjourning”. The group prepares to disband by completing its tasks, reduces levels of dependency among members, and dealing with any unresolved issues.

Sources based on Tuckman (1965) and Tuckman & Jensen (1977)

We also experience change as we pass through a group: We don’t become full-fledged members of a group in an instant. Instead, we gradually become a part of the group and remain in the group until we leave it. Moreland and Levine’s (1982) model of group socialization describes this process, beginning with initial entry into the group and ending when the member exits it. For example, when you are thinking of joining a new group—a social club, a professional society, a fraternity or sorority, or a sports team—you investigate what the group has to offer, but the group also investigates you. During this investigation stage you are still an outsider: interested in joining the group, but not yet committed to it in any way. But once the group accepts you and you accept the group, socialization begins: you learn the group’s norms and take on different responsibilities depending on your role. On a sports team, for example, you may initially hope to be a star who starts every game or plays a particular position, but the team may need something else from you. In time, though, the group will accept you as a full-fledged member and both sides in the process—you and the group itself—increase their commitment to one another. When that commitment wanes, however, your membership may come to an end as well.

Making Decisions in Groups

Groups are particularly useful when it comes to making a decision, for groups can draw on more resources than can a lone individual. A single individual may know a great deal about a problem and possible solutions, but his or her information is far surpassed by the combined knowledge of a group. Groups not only generate more ideas and possible solutions by discussing the problem, but they can also more objectively evaluate the options that they generate during discussion. Before accepting a solution, a group may require that a certain number of people favor it, or that it meets some other standard of acceptability. People generally feel that a group’s decision will be superior to an individual’s decision.

Groups, however, do not always make good decisions. For example, juries sometimes render verdicts that run counter to the evidence presented. Community groups take radical stances on issues before thinking through all the ramifications. Military strategists concoct plans that seem, in retrospect, ill-conceived and short-sighted. Why do groups sometimes make poor decisions?

Group Polarization

Let’s say you are part of a group assigned to make a presentation. One of the group members suggests showing a short video that, although amusing, includes some provocative images. Even though initially you think the clip is inappropriate, you begin to change your mind as the group discusses the idea. The group decides, eventually, to throw caution to the wind and show the clip—and your instructor is horrified by your choice.

This hypothetical example is consistent with studies of groups making decisions that involve risk. Common sense notions suggest that groups exert a moderating, subduing effect on their members. However, when researchers looked at groups closely, they discovered many groups shift toward more extreme decisions rather than less extreme decisions after group interaction. Discussion, it turns out, doesn’t moderate people’s judgments after all. Instead, it leads to  group polarization: judgments made after group discussion will be more extreme in the same direction as the average of individual judgments made prior to discussion (Myers & Lamm, 1976). If a majority of members feel that taking risks is more acceptable than exercising caution, then the group will become riskier after a discussion. For example, in France, where people generally like their government but dislike Americans, group discussion improved their attitude toward their government but exacerbated their negative opinions of Americans (Moscovici & Zavalloni, 1969). Similarly, prejudiced people who discussed racial issues with other prejudiced individuals became even more negative, but those who were relatively unprejudiced exhibited even more acceptance of diversity when in groups (Myers & Bishop, 1970).

Groups sometimes make spectacularly bad decisions. In 1961, a special advisory committee to President John F. Kennedy planned and implemented a covert invasion of Cuba at the Bay of Pigs that ended in total disaster. In 1986, NASA carefully, and incorrectly, decided to launch the Challenger space shuttle in temperatures that were too cold.

Irving Janis (1982), intrigued by these kinds of blundering groups, carried out a number of case studies of such groups: the military experts that planned the defense of Pearl Harbor; Kennedy’s Bay of Pigs planning group; the presidential team that escalated the war in Vietnam. Each group, he concluded, fell prey to a distorted style of thinking that rendered the group members incapable of making a rational decision. Janis labeled this syndrome  groupthink: “a mode of thinking that people engage in when they are deeply involved in a cohesive in-group, when the members’ strivings for unanimity override their motivation to realistically appraise alternative courses of action” (p. 9).

Janis identified both the telltale symptoms that signal the group is experiencing groupthink and the interpersonal factors that combine to cause groupthink. These symptoms include overestimating the group’s skills and wisdom, biased perceptions and evaluations of other groups and people who are outside of the group, strong conformity pressures within the group, and poor decision-making methods.

Janis also singled out four group-level factors that combine to cause groupthink: cohesion, isolation, biased leadership, and decisional stress.

• Cohesion : Groupthink only occurs in cohesive groups. Such groups have many advantages over groups that lack unity. People enjoy their membership much more in cohesive groups, they are less likely to abandon the group, and they work harder in pursuit of the group’s goals. But extreme cohesiveness can be dangerous. When cohesiveness intensifies, members become more likely to accept the goals, decisions, and norms of the group without reservation. Conformity pressures also rise as members become reluctant to say or do anything that goes against the grain of the group, and the number of internal disagreements—necessary for good decision making—decreases.
• Isolation. Groupthink groups too often work behind closed doors, keeping out of the limelight. They isolate themselves from outsiders and refuse to modify their beliefs to bring them into line with society’s beliefs. They avoid leaks by maintaining strict confidentiality and working only with people who are members of their group.
• Biased leadership . A biased leader who exerts too much authority over group members can increase conformity pressures and railroad decisions. In groupthink groups, the leader determines the agenda for each meeting, sets limits on discussion, and can even decide who will be heard.
• Decisional stress. Groupthink becomes more likely when the group is stressed, particularly by time pressures. When groups are stressed they minimize their discomfort by quickly choosing a plan of action with little argument or dissension. Then, through collective discussion, the group members can rationalize their choice by exaggerating the positive consequences, minimizing the possibility of negative outcomes, concentrating on minor details, and overlooking larger issues.

Groupthink, thus, represents and issue with group process. Members in groups that fall victim to groupthink do not spend enough time, energy, or effort on meaningful process (Kramer & Dougherty, 2013). It is also important to note that cohesion alone is not sufficient to prompt groupthink. Teams who are vigilant against biased decision making can avoid problematic groupthink process.

You and Your Groups

Most of us belong to at least one group that must make decisions from time to time: a community group that needs to choose a fund-raising project; a union or employee group that must ratify a new contract; a family that must discuss your college plans; or the staff of a high school discussing ways to deal with the potential for violence during football games. Could these kinds of groups experience groupthink? Yes they could, if the symptoms of groupthink discussed above are present, combined with other contributing causal factors, such as cohesiveness, isolation, biased leadership, and stress. To avoid polarization, the common knowledge effect, and groupthink, groups should strive to emphasize open inquiry of all sides of the issue while admitting the possibility of failure. The leaders of the group can also do much to limit groupthink by requiring full discussion of pros and cons, appointing devil’s advocates, and breaking the group up into small discussion groups.

If these precautions are taken, your group has a much greater chance of making an informed, rational decision. Furthermore, although your group should review its goals, teamwork, and decision-making strategies, the human side of groups—the strong friendships and bonds that make group activity so enjoyable—shouldn’t be overlooked. Groups have instrumental, practical value, but also emotional, psychological value. In groups we find others who appreciate and value us. In groups, we gain the support we need in difficult times, but also have the opportunity to influence others. In groups we find evidence of our self-worth, and secure ourselves from the threat of loneliness and despair. For most of us, groups are the secret source of well-being.

Take a Quiz:

An optional quiz is available for this unit here: https://nobaproject.com/modules/the-psychology-of-groups

Discussion Questions

• What are the advantages and disadvantages of sociality? Why do people often join groups?
• Is self-esteem shaped by your personality qualities or by the value and qualities of groups to which you belong?
• In what ways does membership in a group change a person’s self-concept and social identity?
• What steps would you take if you were to base a self-esteem enrichment program in schools on the sociometer model of self-worth?
• If you were a college professor, what would you do to increase the success of in-class learning teams?
• What are the key ingredients to transforming a working group into a true team?
• Have you ever been part of a group that made a poor decision and, if so, were any of the symptoms of groupthink present in your group?

Outside Resources

https://youtube.com/watch?v=7EYAUazLI9k%3Fcolor%3Dred%26modestbranding%3D1%26showinfo%3D0%26origin%3Dhttps%3A

• Allport, F. H. (1924).  Social psychology . Boston: Houghton Mifflin.
• Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation.  Psychological Bulletin, 117 , 497–529.
• Blascovich, J., Mendes, W. B., Hunter, S. B., & Salomon, K. (1999). Social “facilitation” as challenge and threat.  Journal of Personality and Social Psychology, 77 , 68–77.
• Bond, C. F., Atoum, A. O., & VanLeeuwen, M. D. (1996). Social impairment of complex learning in the wake of public embarrassment.  Basic and Applied Social Psychology, 18 , 31–44.
• Buote, V. M., Pancer, S. M., Pratt, M. W., Adams, G., Birnie-Lefcovitch, S., Polivy, J., & Wintre, M. G. (2007). The importance of friends: Friendship and adjustment among 1st-year university students.  Journal of Adolescent Research, 22(6) , 665–689.
• Crocker, J., & Luhtanen, R. (1990). Collective self-esteem and ingroup bias.  Journal of Personality and Social Psychology, 58 , 60–67.
• Crocker, J., & Major, B. (1989). Social stigma and self-esteem: The self-protective properties of stigma.  Psychological Review, 96 , 608–630.
• Darwin, C. (1859/1963).  The origin of species . New York: Washington Square Press.
• Dashiell, J. F. (1930). An experimental analysis of some group effects.  Journal of Abnormal and Social Psychology, 25 , 190–199.
• Davis, J. A., & Smith, T. W. (2007).  General social surveys (1972–2006) . [machine-readable data file]. Chicago: National Opinion Research Center & Storrs, CT: The Roper Center for Public Opinion Research. Retrieved from http://www.norc.uchicago.edu
• Diehl, M., & Stroebe, W. (1987). Productivity loss in brainstorming groups: Toward the solution of a riddle.  Journal of Personality and Social Psychology, 53 , 497–509.
• Dion, K. L. (2000). Group cohesion: From “field of forces” to multidimensional construct.  Group Dynamics: Theory, Research, and Practice, 4 , 7–26.
• Eisenberger, N. I., Lieberman, M. D., & Williams, K. D. (2003). Does rejection hurt? An fMRI study of social exclusion.  Science, 302 , 290–292.
• Emerson, R. W. (2004).  Essays and poems by Ralph Waldo Emerson . New York: Barnes & Noble. (originally published 1903).
• Festinger, L. (1954). A theory of social comparison processes.  Human Relations, 7 , 117–140.
• Festinger, L. (1950). Informal social communication.  Psychological Review, 57 , 271–282.
• George, J. M. (1992). Extrinsic and intrinsic origins of perceived social loafing in organizations.  Academy of Management Journal, 35 , 191–202.
• Harkins, S. G. (2006). Mere effort as the mediator of the evaluation-performance relationship.  Journal of Personality and Social Psychology, 91(3) , 436–455.
• Hogg, M. A. (2001). Social categorization, depersonalization, and group behavior. In M. A. Hogg & R. S. Tindale (Eds.),  Blackwell handbook of social psychology: Group processes  (pp. 56–85). Malden, MA: Blackwell.
• Huguet, P., Galvaing, M. P., Monteil, J. M., & Dumas, F. (1999). Social presence effects in the Stroop task: Further evidence for an attentional view of social facilitation.  Journal of Personality and Social Psychology, 77 , 1011–1025.
• Janis, I. L. (1982).  Groupthink: Psychological studies of policy decisions and fiascos  (2nd ed.). Boston: Houghton Mifflin.
• Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta-analytic review and theoretical integration.  Journal of Personality and Social Psychology, 65 , 681–706.
• Kramer, M. W., & Dougherty, D. S. (2013). Groupthink as communication process, not outcome.  Communication & Social Change ,  1 (1), 44-62.
• Latané, B. (1981). The psychology of social impact.  American Psychologist, 36 , 343–356.
• Latané, B., Williams, K., & Harkins, S. (1979). Many hands make light the work: The causes and consequences of social loafing.  Journal of Personality and Social Psychology, 37 , 822–832.
• Leary, M. R. (2007). Motivational and emotional aspects of the self.  Annual Review of Psychology, 58 , 317–344.
• Leary, M. R. & Baumeister, R. F. (2000). The nature and function of self-esteem: Sociometer theory.  Advances in Experimental Social Psychology, 32 , 1–62.
• Littlepage, G. E. (1991). Effects of group size and task characteristics on group performance: A test of Steiner’s model.  Personality and Social Psychology Bulletin, 17 , 449–456.
• Moreland, R. L. (1987). The formation of small groups.  Review of Personality and Social Psychology, 8 , 80–110.
• Moreland, R. L., & Levine, J. M. (1982). Socialization in small groups: Temporal changes in individual-group relations.  Advances in Experimental Social Psychology, 15 , 137–192.
• Moscovici, S., & Zavalloni, M. (1969). The group as a polarizer of attitudes.  Journal of Personality and Social Psychology, 12 , 125–135.
• Mullen, B., & Copper, C. (1994). The relation between group cohesiveness and performance: An integration.  Psychological Bulletin, 115 , 210–227.
• Mullen, B., Driskell, J. E., & Salas, E. (1998). Meta-analysis and the study of group dynamics.  Group Dynamics: Theory, Research, and Practice, 2 , 213–229.
• Myers, D. G., & Bishop, G. D. (1970). Discussion effects on racial attitudes.  Science, 169 , 778–789.
• Myers, D. G., & Lamm, H. (1976). The group polarization phenomenon.  Psychological Bulletin, 83 , 602–627.
• Neu, W. A. (2012). Unintended cognitive, affective, and behavioral consequences of group assignments.  Journal of Marketing Education, 34 (1), 67–81.
• Paulus, P. B., & Brown, V. R. (2007). Toward more creative and innovative group idea generation: A cognitive-social-motivational perspective of brainstorming.  Social and Personality Psychology Compass, 1 , 248–265.
• Putnam, R. D. (2000).  Bowling alone: The collapse and revival of American community . New York: Simon & Schuster.
• Salas, E., Rosen, M. A., Burke, C. S., & Goodwin, G. F. (2009). The wisdom of collectives in organizations: An update of the teamwork competencies. In E. Salas, G. F. Goodwin, & C. S. Burke (Eds.),  Team effectiveness in complex organizations: Cross-disciplinary perspectives and approaches  (pp. 39–79). New York: Routledge/Taylor & Francis Group.
• Schachter, S. (1959).  The psychology of affiliation . Stanford, CA: Stanford University Press.
• Seashore, S. E. (1954).  Group cohesiveness in the industrial work group . Ann Arbor, MI: Institute for Social Research.
• Stasser, G., & Titus, W. (1987). Effects of information load and percentage of shared information on the dissemination of unshared information during group discussion.  Journal of Personality and Social Psychology, 53 , 81–93.
• Steiner, I. D. (1972).  Group process and productivity . New York: Academic Press.
• Stroebe, W. (2012). The truth about Triplett (1898), but nobody seems to care.  Perspectives on Psychological Science, 7 (1), 54–57.
• Strube, M. J. (2005). What did Triplett really find? A contemporary analysis of the first experiment in social psychology.  American Journal of Psychology, 118 , 271–286.
• Tajfel, H. & Turner, J.C. (1986). The social identity theory of inter-group behavior. In S. Worchel & L.W. Austin (Eds.), Psychology of Intergroup Relations. (pp. 7-24)Chicago, IL: Nelson-Hall
• Tindale, R. S., Stawiski, S., & Jacobs, E. (2008). Shared cognition and group learning. In V. I. Sessa & M. London (Eds.),  Work group learning: Understanding, improving and assessing how groups learn in organizations  (pp. 73–90). New York: Taylor & Francis Group.
• Triplett, N. (1898). The dynamogenic factors in pacemaking and competition.  American Journal of Psychology, 9 , 507–533.
• Tuckman, B. W. (1965). Developmental sequences in small groups.  Psychological Bulletin, 63 , 384–399.
• Tuckman, B. W., & Jensen, M. A. C. (1977). Stages of small group development revisited.  Group and Organizational Studies, 2 , 419–427.
• Williams, K. D. (2007). Ostracism.  Annual Review of Psychology, 58 , 425–452.
• Zajonc, R. B. (1965). Social facilitation.  Science, 149 , 269–274.

Donelson R. Forsyth, a social and personality psychologist, holds the Colonel Leo K. and Gaylee Thorsness Endowed Chair in Ethical Leadership at the Jepson School of Leadership Studies at the University of Richmond. A fellow of the American Psychological Association, he researches and writes about ethics, groups, and related topics.

