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How to write a case study — examples, templates, and tools

It’s a marketer’s job to communicate the effectiveness of a product or service to potential and current customers to convince them to buy and keep business moving. One of the best methods for doing this is to share success stories that are relatable to prospects and customers based on their pain points, experiences, and overall needs.

That’s where case studies come in. Case studies are an essential part of a content marketing plan. These in-depth stories of customer experiences are some of the most effective at demonstrating the value of a product or service. Yet many marketers don’t use them, whether because of their regimented formats or the process of customer involvement and approval.

A case study is a powerful tool for showcasing your hard work and the success your customer achieved. But writing a great case study can be difficult if you’ve never done it before or if it’s been a while. This guide will show you how to write an effective case study and provide real-world examples and templates that will keep readers engaged and support your business.

In this article, you’ll learn:

What is a case study?

How to write a case study, case study templates, case study examples, case study tools.

A case study is the detailed story of a customer’s experience with a product or service that demonstrates their success and often includes measurable outcomes. Case studies are used in a range of fields and for various reasons, from business to academic research. They’re especially impactful in marketing as brands work to convince and convert consumers with relatable, real-world stories of actual customer experiences.

The best case studies tell the story of a customer’s success, including the steps they took, the results they achieved, and the support they received from a brand along the way. To write a great case study, you need to:

• Celebrate the customer and make them — not a product or service — the star of the story.
• Craft the story with specific audiences or target segments in mind so that the story of one customer will be viewed as relatable and actionable for another customer.
• Write copy that is easy to read and engaging so that readers will gain the insights and messages intended.
• Follow a standardized format that includes all of the essentials a potential customer would find interesting and useful.
• Support all of the claims for success made in the story with data in the forms of hard numbers and customer statements.

Case studies are a type of review but more in depth, aiming to show — rather than just tell — the positive experiences that customers have with a brand. Notably, 89% of consumers read reviews before deciding to buy, and 79% view case study content as part of their purchasing process. When it comes to B2B sales, 52% of buyers rank case studies as an important part of their evaluation process.

Telling a brand story through the experience of a tried-and-true customer matters. The story is relatable to potential new customers as they imagine themselves in the shoes of the company or individual featured in the case study. Showcasing previous customers can help new ones see themselves engaging with your brand in the ways that are most meaningful to them.

Besides sharing the perspective of another customer, case studies stand out from other content marketing forms because they are based on evidence. Whether pulling from client testimonials or data-driven results, case studies tend to have more impact on new business because the story contains information that is both objective (data) and subjective (customer experience) — and the brand doesn’t sound too self-promotional.

Case studies are unique in that there’s a fairly standardized format for telling a customer’s story. But that doesn’t mean there isn’t room for creativity. It’s all about making sure that teams are clear on the goals for the case study — along with strategies for supporting content and channels — and understanding how the story fits within the framework of the company’s overall marketing goals.

Here are the basic steps to writing a good case study.

1. Identify your goal

Start by defining exactly who your case study will be designed to help. Case studies are about specific instances where a company works with a customer to achieve a goal. Identify which customers are likely to have these goals, as well as other needs the story should cover to appeal to them.

The answer is often found in one of the buyer personas that have been constructed as part of your larger marketing strategy. This can include anything from new leads generated by the marketing team to long-term customers that are being pressed for cross-sell opportunities. In all of these cases, demonstrating value through a relatable customer success story can be part of the solution to conversion.

2. Choose your client or subject

Who you highlight matters. Case studies tie brands together that might otherwise not cross paths. A writer will want to ensure that the highlighted customer aligns with their own company’s brand identity and offerings. Look for a customer with positive name recognition who has had great success with a product or service and is willing to be an advocate.

The client should also match up with the identified target audience. Whichever company or individual is selected should be a reflection of other potential customers who can see themselves in similar circumstances, having the same problems and possible solutions.

Some of the most compelling case studies feature customers who:

• Switch from one product or service to another while naming competitors that missed the mark.
• Experience measurable results that are relatable to others in a specific industry.
• Represent well-known brands and recognizable names that are likely to compel action.
• Advocate for a product or service as a champion and are well-versed in its advantages.

Whoever or whatever customer is selected, marketers must ensure they have the permission of the company involved before getting started. Some brands have strict review and approval procedures for any official marketing or promotional materials that include their name. Acquiring those approvals in advance will prevent any miscommunication or wasted effort if there is an issue with their legal or compliance teams.

3. Conduct research and compile data

Substantiating the claims made in a case study — either by the marketing team or customers themselves — adds validity to the story. To do this, include data and feedback from the client that defines what success looks like. This can be anything from demonstrating return on investment (ROI) to a specific metric the customer was striving to improve. Case studies should prove how an outcome was achieved and show tangible results that indicate to the customer that your solution is the right one.

This step could also include customer interviews. Make sure that the people being interviewed are key stakeholders in the purchase decision or deployment and use of the product or service that is being highlighted. Content writers should work off a set list of questions prepared in advance. It can be helpful to share these with the interviewees beforehand so they have time to consider and craft their responses. One of the best interview tactics to keep in mind is to ask questions where yes and no are not natural answers. This way, your subject will provide more open-ended responses that produce more meaningful content.

4. Choose the right format

There are a number of different ways to format a case study. Depending on what you hope to achieve, one style will be better than another. However, there are some common elements to include, such as:

• An engaging headline
• A subject and customer introduction
• The unique challenge or challenges the customer faced
• The solution the customer used to solve the problem
• The results achieved
• Data and statistics to back up claims of success
• A strong call to action (CTA) to engage with the vendor

It’s also important to note that while case studies are traditionally written as stories, they don’t have to be in a written format. Some companies choose to get more creative with their case studies and produce multimedia content, depending on their audience and objectives. Case study formats can include traditional print stories, interactive web or social content, data-heavy infographics, professionally shot videos, podcasts, and more.

5. Write your case study

We’ll go into more detail later about how exactly to write a case study, including templates and examples. Generally speaking, though, there are a few things to keep in mind when writing your case study.

• Be clear and concise. Readers want to get to the point of the story quickly and easily, and they’ll be looking to see themselves reflected in the story right from the start.
• Provide a big picture. Always make sure to explain who the client is, their goals, and how they achieved success in a short introduction to engage the reader.
• Construct a clear narrative. Stick to the story from the perspective of the customer and what they needed to solve instead of just listing product features or benefits.
• Leverage graphics. Incorporating infographics, charts, and sidebars can be a more engaging and eye-catching way to share key statistics and data in readable ways.
• Offer the right amount of detail. Most case studies are one or two pages with clear sections that a reader can skim to find the information most important to them.
• Include data to support claims. Show real results — both facts and figures and customer quotes — to demonstrate credibility and prove the solution works.

6. Promote your story

Marketers have a number of options for distribution of a freshly minted case study. Many brands choose to publish case studies on their website and post them on social media. This can help support SEO and organic content strategies while also boosting company credibility and trust as visitors see that other businesses have used the product or service.

Marketers are always looking for quality content they can use for lead generation. Consider offering a case study as gated content behind a form on a landing page or as an offer in an email message. One great way to do this is to summarize the content and tease the full story available for download after the user takes an action.

Sales teams can also leverage case studies, so be sure they are aware that the assets exist once they’re published. Especially when it comes to larger B2B sales, companies often ask for examples of similar customer challenges that have been solved.

Now that you’ve learned a bit about case studies and what they should include, you may be wondering how to start creating great customer story content. Here are a couple of templates you can use to structure your case study.

Template 1 — Challenge-solution-result format

• Start with an engaging title. This should be fewer than 70 characters long for SEO best practices. One of the best ways to approach the title is to include the customer’s name and a hint at the challenge they overcame in the end.
• Create an introduction. Lead with an explanation as to who the customer is, the need they had, and the opportunity they found with a specific product or solution. Writers can also suggest the success the customer experienced with the solution they chose.
• Present the challenge. This should be several paragraphs long and explain the problem the customer faced and the issues they were trying to solve. Details should tie into the company’s products and services naturally. This section needs to be the most relatable to the reader so they can picture themselves in a similar situation.
• Share the solution. Explain which product or service offered was the ideal fit for the customer and why. Feel free to delve into their experience setting up, purchasing, and onboarding the solution.
• Explain the results. Demonstrate the impact of the solution they chose by backing up their positive experience with data. Fill in with customer quotes and tangible, measurable results that show the effect of their choice.
• Ask for action. Include a CTA at the end of the case study that invites readers to reach out for more information, try a demo, or learn more — to nurture them further in the marketing pipeline. What you ask of the reader should tie directly into the goals that were established for the case study in the first place.

Template 2 — Data-driven format

• Start with an engaging title. Be sure to include a statistic or data point in the first 70 characters. Again, it’s best to include the customer’s name as part of the title.
• Create an overview. Share the customer’s background and a short version of the challenge they faced. Present the reason a particular product or service was chosen, and feel free to include quotes from the customer about their selection process.
• Present data point 1. Isolate the first metric that the customer used to define success and explain how the product or solution helped to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 2. Isolate the second metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 3. Isolate the final metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Summarize the results. Reiterate the fact that the customer was able to achieve success thanks to a specific product or service. Include quotes and statements that reflect customer satisfaction and suggest they plan to continue using the solution.
• Ask for action. Include a CTA at the end of the case study that asks readers to reach out for more information, try a demo, or learn more — to further nurture them in the marketing pipeline. Again, remember that this is where marketers can look to convert their content into action with the customer.

While templates are helpful, seeing a case study in action can also be a great way to learn. Here are some examples of how Adobe customers have experienced success.

Juniper Networks

One example is the Adobe and Juniper Networks case study , which puts the reader in the customer’s shoes. The beginning of the story quickly orients the reader so that they know exactly who the article is about and what they were trying to achieve. Solutions are outlined in a way that shows Adobe Experience Manager is the best choice and a natural fit for the customer. Along the way, quotes from the client are incorporated to help add validity to the statements. The results in the case study are conveyed with clear evidence of scale and volume using tangible data.

