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About the Journal

Case Studies in Strategic Communication (CSSC) is dedicated to the study of strategic communication through the case study form. Case studies illustrate the strategies, tactics, and execution of communication campaigns through in-depth coverage of a single situation. CSSC is a peer-reviewed online publication housed at the University of Texas / Texas Digital Library .

Case studies have long been central to the study of strategic communication, but these cases have been scattered across textbooks and websites, are quickly outdated, are not fully representative of the many facets of strategic communication, and lack a common format useful for teachers and scholars. Through the ongoing publication of strategic communication case studies online, CSSC aims to develop a living resource of diverse case materials for teachers, scholars, and practitioners.

As technological convergence and industry trends demand the integration of several branches of strategic communication in everyday practice, it is necessary to consider the approach to strategic communication holistically. Thus, CSSC welcomes case studies dealing with any number of the following disciplines: public relations, marketing, advertising, integrated marketing communication, social media campaigns, crisis communication, special events planning, development and fundraising, internal or employee communication, investor relations, community relations, media relations, online community management, publicity, and more.

There is no limit to topical coverage, and CSSC hopes to develop a resource that touches on as many industries, tactics, geographic regions, and diverse populations as possible. CSSC seeks case studies concerning all sectors, too: private companies (large and small), publicly-traded corporations, non-profit organizations (large and small), political campaigns, government agencies (local and national), and educational institutions.

In addition to success stories, CSSC also seeks case studies that explore failures, shortcomings, missed opportunities, and crises. Stories of failure are not often told in case study collections, but they sometimes yield the best lessons.

Daren Brabham launched CSSC in 2011 at the University of North Carolina School of Journalism & Mass Communication, began publishing case studies in 2012, and moved to USC Annenberg in 2013. In 2022, the journal is now published through the University of Texas at Austin/Texas Digital Library via the Stan Richards School of Advertising & Public Relations .  

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OpenAI: Idealism Meets Capitalism

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Generative AI and the Future of Work

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China Rapid Finance: The Collapse of China's P2P Lending Industry

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Unilever's Response to the Future of Work

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Insurer of Last Resort?: The Federal Financial Response to September 11

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Under Armour

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Apple's Core

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3.1: Ethics Case Study

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• Jasmine Roberts
• The Ohio State University

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The issue of ethics is important in the strategic communication profession. Creators of content should heavily rely on a code of ethics when carrying out various tasks. Using ethical reasoning, whether you’re designing a campaign or writing a newspaper article, demonstrates basic understanding of the influence of messages on audiences. Ethical communication also helps an organization avoid dilemmas and compromising situations.

Several cases covered in the press highlight the ramifications of failure to use ethical and honest standards in communication efforts. The case study below demonstrates this.

Case study: Ryan Holiday, media manipulation, and the rise of the Tucker Max brand

Media strategist Ryan Holiday made a career of controlling the media to achieve public relations goals. A few years ago, he became a PR specialist for Tucker Max, a controversial blogger and author who garnered attention for his lewd writing and explicit discussions of his sexual adventures with countless women. Holiday played an essential role in a campaign for Max’s book I Hope They Serve Beer in Hell. Pretending to be someone who hated Max’s writings, Holiday contacted influencers, bloggers, and television stations about the social controversy caused by the brand. Soon Max’s book received widespread attention from national media outlets and writers all over the blogosphere (Ariely & Melamede, 2015).

Filmmakers later created a movie based on the book. Holiday used some of the same tactics to promote the film. He emailed college organizations across the country, again pretending to be someone who was disgusted with the Tucker Max brand. He included photos of fake advertisements that were offensive to women (which Holiday himself had created), and said that the advertisements were used to promote the film (Ariely & Melamede, 2015). He told campus leaders, bloggers, and other influencers to urge people not to see the film.