How to cite this Noba module using APA Style

Forsyth, D. R. (2019). The psychology of groups. In R. Biswas-Diener & E. Diener (Eds),  Noba textbook series: Psychology.  Champaign, IL: DEF publishers. DOI: nobaproject.com

a pervasive drive to form and maintain at least a minimum quantity of lasting, positive, and impactful interpersonal relationships

Excluding one or more individuals from a group by reducing or eliminating contact with the person, usually by ignoring, shunning, or explicitly banishing them.

The process of contrasting one’s personal qualities and outcomes, including beliefs, attitudes, values, abilities, accomplishments, and experiences, to those of other people.

the process of comparing ones self to someone else who is in a lesser position (e.g., worse off, more challenged, with fewer resources, etc.)

A theoretical analysis of group processes and intergroup relations that assumes groups influence their members’ self-concepts and self-esteem, particularly when individuals categorize themselves as group members and identify with the group.

Feelings of self-worth that are based on evaluation of relationships with others and membership in social groups.

Improvement in task performance that occurs when people work in the presence of other people.

Responses to stimuli which are well-learned or based on instinctive behaviors

novel, complicated, or untried behaviors that the organism has never performed before or has performed only infrequently)

the amount of energy lost when working in a group or team. This includes the time, energy, and effort associated with coordination.

The reduction of individual effort exerted when people work in groups compared with when they work alone.

The process by which members of the team combine their knowledge, skills, abilities, and other resources through a coordinated series of actions to produce an outcome.

Knowledge, expectations, conceptualizations, and other cognitive representations that members of a group have in common pertaining to the group and its members, tasks, procedures, and resources.

The solidarity or unity of a group resulting from the development of strong and mutual interpersonal bonds among members and group-level forces that unify the group, such as shared commitment to group goals.

The tendency for members of a deliberating group to move to a more extreme position, with the direction of the shift determined by the majority or average of the members’ predeliberation preferences.

A set of negative group-level processes, including illusions of invulnerability, self-censorship, and pressures to conform, that occur when highly cohesive groups seek concurrence when making a decision.

The Psychology of Groups Copyright © 2021 by Cameron W. Piercy, Ph.D. is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

• Product overview
• All features
• App integrations

CAPABILITIES

• project icon Project management
• Project views
• Custom fields
• Status updates
• goal icon Goals and reporting
• Reporting dashboards
• workflow icon Workflows and automation
• portfolio icon Resource management
• Time tracking
• my-task icon Admin and security
• Admin console
• asana-intelligence icon Asana Intelligence
• list icon Personal
• premium icon Starter
• briefcase icon Advanced
• Goal management
• Organizational planning
• Campaign management
• Creative production
• Content calendars
• Marketing strategic planning
• Resource planning
• Project intake
• Product launches
• Employee onboarding
• View all uses arrow-right icon
• Project plans
• Team goals & objectives
• Team continuity
• Meeting agenda
• View all templates arrow-right icon
• Work management resources Discover best practices, watch webinars, get insights
• What's new Learn about the latest and greatest from Asana
• Customer stories See how the world's best organizations drive work innovation with Asana
• Help Center Get lots of tips, tricks, and advice to get the most from Asana
• Asana Academy Sign up for interactive courses and webinars to learn Asana
• Developers Learn more about building apps on the Asana platform
• Community programs Connect with and learn from Asana customers around the world
• Events Find out about upcoming events near you
• Partners Learn more about our partner programs
• Support Need help? Contact the Asana support team
• Asana for nonprofits Get more information on our nonprofit discount program, and apply.

Featured Reads

• Business strategy |
• Problem management: 8 steps to better p ...

Problem management: 8 steps to better problem solving

Problem management is an 8 step framework most commonly used by IT teams. You can use problem management to solve for repeating major incidents. By organizing and structuring your problem solving, you can more effectively get to the root cause of high-impact problems—and devise a solution. Solving the root cause prevents recurrence and creates a repeatable solution to use on similar errors in the future.

In an IT department, errors and mishaps are part of the job. You can't always control these problems, but you can control how you respond to them with problem management. Problem management helps you solve larger problems and reduce the risk that they’ll happen again by identifying all connected problems, solving them, and planning for the future.

What is problem management?

Problem management is an 8 step framework most commonly used by IT teams. Your team can use problem management to solve for repeating major incidents. By organizing and structuring your problem solving, you can more effectively get to the root cause of high-impact problems—and devise a solution. Problem management is a process—used mostly by IT teams—to identify, react, and respond to issues. It’s not for every problem, but it’s a useful response when multiple major incidents occur that cause large work interruptions. Unlike problem solving, problem management goes beyond the initial incident to discover and dissect the root causes, preventing future incidents with permanent solutions.

The goals of problem management are to:

Prevent problems before they start.

Solve for repetitive errors.

Lessen each incident’s impact. 

Problem management vs. incident management 

Example: Someone leaves their unprotected laptop in a coffee shop, causing a security breach. The security team can use incident management to solve for this one, isolated event. In this case, the team could manually shut down the accounts connected to that laptop. If this continues to happen, IT would use problem management to solve the root of this issue—perhaps installing more security features on each company laptop so that if employees lose them, no one else can access the information.

Problem management vs. problem solving

While similar in name, problem management differs slightly from problem-solving. Problem management focuses on every aspect of the incident—identifying the root cause of the problem, solving it, and prevention. Problem solving is, as the name implies, focused solely on the solution step. 

Example: You’re launching a new password management system when it crashes—again. You don’t know if anything leaked, but you know it could contain confidential information. Plus, it’s happened before. You start the problem management process to ensure it doesn’t happen again. In that process, you’ll use problem solving as a step to fix the issue. In this case, perhaps securing confidential information before you try to launch a new software.

Problem management vs. change management 

Change management targets large transitions within your workplace, good and bad. These inevitable changes aren’t always negative, so you can’t always apply problem management as a solution. That’s where change management comes in—a framework that helps you adjust to any new scenario.

Example: Your company is transitioning to a new cloud platform. The transition happens incident-free—meaning you won’t need problem management—but you can ease the transition by implementing some change management best practices. Preparing and training team members in the new software is a good place to start.

Problem management vs. project management

Project management is the framework for larger collections of work. It’s the overarching method for how you work on any project, hit goals, and get results. You can use project management to help you with problem management, but they are not the same thing. Problem management and project management work together to solve issues as part of your problem management process.

Example: During problem management, you uncover a backend security issue that needs to be addressed—employees are using storage software with outdated security measures. To solve this, you create a project and outline the tasks from start to finish. In this case, you might need to alert senior executives, get approval to remove the software, and alert employees. You create a project schedule with a defined timeline and assign the tasks to relevant teams. In this process, you identified a desired outcome—remove the unsafe software—and solved it. That’s project management.

The 8 steps of problem management

It’s easy to get upset when problems occur. In fact, it’s totally normal. But an emotional response is not always the best response when faced with new incidents. Having a reliable system—such as problem management—removes the temptation to respond emotionally. Proactive project management gives your team a framework for problem solving. It’s an iterative process —the more you use it, the more likely you are to have fewer problems, faster response times, and better outputs. 

1. Identify the problem

During problem identification, you’re looking at the present—what’s happening right now? Here, you’ll define what the incident is and its scale. Is this a small, quick-fix, or a full overhaul? Consider using problem framing to define, prioritize, and understand the obstacles involved with these more complex problems. 

2. Diagnose the cause

Use problem analysis or root cause analysis to strategically look at the cause of a problem. Follow the trail of issues all the way back to its beginnings.

To diagnose the underlying cause, you’ll want to answer:

What factors or conditions led to the incident?

Do you see related incidents? Could those be coming from the same source?

Did someone miss a step? Are processes responsible for this problem?

3. Organize and prioritize

Now it’s time to build out your framework. Use an IT project plan to organize information in a space where everyone can make and see updates in real time. The easiest way to do this is with a project management tool where you can input ‌tasks, assign deadlines, and add dependencies to ensure nothing gets missed. To better organize your process, define:

What needs to be done? 

Who’s responsible for each aspect? If no one is, can we assign someone? 

When does each piece need to be completed?

What is the final number of incidents related to this problem?

Are any of these tasks dependent on another one? Do you need to set up dependencies ?

What are your highest priorities? How do they affect our larger business goals ? 

How should you plan for this in the future?

4. Create a workaround

If the incident has stopped work or altered it, you might need to create a workaround. This is not always necessary, but temporary workarounds can keep work on track and avoid backlog while you go through the problem management steps. When these workarounds are especially effective, you can make them permanent processes.

5. Update your known error database

Every time an incident occurs, create a known error record and add it to your known error database (KEDB). Recording incidents helps you catch recurrences and logs the solution, so you know how to solve similar errors in the future. 

6. Pause for change management (if necessary)

Larger, high-impact problems might require change management. For example, if you realize the problem’s root cause is a lack of staff, you might dedicate team members to help. You can use change management to help them transition their responsibilities, see how these new roles fit in with the entire team, and determine how they will collaborate moving forward.

7. Solve the problem

This is the fun part—you get to resolve problems. At this stage, you should know exactly what you’re dealing with and the steps you need to take. But remember—with problem management, it’s not enough to solve the current problem. You’ll want to take any steps to prevent this from happening again in the future. That could mean hiring a new role to cover gaps in workflows , investing in new softwares and tools, or training staff on best practices to prevent these types of incidents.

Read: Turn your team into skilled problem solvers with these problem-solving strategies

8. Reflect on the process

The problem management process has the added benefit of recording the process in its entirety, so you can review it in the future. Once you’ve solved the problem, take the time to review each step and reflect on the lessons learned during this process. Make note of who was involved, what you needed, and any opportunities to improve your response to the next incident. After you go through the problem management process a few times and understand the basic steps, stakeholders, workload, and resources you need, create a template to make the kickoff process easier in the future.

5 benefits of problem management

Problem management helps you discover every piece of the problem—from the current scenario down to its root cause. Not only does this have an immediate positive impact on the current issue at hand, it also promotes collaboration and helps to build a better product overall. 

Here are five other ways ‌problem management can benefit your team:

Avoids repeat incidents. When you manage the entire incident from start to finish, you will address the foundational problems that caused it. This leads to fewer repeat incidents.

Boosts cross-functional collaboration. Problem management is a collaborative process. One incident might require collaboration from IT, the security team, and legal. Depending on the level of the problem, it might trickle all the way back down to the product or service team, where core changes need to be made.

Creates a better user experience. It’s simple—the fewer incidents you have, the better your customer’s experience will be. Reducing incidents means fewer delays, downtime, and frustrations for your users, and a higher rate of customer satisfaction.

Improves response time. As you develop a flow and framework with a project management process, you’ll be better equipped to handle future incidents—even if they’re different scenarios.

Organizes problem solving. Problem management provides a structured, thoughtful approach to solving problems. This reduces impulsive responses and helps you keep a better problem record of incidents and solutions.

Problem management leads to better, faster solutions

IT teams will always have to deal with incidents, but they don’t have to be bogged down by them. That’s because problem management works. Whether you employ a full problem management team or choose to apply these practices to your current IT infrastructure, problem management—especially when combined with a project management tool—saves you time and effort down the road.

With IT project plans, we’ve made it easier than ever to track your problem management work in a shared tool. Try our free IT project template to see your work come together, effortlessly.

Related resources

What is management by objectives (MBO)?

Write better AI prompts: A 4-sentence framework

How to find alignment on AI

What is content marketing? A complete guide

35 problem-solving techniques and methods for solving complex problems

Design your next session with SessionLab

Join the 150,000+ facilitators 
using SessionLab.

Recommended Articles

A step-by-step guide to planning a workshop, how to create an unforgettable training session in 8 simple steps, 47 useful online tools for workshop planning and meeting facilitation.

All teams and organizations encounter challenges as they grow. There are problems that might occur for teams when it comes to miscommunication or resolving business-critical issues . You may face challenges around growth , design , user engagement, and even team culture and happiness. In short, problem-solving techniques should be part of every team’s skillset.

Problem-solving methods are primarily designed to help a group or team through a process of first identifying problems and challenges , ideating possible solutions , and then evaluating the most suitable .

Finding effective solutions to complex problems isn’t easy, but by using the right process and techniques, you can help your team be more efficient in the process.

So how do you develop strategies that are engaging, and empower your team to solve problems effectively?

In this blog post, we share a series of problem-solving tools you can use in your next workshop or team meeting. You’ll also find some tips for facilitating the process and how to enable others to solve complex problems.

Let’s get started! 

How do you identify problems?

How do you identify the right solution.

• Tips for more effective problem-solving

Complete problem-solving methods

• Problem-solving techniques to identify and analyze problems
• Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve. 

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward. 

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.  

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.  

Try different approaches  

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally 

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator 

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

• Six Thinking Hats
• Lightning Decision Jam
• Problem Definition Process
• Discovery & Action Dialogue

Design Sprint 2.0

• Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on. 

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages. 

Lightning Decision Jam (LDJ)   #action   #decision making   #problem solving   #issue analysis   #innovation   #design   #remote-friendly   The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design. 

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition   #problem solving   #idea generation   #creativity   #online   #remote-friendly   A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys 

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges. 

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results. 

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys   #hyperisland   #innovation   This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold. 

World Cafe   #hyperisland   #innovation   #issue analysis   World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD)   #idea generation   #liberating structures   #action   #issue analysis   #remote-friendly   DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology   #action plan   #idea generation   #problem solving   #issue analysis   #large group   #online   #remote-friendly   Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

• The Creativity Dice
• Fishbone Analysis
• Problem Tree
• SWOT Analysis
• Agreement-Certainty Matrix
• The Journalistic Six
• LEGO Challenge
• What, So What, Now What?
• Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed. 

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.  

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It!   #gamestorming   #problem solving   #action   Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed. 

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable. 

The Creativity Dice   #creativity   #problem solving   #thiagi   #issue analysis   Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around. 

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish. 

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis   #problem solving   ##root cause analysis   #decision making   #online facilitation   A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree 

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them. 

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree   #define intentions   #create   #design   #issue analysis   A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward. 

SWOT analysis   #gamestorming   #problem solving   #action   #meeting facilitation   The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results. 

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause. 

Agreement-Certainty Matrix   #issue analysis   #liberating structures   #problem solving   You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic .  A problem is simple when it can be solved reliably with practices that are easy to duplicate.  It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably.  A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail.  Chaotic is when the context is too turbulent to identify a path forward.  A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.”  The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process. 

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID   #gamestorming   #project planning   #issue analysis   #problem solving   When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!   

Speed Boat   #gamestorming   #problem solving   #action   Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How   #idea generation   #issue analysis   #problem solving   #online   #creative thinking   #remote-friendly   A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills. 

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO! 

LEGO Challenge   #hyperisland   #team   A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems. 

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken. 

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What?   #issue analysis   #innovation   #liberating structures   You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists  

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists   #vision   #big picture   #issue analysis   #remote-friendly   This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions 

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

• Improved Solutions
• Four-Step Sketch
• 15% Solutions
• How-Now-Wow matrix
• Impact Effort Matrix

21. Mindspin  

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly. 

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation. 

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex. 

MindSpin   #teampedia   #idea generation   #problem solving   #action   A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result. 

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution. 

Improved Solutions   #creativity   #thiagi   #problem solving   #action   #team   You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged. 

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch   #design sprint   #innovation   #idea generation   #remote-friendly   The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper,  Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change. 

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.   

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change. 

15% Solutions   #action   #liberating structures   #remote-friendly   You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference.  15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change.  With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process. 

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud. 

How-Now-Wow Matrix   #gamestorming   #idea generation   #remote-friendly   When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice. 

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them. 

Impact and Effort Matrix   #gamestorming   #decision making   #action   #remote-friendly   In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action? 

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus. 

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively. 

Dotmocracy   #action   #decision making   #group prioritization   #hyperisland   #remote-friendly   Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

• Check-in/Check-out
• Doodling Together
• Show and Tell
• Constellations
• Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute. 

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out   #team   #opening   #closing   #hyperisland   #remote-friendly   Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together  

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start. 

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems. 

Doodling Together   #collaboration   #creativity   #teamwork   #fun   #team   #visual methods   #energiser   #icebreaker   #remote-friendly   Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team! 

Show and Tell   #gamestorming   #action   #opening   #meeting facilitation   Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible. 