The story of Lenovo’s journey with Adobe is one that spans years of planning, implementation, and rollout. The Lenovo case study does a great job of consolidating all of this into a relatable journey that other enterprise organizations can see themselves taking, despite the project size. This case study also features descriptive headers and compelling visual elements that engage the reader and strengthen the content.

Tata Consulting

When it comes to using data to show customer results, this case study does an excellent job of conveying details and numbers in an easy-to-digest manner. Bullet points at the start break up the content while also helping the reader understand exactly what the case study will be about. Tata Consulting used Adobe to deliver elevated, engaging content experiences for a large telecommunications client of its own — an objective that’s relatable for a lot of companies.

Case studies are a vital tool for any marketing team as they enable you to demonstrate the value of your company’s products and services to others. They help marketers do their job and add credibility to a brand trying to promote its solutions by using the experiences and stories of real customers.

When you’re ready to get started with a case study:

• Think about a few goals you’d like to accomplish with your content.
• Make a list of successful clients that would be strong candidates for a case study.
• Reach out to the client to get their approval and conduct an interview.
• Gather the data to present an engaging and effective customer story.

Adobe can help

There are several Adobe products that can help you craft compelling case studies. Adobe Experience Platform helps you collect data and deliver great customer experiences across every channel. Once you’ve created your case studies, Experience Platform will help you deliver the right information to the right customer at the right time for maximum impact.

To learn more, watch the Adobe Experience Platform story .

Keep in mind that the best case studies are backed by data. That’s where Adobe Real-Time Customer Data Platform and Adobe Analytics come into play. With Real-Time CDP, you can gather the data you need to build a great case study and target specific customers to deliver the content to the right audience at the perfect moment.

Watch the Real-Time CDP overview video to learn more.

Finally, Adobe Analytics turns real-time data into real-time insights. It helps your business collect and synthesize data from multiple platforms to make more informed decisions and create the best case study possible.

Request a demo to learn more about Adobe Analytics.

https://business.adobe.com/blog/perspectives/b2b-ecommerce-10-case-studies-inspire-you

https://business.adobe.com/blog/basics/business-case

https://business.adobe.com/blog/basics/what-is-real-time-analytics

• 14 min read

Data-Driven Decision-Making Case Studies: Insights from Real-World Examples

Data has become crucial for making informed decisions in today's fast-paced and ever-changing business environment. Companies use data to gain valuable insights, improve processes, and foster innovation. By studying successful examples of data-driven decision-making, we can gain valuable insights and comprehend the impact of data-driven strategies on business outcomes.

Define Data-Driven Decision Making (DDDM)

Are you tired of making business decisions based on gut instincts and guesswork? It's time to adopt Data-Driven Decision Making (DDDM). DDDM is a strategic approach that leverages collected data to inform and guide your business decisions. You can gain insights by identifying patterns and making informed choices using relevant and accurate data. "This can enhance the precision and efficiency of your decision-making procedure." allowing you to optimize outcomes, mitigate risks, and adapt more dynamically to changing circumstances in today's data-rich environment. Switch to DDDM and give your business the competitive edge it needs!

Importance of DDDM in Modern Businesses

In today's fast-paced and competitive business world, making informed and accurate decisions is more critical than ever. Data-Driven Decision Making (DDDM) is a powerful tool to help modern businesses achieve this goal. By using data and insights to inform business decisions rather than relying on guesswork, companies "Businesses that strategically position themselves to gain a competitive advantage are more likely to achieve success." With DDDM, businesses can make data-backed decisions, leading to better outcomes and tremendous success. So, if you want to stay ahead of your competition and make helpful decisions that drive success, embracing DDDM is the way to go!

Brief Overview of the Success Stories to be Discussed

Discover the success stories showcasing how businesses leverage advanced technologies to drive growth and profitability. Join me for an engaging and thought-provoking session where we will delve into the intricacies of these fascinating case studies. Your active participation will help us uncover valuable insights and unlock new perspectives that can benefit your work. "Make the most of this valuable opportunity to enhance your knowledge and skills!"

1. Netflix's Personalized Recommendations

2. Amazon's Supply Chain Optimization

3. Starbucks Location Analytics

4. American Express Fraud Detection

5. Zara's Fast Fashion Foresight.

You can benefit greatly from this unique opportunity to learn from some of the most innovative companies in the industry. Ensure you take advantage of this chance to expand your knowledge and skills!

Case Study 1: Netflix's Personalized Recommendation

Overview of netflix's challenges in content delivery.

Netflix faced challenges delivering content due to the diverse viewer preferences and vast content library. However, the company has been working hard to address these challenges and ensure users can discover content that aligns with their tastes. By doing so, Netflix aims to improve user satisfaction and retention rates.

How Netflix Used Viewer Data to Tailor Recommendations

By leveraging extensive viewer data, Netflix confidently tackled the challenge of recommending relevant content to its users. The platform thoroughly analyzed user behavior, viewing history, and preferences to create highly sophisticated algorithms. These algorithms were based on machine learning and could personalize content recommendations for each user. This approach significantly increased the likelihood of viewers engaging with content that resonated with their interests.

The Impact on Customer Retention and Satisfaction

The personalized content recommendations profoundly affected customer retention and satisfaction rates. Netflix enhanced the value of its service by providing users with content that closely matched their preferences. This created a stronger bond between users and the platform, leading to longer subscription durations and increased satisfaction.

Lessons Learned and Key Takeaways

Data is a Strategic Asset: Netflix's strategic use of data has wholly revolutionized content delivery. By utilizing excellent viewer data, they have successfully met the needs and preferences of each viewer in an incredibly effective manner.

Personalization Enhances Customer Experience: Personalized recommendations are essential to enhancing the overall customer experience. They can increase engagement, satisfaction, loyalty, and retention. Make no mistake - if you want to take your business to new heights, personalized recommendations are a must!

Continuous Adaptation is Crucial: It is crucial to adapt to achieve success, as Netflix continuously demonstrates. With the ever-evolving preferences of viewers, it is imperative to perform ongoing analysis and make necessary adjustments to algorithms to ensure that recommendations stay consistently relevant.

Balancing Privacy and Personalization: When utilizing viewer data, it is crucial to hit the right balance between personalization and privacy. Netflix has accomplished this by delivering highly personalized recommendations without compromising user privacy.

Netflix's approach to content delivery serves as an inspiration for the transformative power of data-driven decision-making. The personalized recommendations derived from customer data have proven to be a game changer regarding customer retention and satisfaction. The significance of adaptability, strategic use of data, and the balance between personalization and privacy, as highlighted by Netflix's success, can serve as a guide for other businesses looking to impact their customers positively.

Case study 2: amazon's supply chain optimization.

Understanding Amazon's Complex Supply Chain

Amazon has a complex supply chain involves various stages, from sourcing the products to delivering them to customers. The company manages a vast network of fulfillment centers, distribution hubs, and transportation systems. The complexity arises due to the need to manage different types of products, fluctuating demand, and the commitment to fast and efficient delivery.

Implementation of Predictive Analytics for Inventory Management

Using predictive analytics, Amazon has optimized inventory management by accurately forecasting future demand by analyzing historical data, current market trends, and seasonality. This has helped them prevent stockouts and overstock situations, improving their overall business efficiency and customer satisfaction.

Results Achieved in Cost Savings and Delivery Times

Anticipating the future, the implementation of predictive analytics is expected to yield significant results. Amazon will likely achieve cost savings by minimizing excess inventory and improving warehouse efficiency. Additionally, streamlined inventory management contributes to faster order fulfillment, which reduces delivery times and enhances the customer experience. We can expect a boost in efficiency and a better customer experience shortly.

Insights Gained and How Businesses Can Apply Similar Strategies 

Data-Driven Decision-Making: In today's business landscape, data-driven decision-making has become the cornerstone of success. If you want your business to thrive, you must leverage advanced analytics to gain actionable insights into your supply chains. This will enable you to make proactive and strategic decisions to enhance your projects. Don't fall behind the competition - take charge and start leveraging the power of data-driven decision-making now.

Dynamic Inventory Optimization: Incorporating a dynamic approach to inventory management that relies on predictive analytics is "Businesses must prioritize their competitive edge and remain ahead of the industry. This is crucial to ensure success and longevity.". It helps them to quickly adjust to changing market conditions and meet the ever-evolving demands of consumers. This not only optimizes the utilization of resources but also reduces wastage, making it a sound strategy crucial for any business that wishes to survive in today's competitive market landscape.

Focus on Customer-Centric Logistics: To improve customer satisfaction, businesses can focus on optimizing logistics and reducing delivery times. Amazon's customer-centric approach demonstrates the importance of fast and reliable delivery. Companies can boost customer loyalty and drive growth by enhancing the customer experience.

Investment in Technology: To stay ahead in supply chain optimization, businesses must adopt cutting-edge technologies like AI and machine learning. Amazon's supply chain success is a testament to the power of continuous investment in technology. So, if you want to thrive in today's competitive market, it's high time you leverage these technologies to your advantage.

Amazon's journey toward optimizing its supply chain through predictive analytics has tremendously impacted cost savings and delivery times. Other businesses can achieve similar results by utilizing data-driven decision-making, implementing dynamic inventory management, prioritizing customer-centric logistics, and investing in advanced technologies.

Case study 3: starbucks location analytics.

The Problem with Traditional Site Selection

The traditional approach to retail site selection, which relied on broad demographic data and market trends, must be improved in identifying optimal locations. Adopting a more precise approach that considers specific local factors influencing consumer behavior and store performance is imperative to ensure success.

How Starbucks Leveraged Geographic Information Systems (GIS)

Starbucks has transformed its approach to selecting store locations by leveraging Geographic Information Systems (GIS). This innovative technology has enabled Starbucks to systematically evaluate and visualize location-specific data, such as foot traffic patterns, nearby businesses, demographics, and local economic factors. By conducting this comprehensive analysis, Starbucks can gain a more nuanced understanding of potential store locations and make informed decisions.