Holiday was intentionally trying to create protests to generate media coverage and public awareness about the film and the Tucker Max brand in general (Ariely & Melamede, 2015). He used deceptive measures and some aspects of controversy—strong opinions on a topic, social backlash, and a hated public figure—as leverage. And he was very successful: organized groups across the country held protests against the film, furthering the widespread attention on Tucker Max. In this situation, the saying “any press is good press” worked to his advantage.

Cases such as this raise several concerns related to the field of strategic communication. Most important, the Tucker Max situation calls into question the ethics Holiday used to control the media. How far should one go to promote an organization or brand? The perception exists that strategic communication professionals, specifically those in public relations, are expert spin doctors and media manipulators; because of this, the profession’s credibility has been damaged. In order to reclaim the trustworthiness of the field, strategic communication professionals must abide by strong ethics in their decision-making processes.

The majority of strategic communication professionals promote their client or organization in an honest and straightforward manner. One case study that demonstrates this comes from a Columbus-based public relations agency, Geben Communication. In 2014, the agency helped promote a small catering business, Two Caterers. It used a targeted media relations strategy and pitched to several local publications and news stations (Geben Communication, 2016) in order to enhance brand awareness. The pitches contained factual information, and those working on the account did not use manipulative tactics to achieve their goal.

Geben Communication’s promotional effort had positive results. Local publications wrote several articles on Two Caterers, and a television station invited the small business to do a cooking demonstration for a morning segment. Furthermore, Two Caterers received accolades and recognition from small business associations and magazines.

Artificial intelligence in strategy

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform .

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?

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Yuval Atsmon: You’re right about the limited adoption. Only 7 percent of respondents to our survey about the use of AI say they use it in strategy or even financial planning, whereas in areas like marketing, supply chain, and service operations, it’s 25 or 30 percent. One reason adoption is lagging is that strategy is one of the most integrative conceptual practices. When executives think about strategy automation, many are looking too far ahead—at AI capabilities that would decide, in place of the business leader, what the right strategy is. They are missing opportunities to use AI in the building blocks of strategy that could significantly improve outcomes.

I like to use the analogy to virtual assistants. Many of us use Alexa or Siri but very few people use these tools to do more than dictate a text message or shut off the lights. We don’t feel comfortable with the technology’s ability to understand the context in more sophisticated applications. AI in strategy is similar: it’s hard for AI to know everything an executive knows, but it can help executives with certain tasks.

When executives think about strategy automation, many are looking too far ahead—at AI deciding the right strategy. They are missing opportunities to use AI in the building blocks of strategy.

Joanna Pachner: What kind of tasks can AI help strategists execute today?

Yuval Atsmon: We talk about six stages of AI development. The earliest is simple analytics, which we refer to as descriptive intelligence. Companies use dashboards for competitive analysis or to study performance in different parts of the business that are automatically updated. Some have interactive capabilities for refinement and testing.

The second level is diagnostic intelligence, which is the ability to look backward at the business and understand root causes and drivers of performance. The level after that is predictive intelligence: being able to anticipate certain scenarios or options and the value of things in the future based on momentum from the past as well as signals picked in the market. Both diagnostics and prediction are areas that AI can greatly improve today. The tools can augment executives’ analysis and become areas where you develop capabilities. For example, on diagnostic intelligence, you can organize your portfolio into segments to understand granularly where performance is coming from and do it in a much more continuous way than analysts could. You can try 20 different ways in an hour versus deploying one hundred analysts to tackle the problem.

Predictive AI is both more difficult and more risky. Executives shouldn’t fully rely on predictive AI, but it provides another systematic viewpoint in the room. Because strategic decisions have significant consequences, a key consideration is to use AI transparently in the sense of understanding why it is making a certain prediction and what extrapolations it is making from which information. You can then assess if you trust the prediction or not. You can even use AI to track the evolution of the assumptions for that prediction.

Those are the levels available today. The next three levels will take time to develop. There are some early examples of AI advising actions for executives’ consideration that would be value-creating based on the analysis. From there, you go to delegating certain decision authority to AI, with constraints and supervision. Eventually, there is the point where fully autonomous AI analyzes and decides with no human interaction.