Constellations   #trust   #connection   #opening   #coaching   #patterns   #system   Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic. 

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree   #thiagi   #opening   #perspectives   #remote-friendly   With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

• One Breath Feedback
• Who What When Matrix
• Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space. 

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round. 

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them. 

One breath feedback   #closing   #feedback   #action   This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix 

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward. 

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved. 

Who/What/When Matrix   #gamestorming   #action   #project planning   With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out! 

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised. 

Response Cards   #debriefing   #closing   #structured sharing   #questions and answers   #thiagi   #action   It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks  to build your agenda. When you make changes or update your agenda, your session  timing   adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore  how to use SessionLab  to design effective problem solving workshops or  watch this five minute video  to see the planner in action!

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you! 

thank you very much for these excellent techniques

Certainly wonderful article, very detailed. Shared!

Your list of techniques for problem solving can be helpfully extended by adding TRIZ to the list of techniques. TRIZ has 40 problem solving techniques derived from methods inventros and patent holders used to get new patents. About 10-12 are general approaches. many organization sponsor classes in TRIZ that are used to solve business problems or general organiztational problems. You can take a look at TRIZ and dwonload a free internet booklet to see if you feel it shound be included per your selection process.

Leave a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Going from a mere idea to a workshop that delivers results for your clients can feel like a daunting task. In this piece, we will shine a light on all the work behind the scenes and help you learn how to plan a workshop from start to finish. On a good day, facilitation can feel like effortless magic, but that is mostly the result of backstage work, foresight, and a lot of careful planning. Read on to learn a step-by-step approach to breaking the process of planning a workshop into small, manageable chunks.  The flow starts with the first meeting with a client to define the purposes of a workshop.…

How does learning work? A clever 9-year-old once told me: “I know I am learning something new when I am surprised.” The science of adult learning tells us that, in order to learn new skills (which, unsurprisingly, is harder for adults to do than kids) grown-ups need to first get into a specific headspace.  In a business, this approach is often employed in a training session where employees learn new skills or work on professional development. But how do you ensure your training is effective? In this guide, we'll explore how to create an effective training session plan and run engaging training sessions. As team leader, project manager, or consultant,…

Effective online tools are a necessity for smooth and engaging virtual workshops and meetings. But how do you choose the right ones? Do you sometimes feel that the good old pen and paper or MS Office toolkit and email leaves you struggling to stay on top of managing and delivering your workshop? Fortunately, there are plenty of online tools to make your life easier when you need to facilitate a meeting and lead workshops. In this post, we’ll share our favorite online tools you can use to make your job as a facilitator easier. In fact, there are plenty of free online workshop tools and meeting facilitation software you can…

Design your next workshop with SessionLab

Join the 150,000 facilitators using SessionLab

Sign up for free

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2024 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Problem-Solving Strategies and Obstacles

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Sean is a fact-checker and researcher with experience in sociology, field research, and data analytics.

JGI / Jamie Grill / Getty Images

• Application
• Improvement

From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. doi:10.3389/fnhum.2018.00261

Dunbar K. Problem solving . A Companion to Cognitive Science . 2017. doi:10.1002/9781405164535.ch20

Stewart SL, Celebre A, Hirdes JP, Poss JW. Risk of suicide and self-harm in kids: The development of an algorithm to identify high-risk individuals within the children's mental health system . Child Psychiat Human Develop . 2020;51:913-924. doi:10.1007/s10578-020-00968-9

Rosenbusch H, Soldner F, Evans AM, Zeelenberg M. Supervised machine learning methods in psychology: A practical introduction with annotated R code . Soc Personal Psychol Compass . 2021;15(2):e12579. doi:10.1111/spc3.12579

Mishra S. Decision-making under risk: Integrating perspectives from biology, economics, and psychology . Personal Soc Psychol Rev . 2014;18(3):280-307. doi:10.1177/1088868314530517

Csikszentmihalyi M, Sawyer K. Creative insight: The social dimension of a solitary moment . In: The Systems Model of Creativity . 2015:73-98. doi:10.1007/978-94-017-9085-7_7

Chrysikou EG, Motyka K, Nigro C, Yang SI, Thompson-Schill SL. Functional fixedness in creative thinking tasks depends on stimulus modality .  Psychol Aesthet Creat Arts . 2016;10(4):425‐435. doi:10.1037/aca0000050

Huang F, Tang S, Hu Z. Unconditional perseveration of the short-term mental set in chunk decomposition .  Front Psychol . 2018;9:2568. doi:10.3389/fpsyg.2018.02568

National Alliance on Mental Illness. Warning signs and symptoms .

Mayer RE. Thinking, problem solving, cognition, 2nd ed .

Schooler JW, Ohlsson S, Brooks K. Thoughts beyond words: When language overshadows insight. J Experiment Psychol: General . 1993;122:166-183. doi:10.1037/0096-3445.2.166

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands

Associated data.

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high ( n = 58) or low ( n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies.

Introduction

Complex problems in organizational contexts are seldom solved by individuals. Generally, interdependently working teams of experts deal with complex problems (Fiore et al., 2010 ), which are characterized by element interactivity/ interconnectedness, dynamic developments, non-transparency and multiple, and/or conflicting goals (Dörner et al., 1983 ; Brehmer, 1992 ; Funke, 1995 ). Complex problem solving “takes place for reducing the barrier between a given start state and an intended goal state with the help of cognitive activities and behavior. Start state, intended goal state, and barriers prove complexity, change dynamically over time, and can be partially intransparent” (Funke, 2012 , p. 682). Teams dealing with complex problems in interdependent work contexts, for example in disaster, crisis or accident management, are called High Responsibility Teams. They are named High Responsibility Teams (HRTs; Hagemann, 2011 ; Hagemann et al., 2011 ) due to their dynamic and often unpredictable working conditions and demanding work contexts, in which technical faults and slips have severe consequences for human beings and the environment if they are not identified and resolved within the team immediately (Kluge et al., 2009 ). HRTs bear responsibility regarding lives of third parties and their own lives based on their actions and consequences.

The context of interdependently working HRTs, dealing with complex problems, is described as follows (Zsambok, 1997 ): Members of interdependently working teams have to reach ill-defined or competing goals in common in poor structured, non-transparent and dynamically changing situations under the consideration of rules of engagement and based on several cycles of joint action. Some or all goals are critical in terms of time and the consequences of actions result in decision-based outcomes with high importance for the culture (e.g., human life). In HRT contexts, added to the features of the complexity of the problem, is the complexity of relationships, which is called social complexity (Dörner, 1989/2003 ) or crew coordination complexity (Kluge, 2014 ), which results from the interconnectedness between multiple agents through coordination requirements. The dynamic control aspect of the continuous process is coupled with the need to coordinate multiple highly interactive processes imposing high coordination demands (Roth and Woods, 1988 ; Waller et al., 2004 ; Hagemann et al., 2012 ).

Within this article, it is important to us to describe the theoretical background of complex problem solving in teams in depth and to combine different but compatible theoretical approaches, in order to demonstrate their theoretical and practical use in the context of the analysis of complex problem solving in teams. In Industrial and Organizational Psychology, a detailed description of tasks and work contexts that are in the focus of the analysis is essential. The individual or team task is the point of intersection between organization and individual as a “psychologically most relevant part” of the working conditions (Ulich, 1995 ). Thus, the tasks and the teamwork context of teams that deal with complex problems is of high relevance in the present paper. We will comprehensively describe the context of complex problem solving in teams by introducing a model of an idealized teamwork process that complex problem solving teams pass through and extensively integrate the relevant teamwork skills for these interdependently working teams into the idealized teamwork process model.

Furthermore, we will highlight the episodic aspect concerning complex problem solving in teams and combine the agreed on transition, action, interpersonal and learning processes of teamwork with the idealized teamwork process model. Because we are interested in investigating teamwork competencies and action processes of complex problem solving teams, we will analyze the indirect effect of collective orientation on team performance through the teams' coordination behavior. The focusing of the study will be owed to its validity. Even though that we know that more aspects of the theoretical framework might be of interest and could be analyzed, we will focus on a detail within the laboratory experiment for getting reliable and valid results.

Goal, task, and outcome interdependence in teamwork

Concerning interdependence, teamwork research focuses on three designated features, which are in accordance with general process models of human action (Hertel et al., 2004 ). One type is goal interdependence, which refers to the degree to which teams have distinct goals as well as a linkage between individual members and team goals (Campion et al., 1993 ; Wageman, 1995 ). A second type is task interdependence, which refers to the interaction between team members. The team members depend on each other for work accomplishment, and the actions of one member have strong implications for the work process of all members (Shea and Guzzo, 1987 ; Campion et al., 1993 ; Hertel et al., 2004 ). The third type is outcome interdependence, which is defined as the extent to which one team member's outcomes depend on the performance of other members (Wageman, 1995 ). Accordingly, the rewards for each member are based on the total team performance (Hertel et al., 2004 ). This can occur, for instance, if a team receives a reward based on specific performance criteria. Although interdependence is often the reason why teams are formed in the first place, and it is stated as a defining attribute of teams (Salas et al., 2008 ), different levels of task interdependence exist (Van de Ven et al., 1976 ; Arthur et al., 2005 ).

The workflow pattern of teams can be

• Independent or pooled (activities are performed separately),
• Sequential (activities flow from one member to another in a unidirectional manner),
• Reciprocal (activities flow between team members in a back and forth manner) or
• Intensive (team members must simultaneously diagnose, problem-solve, and coordinate as a team to accomplish a task).

Teams that deal with complex problems work within intensive interdependence, which requires greater coordination patterns compared to lower levels of interdependence (Van de Ven et al., 1976 ; Wageman, 1995 ) and necessitates mutual adjustments as well as frequent interaction and information integration within the team (Gibson, 1999 ; Stajkovic et al., 2009 ).

Thus, in addition to the cognitive requirements related to information processing (e.g., encoding, storage and retrieval processes (Hinsz et al., 1997 ), simultaneously representing and anticipating the dynamic elements and predicting future states of the problem, balancing contradictory objectives and decide on the right timing for actions to execute) of individual team members, the interconnectedness between the experts in the team imposes high team process demands on the team members. These team process demands follow from the required interdependent actions of all team members for effectively using all resources, such as equipment, money, time, and expertise, to reach high team performance (Marks et al., 2001 ). Examples for team process demands are the communication for building a shared situation awareness, negotiating conflicting perspectives on how to proceed or coordinating and orchestrating actions of all team members.

A comprehensive model of the idealized teamwork process

The cognitive requirements, that complex problem solving teams face, and the team process demands are consolidated within our model of an idealized teamwork process in Figure ​ Figure1 1 (Hagemann, 2011 ; Kluge et al., 2014 ). Individual and team processes converge sequential and in parallel and influencing factors as well as process demands concerning complex problem solving in teams can be extracted. The core elements of the model are situation awareness, information transfer, individual and shared mental models, coordination and leadership, and decision making.

Relevant teamwork skills (orange color) for interdependently working teams (see Wilson et al., 2010 ) integrated into the model of an idealized teamwork process.

Complex problem solving teams are responsible for finding solutions and reaching specified goals. Based on the overall goals various sub goals will be identified at the beginning of the teamwork process in the course of mission analysis, strategy formulation and planning, all aspects of the transition phase (Marks et al., 2001 ). The transition phase processes occur during periods of time when teams focus predominantly on evaluation and/or planning activities. The identified and communicated goals within the team represent relevant input variables for each team member in order to build up a Situation Awareness (SA). SA contains three steps and is the foundation for an ideal and goal directed collaboration within a team (Endsley, 1999 ; Flin et al., 2008 ). The individual SA is the start and end within the idealized teamwork process model. SA means the assessment of a situation which is important for complex problem solving teams, as they work based on the division of labor as well as interdependently and each team member needs to achieve a correct SA and to share it within the team. Each single team member needs to utilize all technical and interpersonal resources in order to collect and interpret up-to-date goal directed information and to share this information with other team members via “closed-loop communication.”

This information transfer focuses on sending and receiving single SA between team members in order to build up a Shared Situation Awareness (SSA). Overlapping cuts of individual SA are synchronized within the team and a bigger picture of the situation is developed. Creating a SSA means sharing a common perspective of the members concerning current events within their environment, their meaning and their future development. This shared perspective enables problem-solving teams to attain high performance standards through corresponding and goal directed actions (Cannon-Bowers et al., 1993 ).

Expectations of each team member based on briefings, individual mental models and interpositional knowledge influence the SA, the information transfer and the consolidation process. Mental models are internal and cognitive representations of relations and processes (e.g., execution of tactics) between various aspects or elements of a situation. They help team members to describe, explain and predict circumstances (Mathieu et al., 2000 ). Mental models possess knowledge elements required by team members in order to assess a current situation in terms of SA. Interpositional knowledge refers to an individual understanding concerning the tasks and duties of all team members, in order to develop an understanding about the impact of own actions on the actions of other team members and vice versa. It supports the team in identifying the information needs and the amount of required help of other members and in avoiding team conflicts (Smith-Jentsch et al., 2001 ). This knowledge is the foundation for anticipating the team members' needs for information and it is important for matching information within the team.

Based on the information matching process within the team, a common understanding of the problem, the goals and the current situation is developed in terms of a Shared Mental Model (SMM), which is important for the subsequent decisions. SMM are commonly shared mental models within a team and refer to the organized knowledge structures of all team members, that are shared with each other and which enable the team to interact goal-oriented (Mathieu et al., 2000 ). SMM help complex problem solving teams during high workload to adapt fast and efficiently to changing situations (Waller et al., 2004 ). They also enhance the teams' performance and communication processes (Cannon-Bowers et al., 1993 ; Mathieu et al., 2000 ). Especially under time pressure and in crucial situations when overt verbal communication and explicit coordination is not applicable, SMM are fundamental in order to coordinate implicitly. This information matching process fosters the building of a shared understanding of the current situation and the required actions. In order to do so teamwork skills (see Wilson et al., 2010 ) such as communication, coordination , and cooperation within the team are vitally important. Figure ​ Figure1 1 incorporates the teamwork skills into the model of an idealized teamwork process.

Depending on the shared knowledge and SA within the team, the coordination can be based either on well-known procedures or shared expectations within the team or on explicit communication based on task specific phraseology or closed-loop communication. Cooperation needs mutual performance monitoring within the team, for example, in order to apply task strategies to accurately monitor teammate performance and prevent errors (Salas et al., 2005 ). Cooperation also needs backup behavior of each team member, for example, and continuous actions in reference to the collective events. The anticipation of other team members' needs under high workload maintains the teams' performance and the well-being of each team member (Badke-Schaub, 2008 ). A successful pass through the teamwork process model also depends e.g., on the trust and the cohesion within the team and the collective orientation of each team member.

Collective orientation (CO) is defined “as the propensity to work in a collective manner in team settings” (Driskell et al., 2010 , p. 317). Highly collectively oriented people work with others on a task-activity and team-activity track (Morgan et al., 1993 ) in a goal-oriented manner, seek others' input, contribute to team outcomes, enjoy team membership, and value cooperativeness more than power (Driskell et al., 2010 ). Thus, teams with collectively oriented members perform better than teams with non-collectively oriented members (Driskell and Salas, 1992 ). CO, trust and cohesion as well as other coordination and cooperation skills are so called emergent sates that represent cognitive, affective, and motivational states, and not traits, of teams and team members, and which are influenced, for example, by team experience, so that emergent states can be considered as team inputs but also as team outcomes (Marks et al., 2001 ).

Based on the information matching process the complex problem solving team or the team leader needs to make decisions in order to execute actions. The task prioritization and distribution is an integrated part of this step (Waller et al., 2004 ). Depending on the progress of the dynamic, non-transparent and heavily foreseeable situation tasks have to be re-prioritized during episodes of teamwork. Episodes are “temporal cycles of goal-directed activity” in which teams perform (Marks et al., 2001 , p. 359). Thus, the team acts adaptive and is able to react flexible to situation changes. The team coordinates implicitly when each team member knows what he/she has to do in his/her job, what the others expect from him/her and how he/she interacts with the others. In contrast, when abnormal events occur and they are recognized during SA processes, the team starts coordinating explicitly via communication, for example. Via closed-loop communication and based on interpositional knowledge new strategies are communicated within the team and tasks are re-prioritized.