Outcomes in Terms of New Store Performance and Sales

Starbucks, the renowned coffeehouse chain, has achieved notable success in its site selection strategy by implementing a Geographic Information System (GIS). GIS technology has enabled Starbucks to strategically place its new stores in locations that cater to the preferences and traffic patterns of the local population. As a result, the company has witnessed a significant improvement in the performance of its new stores, surpassing the sales of those selected through traditional methods. The successful implementation of GIS in site selection has contributed to optimizing location decisions, leading to a more efficient and effective expansion strategy for Starbucks.

Broader Implications for Retail Location Decision-Making

Precision in Site Selection: Geographic Information System (GIS) technology has opened new doors for retailers to make informed decisions. By leveraging GIS, businesses can analyze and interpret specific geographic data to optimize their site selection process. This helps them understand local nuances and customer behavior more precisely, allowing them to make data-driven decisions that lead to better business outcomes.

Adaptability to Local Factors: To establish a closer relationship with their customers, retailers must consider various local factors such as competition, demographics, and cultural preferences. By doing so, they can customize their offerings and marketing strategies to fit the local communities' specific needs and preferences. This approach can lead to better customer engagement and loyalty and, ultimately, higher sales for the retailer.

Cost Efficiency: Regarding retail businesses, selecting the right location for a store is crucial for success. Optimal site selection can significantly reduce the risk of underperforming stores and minimize the financial impact of poor location decisions. Retail businesses can enhance their overall cost efficiency and profitability by doing so. This is why it is essential for companies to carefully analyze and consider factors before making any site selection decisions.

Strategic Expansion: Geographic Information System (GIS) provides retailers with a powerful tool to make informed decisions about expanding their business. By leveraging location-based data, retailers can discover new markets and potential locations for growth. This data-driven approach helps retailers create a more sustainable and prosperous expansion plan, resulting in long-term prosperity for the business.

Enhanced Customer Experience: Retailers can improve the shopping experience for their customers by strategically selecting store locations that cater to their preferences and habits. Retailers can attract more foot traffic and enhance customer satisfaction by offering conveniently located stores. In this case, it can increase sales and customer loyalty.

To make it more understandable, Starbucks has been using fantastic GIS technology to help them pick the best locations for their stores. It's like a digital map that allows them to look at much different information, like how many people live nearby, how much traffic there is, and what other businesses are in the area. By using this technology, Starbucks can make better choices about where to put their stores and how they can be successful. Other businesses can also use GIS to make better decisions about where to open new stores and how to compete in the changing world of retail.

Case study 4: american express fraud detection.

Rise in Credit Card Fraud and the Challenge for Card Issuers

As more and more people turn to digital transactions and online commerce, it's essential to be aware of the increased incidence of credit card fraud. Protect yourself and others from financial crimes by staying informed and proactively safeguarding your financial information. Thus, posing a significant challenge for card issuers. Fraudsters are constantly devising new and innovative tactics to steal sensitive information and exploit vulnerabilities in payment systems. This makes it imperative for financial institutions to stay ahead of the game in detecting and preventing fraudulent activities. Today, with advanced technologies like machine learning and artificial intelligence, card issuers can analyze big data that can identify patterns and anomalies and indicate fraudulent behavior. By adopting a proactive approach to fraud detection and prevention, financial institutions can safeguard their customers' personal information and financial assets, thus building trust and loyalty among their clients.

American Express's Use of Machine Learning for Early Detection

American Express always prioritizes the security of its customers' financial transactions. The company has employed advanced machine-learning algorithms to analyze vast amounts of real-time transaction data to achieve this. These algorithms can identify patterns, anomalies, and behavioral indicators typically associated with fraudulent activities. By continuously learning from new data, the system adapts to evolving fraud tactics and enhances its ability to detect irregularities early on. This advanced technology is a critical component of American Express's fraud prevention strategy, and it helps the company safeguard its customers against potential financial losses.

Effectiveness in Preventing Fraud and Protecting Customers

American Express utilizes an advanced fraud detection system powered by machine learning that has demonstrated exceptional efficacy in preventing fraudulent activities and safeguarding customers. By detecting fraudulent transactions early, the company can promptly take necessary measures, such as notifying customers of suspicious activities or blocking them altogether, thus reinforcing trust in the company's commitment to security and ensuring customer satisfaction.

What Companies Can Learn About Proactive Data Monitoring

Invest in Advanced Analytics: Advanced analytics, such as machine learning, helps companies proactively monitor data for potential fraud indicators and unusual patterns. It identifies issues before they become significant problems, saving the company millions. It also identifies new business opportunities, market trends, and operational inefficiencies, enhancing customer satisfaction and the bottom line.

Real-Time Analysis: Real-time data analysis is a powerful tool for detecting and responding to suspicious activities. By monitoring data in real-time, organizations can quickly "Identify possible threats and take prompt action to reduce their impact." we can overcome any challenges that come our way and pave the path to success. This approach reduces the window of vulnerability and enhances the effectiveness of fraud prevention measures. Therefore, real-time data analysis can help organizations prevent fraudsters from exploiting them. It's important to stay vigilant and proactive in protecting yourself and your finances from potential threats. Please take action now and don't give them the chance to cause any harm. Remember, it's better to be safe than sorry. their interests.

Continuous Learning Systems: Adopting systems that can learn and adapt to new fraud patterns is highly recommended. This approach ensures that the monitoring mechanisms remain up-to-date and effective despite the constantly evolving threats. Embracing such systems can protect businesses. The objective is to safeguard individuals and organizations against financial losses and reputational harm resulting from fraudulent activities.

Customer Communication: Implementing solid and effective communication methods is essential to inform customers of any potential fraud promptly. Through transparent communication, customers can be informed of the situation and take immediate action, building trust between them and the organization.

Collaboration with Industry Partners: Collaborating with industry partners and sharing insights on emerging fraud trends is essential. By working together, we can enhance our ability to combat fraud and protect the entire ecosystem. We can stay informed and better equipped to prevent fraudulent activities through a collective effort.

Balancing Security and User Experience: It's crucial to balance strong security measures with a seamless user experience for online platform security. While taking all necessary steps to prevent fraud and unauthorized access to your system is critical, ensuring that your legitimate customers don't face any inconvenience or dissatisfaction due to stringent security protocols is equally essential. Therefore, adopting a multi-layered approach to security is recommended to shield your system from potential threats without making the user experience cumbersome or frustrating. This may involve utilizing two-factor and risk-based authentication and real-time fraud detection. Furthermore, educating users on secure online practices and equipping them with the necessary tools and resources to protect their personal information and transactions is essential.

American Express has implemented machine learning techniques to detect and prevent fraud at an early stage. This is an excellent example for businesses seeking to improve their proactive data monitoring capabilities. By adopting advanced analytical tools, real-time analysis, continuous learning systems, and effective communication, companies can establish a solid and proactive strategy to combat emerging threats in the digital realm.

Case study 5: zara's fast fashion foresight.

Fast Fashion Industry Challenges in Demand Forecasting

The fast fashion industry, known for producing trendy and affordable clothing rapidly, faces significant challenges in accurately predicting consumer demand. One of the main reasons for this is the constantly changing nature of fashion trends. What is popular today may be out of fashion tomorrow, making it difficult for companies to plan their production processes effectively.

Additionally, fast fashion products have short life cycles, meaning they are only in style for a limited time. As a result, companies need to be able to respond to market shifts and adjust their production accordingly quickly. This can be challenging, as traditional forecasting methods rely on historical data, which may need to be more relevant in a fast-changing market.

To overcome these challenges, the fast fashion industry needs innovative and agile forecasting methods to keep up with the dynamic nature of consumer preferences. This may involve leveraging data analytics and machine learning algorithms to identify emerging trends and predict future demand. Companies can enhance efficiency, reduce waste, and provide excellent customer value.

Zara's Integration of Real-Time Sales Data into Production Decisions

Zara, one of the world's leading fashion retailers, has redefined the fashion industry by leveraging real-time sales data. Zara has integrated real-time sales data into its production decisions, allowing the company to stay ahead of the competition. Zara's vertically integrated supply chain and responsive production model enable it to capture up-to-the-minute sales data from its stores worldwide. This data is then fed back to the design and production teams, who use it to rapidly adjust inventory levels and introduce new designs based on current demand trends. Using real-time sales data, Zara can create a customer-centric approach, ensuring its customers always have access to the latest and most stylish designs.

Benefits Seen in Reduced Waste and Increased Sales

Zara has adopted a real-time analytics approach that has proven to be highly beneficial. The company's production is now closely aligned with actual customer demand, which results in a significant reduction in overstock and markdowns. This approach has minimized the environmental impact of excessive inventory. In addition, the quick response to emerging trends and consumer preferences has led to an increase in full-price sales, boosting revenue and profitability for Zara.

Strategies for Incorporating Real-Time Analytics into Product Development

Connected Supply Chain: Establishing a connected and transparent supply chain that enables seamless real-time data flow from sales channels to production and design teams is imperative. This will ensure that all the teams are on the same page and can make quick, informed decisions based on accurate, up-to-date information. Failure to do so can result in costly delays, inefficiencies, and missed opportunities. So, let's prioritize this and set up a robust supply chain that works for us!

Agile Production Processes: To maintain a competitive edge, it is crucial to adopt constructive and flexible production processes that can quickly respond to changes in demand. This involves embracing shorter production cycles and smaller batch sizes, which makes us more efficient and proactive in meeting customer needs.

Advanced Data Analytics: To optimize your sales strategies, you can use advanced data analytics tools to process and analyze real-time sales data efficiently. You can accurately forecast demand and make data-driven decisions by implementing predictive modeling and machine learning algorithms.

Cross-Functional Collaboration: Promoting collaboration among different organizational departments is crucial to ensure the sales, marketing, design, and production teams have a unified interpretation of real-time data. This way, they can collectively make informed decisions that are in the company's best interest. The organization can improve its efficiency, productivity, and profitability by promoting open communication and collaboration between departments.