Because strategic decisions have significant consequences, you need to understand why AI is making a certain prediction and what extrapolations it’s making from which information.

Joanna Pachner: What kind of businesses or industries could gain the greatest benefits from embracing AI at its current level of sophistication?

Yuval Atsmon: Every business probably has some opportunity to use AI more than it does today. The first thing to look at is the availability of data. Do you have performance data that can be organized in a systematic way? Companies that have deep data on their portfolios down to business line, SKU, inventory, and raw ingredients have the biggest opportunities to use machines to gain granular insights that humans could not.

Companies whose strategies rely on a few big decisions with limited data would get less from AI. Likewise, those facing a lot of volatility and vulnerability to external events would benefit less than companies with controlled and systematic portfolios, although they could deploy AI to better predict those external events and identify what they can and cannot control.

Third, the velocity of decisions matters. Most companies develop strategies every three to five years, which then become annual budgets. If you think about strategy in that way, the role of AI is relatively limited other than potentially accelerating analyses that are inputs into the strategy. However, some companies regularly revisit big decisions they made based on assumptions about the world that may have since changed, affecting the projected ROI of initiatives. Such shifts would affect how you deploy talent and executive time, how you spend money and focus sales efforts, and AI can be valuable in guiding that. The value of AI is even bigger when you can make decisions close to the time of deploying resources, because AI can signal that your previous assumptions have changed from when you made your plan.

Joanna Pachner: Can you provide any examples of companies employing AI to address specific strategic challenges?

Yuval Atsmon: Some of the most innovative users of AI, not coincidentally, are AI- and digital-native companies. Some of these companies have seen massive benefits from AI and have increased its usage in other areas of the business. One mobility player adjusts its financial planning based on pricing patterns it observes in the market. Its business has relatively high flexibility to demand but less so to supply, so the company uses AI to continuously signal back when pricing dynamics are trending in a way that would affect profitability or where demand is rising. This allows the company to quickly react to create more capacity because its profitability is highly sensitive to keeping demand and supply in equilibrium.

Joanna Pachner: Given how quickly things change today, doesn’t AI seem to be more a tactical than a strategic tool, providing time-sensitive input on isolated elements of strategy?

Yuval Atsmon: It’s interesting that you make the distinction between strategic and tactical. Of course, every decision can be broken down into smaller ones, and where AI can be affordably used in strategy today is for building blocks of the strategy. It might feel tactical, but it can make a massive difference. One of the world’s leading investment firms, for example, has started to use AI to scan for certain patterns rather than scanning individual companies directly. AI looks for consumer mobile usage that suggests a company’s technology is catching on quickly, giving the firm an opportunity to invest in that company before others do. That created a significant strategic edge for them, even though the tool itself may be relatively tactical.

Joanna Pachner: McKinsey has written a lot about cognitive biases  and social dynamics that can skew decision making. Can AI help with these challenges?

Yuval Atsmon: When we talk to executives about using AI in strategy development, the first reaction we get is, “Those are really big decisions; what if AI gets them wrong?” The first answer is that humans also get them wrong—a lot. [Amos] Tversky, [Daniel] Kahneman, and others have proven that some of those errors are systemic, observable, and predictable. The first thing AI can do is spot situations likely to give rise to biases. For example, imagine that AI is listening in on a strategy session where the CEO proposes something and everyone says “Aye” without debate and discussion. AI could inform the room, “We might have a sunflower bias here,” which could trigger more conversation and remind the CEO that it’s in their own interest to encourage some devil’s advocacy.

We also often see confirmation bias, where people focus their analysis on proving the wisdom of what they already want to do, as opposed to looking for a fact-based reality. Just having AI perform a default analysis that doesn’t aim to satisfy the boss is useful, and the team can then try to understand why that is different than the management hypothesis, triggering a much richer debate.