The result of the decision making and action taking flows back into the individual SA and the as-is state will be compared with the original goals. This model of an idealized teamwork process (Figure ​ (Figure1) 1 ) is a regulator circuit with feedback loops, which enables a team to adapt flexible to changing environments and goals. The foundation of this model is the classic Input-Process-Outcome (IPO) framework (Hackman, 1987 ) with a strong focus on the process part. IPO models view processes as mechanisms linking variables such as member, team, or organizational features with outcomes such as performance quality and quantity or members' reactions. This mediating mechanism, the team process , can be defined as “members' interdependent acts that convert inputs to outcomes through cognitive, verbal, and behavioral activities directed toward organizing taskwork to achieve collective goals” (Marks et al., 2001 , p. 357). That means team members interact interdependently with other members as well as with their environment. These cognitive, verbal, and behavioral activities directed toward taskwork and goal attainment are represented as gathering situation awareness, communication, coordination, cooperation, the consolidation of information, and task prioritization within our model of an idealized teamwork process. Within the context of complex problem solving, teams have to face team process demands in addition to cognitive challenges related to individual information processing. That means teamwork processes and taskwork to solve complex problems co-occur, the processes guide the execution of taskwork.

The dynamic nature of teamwork and temporal influences on complex problem solving teams are considered within adapted versions (Marks et al., 2001 ; Ilgen et al., 2005 ) of the original IPO framework. These adaptations propose that teams experience cycles of joint action, so called episodes, in which teams perform and also receive feedback for further actions. The IPO cycles occur sequentially and simultaneously and are nested in transition and action phases within episodes in which outcomes from initial episodes serve as inputs for the next cycle (see Figure ​ Figure2). 2 ). These repetitive IPO cycles are a vital element of our idealized teamwork process model, as it incorporates feedback loops in such a way, that the outcomes, e.g., changes within the as-is state, are continuously compared with the original goals. Detected discrepancies within the step of updating SA motivate the team members to consider further actions for goal accomplishment.

Teamwork episodes with repetitive IPO cycles (Marks et al., 2001 ).

When applying this episodic framework to complex problem solving teams it becomes obvious that teams handle different types of taskwork at different phases of task accomplishment (Marks et al., 2001 ). That means episodes consist of two phases, so-called action and transition phases , in which teams are engaged in activities related to goal attainment and in other time in reflecting on past performance and planning for further common actions. The addition of the social complexity to the complexity of the problem within collaborative complex problem solving comes to the fore here. During transition phases teams evaluate their performance, compare the as-is state against goals, reflect on their strategies and plan future activities to guide their goal accomplishment. For example, team members discuss alternative courses of action, if their activities for simulated firefighting, such as splitting team members in order to cover more space of the map, are not successful. During action phases, teams focus directly on the taskwork and are engaged in activities such as exchanging information about the development of the dynamic situation or supporting each other. For example, a team member recognizes high workload of another team member and supports him/her in collecting information or in taking over the required communication with other involved parties.

Transition and action phases

The idealized teamwork process model covers these transition and action phases as well as the processes occurring during these two phases of team functioning, which can be clustered into transition, action, and interpersonal processes. That means during complex problem solving the relevant or activated teamwork processes in the transition and action phases change as teams move back and forth between these phases. As this taxonomy of team processes from Marks et al. ( 2001 ) states that a team process is multidimensional and teams use different processes simultaneously, some processes can occur either during transition periods or during action periods or during both periods. Transition processes especially occur during transition phases and enable the team to understand their tasks, guide their attention, specify goals and develop courses of action for task accomplishment. Thus, transition processes include (see Marks et al., 2001 ) mission analysis, formulation and planning (Prince and Salas, 1993 ), e.g., fighting a forest fire, goal specification (Prussia and Kinicki, 1996 ), e.g., saving as much houses and vegetation as possible, and strategy formulation (Prince and Salas, 1993 ; Cannon-Bowers et al., 1995 ), e.g., spreading team members into different geographic directions. Action processes predominantly occur during action phases and support the team in conducting activities directly related to goal accomplishment. Thus, action processes are monitoring progress toward goals (Cannon-Bowers et al., 1995 ), e.g., collecting information how many cells in a firefighting simulation are still burning, systems monitoring (Fleishman and Zaccaro, 1992 ), e.g., tracking team resources such as water for firefighting, team monitoring and backup behavior (Stevens and Campion, 1994 ; Salas et al., 2005 ), e.g., helping a team member and completing a task for him/her, and coordination (Fleishman and Zaccaro, 1992 ; Serfaty et al., 1998 ), e.g., orchestrating the interdependent actions of the team members such as exchanging information during firefighting about positions of team members for meeting at the right time at the right place in order to refill the firefighters water tanks. Especially the coordination process is influenced by the amount of task interdependence as coordination becomes more and more important for effective team functioning when interdependence increases (Marks et al., 2001 ). Interpersonal processes occur during transition and action phases equally and lay the foundation for the effectiveness of other processes and govern interpersonal activities (Marks et al., 2001 ). Thus, interpersonal processes include conflict management (Cannon-Bowers et al., 1995 ), like the development of team rules, motivation and confidence building (Fleishman and Zaccaro, 1992 ), like encourage team members to perform better, and affect management (Cannon-Bowers et al., 1995 ), e.g., regulating member emotions during complex problem solving.

Summing up, process demands such as transition processes that complex problem solving teams pass through, are mission analysis, planning, briefing and goal specification, visualized on the left side of the idealized teamwork process model (see Figure ​ Figure3). 3 ). The results of these IPO cycles lay the foundation for gathering a good SA and initiating activities directed toward taskwork and goal accomplishment and therefore initiating action processes. The effective execution of action processes depends on the communication, coordination, cooperation, matching of information, and task prioritization as well as emergent team cognition variables (SSA and SMM) within the team. The results, like decisions, of these IPO cycles flow back into the next episode and may initiate further transition processes. In addition, interpersonal processes play a crucial role for complex problem solving teams. That means, conflict management, motivating and confidence building, and affect management are permanently important, no matter whether a team runs through transition or action phases and these interpersonal processes frame the whole idealized teamwork process model. Therefore, interpersonal processes are also able to impede successful teamwork at any point as breakdowns in conflict or affect management can lead to coordination breakdowns (Wilson et al., 2010 ) or problems with monitoring or backing up teammates (Marks et al., 2001 ). Thus, complex problem solving teams have to face these multidimensional team process demands in addition to cognitive challenges, e.g., information storage or retrieval (Hinsz et al., 1997 ), related to individual information processing.

The integration of transition, action, interpersonal, and learning processes into the model of an idealized teamwork process.

Team learning opportunities for handling complex problems

In order to support teams in handling complex situations or problems, learning opportunities seem to be very important for successful task accomplishment and for reducing possible negative effects of team process demands. Learning means any kind of relative outlasted changes in potential of human behavior that cannot be traced back to age-related changes (Bower and Hilgard, 1981 ; Bredenkamp, 1998 ). Therefore, Schmutz et al. ( 2016 ) amended the taxonomy of team processes developed by Marks et al. ( 2001 ) and added learning processes as a fourth category of processes, which occur during transition and action phases and contribute to overall team effectiveness. Learning processes (see also Edmondson, 1999 ) include observation, e.g., observing own and other team members' actions such as the teammate's positioning of firewalls in order to protect houses in case of firefighting, feedback, like giving a teammate information about the wind direction for effective positioning of firewalls, and reflection, e.g., talking about procedures for firefighting or refilling water tanks, for example, within the team. Learning from success and failure and identifying future problems is crucial for the effectiveness of complex problem solving teams and therefore possibilities for learning based on repetitive cycles of joint action or episodes and reflection of team members' activities during action and transition phases should be used effectively (Edmondson, 1999 ; Marks et al., 2001 ). The processes of the idealized teamwork model are embedded into these learning processes (see Figure ​ Figure3 3 ).

The fulfillment of transition, action, interpersonal and learning processes contribute significantly to successful team performance in complex problem solving. For clustering these processes, transition and action processes could be seen as operational processes and interpersonal and learning process as support processes. When dealing with complex and dynamic situations teams have to face these team process demands more strongly than in non-complex situations. For example, goal specification and prioritization or strategy formulation, both aspects of transition processes, are strongly influenced by multiple goals, interconnectedness or dynamically and constantly changing conditions. The same is true for action processes, such as monitoring progress toward goals, team monitoring and backup behavior or coordination of interdependent actions. Interpersonal processes, such as conflict and affect management or confidence building enhance the demands put on team members compared to individuals working on complex problems. Interpersonal processes are essential for effective teamwork and need to be cultivated during episodes of team working, because breakdowns in confidence building or affect management can lead to coordination breakdowns or problems with monitoring or backing up teammates (Marks et al., 2001 ). Especially within complex situations aspects such as interdependence, delayed feedback, multiple goals and dynamic changes put high demands on interpersonal processes within teams. Learning processes, supporting interpersonal processes and the result of effective teamwork are e.g., observation of others' as well as own actions and receiving feedback by others or the system and are strongly influenced by situational characteristics such as non-transparency or delayed feedback concerning actions. It is assumed that amongst others team learning happens through repetitive cycles of joint action within the action phases and reflection of team members within the transition phases (Edmondson, 1999 ; Gabelica et al., 2014 ; Schmutz et al., 2016 ). The repetitive cycles help to generate SMM (Cannon-Bowers et al., 1993 ; Mathieu et al., 2000 ), SSA (Endsley and Robertson, 2000 ) or transactive memory systems (Hollingshead et al., 2012 ) within the team.

Emergent states in complex team work and the role of collective orientation

IPO models propose that input variables and emergent states are able to influence team processes and therefore outcomes such as team performance positively. Emergent states represent team members' attitudes or motivations and are “properties of the team that are typically dynamic in nature and vary as a function of team context, inputs, processes, and outcomes” (Marks et al., 2001 , p. 357). Both emergent states and interaction processes are relevant for team effectiveness (Kozlowski and Ilgen, 2006 ).

Emergent states refer to conditions that underlie and dynamically enable effective teamwork (DeChurch and Mesmer-Magnus, 2010 ) and can be differentiated from team process, which refers to interdependent actions of team members that transform inputs into outcomes based on activities directed toward task accomplishment (Marks et al., 2001 ). Emergent states mainly support the execution of behavioral processes (e.g., planning, coordination, backup behavior) during the action phase, meaning during episodes when members are engaged in acts that focus on task work and goal accomplishment. Emergent states like trust, cohesion and CO are “products of team experiences (including team processes) and become new inputs to subsequent processes and outcomes” (Marks et al., 2001 , p. 358). Trust between team members and cohesion within the team are emergent states that develop over time and only while experiencing teamwork in a specific team. CO is an emergent state that a team member brings along with him/her into the teamwork, is assumed to be more persistent than trust and cohesion, and can, but does not have to, be positively and negatively influenced by experiencing teamwork in a specific team for a while or by means of training (Eby and Dobbins, 1997 ; Driskell et al., 2010 ). Thus, viewing emergent states on a continuum, trust and cohesion are assumed more fluctuating than CO, but CO is much more sensitive to change and direct experience than a stable trait such as a personality trait.

CO of team members is one of the teamwork-relevant competencies that facilitates team processes, such as collecting and sharing information between team members, and positively affects the success of teams, as people who are high in CO work with others in a goal-oriented manner, seek others' input and contribute to team outcomes (Driskell et al., 2010 ). CO is an emergent state, as it can be an input variable as well as a teamwork outcome. CO is context-dependent, becomes visible in reactions to situations and people, and can be influenced by experience (e.g., individual learning experiences with various types of teamwork) or knowledge or training (Eby and Dobbins, 1997 ; Bell, 2007 ). CO enhances team performance through activating transition and action processes such as coordination, evaluation and consideration of task inputs from other team members while performing a team task (Driskell and Salas, 1992 ; Salas et al., 2005 ). Collectively oriented people effectively use available resources in due consideration of the team's goals, participate actively and adapt teamwork processes adequately to the situation.

Driskell et al. ( 2010 ) and Hagemann ( 2017 ) provide a sound overview of the evidence of discriminant and convergent validity of CO compared to other teamwork-relevant constructs, such as cohesion, also an emergent state, or cooperative interdependence or preference for solitude. Studies analyzing collectively and non-collectively oriented persons' decision-making in an interdependent task demonstrated that teams with non-collectively oriented members performed poorly in problem solving and that members with CO judged inputs from teammates as more valuable and considered these inputs more frequently (Driskell and Salas, 1992 ). Eby and Dobbins ( 1997 ) also showed that CO results in increased coordination among team members, which may enhance team performance through information sharing, goal setting and strategizing (Salas et al., 2005 ). Driskell et al. ( 2010 ) and Hagemann ( 2017 ) analyzed CO in relation to team performance and showed that the effect of CO on team performance depends on the task type (see McGrath, 1984 ). Significant positive relationships between team members' CO and performance were found in relation to the task types choosing/decision making and negotiating (Driskell et al., 2010 ) respectively choosing/decision making (Hagemann, 2017 ). These kinds of tasks are characterized by much more interdependence than task types such as executing or generating tasks. As research shows that the positive influence of CO on team performance unfolds especially in interdependent teamwork contexts (Driskell et al., 2010 ), which require more team processes such as coordination patterns (Van de Ven et al., 1976 ; Wageman, 1995 ) and necessitate mutual adjustments as well as frequent information integration within the team (Gibson, 1999 ; Stajkovic et al., 2009 ), CO might be vitally important for complex problem solving teams. Thus, CO as an emergent state of single team members might be a valuable resource for enhancing the team's performance when exposed to solving complex problems. Therefore, it will be of interest to analyze the influence of CO on team process demands such as coordination processes and performance within complex problem solving teams. We predict that the positive effect of CO on team performance is an indirect effect through coordination processes within the team, which are vitally important for teams working in intensive interdependent work contexts.

• Hypothesis 1: CO leads to a better coordination behavior, which in turn leads to a higher team performance.

As has been shown in team research that emergent states like trust and cohesion (see also Figure ​ Figure1) 1 ) affect team performance, these two constructs are analyzed in conjunction with CO concerning action processes, such as coordination behavior and team performance. Trust between team members supports information sharing and the willingness to accept feedback, and therefore positively influences teamwork processes (McAllister, 1995 ; Salas et al., 2005 ). Cohesion within a team facilitates motivational factors and group processes like coordination and enhances team performance (Beal et al., 2003 ; Kozlowski and Ilgen, 2006 ).

• Hypothesis 2: Trust shows a positive relationship with (a) action processes (team coordination) and with (b) team performance.
• Hypothesis 3: Cohesion shows a positive relationship with (a) action processes (team coordination) and with (b) team performance.

Materials and methods

In order to demonstrate the importance of team process demands for complex problem solving in teams, we used a computer-based microworld in a laboratory study. We analyzed the effectiveness of complex problem solving teams while considering the influence of input variables, like collective orientation of team members and trust and cohesion within the team, on action processes within teams, like coordination.

The microworld for investigating teams process demands

We used the simulation-based team task C 3 Fire (Granlund et al., 2001 ; Granlund and Johansson, 2004 ), which is described as an intensive interdependence team task for complex problem solving (Arthur et al., 2005 ). C 3 Fire is a command, control and communications simulation environment that allows teams' coordination and communication in complex and dynamic environments to be analyzed. C 3 Fire is a microworld, as important characteristics of the real world are transferred to a small and well-controlled simulation system. The task environment in C 3 Fire is complex, dynamic and opaque (see Table ​ Table1) 1 ) and therefore similar to the cognitive tasks people usually encounter in real-life settings, in and outside their work place (Brehmer and Dörner, 1993 ; Funke, 2001 ). Figure ​ Figure4 4 demonstrates how the complexity characteristics mentioned in Table ​ Table1 1 are realized in C 3 Fire. The screenshot represents the simulation manager's point of view, who is able to observe all units and actions and the scenario development. For more information about the units and scenarios, please (see the text below and the Supplementary Material). Complexity requires people to consider a number of facts. Because executed actions in C 3 Fire influence the ongoing process, the sequencing of actions is free and not stringent, such as a fixed (if X then Y) or parallel (if X then Y and Z) sequence (Ormerod et al., 1998 ). This can lead to stressful situations. Taking these characteristics of microworlds into consideration, team processes during complex problem solving can be analyzed within laboratories under controlled conditions. Simulated microworlds such as C 3 Fire allow the gap to be bridged between laboratory studies, which might show deficiencies regarding ecological validity, and field studies, which have been criticized due to their small amount of control (see Brehmer and Dörner, 1993 ).

Overview of complexity characteristics of microworlds in general and in C 3 Fire (cf. Funke, 2001 ).