Customer Feedback Integration: One way to enhance the accuracy of real-time analytics is to consider customer feedback and preferences. Social media listening and direct customer interactions can provide valuable insights into emerging trends and demands.

Technology Integration: As we look towards the future, it's becoming increasingly clear that investing in technologies that facilitate real-time data collection and processing will be crucial. With the rise of automation and the growing need for instant information, businesses that have point-of-sale systems, inventory management software, and communication tools that streamline information flow will be better equipped to thrive in the fast-paced and ever-changing world of tomorrow. So, it's never too soon to start thinking about how you can integrate these technologies into your business strategy.

Zara's outstanding achievement in the fast fashion industry is a remarkable example of how incorporating real-time sales data into production decisions can lead to immense success. By reducing waste, swiftly responding to market trends, and utilizing advanced analytics, Zara has set a benchmark for other companies in integrating real-time insights into their product development strategies. This approach enhances efficiency and competitiveness in the highly dynamic and ever-evolving fashion industry.

In the constantly shifting business realm, the adage' knowledge is power' has never been more accurate, particularly about tangible, data-derived knowledge. data-driven decision making (dddm) presents an approach where critical business decisions are made not on intuition or experience alone, but on deep dives into data analysis. empirical evidence garnered through this method provides actionable insights leading to strategic, evidence-based decisions..

The stories of Netflix, Amazon, Starbucks, American Express, and Zara demonstrate the immense potential of Data-Driven Decision Making (DDDM). By analyzing vast data points and leveraging advanced analytics, these companies transformed their businesses and achieved unparalleled success.

For instance, Netflix utilized DDDM to create tailor-made recommendations, engaging existing users and attracting new ones. Amazon used data analytics to optimize its supply chain, lowering costs and accelerating shipping times. Starbucks leveraged location analytics to predict the profitability of new store locations with impressive accuracy. American Express used machine learning algorithms to identify frauds faster than ever, saving millions in potential losses. Lastly, Zara demonstrated agility in the competitive fast fashion market by adapting its production and supply chain to meet real-time demand.

As seen in these success stories, data-driven decision-making can powerfully impact business, from customer engagement to trend forecasting. They underscore the importance of meticulous data analysis in navigating the present and forecasting an ever-changing future, paving the way for unparalleled business success. Companies can draw inspiration from these cases and embark on their DDDM journey to achieve similar outcomes.

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• Case Studies from the New York Times These case studies offer readers the opportunity to think along with a small-business owner who has confronted an interesting challenge. In each article, you can watch the owner assess his or her options and then make a decision -- and then you can click on the related blog post to see how other owners analyze the situation. You can also join the discussion and leave your own comments.
• MIT Sloan School of Management/Learning Edge Case Studies Some of the case studies featured highlight the decision-making process in a business or management setting. Other cases are descriptive or demonstrative in nature, showcasing something that has happened or is happening in a particular business or management environment. Whether decision based or demonstrative, teaching cases give students the chance to be in the shoes of a protagonist. With the help of context and detailed data, students can analyze what they would and would not do in a particular situation, why, and how.
• Free Cases from the Case Centre As part of The Case Centre’s commitment to promoting the case method and supporting case teachers, we offer a growing range of free cases produced by a number of prominent schools and organisations across the globe. You must register to access cases.
• Free Business Case Studies from the UK List of free case studies from Business Case Studies organised by Topic. Choose your sub topic by clicking the arrowed links below your selected business studies topic heading.
• Arthur Andersen Case Studies in Business Ethics During the period 1987-94 Arthur Andersen funded a $5 million joint project with 525 universities to raise awareness of ethical issues in business. This collection of 90 case studies is one product of that effort.
• Acadia Institute of Case Studies The Acadia Institute of Case Studies (AICS) has developed a series of case studies that can help prepare the entrepreneur and would-be entrepreneur for the realities facing the small business operator. These case studies are intended to help students learn problem-solving and decision-making skills, sometimes under complex and difficult circumstances.
• Free Cases from the Ivey School at University of Western Ontario Ivey is renowned for its Case-Method of Learning and is a top publisher of business cases worldwide (second only to Harvard).
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• Highlight Cases/Case Studies: Daniels Fund Ethics Initiative at U. New Mexico Online library of "simple, straightforward business cases focused on principle-based ethics."
• Oikos International Cases Currently consists of over 80 peer-reviewed cases on sustainability in management and entrepreneurship.
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• Curriculum Library for Employee Ownership Free Case Studies (CLEO) from Rutgers University School of Management and Labor Relations The CLEO Collection of Free Case Studies of employee owned companies. Discover and use these full-text downloadable case studies in your courses and scholarship. Case studies facilitate classroom discussion and enable students to grapple with real-world scenarios.
• Merlot-Free Business Cases This is a collection of free cases in a wide variety of business disciplines. The MERLOT system provides access to curated online learning and support materials and content creation tools, led by an international community of educators, learners and researchers.
• Ethics Unwrapped from U. of Texas Ethics Unwrapped is a free educational program that combines the latest ethics research with top experts and creative zing to make learning easy, memorable, and fun. This accessible, research-based resource is used around the world by more than 1,700 colleges and universities, in hundreds of businesses and organizations, and by tens of thousands of ethics learners.
• Enduring Legacies Native Cases The Enduring Legacies Native Cases Initiative develops culturally relevant curriculum and teaching resources in the form of case studies on key issues in Indian Country.
• Portland State University: Social Innovation & Social Entrepreneurship A collection of award-winning cases on social entrepreneurship and sustainability written by Portland State University faculty, staff, and students. Email Jacen Greene ([email protected]) for teaching notes or questions on usage. Many of these cases are available to use for free in educational settings.
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4 Examples of Business Analytics in Action

• 15 Jan 2019

Data is a valuable resource in today’s ever-changing marketplace. For business professionals, knowing how to interpret and communicate data is an indispensable skill that can inform sound decision-making.

“The ability to bring data-driven insights into decision-making is extremely powerful—all the more so given all the companies that can’t hire enough people who have these capabilities,” says Harvard Business School Professor Jan Hammond , who teaches the online course Business Analytics . “It’s the way the world is going.”

Before taking a look at how some companies are harnessing the power of data, it’s important to have a baseline understanding of what the term “business analytics” means.

Access your free e-book today.

What Is Business Analytics?

Business analytics is the use of math and statistics to collect, analyze, and interpret data to make better business decisions.

There are four key types of business analytics: descriptive, predictive, diagnostic, and prescriptive. Descriptive analytics is the interpretation of historical data to identify trends and patterns, while predictive analytics centers on taking that information and using it to forecast future outcomes. Diagnostic analytics can be used to identify the root cause of a problem. In the case of prescriptive analytics , testing and other techniques are employed to determine which outcome will yield the best result in a given scenario.

Related : 4 Types of Data Analytics to Improve Decision-Making

Across industries, these data-driven approaches have been employed by professionals to make informed business decisions and attain organizational success.

Check out the video below to learn more about business analytics, and subscribe to our YouTube channel for more explainer content!

Business Analytics vs. Data Science

It’s important to highlight the difference between business analytics and data science . While both processes use big data to solve business problems they’re separate fields.

The main goal of business analytics is to extract meaningful insights from data to guide organizational decisions, while data science is focused on turning raw data into meaningful conclusions through using algorithms and statistical models. Business analysts participate in tasks such as budgeting, forecasting, and product development, while data scientists focus on data wrangling , programming, and statistical modeling.

While they consist of different functions and processes, business analytics and data science are both vital to today’s organizations. Here are four examples of how organizations are using business analytics to their benefit.

Business Analytics Examples

According to a recent survey by McKinsey , an increasing share of organizations report using analytics to generate growth. Here’s a look at how four companies are aligning with that trend and applying data insights to their decision-making processes.

1. Improving Productivity and Collaboration at Microsoft

At technology giant Microsoft , collaboration is key to a productive, innovative work environment. Following a 2015 move of its engineering group's offices, the company sought to understand how fostering face-to-face interactions among staff could boost employee performance and save money.

Microsoft’s Workplace Analytics team hypothesized that moving the 1,200-person group from five buildings to four could improve collaboration by increasing the number of employees per building and reducing the distance that staff needed to travel for meetings. This assumption was partially based on an earlier study by Microsoft , which found that people are more likely to collaborate when they’re more closely located to one another.

In an article for the Harvard Business Review , the company’s analytics team shared the outcomes they observed as a result of the relocation. Through looking at metadata attached to employee calendars, the team found that the move resulted in a 46 percent decrease in meeting travel time. This translated into a combined 100 hours saved per week across all relocated staff members and an estimated savings of $520,000 per year in employee time.

The results also showed that teams were meeting more often due to being in closer proximity, with the average number of weekly meetings per person increasing from 14 to 18. In addition, the average duration of meetings slightly declined, from 0.85 hours to 0.77 hours. These findings signaled that the relocation both improved collaboration among employees and increased operational efficiency.

For Microsoft, the insights gleaned from this analysis underscored the importance of in-person interactions and helped the company understand how thoughtful planning of employee workspaces could lead to significant time and cost savings.

2. Enhancing Customer Support at Uber

Ensuring a quality user experience is a top priority for ride-hailing company Uber. To streamline its customer service capabilities, the company developed a Customer Obsession Ticket Assistant (COTA) in early 2018—a tool that uses machine learning and natural language processing to help agents improve their speed and accuracy when responding to support tickets.

COTA’s implementation delivered positive results. The tool reduced ticket resolution time by 10 percent, and its success prompted the Uber Engineering team to explore how it could be improved.

For the second iteration of the product, COTA v2, the team focused on integrating a deep learning architecture that could scale as the company grew. Before rolling out the update, Uber turned to A/B testing —a method of comparing the outcomes of two different choices (in this case, COTA v1 and COTA v2)—to validate the upgraded tool’s performance.

Preceding the A/B test was an A/A test, during which both a control group and a treatment group used the first version of COTA for one week. The treatment group was then given access to COTA v2 to kick off the A/B testing phase, which lasted for one month.