In terms of social dynamics, agency problems can create conflicts of interest. Every business unit [BU] leader thinks that their BU should get the most resources and will deliver the most value, or at least they feel they should advocate for their business. AI provides a neutral way based on systematic data to manage those debates. It’s also useful for executives with decision authority, since we all know that short-term pressures and the need to make the quarterly and annual numbers lead people to make different decisions on the 31st of December than they do on January 1st or October 1st. Like the story of Ulysses and the sirens, you can use AI to remind you that you wanted something different three months earlier. The CEO still decides; AI can just provide that extra nudge.

Joanna Pachner: It’s like you have Spock next to you, who is dispassionate and purely analytical.

Yuval Atsmon: That is not a bad analogy—for Star Trek fans anyway.

Joanna Pachner: Do you have a favorite application of AI in strategy?

Yuval Atsmon: I have worked a lot on resource allocation, and one of the challenges, which we call the hockey stick phenomenon, is that executives are always overly optimistic about what will happen. They know that resource allocation will inevitably be defined by what you believe about the future, not necessarily by past performance. AI can provide an objective prediction of performance starting from a default momentum case: based on everything that happened in the past and some indicators about the future, what is the forecast of performance if we do nothing? This is before we say, “But I will hire these people and develop this new product and improve my marketing”— things that every executive thinks will help them overdeliver relative to the past. The neutral momentum case, which AI can calculate in a cold, Spock-like manner, can change the dynamics of the resource allocation discussion. It’s a form of predictive intelligence accessible today and while it’s not meant to be definitive, it provides a basis for better decisions.

Joanna Pachner: Do you see access to technology talent as one of the obstacles to the adoption of AI in strategy, especially at large companies?

Yuval Atsmon: I would make a distinction. If you mean machine-learning and data science talent or software engineers who build the digital tools, they are definitely not easy to get. However, companies can increasingly use platforms that provide access to AI tools and require less from individual companies. Also, this domain of strategy is exciting—it’s cutting-edge, so it’s probably easier to get technology talent for that than it might be for manufacturing work.

The bigger challenge, ironically, is finding strategists or people with business expertise to contribute to the effort. You will not solve strategy problems with AI without the involvement of people who understand the customer experience and what you are trying to achieve. Those who know best, like senior executives, don’t have time to be product managers for the AI team. An even bigger constraint is that, in some cases, you are asking people to get involved in an initiative that may make their jobs less important. There could be plenty of opportunities for incorpo­rating AI into existing jobs, but it’s something companies need to reflect on. The best approach may be to create a digital factory where a different team tests and builds AI applications, with oversight from senior stakeholders.

The big challenge is finding strategists to contribute to the AI effort. You are asking people to get involved in an initiative that may make their jobs less important.

Joanna Pachner: Do you think this worry about job security and the potential that AI will automate strategy is realistic?

Yuval Atsmon: The question of whether AI will replace human judgment and put humanity out of its job is a big one that I would leave for other experts.

The pertinent question is shorter-term automation. Because of its complexity, strategy would be one of the later domains to be affected by automation, but we are seeing it in many other domains. However, the trend for more than two hundred years has been that automation creates new jobs, although ones requiring different skills. That doesn’t take away the fear some people have of a machine exposing their mistakes or doing their job better than they do it.

Joanna Pachner: We recently published an article about strategic courage in an age of volatility  that talked about three types of edge business leaders need to develop. One of them is an edge in insights. Do you think AI has a role to play in furnishing a proprietary insight edge?

Yuval Atsmon: One of the challenges most strategists face is the overwhelming complexity of the world we operate in—the number of unknowns, the information overload. At one level, it may seem that AI will provide another layer of complexity. In reality, it can be a sharp knife that cuts through some of the clutter. The question to ask is, Can AI simplify my life by giving me sharper, more timely insights more easily?

Joanna Pachner: You have been working in strategy for a long time. What sparked your interest in exploring this intersection of strategy and new technology?