Examples for the complexity characteristics in Table ​ Table1 1 represented within a simulation scenario in C 3 Fire.

In C 3 Fire, the teams' task is to coordinate their actions to extinguish a forest fire whilst protecting houses and saving lives. The team members' actions are interdependent. The simulation includes, e.g., forest fires, houses, tents, gas tanks, different kinds of vegetation and computer-simulated agents such as firefighting units (Granlund, 2003 ). It is possible, for example, that the direction of wind will change during firefighting and the time until different kinds of vegetation are burned down varies between those. In the present study, two simulation scenarios were developed for two-person teams and consisted of two firefighting units, one mobile water tank unit (responsible for re-filling the firefighting units' water tanks that contain a predefined amount of water) and one fire-break unit (a field defended with a fire-break cannot be ignited; the fire spreads around its ends). The two developed scenarios lasted for 15 min maximum. Each team member was responsible for two units in each scenario; person one for firefighting and water tank unit and person two for firefighting and fire-break unit. The user interface was a map system (40 × 40 square grid) with all relevant geographic information and positions of all symbols representing houses, water tank units and so on. All parts of the map with houses and vegetation were visible for the subjects, but not the fire itself or the other units; instead, the subjects were close to them with their own units (restricted visibility field; 3 × 3 square grid). The simulation was run on computers networked in a client-server configuration. The subjects used a chat system for communication that was logged. For each scenario, C 3 Fire creates a detailed log file containing all events that occurred over the course of the simulation. Examples of the C 3 Fire scenarios are provided in the Figures S1 – 3 and a short introduction into the microworld is given in the video. Detailed information regarding the scenario characteristics are given in Table S1 . From scenario one to two, the complexity and interdependence increased.

Participants

The study was conducted from Mai 2014 until March 2015. Undergraduate and graduate students ( N = 116) studying applied cognitive sciences participated in the study (68.1% female). Their mean age was 21.17 years ( SD = 3.11). Participants were assigned to 58 two-person teams, with team assignments being based on the pre-measured CO values (see procedure). They received 2 hourly credits as a trial subject and giveaways such as pencils and non-alcoholic canned drinks. The study was approved by the university's ethics committee in February 2014.

The study was conducted within a laboratory setting at a university department for business psychology. Prior to the experiment, the participants filled in the CO instrument online and gave written informed consent (see Figure ​ Figure5). 5 ). The median was calculated subsequently ( Md = 3.12; range: 1.69–4.06; scale range: 1–5) relating to the variable CO and two individuals with either high ( n = 58) or low ( n = 58) CO values were randomly matched as teammates. The matching process was random in part, as those two subjects were matched to form a team, whose preferred indicated time for participation in a specific week during data collection were identical. The participants were invited to the experimental study by e-mail 1–2 weeks after filling in the CO instrument. The study began with an introduction to the experimental procedure and the teams' task. The individuals received time to familiarize themselves with the simulation, received 20 min of training and completed two practice trials. After the training, participants answered a questionnaire collecting demographic data. Following this, a simulation scenario started and the participants had a maximum of 15 min to coordinate their actions to extinguish a forest fire whilst protecting houses and saving lives. After that, at measuring time T1, participants answered questionnaires assessing trust and cohesion within the team. Again, the teams worked on the following scenario 2 followed by a last round of questionnaires assessing trust and cohesion at T2.

Overview about the procedure and measures.

Demographic data such as age, sex, and study course were assessed after the training at the beginning of the experiment.

Collective Orientation was measured at an individual level with 16 items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ) developed by the authors (Hagemann, 2017 ) based on the work of Driskell et al. ( 2010 ). The factorial structure concerning the German-language CO scale was proven prior to this study (χ 2 = 162.25, df = 92, p = 0.000, χ 2 /df = 1.76, CFI = 0.97, TLI = 0.96, RMSEA = 0.040, CI = 0.030-0.051, SRMR = 0.043) and correlations for testing convergent and discriminant evidence of validity were satisfying. For example, CO correlated r = 0.09 ( p > 0.10) with cohesion, r = 0.34 ( p < 0.01) with cooperative interdependence and r = −0.28 ( p < 0.01) with preference for solitude (Hagemann, 2017 ). An example item is “ I find working on team projects to be very satisfying ”. Coefficient alpha for this scale was 0.81.

Trust in team members' integrity, trust in members' task abilities and trust in members' work-related attitudes (Geister et al., 2006 ) was measured with seven items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ). An example item is “ I can trust that I will have no additional demands due to lack of motivation of my team member .” Coefficient alpha for this scale was 0.83 (T1) and 0.87 (T2).

Cohesion was measured with a six-item scale from Riordan and Weatherly ( 1999 ) rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree ). An example item is “ In this team, there is a lot of team spirit among the members .” Coefficient alpha for this scale was 0.87 (T1) and 0.87 (T2).

Action process: coordination

Successful coordination requires mechanisms that serve to manage dependencies between the teams' activities and their resources. Coordination effectiveness was assessed based on the time the firefighting units spent without water in the field in relation to the total scenario time. This measure is an indicator of the effectiveness of resource-oriented coordination, as it reflects an efficient performance regarding the water refill process in C 3 Fire, which requires coordinated actions between the two firefighting units and one water tank unit (Lafond et al., 2011 ). The underlying assumption is that a more successful coordination process leads to fewer delays in conducting the refill process. Coordination was calculated by a formula and values ranged between 0 and 1, with lower values indicating better coordination in the team (see Jobidon et al., 2012 ).

Team performance

This measure related to the teams' goals (limiting the number of burned out cells and saving as many houses/buildings as possible) and was quantified as the number of protected houses and the number of protected fields and bushes/trees in relation to the number of houses, fields, and bushes/trees, respectively, which would burn in a worst case scenario. This formula takes into account that teams needing more time for firefighting also have more burning cells and show a less successful performance than teams that are quick in firefighting. To determine the worst case scenario, both 15-min scenarios were run with no firefighting action taken. Thus, the particularities (e.g., how many houses would burn down if no action was taken) of each scenario were considered. Furthermore, the houses, bushes/trees and fields were weighted according to their differing importance, mirroring the teams' goals. Houses should be protected and were most important. Bushes/trees (middle importance) burn faster than fields (lowest importance) and foster the expansion of the fire. Values regarding team performance ranged between 0 and 7.99, with higher values indicating a better overall performance. Team performance was calculated as follows (see Table ​ Table2 2 ):

Explanation of formula for calculating team performance in both scenarios.

Means, standard deviations, internal consistencies, and correlations for all study variables are provided in Table ​ Table3 3 .

Means, standard deviations, internal consistencies, and correlations for all study variables.

Performance range from 0 to 7.99; Time without Water range from 0 to 1 (lower values indicate a more effective handling of water); CO range from 1 to 5 .

Team complex problem solving in scenario 1 correlated significantly negative with time without water in scenario 1, indicating that a high team performance is attended by the coordination behavior (as a team process). The same was true for scenario 2. In addition, time without water as an indicator for team coordination correlated significantly negative with the team members' CO, indicating that team members with high CO values experience less time without water in the microworld than teams with members with low CO values.

In order to analyze the influence of CO on team process demands such as coordination processes and thereby performance within complex problem solving teams we tested whether CO would show an indirect effect on team performance through the teams' coordination processes. To analyze this assumption, indirect effects in simple mediation models were estimated for both scenarios (see Preacher and Hayes, 2004 ). The mean for CO was 3.44 ( SD = 0.32) for teams with high CO values and it was 2.79 ( SD = 0.35) for teams with low CO values. The mean concerning team performance in scenario 1 for teams with high CO values was 6.30 ( SD = 1.64) and with low CO values 5.35 ( SD = 2.30). The mean concerning time without water (coordination behavior) for teams with high CO values was 0.16 ( SD = 0.08) and with low CO values 0.20 ( SD = 0.09). In scenario 2 the mean for team performance was 6.26 ( SD = 2.51) for teams with high CO values and it was 4.36 ( SD = 2.24) for teams with low CO values. The mean concerning time without water for teams with high CO values was 0.18 ( SD = 0.08) and with low CO values 0.25 ( SD = 0.11).

For analyzing indirect effects, CO was the independent variable, time without water the mediator and team performance the dependent variable. The findings indicated that CO has an indirect effect on team performance mediated by time without water for scenario 1 (Table ​ (Table4) 4 ) and scenario 2 (Table ​ (Table5). 5 ). In scenario 1, CO had no direct effect on team performance ( b(YX) ), but CO significantly predicted time without water ( b(MX) ). A significant total effect ( b(YX) ) is not an assumption in the assessment of indirect effects, and therefore the non-significance of this relationship does not violate the analysis (see Preacher and Hayes, 2004 , p. 719). Furthermore, time without water significantly predicted team performance when controlling for CO ( b(YM.X) ), whereas the effect of CO on team performance was not significant when controlling for time without water ( b(YX.M) ). The indirect effect was 0.40 and significant when using normal distribution and estimated with the Sobel test ( z = 1.97, p < 0.05). The bootstrap procedure was applied to estimate the effect size not based on the assumption of normal distribution. As displayed in Table ​ Table4, 4 , the bootstrapped estimate of the indirect effect was 0.41 and the true indirect effect was estimated to lie between 0.0084 and 0.9215 with a 95% confidence interval. As zero is not in the 95% confidence interval, it can be concluded that the indirect effect is indeed significantly different from zero at p < 0.05 (two-tailed).

Indirect Effect for Coordination and Team Performance in Scenario 1.

Y = Team Performance Scenario 1; X = Collective Orientation T0; M = Coordination (time without water in scenario 1); Number of Bootstrap Resamples 5000 .

Indirect Effect for Coordination and Team Performance in Scenario 2.

Y = Team Performance Scenario 2; X = Collective Orientation T0; M = Coordination (time without water in scenario 2); Number of Bootstrap Resamples 5000 .

Regarding scenario 2, CO had a direct effect on team performance ( b(YX) ) and on time without water ( b(MX) ). Again, time without water significantly predicted team performance when controlling for CO ( b(YM.X) ), whereas the effect of CO on team performance was not significant when controlling for time without water ( b(YX.M) ). This time, the indirect effect was 0.60 (Sobel test, z = 2.31, p < 0.05). As displayed in Table ​ Table5, 5 , the bootstrapped estimate of the indirect effect was 0.61 and the true indirect effect was estimated to lie between 0.1876 and 1.1014 with a 95% confidence interval and between 0.0340 and 1.2578 with a 99% confidence interval. Because zero is not in the 99% confidence interval, it can be concluded that the indirect effect is indeed significantly different from zero at p < 0.01 (two-tailed).

The indirect effects for both scenarios are visualized in Figure ​ Figure6. 6 . Summing up, the results support hypothesis 1 and indicate that CO has an indirect effect on team performance mediated by the teams' coordination behavior, an action process. That means, fulfilling team process demands affect the dynamic decision making quality of teams acting in complex situations and input variables such as CO influence the action processes within teams positively.

Indirect effect of collective orientation on team performance via coordination within the teams for scenario 1 and 2, * p < 0.05, ** p < 0.01, *** p < 0.001, numbers in italic represent results from scenario 2, non-italic numbers are from scenario 1.

Trust between team members assessed after scenario 1 (T1) and after scenario 2 (T2) did not show any significant correlation with the coordination behavior or with team complex problem solving in scenarios 1 and 2 (Table ​ (Table3). 3 ). Thus, hypotheses 2a and 2b are not supported. Cohesion at T1 showed no significant relationship with team performance in both scenarios, one significant negative correlation ( r = −0.22, p < 0.05) with the coordination behavior in scenario 1 and no correlation with the coordination behavior in scenario 2. Cohesion at T2 did not show any significant correlation with the coordination behavior or with team performance in both scenarios. Thus, hypotheses 3a and 3b could also not be supported. Furthermore, the results showed no significant relations between CO and trust and cohesion. The correlations between trust and cohesion ranged between r = 0.39 and r = 0.51 ( p < 0.01).

The purpose of our paper was first to give a sound theoretical overview and to combine theoretical approaches about team competencies and team process demands in collaborative complex problem solving and second to demonstrate the importance of selected team competencies and processes on team performance in complex problem solving by means of results from a laboratory study. We introduced the model of an idealized teamwork process that complex problem solving team pass through and integrated the relevant teamwork skills for interdependently working teams into it. Moreover, we highlighted the episodic aspect concerning complex problem solving in teams and combined the well-known transition, action, interpersonal and learning processes of teamwork with the idealized teamwork process model. Finally, we investigated the influence of trust, cohesion, and CO on action processes, such as coordination behavior of complex problem solving teams and on team performance.

Regarding hypothesis 1, studies have indicated that teams whose members have high CO values are more successful in their coordination processes and task accomplishment (Eby and Dobbins, 1997 ; Driskell et al., 2010 ; Hagemann, 2017 ), which may enhance team performance through considering task inputs from other team members, information sharing and strategizing (Salas et al., 2005 ). Thus, we had a close look on CO as an emergent state in the present study, because emergent states support the execution of behavioral processes. In order to analyze this indirect effect of CO on team performance via coordination processes, we used the time, which firefighters spent without water in a scenario, as an indicator for high-quality coordination within the team. A small amount of time without water represents sharing information and resources between team members in a reciprocal manner, which are essential qualities of effective coordination (Ellington and Dierdorff, 2014 ). One of the two team members was in charge of the mobile water tank unit and therefore responsible for filling up the water tanks of his/her own firefighting unit and that of the other team member on time. In order to avoid running out of water for firefighting, the team members had to exchange information about, for example, their firefighting units' current and future positions in the field, their water levels, their strategies for extinguishing one or two fires, and the water tank unit's current and future position in the field. The simple mediation models showed that CO has an indirect effect on team performance mediated by time without water, supporting hypothesis 1. Thus, CO facilitates high-quality coordination within complex problem solving teams and this in turn influences decision-making and team performance positively (cf. Figure ​ Figure1). 1 ). These results support previous findings concerning the relationships between emergent states, such as CO, and the team process, such as action processes like coordination (Cannon-Bowers et al., 1995 ; Driskell et al., 2010 ) and between the team process and the team performance (Stevens and Campion, 1994 ; Dierdorff et al., 2011 ).

Hypotheses 2 and 3 analyzed the relationships between trust and cohesion and coordination and team performance. Because no correlations between trust and cohesion and the coordination behavior and team complex problem solving existed, further analyses, like mediation analyses, were unnecessary. In contrast to other studies (McAllister, 1995 ; Beal et al., 2003 ; Salas et al., 2005 ; Kozlowski and Ilgen, 2006 ), the present study was not able to detect effects of trust and cohesion on team processes, like action processes, or on team performance. This can be attributed to the restricted sample composition or the rather small sample size. Nevertheless, effect sizes were small to medium, so that they would have become significant with an increased sample sizes. The prerequisite, mentioned by the authors, that interdependence of the teamwork is important for identifying those effects, was given in the present study. Therefore, this aspect could not have been the reason for finding no effects concerning trust and cohesion. Trust and cohesion within the teams developed during working on the simulation scenarios while fighting fires, showed significant correlations with each other, and were unrelated to CO, which showed an effect on the coordination behavior and the team performance indeed. The results seem to implicate, that the influence of CO on action processes and team performance might be much more stronger than those of trust and cohesion. If these results can be replicated should be analyzed in future studies.

As the interdependent complex problem-solving task was a computer-based simulation, the results might have been affected by the participants' attitudes to using a computer. For example, computer affinity seems to be able to minimize potential fear of working with a simulation environment and might therefore, be able to contribute to successful performance in a computer-based team task. Although computers and other electronic devices are pervasive in present-day life, computer aversion has to be considered in future studies within complex problem-solving research when applying computer-based simulation team tasks. As all of the participants were studying applied cognitive science, which is a mix of psychology and computer science, this problem might not have been influenced the present results. However, the specific composition of the sample reduces the external validity of the study and the generalizability of the results. A further limitation is the small sample size, so that moderate to small effects are difficult to detect.

Furthermore, laboratory research of teamwork might have certain limitations. Teamwork as demonstrated in this study fails to account for the fact that teams are not simple, static and isolated entities (McGrath et al., 2000 ). The validity of the results could be reduced insofar as the complex relationships in teams were not represented, the teamwork context was not considered, not all teammates and teams were comparable, and the characteristic as a dynamic system with a team history and future was not given in the present study. This could be a possible explanation why no effects of trust and cohesion were found in the present study. Maybe, the teams need more time working together on the simulation scenarios in order to show that trust and cohesion influence the coordination with the team and the team performance. Furthermore, Bell ( 2007 ) demonstrated in her meta-analysis that the relationship between team members' attitudes and the team's performance was proven more strongly in the field compared to the laboratory. In consideration of this fact, the findings of the present study concerning CO are remarkable and the simulation based microworld C3Fire (Granlund et al., 2001 ; Granlund, 2003 ) seems to be appropriate for analyzing complex problem solving in interdependently working teams.