At the conclusion of testing, it was found that there was a nearly seven percent relative reduction in average handle time per ticket for the treatment group during the A/B phase, indicating that the use of COTA v2 led to faster service and more accurate resolution recommendations. The results also showed that customer satisfaction scores slightly improved as a result of using COTA v2.

With the use of A/B testing, Uber determined that implementing COTA v2 would not only improve customer service, but save millions of dollars by streamlining its ticket resolution process.

Related : How to Analyze a Dataset: 6 Steps

3. Forecasting Orders and Recipes at Blue Apron

For meal kit delivery service Blue Apron, understanding customer behavior and preferences is vitally important to its success. Each week, the company presents subscribers with a fixed menu of meals available for purchase and employs predictive analytics to forecast demand , with the aim of using data to avoid product spoilage and fulfill orders.

To arrive at these predictions, Blue Apron uses algorithms that take several variables into account, which typically fall into three categories: customer-related features, recipe-related features, and seasonality features. Customer-related features describe historical data that depicts a given user’s order frequency, while recipe-related features focus on a subscriber’s past recipe preferences, allowing the company to infer which upcoming meals they’re likely to order. In the case of seasonality features, purchasing patterns are examined to determine when order rates may be higher or lower, depending on the time of year.

Through regression analysis—a statistical method used to examine the relationship between variables—Blue Apron’s engineering team has successfully measured the precision of its forecasting models. The team reports that, overall, the root-mean-square error—the difference between predicted and observed values—of their projection of future orders is consistently less than six percent, indicating a high level of forecasting accuracy.

By employing predictive analytics to better understand customers, Blue Apron has improved its user experience, identified how subscriber tastes change over time, and recognized how shifting preferences are impacted by recipe offerings.

Related : 5 Business Analytics Skills for Professionals

4. Targeting Consumers at PepsiCo

Consumers are crucial to the success of multinational food and beverage company PepsiCo. The company supplies retailers in more than 200 countries worldwide , serving a billion customers every day. To ensure the right quantities and types of products are available to consumers in certain locations, PepsiCo uses big data and predictive analytics.

PepsiCo created a cloud-based data and analytics platform called Pep Worx to make more informed decisions regarding product merchandising. With Pep Worx, the company identifies shoppers in the United States who are likely to be highly interested in a specific PepsiCo brand or product.

For example, Pep Worx enabled PepsiCo to distinguish 24 million households from its dataset of 110 million US households that would be most likely to be interested in Quaker Overnight Oats. The company then identified specific retailers that these households might shop at and targeted their unique audiences. Ultimately, these customers drove 80 percent of the product’s sales growth in its first 12 months after launch.

PepsiCo’s analysis of consumer data is a prime example of how data-driven decision-making can help today’s organizations maximize profits.

Developing a Data Mindset

As these companies illustrate, analytics can be a powerful tool for organizations seeking to grow and improve their services and operations. At the individual level, a deep understanding of data can not only lead to better decision-making, but career advancement and recognition in the workplace.

“Using data analytics is a very effective way to have influence in an organization,” Hammond says . “If you’re able to go into a meeting, and other people have opinions, but you have data to support your arguments and your recommendations, you’re going to be influential.”

Do you want to leverage the power of data within your organization? Explore Business Analytics —one of our online business essentials courses —to learn how to use data analysis to solve business problems.

This post was updated on March 24, 2023. It was originally published on January 15, 2019.

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Effective Decision-Making: A Case Study

Effective decision-making:, leading an organization through timely and impactful action.

Senior leaders at a top New England insurance provider need to develop the skills and behaviors for better, faster decision-making. This virtually delivered program spans four half-day sessions and includes individual assignments, facilitator-led presentations, and simulation decision-making. Over the past two months, this program touched over 100 leaders, providing them with actionable models and frameworks to use back on the job.

For one of New England’s most iconic insurers, senior leaders are challenged to make timely, effective decisions. These leaders face decisions on three levels: ones they translate to their teams, ones they make themselves, and ones they influence. But in a quickly changing, highly regulated market, risk aversion can lead to slow and ineffective decisions. How can senior leaders practice in a safe environment the quick, yet informed, decision-making necessary for the job while simultaneously learning new models and techniques — and without the learning experience burdening their precious time?

The Effective Decision-Making program was artfully designed to immerse senior leaders in 16 hours of hands-on experience, including reflection and feedback activities, applicable exercises, supporting content, and participation in a business simulation to practice the core content of the program. Participants work together in small groups to complete these activities within a limited time frame, replicating the work environment in which these leaders must succeed. Continuous reflection and group discussion around results create real-time learning for leaders. Application exercises then facilitate the simulation experience and their work back on the job. The program employs a variety of learning methodologies, including:

• Individual assignments that incorporate content and frameworks designed to develop effective decision-making skills.
• Guided reflection activities to encourage self-awareness and commitments for action.
• Large group conversations — live discussions focused on peer input around key learning points.
• Small group activities, including virtual role plays designed to build critical interpersonal and leadership skills.
• A dynamic business simulation in which participants are charged with translating, making, and influencing difficult decisions.
• Facilitator-led discussions and presentations.

Learning Objectives

Participants develop and improve skills to:

• Cultivate a leadership mindset that empowers, inspires, and challenges others.
• Translate decisions for stronger team alignment and performance.
• Make better decisions under pressure.
• Influence individuals across the organization.
• Better understand how one’s leadership actions impact business results

Design Highlights

Program agenda.

As a result of the COVID-19 pandemic and the need for social distancing, this program was delivered virtually. However, this didn't preclude the need to give leaders an opportunity to connect with, and learn from, one another. In response to those needs, Insight Experience developed a fully remote, yet highly interactive, offering delivered over four half-day sessions.

Interactive Virtual Learning Format

Effective Decision-Making was designed to promote both individual and group activities and reflection. Participants access the program via a video-conferencing platform that allows them to work together both in large and small groups. Learning content and group discussions are done as one large group, enabling consistency in learning and opportunities to hear from all participants. The business simulation decision-making and reflection activities are conducted in small groups, allowing teams to develop deeper connections and conversations.

Simulation Overview

Participants assume the role of a General Manager for InfoMaster, a message management provider. Their leadership challenge as the GM is to translate the broader IIC organizational goals into strategy for their business, support that strategy though the development of organizational capabilities and product offerings, manage multiple divisions and stakeholders, and consider their contribution and responsibility to the broader organization of which they are a part. 

Success in the simulation is based on how well teams:

• Understand and translate organizational strategy into goals and plans for their business unit.
• Align organizational initiatives and product development with broader strategies.
• Develop employee capabilities required to execute strategic goals.
• Hold stakeholders accountable to commitments and results.
• Communicate with stakeholders and involve others in plans and decision-making.
• Develop their network and their influence within IIC to help support initiatives for the organization

History and Results

Effective Decision-Making was developed in 2020 as an experience for senior-level leaders. After a successful pilot, the program was then rolled out to two more cohorts in 2021 and 2022. The senior-level leaders who participated in the program then requested we offer the same program to their direct reports. After some small adjustments to make the program more appropriate for director-level leaders, the program was launched in 2022 for approximately 100 directors.

Here is what some participants have said about this program:

• “ One of the better programs we've done here at [our organization]. Pace was very quick but content was excellent and approach made it fun .”
• “ Loved the content and the flow. Very nicely organized and managed. Thank you! ”
• “ Really enjoyed the collaborative nature of the simulation.”
• “ It was wonderful and I felt it is a great opportunity. Learnt and reinforced leadership training and what it would take to be successful.”
• “One of the best I've experienced — especially appreciated how the reality of [our organization] was incorporated and it was with similarly situated peers.”
• “This program was great! It gave good insight into how to enhance my skills as leader by adopting the leadership mindset.”
• “Loved the fast pace, having a sim group that had various backgrounds in the company and seeing the results of our decisions at the corporate level.”
• “Great program — I love the concepts highlighted during these sessions.”

Looking for results like these?

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Top 40 Most Popular Case Studies of 2018

Cases about food and agriculture took center stage in 2018. A case on the coffee supply chain remained the top case and cases on burgers, chocolate, and palm oil all made the top ten.

Cases about food and agriculture took center stage in 2018. A case on the coffee supply chain remained the top case and cases on burgers, chocolate, and palm oil all made the top ten, according to data compiled by Yale School of Management Case Research and Development Team (SOM CRDT).

Other topics in the top ten included corporate social responsibility, healthcare, solar energy, and financial inclusion.

The annual ranking of the 40 most popular Yale School of Management case studies combines data from publishers, Google analytics, SOM class syllabi, and other measures of interest and adoption. This is the second year that SOM CRDT has published its Top 40 list.

Cases published in 2018 on the top 40 list included Marina Bay Sands Hotel (#13), AgBiome (#18), Canary Wharf (#20), Mastercard (#21), and Peabody Museum (#35). Both the Marina Bay Sands and Peabody cases were featured in major student competitions in 2018.

The cases on the Top 40 list represent a variety of different business disciplines, as Yale SOM cases tend to combine a variety of perspectives. For example, the top coffee case can be taught in marketing, operations, and strategy classes. The number two case on Shake Shack covers finance, strategy, and even innovation and design. The list features a number of cases related to the interplay of state and commerce and social enterprise, traditional strengths of the Yale SOM curriculum.

While there are many US-based cases among the top 40, a range of locales are highlighted among the top 40 entries. Cases set in France (AXA), Great Britain (Cadbury, Canary Wharf, George Hudson), Indonesia (Palm Oil, Golden Agri), China (Ant Financial, Alibaba), India (SELCO, Project Sammaan), Singapore (Marina Bay Sands), Canada (Air Canada, Potash Corporation of Saskatchewan), and South Africa (Project Masiluleke) made the top 40 list.

SOM CRDT has been working to increase the number of women featured as case protagonists. The 2018 list boasts 13 cases where women play prominent roles in the narrative.

The top 40 list also demonstrates a wide range of SOM faculty involvement. Thirty different faculty members worked as case supervisors on the top 40 cases.

Read on to learn more about the top 10 most popular cases followed by a complete list of the top 40 cases of 2018. A selection of the top 40 cases are available for purchase through our online store . 