Yuval Atsmon: I have always been intrigued by things at the boundaries of what seems possible. Science fiction writer Arthur C. Clarke’s second law is that to discover the limits of the possible, you have to venture a little past them into the impossible, and I find that particularly alluring in this arena.

AI in strategy is in very nascent stages but could be very consequential for companies and for the profession. For a top executive, strategic decisions are the biggest way to influence the business, other than maybe building the top team, and it is amazing how little technology is leveraged in that process today. It’s conceivable that competitive advantage will increasingly rest in having executives who know how to apply AI well. In some domains, like investment, that is already happening, and the difference in returns can be staggering. I find helping companies be part of that evolution very exciting.

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Chapter 3: Strategic Communication Ethics

11 Ethics case study

The issue of ethics is important in the strategic communication profession. Creators of content should heavily rely on a code of ethics when carrying out various tasks. Using ethical reasoning, whether you’re designing a campaign or writing a newspaper article, demonstrates basic understanding of the influence of messages on audiences. Ethical communication also helps an organization avoid dilemmas and compromising situations.

Several cases covered in the press highlight the ramifications of failure to use ethical and honest standards in communication efforts. The case study below demonstrates this.

Case study: Ryan Holiday, media manipulation, and the rise of the Tucker Max brand

Media strategist Ryan Holiday made a career of controlling the media to achieve public relations goals. A few years ago, he became a PR specialist for Tucker Max, a controversial blogger and author who garnered attention for his lewd writing and explicit discussions of his sexual adventures with countless women. Holiday played an essential role in a campaign for Max’s book I Hope They Serve Beer in Hell. Pretending to be someone who hated Max’s writings, Holiday contacted influencers, bloggers, and television stations about the social controversy caused by the brand. Soon Max’s book received widespread attention from national media outlets and writers all over the blogosphere (Ariely & Melamede, 2015).

Filmmakers later created a movie based on the book. Holiday used some of the same tactics to promote the film. He emailed college organizations across the country, again pretending to be someone who was disgusted with the Tucker Max brand. He included photos of fake advertisements that were offensive to women (which Holiday himself had created), and said that the advertisements were used to promote the film (Ariely & Melamede, 2015). He told campus leaders, bloggers, and other influencers to urge people not to see the film.

Holiday was intentionally trying to create protests to generate media coverage and public awareness about the film and the Tucker Max brand in general (Ariely & Melamede, 2015). He used deceptive measures and some aspects of controversy—strong opinions on a topic, social backlash, and a hated public figure—as leverage. And he was very successful: organized groups across the country held protests against the film, furthering the widespread attention on Tucker Max. In this situation, the saying “any press is good press” worked to his advantage.

Cases such as this raise several concerns related to the field of strategic communication. Most important, the Tucker Max situation calls into question the ethics Holiday used to control the media. How far should one go to promote an organization or brand? The perception exists that strategic communication professionals, specifically those in public relations, are expert spin doctors and media manipulators; because of this, the profession’s credibility has been damaged. In order to reclaim the trustworthiness of the field, strategic communication professionals must abide by strong ethics in their decision-making processes.

The majority of strategic communication professionals promote their client or organization in an honest and straightforward manner. One case study that demonstrates this comes from a Columbus-based public relations agency, Geben Communication. In 2014, the agency helped promote a small catering business, Two Caterers. It used a targeted media relations strategy and pitched to several local publications and news stations (Geben Communication, 2016) in order to enhance brand awareness. The pitches contained factual information, and those working on the account did not use manipulative tactics to achieve their goal.

Geben Communication’s promotional effort had positive results. Local publications wrote several articles on Two Caterers, and a television station invited the small business to do a cooking demonstration for a morning segment. Furthermore, Two Caterers received accolades and recognition from small business associations and magazines.

Writing for Strategic Communication Industries Copyright © 2016 by Jasmine Roberts is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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