An asset of the present study is, that the teams' action processes, the coordination performance, was assessed objectively based on logged data and was not a subjective measure, as is often the case in group and team research studies (cf. Van de Ven et al., 1976 ; Antoni and Hertel, 2009 ; Dierdorff et al., 2011 ; Ellington and Dierdorff, 2014 ). As coordination was the mediator in the analysis, this objective measurement supports the validity of the results.

As no transition processes such as mission analysis, formulation, and planning (Prince and Salas, 1993 ), goal specification (Prussia and Kinicki, 1996 ), and strategy formulation (Prince and Salas, 1993 ; Cannon-Bowers et al., 1995 ) as well as action processes such as monitoring progress toward goals (Cannon-Bowers et al., 1995 ) and systems monitoring (Fleishman and Zaccaro, 1992 ) were analyzed within the present study, future studies should collect data concerning these processes in order to show their importance on performance within complex problem solving teams. Because these processes are difficult to observe, subjective measurements are needed, for example asking the participants after each scenario how they have prioritized various tasks, if and when they have changed their strategy concerning protecting houses or fighting fires, and on which data within the scenarios they focused for collecting information for goal and systems monitoring. Another possibility could be using eye-tracking methods in order to collect data about collecting information for monitoring progress toward goals, e.g., collecting information how many cells are still burning, and systems monitoring, e.g., tracking team resources like water for firefighting.

CO is an emergent state and emergent states can be influenced by experience or learning, for example (Kozlowski and Ilgen, 2006 ). Learning processes (Edmondson, 1999 ), that Schmutz et al. ( 2016 ) added to the taxonomy of team processes developed by Marks et al. ( 2001 ) and which occur during transition and action phases and contribute to team effectiveness include e.g., feedback . Feedback can be useful for team learning when team learning is seen as a form of information processing (Hinsz et al., 1997 ). Because CO supports action processes, such as coordination and it can be influenced by learning, learning opportunities, such as feedback, seem to be important for successful task accomplishment and for supporting teams in handling complex situations or problems. If the team is temporarily and interpersonally unstable, as it is the case for most of the disaster or crisis management teams dealing with complex problems, there might be less opportunities for generating shared mental models by experiencing repetitive cycles of joint action (cf. Figure ​ Figure2) 2 ) and strategies such as cross training (Salas et al., 2007 ) or feedback might become more and more important for successful complex problem solving in teams. Thus, for future research it would be of interest to analyze what kind of feedback is able to influence CO positively and therefore is able to enhance coordination and performance within complex problem-solving teams.

Depending on the type of feedback, different main points will be focused during the feedback (see Gabelica et al., 2012 ). Feedback can be differentiated into performance and process feedback. Process feedback can be further divided into task-related and interpersonal feedback. Besides these aspects, feedback can be given on a team-level or an individual-level. Combinations of the various kinds of feedback are possible and are analyzed in research concerning their influence on e.g., self- and team-regulatory processes and team performance (Prussia and Kinicki, 1996 ; Hinsz et al., 1997 ; Jung and Sosik, 2003 ; Gabelica et al., 2012 ). For future studies it would be relevant to analyze, whether it is possible to positively influence the CO of team members and therefore action processes such as coordination and team performance or not. A focus could be on the learning processes, especially on feedback, and its influence on CO in complex problem solving teams. So far, no studies exist that analyzed the relationship between feedback and a change in CO, even though researchers already discuss the possibility that team-level process feedback shifts attention processes on team actions and team learning (McLeod et al., 1992 ; Hinsz et al., 1997 ). These results would be very helpful for training programs for fire service or police or medical teams working in complex environments and solving problems collaboratively, in order to support their team working and their performance.

In summary, the idealized teamwork process model is in combination with the transition, action, interpersonal and learning processes a good framework for analyzing the impact of teamwork competencies and teamwork processes in detail on team performance in complex environments. Overall, the framework offers further possibilities for investigating the influence of teamwork competencies on diverse processes and teamwork outcomes in complex problem solving teams than demonstrated here. The results of our study provide evidence of how CO influences complex problem solving teams and their performance. Accordingly, future researchers and practitioners would be well advised to find interventions how to influence CO and support interdependently working teams.

Ethics statement

This study was carried out in accordance with the recommendations of Ethical guidelines of the German Association of Psychology, Ethics committee of the University of Duisburg-Essen, Department of Computer Science and Applied Cognitive Science with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics committee of the University of Duisburg-Essen, Department of Computer Science and Applied Cognitive Science.

Author contributions

VH and AK were responsible for the conception of the work and the study design. VH analyzed and interpreted the collected data. VH and AK drafted the manuscript. They approved it for publication and act as guarantors for the overall content.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01730/full#supplementary-material

• Antoni C., Hertel G. (2009). Team processes, their antecedents and consequences: implications for different types of teamwork . Eur. J. Work Organ. Psychol. 18 , 253–266. 10.1080/13594320802095502 [ CrossRef ] [ Google Scholar ]
• Arthur W., Edwards B., Bell S., Villado A., Bennet W. (2005). Team task analysis: identifying tasks and jobs that are team based . Hum. Factors 47 , 654–669. 10.1518/001872005774860087 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Badke-Schaub P. (2008). Teamarbeit und Teamführung: Erfolgsfaktoren und sicheres Handeln. [Teamwork and Team leadership: Factors of success and reliable action] , in Führung und Teamarbeit in kritischen Situationen [Leadership and teamwork in critical situations] eds Buerschaper C., Starke S. (Frankfurt: Verlag für Polizeiwissenschaft; ), 3–19. [ Google Scholar ]
• Beal D. J., Cohen R. R., Burke M. J., McLendon C. L. (2003). Cohesion and performance in groups: a meta-analytic clarification of construct relations . J. Appl. Psychol. 88 , 989–1004. 10.1037/0021-9010.88.6.989 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bell S. T. (2007). Deep-level composition variables as predictors of team performance: a meta-analysis . J. Appl. Psychol. 92 , 595–615. 10.1037/0021-9010.92.3.595 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bower G. H., Hilgard E. R. (1981). Theories of Learning . Englewood Cliffs, NJ: Prentice-Hall. [ Google Scholar ]
• Bredenkamp J. (1998). Lernen, Erinnern, Vergessen [Learning, Remembering, Forgetting]. München: C.H. Beck. [ Google Scholar ]
• Brehmer B. (1992). Dynamic decision-making: human control of complex systems . Acta Psychol. 81 , 211–241. 10.1016/0001-6918(92)90019-A [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Brehmer B., Dörner D. (1993). Experiments with computer-simulated microworlds: escaping both the narrow straits of the laboratory and the deep blue sea of the field study . Comput. Hum. Behav. 9 , 171–184. 10.1016/0747-5632(93)90005-D [ CrossRef ] [ Google Scholar ]
• Campion M. A., Medsker G. J., Higgs C. (1993). Relations between work group characteristics and effectiveness: implications for designing effective work groups . Pers. Psychol. 46 , 823–850. 10.1111/j.1744-6570.1993.tb01571.x [ CrossRef ] [ Google Scholar ]
• Cannon-Bowers J. A., Salas E., Converse S. (1993). Shared mental models in expert team decision making , in Individual and Group Decision Making , ed Castellan N. J. (Hillsdale, NJ: Lawrence Erlbaum Associates; ), 221–246. [ Google Scholar ]
• Cannon-Bowers J. A., Tannenbaum S. I., Salas E., Volpe C. E. (1995). Defining competencies and establishing team training requirements , in Team Effectiveness and Decision Making in Organizations , eds Guzzo R. A., E. Salas and Associates (San Francisco, CA: Jossey-Bass; ), 333–380. [ Google Scholar ]
• DeChurch L. A., Mesmer-Magnus J. R. (2010). The cognitive underpinnings of effective teamwork: a meta-analysis . J. Appl. Psychol. 95 , 32–53. 10.1037/a0017328 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dierdorff E. C., Bell S. T., Belohlav J. A. (2011). The “power of we”: effects of psychological collectivism on team performance over time . J. Appl. Psychol. 96 , 247–262. 10.1037/a0020929 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dörner D. (1989/2003). Die Logik des Misslingens. Strategisches Denken in komplexen Situationen [The logic of failure. Strategic thinking in complex situations] 11th Edn . Reinbeck: rororo. [ Google Scholar ]
• Dörner D., Kreuzig H. W., Reither F., Stäudel T. (1983). Lohhausen. Vom Umgang mit Unbestimmtheit und Komplexität. Bern; Stuttgart; Wien: Verlag Hans Huber. [ Google Scholar ]
• Driskell J. E., Salas E. (1992). Collective behavior and team performance . Hum. Factors 34 , 277–288. 10.1177/001872089203400303 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Driskell J., Salas E., Hughes S. (2010). Collective orientation and team performance: development of an individual differences measure . Hum. Factors 52 , 316–328. 10.1177/0018720809359522 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Eby L. T., Dobbins G. H. (1997). Collectivistic orientation in teams: an individual and group-level analysis . J. Organ. Behav. 18 , 275–295. 10.1002/(SICI)1099-1379(199705)18:3<275::AID-JOB796>3.0.CO;2-C [ CrossRef ] [ Google Scholar ]
• Edmondson A. (1999). Psychological safety and learning behavior in work teams . Adm. Sci. Q. 44 , 350–383. 10.2307/2666999 [ CrossRef ] [ Google Scholar ]
• Ellington J. K., Dierdorff E. C. (2014). Individual learning in team training: self-regulation and team context effects . Small Group Res. 45 , 37–67. 10.1177/1046496413511670 [ CrossRef ] [ Google Scholar ]
• Endsley M. R. (1999). Situation Awareness in Aviation Systems , in Handbook of Aviation Human Factors , eds Garland D. J., Wise J. A., Hopkin V. D. (Mahwah, NJ: Lawrence Erlbaum Associates Publishers; ), 257–276. [ Google Scholar ]
• Endsley M. R., Robertson M. M. (2000). Training for Situation Awareness in Individuals and Teams , in Situation awareness Analysis and Measurement , eds Endsley M. R., Garland D. J. (Mahwah, NJ: Lawrence Erlbaum Associates Publishers; ), 349–365. [ Google Scholar ]
• Fiore S. M., Rosen M. A., Smith-Jentsch K. A., Salas E., Letsky M., Warner N. (2010). Toward an understanding of macrocognition in teams: predicting processes in complex collaborative contexts . Hum. Factors 52 , 203–224. 10.1177/0018720810369807 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fleishman E. A., Zaccaro S. J. (1992). Toward a taxonomy of team performance funtions , in Teams: Their Training and Performance , eds Swezey R. W., Salas E. (Norwood, NJ: Ables; ), 31–56. [ Google Scholar ]
• Flin R., O'Connor P., Crichton M. (2008). Safety at the Sharp End. Aldershot: Ashgate. [ Google Scholar ]
• Funke J. (1995). Experimental research on complex problem solving , in Complex Problem Solving: The European Perspective eds Frensch P. A., Funke J. (Hillsdale, NJ: Lawrence Erlbaum Associates; ), 243–268. [ Google Scholar ]
• Funke J. (2001). Daynamic systems as tools for analysing human judgement . Think. Reason. 7 , 69–89. 10.1080/13546780042000046 [ CrossRef ] [ Google Scholar ]
• Funke J. (2012). Complex Problem Solving , in Encyclopedia of the Sciences of Learning ed Seel N. M. (Heidelberg: Springer; ), 682–685. [ Google Scholar ]
• Gabelica C., van den Bossche P., de Maeyer S., Segers M., Gijselaers W. (2014). The effect of team feedback and guided reflexivity on team performance change . Learn. Instruct. 34 , 86–96. 10.1016/j.learninstruc.2014.09.001 [ CrossRef ] [ Google Scholar ]
• Gabelica C., Van den Bossche P., Segers M., Gijselaers W. (2012). Feedback, a powerful lever in teams: a review . Educ. Res. Rev. 7 , 123–144. 10.1016/j.edurev.2011.11.003 [ CrossRef ] [ Google Scholar ]
• Geister S., Konradt U., Hertel G. (2006). Effects of process feedback on motivation, satisfaction, and performance in virtual teams . Small Group Res. 37 , 459–489. 10.1177/1046496406292337 [ CrossRef ] [ Google Scholar ]
• Gibson C. B. (1999). Do they do what they believe they can? group efficacy and group effectiveness across tasks and cultures . Acad. Manag. J. 42 , 138–152. 10.2307/257089 [ CrossRef ] [ Google Scholar ]
• Granlund R. (2003). Monitoring experiences from command and control research with the C 3 Fire microworld . Cogn. Technol. Work 5 , 183–190. 10.1007/s10111-003-0129-8 [ CrossRef ] [ Google Scholar ]
• Granlund R., Johansson B. (2004). Monitoring distributed collaboration in the C 3 Fire Microworld , in Scaled Worlds: Development, Validation and Applications , eds Schiflett G., Elliot L. R., Salas E., Coovert M. D. (Aldershot: Ashgate; ), 37–48. [ Google Scholar ]
• Granlund R., Johansson B., Persson M. (2001). C3Fire a micro-world for collaboration training and investigations in the ROLF environment , in Proceedings of 42nd Conference on Simulation and Modeling: Simulation in Theory and Practice (Porsgrunn: ). [ Google Scholar ]
• Hackman J. R. (1987). The design of work teams , in Handbook of Organizational Behavior ed Lorsch J. W. (Englewood Cliffs, NJ: Prentice-Hall; ), 315–342. [ Google Scholar ]
• Hagemann V. (2011). Trainingsentwicklung für High Responsibility Teams [Training development for High Responsibility Teams] . Lengerich: Pabst Verlag. [ Google Scholar ]
• Hagemann V. (2017). Development of a German-language questionnaire to measure collective orientation as an individual attitude . Swiss J. Psychol. 76 , 91–105. 10.1024/1421-0185/a000198 [ CrossRef ] [ Google Scholar ]
• Hagemann V., Kluge A., Ritzmann S. (2011). High responsibility teams - Eine systematische Analyse von Teamarbeitskontexten für einen effektiven Kompetenzerwerb [A systematic analysis of teamwork contexts for effective competence acquisition] . Psychologie des Alltagshandelns 4 , 22–42. Available online at: http://www.allgemeine-psychologie.info/cms/images/stories/allgpsy_journal/Vol%204%20No%201/hagemann_kluge_ritzmann.pdf [ Google Scholar ]
• Hagemann V., Kluge A., Ritzmann S. (2012). Flexibility under complexity: work contexts, task profiles and team processes of high responsibility teams . Empl. Relat. 34 , 322–338. 10.1108/01425451211217734 [ CrossRef ] [ Google Scholar ]
• Hertel G., Konradt U., Orlikowski B. (2004). Managing distance by interdependence: goal setting, task interdependence, and team-based rewards in virtual teams . Euro. J. Work Organ. Psychol. 13 , 1–28. 10.1080/13594320344000228 [ CrossRef ] [ Google Scholar ]
• Hinsz V., Tindale R., Vollrath D. (1997). The emerging concept of groups as information processors . Psychol. Bull. 121 , 43–64. 10.1037/0033-2909.121.1.43 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hollingshead A. B., Gupta N., Yoon K., Brandon D. (2012). Transactive memory theory and teams: past, present, and future , in Theories of Team Cognition , eds Salas E., Fiore S. M., Letsky M. (New York, NY: Routledge Taylor & Francis Group; ), 421–455. [ Google Scholar ]
• Ilgen D. R., Hollenbeck J. R., Johnson M., Jundt D. (2005). Teams in organizations: from input-process-output models to IMOI models . Annu. Rev. Psychol. 56 , 517–543. 10.1146/annurev.psych.56.091103.070250 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jobidon M.-E., Muller-Gass A., Duncan M., Blais A.-R. (2012). The enhance of mental models and its impact on teamwork . Proc. Hum. Factors Ergon. Soc. Annu. Meet. 56 , 1703–1707. 10.1177/1071181312561341 [ CrossRef ] [ Google Scholar ]
• Jung D. I., Sosik J. J. (2003). Group potency and collective efficacy . Group Organ. Manage. 28 , 366–391. 10.1177/1059601102250821 [ CrossRef ] [ Google Scholar ]
• Kluge A. (2014). The Acquisition of Knowledge and Skills for Taskwork and Teamwork to Control Complex Technical Systems: A Cognitive and Macroergonomics Perspective . Dordrecht: Springer. [ Google Scholar ]
• Kluge A., Hagemann V., Ritzmann S. (2014). Military crew resource management – Das Streben nach der bestmöglichen Teamarbeit [Striving for the best of teamwork] , in Psychologie für Einsatz und Notfall [Psychology for mission and emergency] , eds Kreim G., Bruns S., Völker B. (Bonn: Bernard & Graefe in der Mönch Verlagsgesellschaft mbH; ), 141–152. [ Google Scholar ]
• Kluge A., Sauer J., Schüler K., Burkolter D. (2009). Designing training for process control simulators: a review of empirical findings and current practices, theoretical issues in ergonomics Science 10 , 489–509. 10.1080/14639220902982192 [ CrossRef ] [ Google Scholar ]
• Kozlowski S. W. J., Ilgen D. R. (2006). Enhancing the effectiveness of work groups and teams . Psychol. Sci. Public Interest 7 , 77–124. 10.1111/j.1529-1006.2006.00030.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lafond D., Jobidon M.-E., Aubé C., Tremblay S. (2011). Evidence of structure- specific teamwork requirements and implications for team design . Small Group Res. 42 , 507–535. 10.1177/1046496410397617 [ CrossRef ] [ Google Scholar ]
• Marks M. A., Mathieu J. E., Zaccaro S. J. (2001). A temporally based framework and taxonomy of team processes . Acad. Manag. Rev. 26 , 356–376. 10.2307/259182 [ CrossRef ] [ Google Scholar ]
• Mathieu J. E., Heffner T. S., Goodwin G. F., Salas E., Cannon-Bowers J. A. (2000). The influence of shared mental models on team process and performance . J. Appl. Psychol. 85 , 273–283. 10.1037/0021-9010.85.2.273 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• McAllister D. J. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations . Acad. Manag. J. 38 , 24–59. 10.2307/256727 [ CrossRef ] [ Google Scholar ]
• McGrath J. E. (1984). Groups: Interaction and Performance . Englewood Cliffs, NJ: Prentice-Hall. [ Google Scholar ]
• McGrath J. E., Arrow H., Berdahl J. L. (2000). The study of groups: past, present, and future . Pers. Soc. Psychol. Rev. 4 , 95–105. 10.1207/S15327957PSPR0401_8 [ CrossRef ] [ Google Scholar ]
• McLeod P. L., Liker J. K., Lobel S. A. (1992). Process feedback in task groups: an application of goal setting . J. Appl. Behav. Sci. 28 , 15–41. 10.1177/0021886392281003 [ CrossRef ] [ Google Scholar ]
• Morgan B. B., Salas E., Glickman A. S. (1993). An analysis of team evolution and maturation . J. Gen. Psychol. 120 , 277–291. 10.1080/00221309.1993.9711148 [ CrossRef ] [ Google Scholar ]
• Ormerod T. C., Richardson J., Shepherd A. (1998). Enhancing the usability of a task analysis method: a notation and environment for requirements specification . Ergonomics 41 , 1642–1663. 10.1080/001401398186117 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Preacher K., Hayes A. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models . Behav. Res. Methods Instrum. Comput. 36 , 717–731. 10.3758/BF03206553 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Prince C., Salas E. (1993). Training and research for teamwork in the military aircrew , in Cockpit Resource Management , eds Wiener E. L., Kanki B. G., Helmreich R. L. (San Diego, CA: Academic Press; ), 337–366. [ Google Scholar ]
• Prussia G. E., Kinicki A. J. (1996). A motivation investigation of group effectiveness using social-cognitive theory . J. Appl. Psychol. 81 , 187–198. 10.1037/0021-9010.81.2.187 [ CrossRef ] [ Google Scholar ]
• Riordan C. M., Weatherly E. W. (1999). Defining and measuring employees‘identification with their work groups . Educ. Psychol. Meas. 59 , 310–324. 10.1177/00131649921969866 [ CrossRef ] [ Google Scholar ]
• Roth E. M., Woods D. D. (1988). Aiding human performance i: cognitive analysis . Trav. Hum. 51 , 39–64. [ Google Scholar ]
• Salas E., Cooke N. J., Rosen M. A. (2008). On teams, teamwork, and team performance: discoveries and developments . Hum. Factors 50 , 540–547. 10.1518/001872008X288457 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Salas E., Nichols D. R., Driskell J. E. (2007). Testing three team training strategies in intact teams . Small Group Res. 38 , 471–488. 10.1177/1046496407304332 [ CrossRef ] [ Google Scholar ]
• Salas E., Sims D., Burke S. (2005). Is there a “big five” in teamwork? Small Group Res. 36 , 555–599. 10.1177/1046496405277134 [ CrossRef ] [ Google Scholar ]
• Schmutz J., Welp A., Kolbe M. (2016). Teamwork in healtcare organizations , in Management Innovations for Health Care Organizations , eds Örtenblad A., Löfström C. A., Sheaff R. (New York, NY: Routledge Taylor & Francis; ), 359–377. [ Google Scholar ]
• Serfaty D., Entin E. E., Johnston J. H. (1998). Team coordination training , in Making Decisions Under Stress , eds Cannon-Bowers J. A., Salas E. (Washington, DC: American Psychological Association; ), 221–246. [ Google Scholar ]
• Shea G. P., Guzzo R. A. (1987). Group effectiveness: what really matters? Sloan Manage. Rev. 28 , 25–31. [ Google Scholar ]
• Smith-Jentsch K. A., Baker D. P., Salas E., Cannon-Bowers J. A. (2001). Uncovering differences in team competency requirements: The case of air traffic control teams , in Improving Teamwork in Organizations. Applications of Resource Management Training , eds Salas E., Bowers C. A., Edens E. (Mahwah, NJ: Lawrence Erlbaum Associates Publishers; ), 31–54. [ Google Scholar ]
• Stajkovic A. D., Lee D., Nyberg A. J. (2009). Collective efficacy, group potency, and group performance: meta-analyses of their relationships, and test of a mediation model . J. Appl. Psychol. 94 , 814–828. 10.1037/a0015659 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stevens M. J., Campion M. A. (1994). The knowledge, skill, and ability requirements for teamwork: implications for human resource management . J. Manage. 20 , 503–530. 10.1177/014920639402000210 [ CrossRef ] [ Google Scholar ]
• Ulich E. (1995). Gestaltung von Arbeitstätigkeiten [Designing job tasks] , in Lehrbuch Organisationspsychologie [Schoolbook Organizational Psychology] , ed Schuler H. (Bern: Huber; ), 189–208. [ Google Scholar ]
• Van de Ven A. H., Delbecq A. L., Koenig R. (1976). Determinants of coordination modes with organizations . Am. Sociol. Rev. 41 , 322–338. 10.2307/2094477 [ CrossRef ] [ Google Scholar ]
• Wageman R. (1995). Interdependence and group effectiveness . Adm. Sci. Q. 40 , 145–180. 10.2307/2393703 [ CrossRef ] [ Google Scholar ]
• Waller M. J., Gupta N., Giambatista R. C. (2004). Effects of adaptive behaviors and shared mental models on control crew performance . Manage. Sci. 50 , 1534–1544. 10.1287/mnsc.1040.0210 [ CrossRef ] [ Google Scholar ]
• Wilson K. A., Salas E., Andrews D. H. (2010). Preventing errors in the heat of the battle: formal and informal learning strategies to prevent teamwork breakdowns , in Human Factors Issues in Combat Identification , eds Andrews D. H., Herz R. P., Wolf M. B. (Aldershot: Ashgate; ), 1–28. [ Google Scholar ]
• Zsambok C. E. (1997). Naturalistic decision making: where are we now? , in Naturalistic Decision Making , eds Zsambok C. E., Klein G. (New York, NY: Routledge; ), 3–16. [ Google Scholar ]