#1 - Coffee 2016

Faculty Supervision: Todd Cort

Coffee 2016 asks students to consider the coffee supply chain and generate ideas for what can be done to equalize returns across various stakeholders. The case draws a parallel between coffee and wine. Both beverages encourage connoisseurship, but only wine growers reap a premium for their efforts to ensure quality.  The case describes the history of coffee production across the world, the rise of the “third wave” of coffee consumption in the developed world, the efforts of the Illy Company to help coffee growers, and the differences between “fair” trade and direct trade. Faculty have found the case provides a wide canvas to discuss supply chain issues, examine marketing practices, and encourage creative solutions to business problems. 

#2 - Shake Shack IPO

Faculty Supervision: Jake Thomas and Geert Rouwenhorst

From an art project in a New York City park, Shake Shack developed a devoted fan base that greeted new Shake Shack locations with cheers and long lines. When Shake Shack went public on January 30, 2015, investors displayed a similar enthusiasm. Opening day investors bid up the $21 per share offering price by 118% to reach $45.90 at closing bell. By the end of May, investors were paying $92.86 per share. Students are asked if this price represented a realistic valuation of the enterprise and if not, what was Shake Shack truly worth? The case provides extensive information on Shake Shack’s marketing, competitors, operations and financials, allowing instructors to weave a wide variety of factors into a valuation of the company.

#3 - IBM Corporate Service Corps

Faculty Supervision: David Bach in cooperation with University of Ghana Business School and EGADE

The case considers IBM’s Corporate Service Corps (CSC), a program that had become the largest pro bono consulting program in the world. The case describes the program’s triple-benefit: leadership training to the brightest young IBMers, brand recognition for IBM in emerging markets, and community improvement in the areas served by IBM’s host organizations. As the program entered its second decade in 2016, students are asked to consider how the program can be improved. The case allows faculty to lead a discussion about training, marketing in emerging economies, and various ways of providing social benefit. The case highlights the synergies as well as trade-offs between pursuing these triple benefits.

#4 - Children’s Premier

Faculty Supervision: Edieal Pinker

The case describes Children’s Premier, a popular group practice in Greenwich, Connecticut which, due to a change in the state’s vaccination law, decides to dramatically change its business model. Did the group make the right adjustments in order to stay competitive and cover their increasing costs? Should the new practices cause a newcomer to the practice to look elsewhere for his children?

#5 - Design at Mayo

Faculty Supervision: Rodrigo Canales and William Drentell

The case describes how the Mayo Clinic, one of the most prominent hospitals in the world, engaged designers and built a research institute, the Center for Innovation (CFI), to study the processes of healthcare provision. The case documents the many incremental innovations the designers were able to implement and the way designers learned to interact with physicians and vice-versa.

In 2010 there were questions about how the CFI would achieve its stated aspiration of “transformational change” in the healthcare field. Students are asked what would a major change in health care delivery look like? How should the CFI's impact be measured? Were the center's structure and processes appropriate for transformational change? Faculty have found this a great case to discuss institutional obstacles to innovation, the importance of culture in organizational change efforts, and the differences in types of innovation.

This case is freely available to the public.

#6 - AXA: Creating New Corporate Responsibility Metrics

Faculty Supervision: Todd Cort and David Bach

The case describes AXA’s corporate responsibility (CR) function. The company, a global leader in insurance and asset management, had distinguished itself in CR since formally establishing a CR unit in 2008. As the case opens, AXA’s CR unit is being moved from the marketing function to the strategy group occasioning a thorough review as to how CR should fit into AXA’s operations and strategy. Students are asked to identify CR issues of particular concern to the company, examine how addressing these issues would add value to the company, and then create metrics that would capture a business unit’s success or failure in addressing the concerns.

#7 - Cadbury: An Ethical Company Struggles to Insure the Integrity of Its Supply Chain

Faculty Supervision: Ira Millstein

The case describes revelations that the production of cocoa in the Côte d’Ivoire involved child slave labor. These stories hit Cadbury especially hard. Cadbury's culture had been deeply rooted in the religious traditions of the company's founders, and the organization had paid close attention to the welfare of its workers and its sourcing practices. The US Congress was considering legislation that would allow chocolate grown on certified plantations to be labeled “slave labor free,” painting the rest of the industry in a bad light. Chocolate producers had asked for time to rectify the situation, but the extension they negotiated was running out. Students are asked whether Cadbury should join with the industry to lobby for more time?  What else could Cadbury do to ensure its supply chain was ethically managed?

#8 - Palm Oil 2016

Faculty Supervision: Kenneth Richards in cooperation with National University of Singapore Business School and David Bach

The case looks at the palm oil industry in Indonesia and how the industry effects deforestation and native rights. The case focuses on a proposal forwarded by leading palm oil traders and environmental NGOs that would ban the sale of palm oil from deforested land. The proposal is opposed by elements of the government, and smaller palm oil companies. Some voices in the Indonesian government are suggesting an agreement to end deforestation needs to be scrapped. What should companies and NGOs do?

#9 - Ant Financial

Faculty Supervision: K. Sudhir in cooperation with Renmin University of China School of Business

In 2015, Ant Financial’s MYbank (an offshoot of Jack Ma’s Alibaba company) was looking to extend services to rural areas in China by providing small loans to farmers. Microloans have always been costly for financial institutions to offer to the unbanked (though important in development) but MYbank believed that fintech innovations such as using the internet to communicate with loan applicants and judge their credit worthiness would make the program sustainable. Students are asked whether MYbank could operate the program at scale? Would its big data and technical analysis provide an accurate measure of credit risk for loans to small customers? Could MYbank rely on its new credit-scoring system to reduce operating costs to make the program sustainable?

#10 - SELCO

Faculty Supervision: Tony Sheldon

The case looks at SELCO, an Indian company that specialized in bringing solar electric products to the poor. In 2009, the company needed a new growth strategy. As students consider the company’s dilemma, the raw case allows them to view video interviews with company leaders and customers, inspect maps of SELCO’s service areas, see videos describing how SELCO’s products were being used, consider articles on India’s electricity grid and socio-economic conditions, read about the company’s founding, consult the company’s organization charts, income statements and balance sheets, inspect the company’s innovative products, review the company’s business models, read news articles about the company’s success, etc.

SELCO, India's innovative solar electric company, was at a strategic crossroads. Should it go “deeper” and serve even poorer people or go “wider” and expand beyond its current geographical areas?

40 Most Popular Case Studies of 2018

Click on the case title to learn more about the dilemma. A selection of our most popular cases are available for purchase via our online store .

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Case studies.

The teaching business case studies available here are narratives that facilitate class discussion about a particular business or management issue. Teaching cases are meant to spur debate among students rather than promote a particular point of view or steer students in a specific direction.  Some of the case studies in this collection highlight the decision-making process in a business or management setting. Other cases are descriptive or demonstrative in nature, showcasing something that has happened or is happening in a particular business or management environment. Whether decision-based or demonstrative, case studies give students the chance to be in the shoes of a protagonist. With the help of context and detailed data, students can analyze what they would and would not do in a particular situation, why, and how.

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A business organisation is a decision-making unit that sets out to produce a product in the form of goods or services. Key decisions need to be made about an organisation’s plant, its products, and its people.

• Plant – e.g. whether to invest in a new factory or in updating present facilities
• Products – e.g. whether to introduce new lines
• People – e.g through investment in training and development.

Most classifications of types of decisions are based upon the predictability of decisions. For example, Herbert Simon (The New Science of Management Decision, 1960) made a distinction between programmed and non-programmed decisions.

Programmed decisions are straightforward, repetitive and routine so that they can be dealt with by formal patterns, e.g. the re-ordering of stock by a company.

Non-programmed decisions are novel, unstructured and consequential. There is no cut-and-dried method for handling situations which have not arisen before.

Typically, there are three levels of decision-making within the organisation:

1. Short-term operating control decisions. These have to be made frequently involving short-term, predictable operations.

2. Periodic control decisions. These are made less frequently and are concerned with monitoring how effectively an organisation is managing its resources. For example, this might include the review of pricing strategies for certain products, reviewing problems occurring in an ongoing company budget, or the re-appraisal of the way the sales force is being used. Such decisions are concerned with checking for and rectifying problems concerned with meeting company objectives.

3. Strategic decisions. These are major decisions about overall strategy. They will often require considerable use of judgment by the person or group responsible for making the decisions. This is because although such decisions will require a considerable amount of analysis, important pieces of information will frequently be missing and so the risk will be involved. Such decisions might involve the development of a new product, investment in a new plant, or the development of a new marketing strategy.

Decision Trees

Decision trees are so named because of the way in which they separate out into branches (outcomes) from an original stem (a decision). Decision trees are a technique for tracing through all the known outcomes of a particular decision in order to draw out the possible consequences.

In a decision tree, points at which decisions are made are represented by squares (decision forks), and points, where chance/probability comes into play, are represented by circles.

For example, a property development company may be faced with the decision of whether to sell one of its properties now, or whether to wait for a year in the hope the property market improves. If it sells the property now it knows it will receive £250,000.

However, if it sells in one year there are two possibilities:

1. There is a slump in the property market so the property can only be sold for £200,000. There is a nine out of ten chance that this will happen.

2. There is a boom in the property market so that the property can be sold for £800,000. There is a one out of ten chance that this will happen.

We can use decision tree analysis to identify the ‘best’ course of action.

• Sell now – result = £250,000.
• Sell in a year:

£200,000 X 9/10 £800,000 x 1/10 = £260,000

You can see that the preferred option is to sell in a year’s time because the outcome is higher at £260,000 than to sell now at £250,000.

The mathematics for selling in one year’s time is easy. We multiply the expected outcome by the probability of that outcome happening. Although there is only a one in ten chance of a property boom it is worth taking the risk.

However, it is important to remember that some decision-makers are more prepared to take a risk than others. In the example given many decision makers will take the cautious line and with the 9 out of the chance of the property slump, decide to sell now.