Problem-Solving Mindset: How to Achieve It (15 Ways)

One of the most valuable skills you can have in life is a problem-solving mindset. It means that you see challenges as opportunities to learn and grow, rather than obstacles to avoid or complain about. A problem-solving mindset helps you overcome difficulties, achieve your goals, and constantly improve yourself. By developing a problem-solving mindset, you can become more confident, creative, and resilient in any situation.A well-defined problem paves the way for targeted, effective solutions. Resist the urge to jump straight into fixing things. Invest the time upfront to truly understand what needs to be solved. Starting with the end in mind will make the path to resolution that much smoother.

Sanju Pradeepa

* This Post may contain affiliate Links, and we receive an affiliate commission for any purchases made by you using such links. *

Ever feel like you’re stuck in a rut with no way out? We’ve all been there. The problems life throws at us can seem insurmountable. But the truth is, you have everything you need to overcome any challenge already within you. It’s called a problem-solving mindset. Developing the ability to see problems as puzzles to solve rather than obstacles to overcome is a game changer. With the right mindset, you can achieve amazing things.

In this article, we’ll explore what having a problem-solving mindset really means and how you can cultivate one for yourself. You’ll learn proven techniques to shift your perspective, expand your creativity, and find innovative solutions to your biggest problems. We’ll look at examples of people who have used a problem-solving mindset to accomplish extraordinary feats. By the end, you’ll have the tools and inspiration to transform how you think about and approach problems in your own life.

Table of Contents

What is a problem-solving mindset.

A problem solving mindset is all about approaching challenges in a solution-focused way. Rather than feeling defeated by obstacles, you look at them as puzzles to solve. Developing this mindset takes practice, but the rewards of increased resilience, creativity and confidence make it worth the effort.

• Identify problems, not excuses. Rather than blaming external factors, look for the issues within your control. Ask yourself, “What’s really going on here and what can I do about it?”
• Focus on solutions, not problems. Once you’ve pinpointed the issue, brainstorm options to fix it. Don’t get stuck in a negative loop. Shift your mindset to answer the question, “What are some possible solutions?”
• Look for opportunities, not obstacles. Reframe the way you view problems. See them as chances to improve and learn, rather than roadblocks stopping your progress. Ask, “What’s the opportunity or lesson here?”
• Start small and build up. Don’t feel overwhelmed by big challenges. Break them into manageable steps and celebrate small wins along the way. Solving little problems builds your confidence to tackle bigger issues.

Be patient with yourself and maintain an open and curious attitude . With regular practice, you’ll get better at seeing the solutions, rather than the obstacles. You’ll become more flexible and innovative in your thinking. And you’ll discover that you have the ability to solve problems you once thought insurmountable. That’s the power of a problem-solving mindset.

Why Developing a Problem Solving Mindset Is Important

Developing a problem-solving mindset is crucial these days. Why? Because life throws curveballs at us constantly and the only way to overcome them is through creative solutions.

Having a problem-solving mindset means you view challenges as opportunities rather than obstacles. You approach them with curiosity and optimism instead of dread. This allows you to see problems from new angles and come up with innovative solutions.

Some key characteristics of a problem-solving mindset include:

• Flexibility. You’re open to different perspectives and willing to consider alternative options.
• Creativity. You think outside the box and make unexpected connections between ideas.
• Persistence. You don’t give up easily in the face of difficulties or setbacks. You continue experimenting and adjusting your approach.
• Adaptability. You accept change and are able to quickly adjust your strategies or plans to suit new situations.
• Resourcefulness. You make the most of what you have access to and find ways to overcome limitations.

Developing a problem-solving mindset takes conscious effort and practice.

The Key Characteristics of Effective Problem Solvers

To become an effective problem solver, you need to develop certain characteristics and mindsets. Here are some of the key traits shared by great problem solvers:

1. Openness to New Ideas

Effective problem solvers have an open and curious mind. They seek out new ways of looking at problems and solutions. Rather than dismissing ideas that seem “out there,” they explore various options with an open mind.

2. Flexibility

Great problem solvers are flexible in their thinking. They can see problems from multiple perspectives and are willing to adapt their approach. If one solution isn’t working, they try another. They understand that there are many paths to solving a problem.

3. Persistence

Solving complex problems often requires persistence and determination. Effective problem solvers don’t give up easily. They continue exploring options and trying new solutions until they find one that works. They see setbacks as learning opportunities rather than failures.

Why Persistence is Important: 8 Benefits & 6 Ways to Develop

4. creativity.

Innovative problem solvers think outside the box . They make unexpected connections and come up with unconventional solutions. They utilize techniques like brainstorming, mind mapping, and lateral thinking to spark new ideas.

5. Analytical Thinking

While creativity is key, problem solvers also need to be able to evaluate solutions in a logical and analytical manner. They need to be able to determine the pros and cons, costs and benefits, and potential obstacles or issues with any solution. They rely on data, evidence, and objective reasoning to make decisions.

7 Types of Critical Thinking: A Guide to Analyzing Problems

How to cultivate a problem-solving mindset.

To cultivate a problem-solving mindset, you need to develop certain habits and ways of thinking. Here are some tips to get you started:

1. Look for Opportunities to Solve Problems

The more you practice problem solving, the better you’ll get at it. Look for opportunities in your daily life to solve small problems. This could be figuring out a better way to organize your tasks at work or coming up with a solution to traffic in your neighborhood. Start with small, low-risk problems and work your way up to more complex challenges.

2. Ask Good Questions

One of the most important skills in problem solving is asking good questions. Questions help you gain a deeper understanding of the issue and uncover new perspectives. Ask open-ended questions like:

• What’s the real problem here?
• What are the underlying causes?
• Who does this impact and how?
• What has been tried before? What worked and what didn’t?

3. Do Your Research

Don’t go into problem solving blind. Do some research to gather relevant facts and data about the situation. The more you know, the better equipped you’ll be to come up with innovative solutions. Talk to people with different viewpoints and life experiences to gain new insights.

4. Brainstorm Many Options

When you start thinking of solutions, don’t settle for the first idea that comes to mind. Brainstorm many options to open up possibilities. The more choices you have, the more likely you are to discover an unconventional solution that really fits the needs of the situation. Think outside the box!

5. Evaluate and Decide

Once you have a list of possible solutions, evaluate each option objectively based on criteria like cost, time, and effectiveness. Get input from others if needed. Then make a decision and take action. Even if it’s not the perfect solution, you can make changes as you go based on feedback and results.

6. Question your beliefs

The beliefs and assumptions you hold can influence how you perceive and solve problems. Ask yourself:

• What beliefs or stereotypes do I have about this situation or the people involved?
• Are these beliefs grounded in facts or just my personal experiences?
• How might my beliefs be limiting my thinking?

Challenging your beliefs helps you see the problem with fresh eyes and identify new solutions.

The Ultimate Guide of Overcoming Self-Limiting Beliefs

7. seek different perspectives.

Get input from people with different backgrounds, experiences, and thought processes than your own. Their unique perspectives can reveal new insights and spark innovative ideas. Some ways to gain new perspectives include:

• Discuss the problem with colleagues from different departments or areas of expertise.
• Interview customers or clients to understand their needs and priorities.
• Consult experts in unrelated fields for an outside-the-box opinion.
• Crowdsource solutions from people of diverse ages, cultures, and socioeconomic backgrounds.

8. Look beyond the obvious

We tend to focus on the most conspicuous or straightforward solutions, but the best option isn’t always obvious. Try these techniques to stimulate unconventional thinking:

• Restate the problem in new ways. A new phrasing can reveal alternative solutions.
• Remove constraints and imagine an ideal scenario. Then work backwards to find realistic options.
• Make unexpected associations between the problem and unrelated concepts or objects. Look for parallels and analogies in different domains.
• Play with hypothetical scenarios to find combinations you may not logically deduce. Some of the wildest ideas can lead to innovative solutions!

With an open and curious mindset, you can overcome assumptions, gain new insights, and find unconventional solutions to your most complex problems. The key is looking at the situation in new ways and exploring all possibilities.

Mindset is Everything: Reprogram Your Thinking for Success

9. practice active listening.

To become an effective problem solver, you need to practice active listening. This means paying close attention to what others are saying and asking follow-up questions to gain a deeper understanding of the issues.

Listen without judgment

When someone is explaining a problem to you, listen with an open mind. Avoid interrupting or criticizing them. Your role is to understand their perspective and concerns, not pass judgment. Nod, make eye contact, and give verbal affirmations like “I see” or “go on” to show you’re engaged.

Ask clarifying questions

If something is unclear or you need more details, ask questions. Say something like, “Can you explain that in more detail?” or “What specifically do you mean by that?” The more information you have about the problem, the better equipped you’ll be to solve it. Ask open-ended questions to encourage the other person to elaborate on their points.

Paraphrase and summarize

Repeat back parts of what the speaker said in your own words to confirm you understood them correctly. Say something like, “It sounds like the main issues are…” or “To summarize, the key points you’re making are…” This also shows the other person you were paying attention and care about addressing their actual concerns.

10. Withhold suggestions initially

When someone first presents you with a problem, avoid immediately suggesting solutions. Your first task is to understand the issue thoroughly. If you start proposing solutions too soon, it can seem like you’re not really listening and are just waiting for your turn to talk. Get clarification, summarize the issues, and ask any follow up questions needed before offering your input on how to solve the problem.

Developing the patience and discipline to actively listen takes practice. But by listening without judgment, asking clarifying questions, paraphrasing, and withholding suggestions initially, you’ll gain valuable insight into problems and be better equipped to solve them. Active listening is a skill that will serve you well in all areas of life.

11. Ask Lots of Questions

To solve problems effectively, you need to ask lots of questions. Questioning helps you gain a deeper understanding of the issue, uncover hidden factors, and open your mind to new solutions.

Asking “why” helps you determine the root cause of the problem. Keep asking “why” until you reach the underlying reason. For example, if sales numbers are down, ask why. The answer may be that you lost a key client. Ask why you lost the client. The answer could be poor customer service. Ask why the customer service was poor. And so on. Getting to the root cause is key to finding the right solution.

Challenge Assumptions

We all have implicit assumptions and biases that influence our thinking. Challenge any assumptions you have about the problem by asking questions like:

• What if the opposite is true?
• What are we missing or ignoring?
• What do we think is impossible but perhaps isn’t?

Questioning your assumptions opens you up to new perspectives and innovative solutions.

12. Consider Different Viewpoints

Try to see the problem from multiple angles by asking:

• How do others see this problem?
• What solutions might employees, customers, or experts suggest?
• What would someone from a different industry or background recommend?

Getting input from people with diverse experiences and ways of thinking will lead to better solutions.

13. Brainstorm New Possibilities

Once you have a good understanding of the root problem, start generating new solutions by asking open-ended questions like:

• What if anything were possible, what solutions come to mind?
• What are some wild and crazy ideas, even if implausible?
• What solutions have we not yet thought of?

Don’t judge or evaluate ideas at this stage. Just let the questions spark new creative solutions. The more questions you ask, the more solutions you’ll discover. With an inquisitive mindset, you’ll be well on your way to solving any problem.

14. Document what you find

As you research, keep notes on key details, facts, statistics, examples, and advice that stand out as most relevant or interesting. Look for common themes and threads across the different resources. Organize your notes by topic or theme to get a better sense of the big picture. Refer back to your notes to recall important points as you evaluate options and determine next steps.

Doing thorough research arms you with the knowledge and understanding to develop effective solutions. You’ll gain a deeper appreciation for the complexity of the problem and be able to make more informed choices. Research also exposes you to new ideas you may not have considered. While it requires an investment of time, research is a crucial step for achieving an optimal solution.

15. Start With the End in Mind: Define the Problem Clearly

To solve a problem effectively, you need to first define it clearly. Without a concrete understanding of the issue at hand, you’ll waste time and energy grappling with a vague, nebulous challenge.

Identify the root cause

Ask probing questions to determine the underlying reason for the problem. Get specific by figuring out who is affected, what’s not working, where the breakdown is happening, when it started, and why it’s an issue. Look beyond the symptoms to find the source. The solution lies in resolving the root cause, not just alleviating surface-level pain points.

Gather objective data

Rely on facts, not opinions or assumptions. Observe the situation directly and collect information from multiple sources. Get input from people with different perspectives. Hard data and evidence will give you an accurate, unbiased view of the problem.

Define constraints and priorities

Determine any restrictions around time, money, resources, or policies that could impact your solution. Also identify what’s most important to solve—you can’t fix everything at once. Focus on high-priority issues and leave lower-priority problems for another time.

Frame the problem statement

With a clear understanding of the root cause, supporting data, and constraints, you can craft a concise problem statement. This articulates the issue in 1 or 2 sentences and serves as a guiding vision for developing solutions. Refer back to your problem statement regularly to ensure you stay on track.

Final Thought

Developing a problem-solving mindset is within your reach if you commit to continuous learning, looking at challenges from new angles, and not being afraid to fail. Start small by picking one problem each day to solve in a creative way. Build up your confidence and skills over time through practice.

While it may feel uncomfortable at first, having an adaptable and solution-focused mindset will serve you well in all areas of life. You’ll be able to navigate obstacles and setbacks with more ease and grace. And who knows, you may even start to enjoy the problem-solving process and see problems as opportunities in disguise. The problem-solving mindset is a gift that keeps on giving. Now go out there, face your challenges head on, and solve away!

Solve It!: The Mindset and Tools of Smart Problem Solvers by  Dietmar Sternad

• Creative Problem Solving as Overcoming a Misunderstanding by Maria Bagassi  and  Laura Macchi * (Department of Psychology, University of Milano-Bicocca, Milan, Italy) ,
• Mindsets: A View From Two Eras by Carol S. Dweck 1  and  David S. Yeager 2 published in National Library of Medicine ( Perspect Psychol Sci.  Author manuscript; available in PMC 2020 May 1. Published in final edited form as: Perspect Psychol Sci. 2019 May; 14(3): 481–496. )

Call to Action

With regular practice, a problem solving mindset can become second nature. You’ll get better at seeing opportunities, asking the right questions, uncovering creative solutions, and taking action. And that will make you a highly valuable thinker in any organization or team.

Let’s boost your self-growth with Believe in Mind.

Interested in self-reflection tips, learning hacks, and knowing ways to calm down your mind? We offer you the best content which you have been looking for.

Follow Me on

You May Like Also

Leave a Comment Cancel reply

Save my name, email, and website in this browser for the next time I comment.

How it works

For Business

Join Mind Tools

Article • 0 min read

Team Building Exercises – Problem Solving and Decision Making

Fun ways to turn problems into opportunities.

By the Mind Tools Content Team

Whether there's a complex project looming or your team members just want to get better at dealing with day-to-day issues, your people can achieve much more when they solve problems and make decisions together.

By developing their problem-solving skills, you can improve their ability to get to the bottom of complex situations. And by refining their decision-making skills, you can help them work together maturely, use different thinking styles, and commit collectively to decisions.

In this article, we'll look at three team-building exercises that you can use to improve problem solving and decision making in a new or established team.

Exercises to Build Decision-Making and Problem-Solving Skills

Use the following exercises to help your team members solve problems and make decisions together more effectively.

Exercise 1: Lost at Sea*

In this activity, participants must pretend that they've been shipwrecked and are stranded in a lifeboat. Each team has a box of matches, and a number of items that they've salvaged from the sinking ship. Members must agree which items are most important for their survival.

Download and print our team-building exercises worksheet to help you with this exercise.

This activity builds problem-solving skills as team members analyze information, negotiate and cooperate with one another. It also encourages them to listen and to think about the way they make decisions.

What You'll Need

• Up to five people in each group.
• A large, private room.
• A "lost at sea" ranking chart for each team member. This should comprise six columns. The first simply lists each item (see below). The second is empty so that each team member can rank the items. The third is for group rankings. The fourth is for the "correct" rankings, which are revealed at the end of the exercise. And the fifth and sixth are for the team to enter the difference between their individual and correct score, and the team and correct rankings, respectively.
• The items to be ranked are: a mosquito net, a can of petrol, a water container, a shaving mirror, a sextant, emergency rations, a sea chart, a floating seat or cushion, a rope, some chocolate bars, a waterproof sheet, a fishing rod, shark repellent, a bottle of rum, and a VHF radio. These can be listed in the ranking chart or displayed on a whiteboard, or both.
• The experience can be made more fun by having some lost-at-sea props in the room.

Flexible, but normally between 25 and 40 minutes.

Instructions

• Divide participants into their teams, and provide everyone with a ranking sheet.
• Ask team members to take 10 minutes on their own to rank the items in order of importance. They should do this in the second column of their sheet.
• Give the teams a further 10 minutes to confer and decide on their group rankings. Once agreed, they should list them in the third column of their sheets.
• Ask each group to compare their individual rankings with their collective ones, and consider why any scores differ. Did anyone change their mind about their own rankings during the team discussions? How much were people influenced by the group conversation?
• Now read out the "correct" order, collated by the experts at the US Coast Guard (from most to least important): - Shaving mirror. (One of your most powerful tools, because you can use it to signal your location by reflecting the sun.) - Can of petrol. (Again, potentially vital for signaling as petrol floats on water and can be lit by your matches.) - Water container. (Essential for collecting water to restore your lost fluids.) -Emergency rations. (Valuable for basic food intake.) - Plastic sheet. (Could be used for shelter, or to collect rainwater.) -Chocolate bars. (A handy food supply.) - Fishing rod. (Potentially useful, but there is no guarantee that you're able to catch fish. Could also feasibly double as a tent pole.) - Rope. (Handy for tying equipment together, but not necessarily vital for survival.) - Floating seat or cushion. (Useful as a life preserver.) - Shark repellent. (Potentially important when in the water.) - Bottle of rum. (Could be useful as an antiseptic for treating injuries, but will only dehydrate you if you drink it.) - Radio. (Chances are that you're out of range of any signal, anyway.) - Sea chart. (Worthless without navigational equipment.) - Mosquito net. (Assuming that you've been shipwrecked in the Atlantic, where there are no mosquitoes, this is pretty much useless.) - Sextant. (Impractical without relevant tables or a chronometer.)

Advice for the Facilitator

The ideal scenario is for teams to arrive at a consensus decision where everyone's opinion is heard. However, that doesn't always happen naturally: assertive people tend to get the most attention. Less forthright team members can often feel intimidated and don't always speak up, particularly when their ideas are different from the popular view. Where discussions are one-sided, draw quieter people in so that everyone is involved, but explain why you're doing this, so that people learn from it.

You can use the Stepladder Technique when team discussion is unbalanced. Here, ask each team member to think about the problem individually and, one at a time, introduce new ideas to an appointed group leader – without knowing what ideas have already been discussed. After the first two people present their ideas, they discuss them together. Then the leader adds a third person, who presents his or her ideas before hearing the previous input. This cycle of presentation and discussion continues until the whole team has had a chance to voice their opinions.

After everyone has finished the exercise, invite your teams to evaluate the process to draw out their experiences. For example, ask them what the main differences between individual, team and official rankings were, and why. This will provoke discussion about how teams arrive at decisions, which will make people think about the skills they must use in future team scenarios, such as listening , negotiating and decision-making skills, as well as creativity skills for thinking "outside the box."

A common issue that arises in team decision making is groupthink . This can happen when a group places a desire for mutual harmony above a desire to reach the right decision, which prevents people from fully exploring alternative solutions.

If there are frequent unanimous decisions in any of your exercises, groupthink may be an issue. Suggest that teams investigate new ways to encourage members to discuss their views, or to share them anonymously.

Exercise 2: The Great Egg Drop*

In this classic (though sometimes messy!) game, teams must work together to build a container to protect an egg, which is dropped from a height. Before the egg drop, groups must deliver presentations on their solutions, how they arrived at them, and why they believe they will succeed.

This fun game develops problem-solving and decision-making skills. Team members have to choose the best course of action through negotiation and creative thinking.

• Ideally at least six people in each team.
• Raw eggs – one for each group, plus some reserves in case of accidents!
• Materials for creating the packaging, such as cardboard, tape, elastic bands, plastic bottles, plastic bags, straws, and scissors.
• Aprons to protect clothes, paper towels for cleaning up, and paper table cloths, if necessary.
• Somewhere – ideally outside – that you can drop the eggs from. (If there is nowhere appropriate, you could use a step ladder or equivalent.)
• Around 15 to 30 minutes to create the packages.
• Approximately 15 minutes to prepare a one-minute presentation.
• Enough time for the presentations and feedback (this will depend on the number of teams).
• Time to demonstrate the egg "flight."
• Put people into teams, and ask each to build a package that can protect an egg dropped from a specified height (say, two-and-a-half meters) with the provided materials.
• Each team must agree on a nominated speaker, or speakers, for their presentation.
• Once all teams have presented, they must drop their eggs, assess whether the eggs have survived intact, and discuss what they have learned.

When teams are making their decisions, the more good options they consider, the more effective their final decision is likely to be. Encourage your groups to look at the situation from different angles, so that they make the best decision possible. If people are struggling, get them to brainstorm – this is probably the most popular method of generating ideas within a team.

Ask the teams to explore how they arrived at their decisions, to get them thinking about how to improve this process in the future. You can ask them questions such as:

• Did the groups take a vote, or were members swayed by one dominant individual?
• How did the teams decide to divide up responsibilities? Was it based on people's expertise or experience?
• Did everyone do the job they volunteered for?
• Was there a person who assumed the role of "leader"?
• How did team members create and deliver the presentation, and was this an individual or group effort?

Exercise 3: Create Your Own*

In this exercise, teams must create their own, brand new, problem-solving activity.

This game encourages participants to think about the problem-solving process. It builds skills such as creativity, negotiation and decision making, as well as communication and time management. After the activity, teams should be better equipped to work together, and to think on their feet.

• Ideally four or five people in each team.
• Paper, pens and flip charts.

Around one hour.

• As the participants arrive, you announce that, rather than spending an hour on a problem-solving team-building activity, they must design an original one of their own.
• Divide participants into teams and tell them that they have to create a new problem-solving team-building activity that will work well in their organization. The activity must not be one that they have already participated in or heard of.
• After an hour, each team must present their new activity to everyone else, and outline its key benefits.

There are four basic steps in problem solving : defining the problem, generating solutions, evaluating and selecting solutions, and implementing solutions. Help your team to think creatively at each stage by getting them to consider a wide range of options. If ideas run dry, introduce an alternative brainstorming technique, such as brainwriting . This allows your people to develop one others' ideas, while everyone has an equal chance to contribute.

After the presentations, encourage teams to discuss the different decision-making processes they followed. You might ask them how they communicated and managed their time . Another question could be about how they kept their discussion focused. And to round up, you might ask them whether they would have changed their approach after hearing the other teams' presentations.

Successful decision making and problem solving are at the heart of all effective teams. While teams are ultimately led by their managers, the most effective ones foster these skills at all levels.

The exercises in this article show how you can encourage teams to develop their creative thinking, leadership , and communication skills , while building group cooperation and consensus.

* Original source unknown. Please let us know if you know the original source.

You've accessed 1 of your 2 free resources.

Get unlimited access

Discover more content

The plan-do-check-act process.

How to Minimize Risk

PDCA (Plan Do Check Act)

Continually Improving, in a Methodical Way

Add comment

Comments (0)

Be the first to comment!

Gain essential management and leadership skills

Busy schedule? No problem. Learn anytime, anywhere. 

Subscribe to unlimited access to meticulously researched, evidence-based resources.

Join today and save on an annual membership!

Sign-up to our newsletter

Subscribing to the Mind Tools newsletter will keep you up-to-date with our latest updates and newest resources.

Subscribe now

Business Skills

Personal Development

Leadership and Management

Member Extras

Most Popular

Latest Updates

Better Public Speaking

How to Build Confidence in Others

Mind Tools Store

About Mind Tools Content

Discover something new today

How to create psychological safety at work.

Speaking up without fear

How to Guides

Pain Points Podcast - Presentations Pt 1

How do you get better at presenting?

How Emotionally Intelligent Are You?

Boosting Your People Skills

Self-Assessment

What's Your Leadership Style?

Learn About the Strengths and Weaknesses of the Way You Like to Lead

Recommended for you

Confidence hacks.

Eight Tricks to Develop Your Confidence

Business Operations and Process Management

Strategy Tools

Customer Service

Business Ethics and Values

Handling Information and Data

Project Management

Knowledge Management

Self-Development and Goal Setting

Time Management

Presentation Skills

Learning Skills

Career Skills

Communication Skills

Negotiation, Persuasion and Influence

Working With Others

Difficult Conversations

Creativity Tools

Self-Management

Work-Life Balance

Stress Management and Wellbeing

Coaching and Mentoring

Change Management

Team Management

Managing Conflict

Delegation and Empowerment

Performance Management

Leadership Skills

Developing Your Team

Talent Management

Problem Solving

Decision Making

Member Podcast