Probability: Likelihood of an event occurring, measured by the ratio of the cases to the total number of cases possible.

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How to Make Great Decisions, Quickly

• Martin G. Moore

It’s a skill that will set you apart.

As a new leader, learning to make good decisions without hesitation and procrastination is a capability that can set you apart from your peers. While others vacillate on tricky choices, your team could be hitting deadlines and producing the type of results that deliver true value. That’s something that will get you — and them — noticed. Here are a few of a great decision:

• Great decisions are shaped by consideration of many different viewpoints. This doesn’t mean you should seek out everyone’s opinion. The right people with the relevant expertise need to clearly articulate their views to help you broaden your perspective and make the best choice.
• Great decisions are made as close as possible to the action. Remember that the most powerful people at your company are rarely on the ground doing the hands-on work. Seek input and guidance from team members who are closest to the action.
• Great decisions address the root cause, not just the symptoms. Although you may need to urgently address the symptoms, once this is done you should always develop a plan to fix the root cause, or else the problem is likely to repeat itself.
• Great decisions balance short-term and long-term value. Finding the right balance between short-term and long-term risks and considerations is key to unlocking true value.
• Great decisions are timely. If you consider all of the elements listed above, then it’s simply a matter of addressing each one with a heightened sense of urgency.

Where your work meets your life. See more from Ascend here .

Like many young leaders, early in my career, I thought a great decision was one that attracted widespread approval. When my colleagues smiled and nodded their collective heads, it reinforced (in my mind, at least) that I was an excellent decision maker.

• MM Martin G. Moore is the founder of Your CEO Mentor and author of No Bullsh!t Leadership and host of the No Bullsh!t Leadership podcast. His purpose is to improve the quality of leaders globally through practical, real world leadership content. For more information, please visit, www.martingmoore.com.

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7 Favorite Business Case Studies to Teach Undergrads—and Why

Explore more.

• Case Teaching
• Course Design
• Course Materials

FEATURED CASES

Chris and Alison Weston (A) , selected by Amy Wallis of Wake Forest University School of Business, United States

Cynthia Carroll at Anglo American (A) , selected by Mihran A. Aroian of McCombs College of Business, United States

Merck: Managing Vioxx (A) , selected by Johanna Glauber of IE University, Spain

Starbucks: Delivering Customer Service , selected by Joseph C. Miller of St. Ambrose University, United States

Swoon: Mixing Up the Perfect Marketing Cocktail , selected by Sheri L. Lambert of Fox School of Business, Temple University, United States

Tesla Motors: Financing Growth , selected by Oscar Melo-Vega Angeles of the University of Lima, Peru

Trader Joe’s , selected by Michael Roberto of Bryant University, United States

To understand how undergraduate educators use the case method and find out which cases they gravitate toward, we asked several experienced case instructors, “What is your favorite case to teach undergrads and why does it work particularly well with them?”

The cases they shared range in industry and topic—from mining to pharmaceuticals and finance to marketing—but all offer valuable learning for undergraduate students.

1. Chris and Alison Weston (A)

Chris and Alison Weston (A) is an exceptional tool to help undergraduate students grasp moral disengagement and its ethical implications. The Westons are characters that students identify with—a married couple seeking to have fulfilling, lucrative careers—which makes the case personal for them. By examining a real-world scenario and the slippery slope that the Westons found themselves on, students see how easy it is to begin practicing unethical behavior. Reading about the implications of the Westons’ actions also highlights the situation through multiple ethical lenses, driving home the importance of perspective-taking and critical-thinking skills.

Coupling this case with “ A Note on Moral Disengagement ”—which expertly explains Bandura’s work on the psychological elements of ethical decision-making—brings the concepts to life for students; they find it intriguing to identify moral disengagement mechanisms at work in the case and eye-opening to see how easily the Westons fall into predictable traps of their own making.

I like to divide the class into breakout groups so students can practice both anticipating and preventing moral disengagement, as well as intervening when they see it happening. This builds important skills for ethical leadership.

2. Cynthia Carroll at Anglo American (A)

This semester, I’m teaching undergraduate students minoring in business. Since it’s an overview course, I needed a case study that touches upon several different areas of management. My favorite case this semester is Cynthia Carroll at Anglo American (A) .

Located in South Africa, Anglo American is one of the largest mining companies in the world. The case opens with then-new (now former) CEO Cynthia Carroll learning about a fatality at one of the mining facilities. She finds the incident unacceptable and immediately closes the mine. The case is powerful—Carroll brings radical change to the organization not only in addressing worker safety but also in addressing the overall operations of an organization that employs more than 150,000 workers.

The case shows us how, despite opposition from all sides, Carroll transforms the operations of a large corporation in which worker fatality is accepted as a norm. How she engages with skeptical stakeholders and moves the mining workforce (where the illiteracy rate was 70 percent) to participate is a tremendous example of great leadership. The way she conceives her strategy is an uplifting story for undergraduates and how she improves the operational and financial performance of the company is inspiring. The opportunity to teach about leadership, organizational transformation, crisis management, changing organizational culture, and employee empowerment in one case is simply elegant.

3. Merck: Managing Vioxx (A)

When teaching cases to undergraduates, I encourage my students to put themselves in the shoes of the decision maker(s) and get their hands sweaty under the pressure. When students have less work experience, case discussions are fabulous for allowing them to apply frameworks in business decisions. Students directly experience the challenges and complexities, gaining hands-on skills for their future careers.

One of my favorite cases to teach is Merck: Managing Vioxx (A) . Students are explicitly asked to stand in the shoes of CEO Ray Gilmartin, who learns about potentially severe cardiovascular risks of the painkiller drug Vioxx. A great strength of the case is that information is presented step by step—through six supplements—simulating Ray Gilmartin’s decision situation. This setup and great supplementary video material make it an exceptionally strong case for undergraduate teaching.

4. Starbucks: Delivering Customer Service

When I teach marketing strategy to undergraduates, I like to ask the students, “Have you ever shopped at a store that felt like it was made for you, but then one day it just seemed like it sold out by becoming more mainstream?” The question elicits responses consisting of various clothing stores, restaurants, and so forth. When discussing their experiences, students often seem to suspect that the growth of a service business comes at the cost of the elements that initially drew a core group of dedicated customers.

I find that students love giving definition to marketing phenomena they’ve actually experienced and they love talking about the products and services they use. For that reason, the case Starbucks: Delivering Customer Service is a favorite of mine to introduce to strategy undergrads.

Today’s students are interested in understanding the kind of service organization Starbucks was at its onset. They are interested in knowing who Starbucks’s initial core customers are and eager to discuss Starbucks’ growth intentions in the 90s and early 2000s, as well as how it coincided with changes to the external social environment.

As a coda, I often call upon the students’ experiences with today’s Starbucks. We discuss how the company has learned to bifurcate its operation to appeal to the service-intensive core consumer as well as the product-intensive casual consumer. It’s a great case to explain the pitfalls of the wheel of retailing to undergraduates.

5. Swoon: Mixing Up the Perfect Marketing Cocktail

There are several cases that I love to use for my marketing strategy capstone course with undergraduates. One of those is Swoon: Mixing Up the Perfect Marketing Cocktail , which centers around a nimble beverage startup. Students put themselves in the shoes of the two cofounders to design a marketing strategy for branding.

Many times, I’ve had students approach me wondering, “Why don’t any of the protagonists look like me?” The Swoon case is perfect: The cofounders are young women and many of my students can relate to them or see themselves in the protagonists. The case also comes with a “meet the protagonist” video, which immerses the students in a conversation between the two founders.

Two other cases I love to use, Opera Philadelphia: Segmentation Strategies for Changing Markets and Hamilton Won More Than Twitter , deal with non-traditional businesses (an opera company and a Broadway show). Students love interacting with these cases and applying marketing theory to the arts. On top of that, the Opera Philadelphia case enables students to roll up their sleeves, analyze consumer data, and formulate a plan forward.

It is all about engagement. Teaching concepts through these cases gets our students fully engaged.

6. Tesla Motors: Financing Growth

I use several cases for my undergraduate classes. My favorite one now is Tesla Motors: Financing Growth . This case can be applied to intermediate finance courses and can be used at many levels: undergraduate, MBA, and executive education. It is also specifically perfect to use in the Financial Management in International Business course, an undergraduate course in the Faculty of Business and Economics department at the University of Lima.

These are the main reasons I love teaching with it:

It is stimulating and provocative for students. They get excited about the numbers and the discussion. It incites them to participate, explain their assumptions, and compare their answers.

The company is trending and students around the world know about it; the case provides new information on a company they know. It is also great for discussing the impact of sustainability in company valuations.

It provides the opportunity to apply various finance learnings, including the shifting price of the company and shares according to valuation method, the value stock and growth stock and why investors pay more or less for it, equity financing, comparison with the market’s price, and companies with negative profit and positive value.

I can link the concepts back to other core curriculum readings I use for the course, including Financial Accounting Reading: Introduction to Valuation and Finance Reading: Cost of Capital .

It uses simple but technical language. And while it involves many numbers, and it can be discussed in a 90-minute class.

7. Trader Joe’s

WEBINAR: USING ACTIVE LEARNING STRATEGIES WITH UNDERGRADS

For more about using active learning strategies with undergrads, watch the recording of a recent HBP webinar with Michael Roberto, Trustee Professor of Management at Bryant University. In the webinar, Why Undergraduate Students (and Faculty) Struggle with Active Learning , Roberto speaks to the challenges faculty face and recommends strategies to address those problems.

Trader Joe’s is a highly successful firm in a very challenging industry, so the case provides a great platform for exploring many concepts in competitive strategy. Moreover, the company seems to be executing a rather counterintuitive strategy, forgoing many of the services and offerings that rivals consider essential in the supermarket business. That sparks the interest of inquisitive undergraduates.

SHARE WITH US Do you have a favorite case to teach your undergraduate students? We would love to hear about it!

To find other great cases to teach undergrads, check out this collection of Engaging Cases for Undergraduate Students or browse best-selling undergraduate cases by discipline .

Amy Wallis is a full teaching professor at the Wake Forest University School of Business. As an organizational development leader and academic professional, Wallis’s teaching and expertise are in leadership, ethics, organizational behavior, team development, and change management.

Mihran A. Aroian is an assistant professor of instruction in the department of management at McCombs College of Business, University of Texas at Austin. He is a graduate of Worcester Polytechnic Institute and has an MBA from the University of Texas at Austin.

Johanna Glauber is an assistant professor in the strategy department at IE University. Her research focuses on firms’ strategy and behavior in case of failure. Having a background in management and mechanical engineering, Glauber is particularly interested in product failures in manufacturing industries, such as product recalls in the automotive industry. She also is an active member of the international research community.

Joseph C. Miller is professor and chair of the marketing and sales departments at St. Ambrose University.

Sheri L. Lambert is an associate professor of practice in the department of marketing at Temple University’s Fox School of Business where she teaches marketing strategy, digital innovation in marketing, and consumer buyer behavior at the undergraduate, graduate, and executive levels. Lambert is also academic director of the MS-Market Research Program and managing director of the Fox Center for Executive Education.

Oscar Melo-Vega Angeles is an associate professor of finance, a researcher, and the international financing area coordinator at the University of Lima. He is also responsible for the University of London program at the University of Lima. Melo-Vega has experience in researching and consulting in economics and finance. He has used cases in undergraduate classes for 15 years.

Michael Roberto  is the Trustee Professor of Management and the director of the Center for Program Innovation at Bryant University. He joined the tenured faculty at Bryant after serving for six years on the faculty at Harvard Business School.

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A case study in combating bias

The Quarterly : Tell us a bit about the circumstances that motivated RWE’s management to undertake a broad debiasing operation.

Stay current on your favorite topics

Bernhard Günther: In the second half of the last decade, we spent more than €10 billion on big capital-expenditure programs and acquisitions in conventional power plants. In the business cases underlying these decisions, we were betting on the assumptions of ever-rising commodity prices, ever-rising power prices. We were not alone in our industry in hitting a kind of investment peak at that time. What we and most other peers totally underestimated was the turnaround in public sentiment toward conventional power generation—for example, the green transformation of the German energy system, and the technological progress in renewable generation and related production costs. These factors went in a completely opposite direction compared to our scenarios.

Conventional power generation in continental Europe went through the deepest crisis the industry has ever seen. This ultimately led to the split of the two biggest German players in the industry, E.ON and RWE. Both companies separated their ailing conventional power-generation businesses from the rest of the company.

The Quarterly : Was it difficult to convince members of the executive and supervisory boards to scrutinize your decision-making practices?

Bernhard Günther: Actually, it was the supervisory board asking, “Where has the shareholders’ money gone?” and we in the executive board wanted to learn our lessons from this experience as well. So we embarked on a postmortem analysis to understand what went wrong and why, by looking at a sample of these €10 billion investments. We asked ourselves, “Is there anything we could have done differently, and if so, how can we learn from this in the future?” The spirit of it was not about shaming and blaming, but about learning from our own mistakes.

The Quarterly : What were the main contributing factors that you identified in your investigation?

Bernhard Günther: There were a few outright areas of managerial under-performance such as some time and cost overruns on the €10 billion investments, totally unrelated to external factors. There were also exogenous factors that were not in our base-case assumption but that should have been within our solution space—the most obvious being the political intent to push renewables into the market, which was publicly known at the time our investment decisions were made. There was also at least one unforeseeable factor—the Fukushima disaster. The German government reacted by rushing into a sudden exit from nuclear-power generation. Roughly half of the nuclear plants were switched off immediately, significantly shortening the economic lifetime of the remaining plants. But even if you discount for Fukushima, I think the ultimate end game wouldn’t have looked much different from today’s perspective; it just speeded the whole thing up.

The Quarterly : As you analyzed the decision-making dynamics at work, what biases did you start to see?

Bernhard Günther: What became obvious is that we had fallen victim to a number of cognitive biases in combination. We could see that status quo and confirmation biases had led us to assume the world would always be what it used to be. Beyond that, we neglected to heed the wisdom of portfolio theory that you shouldn’t lay all your eggs in one basket. We not only laid them in the same basket, but also within a very short period of time—the last billion was committed before the construction period of the first billion had been finalized. If we had stretched this whole €10 billion program out over a longer period, say 10 or 15 years, we might still have lost maybe €1 billion or €2 billion but not the amount we incurred later.

We also saw champion and sunflower biases, which are about hierarchical patterns and vertical power distance. Depending on the way you organize decision processes, when the boss speaks up first, the likelihood that anybody who’s not the boss will speak up with a dissenting opinion is much lower than if you, for example, have a conscious rule that the bigwigs in the hierarchy are the ones to speak up last, and you listen to all the other evidence before their opinion is offered.

And we certainly overestimated our own abilities to deliver, due to a good dose of action-oriented biases like overconfidence and excessive optimism. Our industry, like many other capital-intensive ones, has had boom and bust cycles in investments. We embarked on a huge investment program with a whole generation of managers who hadn’t built a single power plant in their professional lives; there were just a few people left who could really remember how big investments were done. So we did something that the industry, by and large, hadn’t been doing on a large scale for 20 years.

The Quarterly : On the sunflower bias, how far down in the organization do you think that went? Were people having a hard time getting past their superiors’ views just on the executive level, or all the way down?

Bernhard Günther: Our investigation revealed that it went much farther down, to almost all levels of our organizational hierarchy. For example, there was a feeling within the rank and file who produced the investment valuations for major decisions that certain scenarios were not desired—that you exposed yourself to the risk of being branded an eternal naysayer, or worse, when you pushed for more pessimistic scenarios. People knew that there were no debiasing mechanisms upstairs, so they would have no champion too if they were to suggest, for example, that if we looked at a “brilliant” new investment opportunity from a different angle, it might not look that brilliant anymore.

Are you ready to decide?

The Quarterly : So, what kind of countermeasures did you put in place to tackle these cultural issues?

Bernhard Günther: We started a cultural-change program early on, with the arrival of our new CEO, to address our need for a different management mind-set in light of an increasingly uncertain future. A big component of that was mindfulness—becoming aware of not only your own cognitive patterns, but also the likely ones of the people you work with. We also sought to embed this awareness in practical aspects of our process. For example, we’ve now made it mandatory to list the debiasing techniques that were applied as part of any major proposal that is put before us as a board.

It was equally important for us to start to create an atmosphere in which people are comfortable with a certain degree of conflict, where there is an obligation to dissent. This is not something I would say is part of the natural DNA of many institutions, including ours. We’ve found that we have to push it forward and safeguard it, because as soon as hierarchy prevails, it can be easily discouraged.

So, for example, when making big decisions, we now appoint a devil’s advocate—someone who has no personal stake in the decision and is senior enough in the hierarchy to be as independent as possible, usually a level below the executive board. And nobody blames the devil’s advocate for making the negative case because it’s not necessary for them to be personally convinced; it’s about making the strongest case possible. People see that constructive tension brings us further than universal consent.

Rapid reflections from Bernhard Günther

1. in your experience, what piece of common leadership advice is wrong or misleading.

People development based on weaknesses—or gaps versus “ideal candidate” profile—instead of building on strengths

2. Which historical figures do you admire the most?

Nelson Mandela and Martin Luther King Jr.

3. What’s the best book you’ve read in the past year?

Freedom , by Jonathan Franzen (fiction)

You! The Positive Force in Change: Leveraging Insights from Neuroscience and Positive Psychology , by Eileen Rogers and Nick van Dam (nonfiction)

4. What skill do you think is most undervalued in leaders today?

The Quarterly : How did you roll all this out?

Bernhard Günther: There were two areas of focus. First, over a period of two years, we sent the top 300 of our company’s management to a two-week course, which we had self-assembled with external experts. The main thrust of this program was self-awareness: being more open to dissent, more open to a certain amount of controlled risk taking, more agile, as with rapid prototyping, and so forth.

Then we also launched a training program for managers and experts, especially those involved in project work—for example, the financial controllers that have to run the models for big investment decisions. This was a combination of a training course, some desktop training you could do on your own, and some distributed materials.

This program explicitly focused on debiasing. It started with these typical examples where you can show everybody how easily we fall into those cognitive traps, framing it not as a personal defect but as something that’s just there. Secondly, it emphasized that debiasing can be done much more easily within a group, because it’s a collective, conscious effort. And not some kind of empty ritual either. We taught very specific things that people could apply in their daily practices. For example, you can do a kind of premortem analysis and ask your team, “Imagine we are five years into the future, and this whole project we’re deciding on today has turned out to be a complete disaster. What could have happened in the meantime? What could have gone wrong?” This is something that we are now doing regularly on big projects, especially when there are uncertain environmental factors—whether macroeconomic, technological, ecological, or political.

The Quarterly : Could you tell us about an example or two where you made a different decision as the result of debiasing practice, where it went the other way from what you initially thought was the right answer?

Bernhard Günther: Two examples immediately come to my mind. The first one came up in the middle of 2015, when it became obvious that our company was in a strategic deadlock with the power-generation business—the cash cow of the company for years but now with a broken business model. There was a growing awareness among senior management that trying to cure the crisis with yet another round of cost cutting might not be good enough, that we needed to consider more radical strategic options. We established a red team and a blue team to come up with different proposals, one staffed internally and one with externals. We wanted an unbiased view from the outside, from people who were not part of our company or industry; in this case, we brought in external people with backgrounds in investment banking.

The internal team came up with the kind of solution that I think everybody was initially leaning toward, which was more incremental. And the external team came up with a more disruptive solution. But because it was consciously pitched as an independent view, everybody on the board took their time to seriously consider it with an open mind. It planted the seedling of the strategy that we adopted to split the company into two parts, which now, a good year later, has successfully concluded with the IPO of Innogy. If we hadn’t taken this approach, maybe months later or years later, somebody would have come up with a similar idea, but it wouldn’t have happened that fast, with that kind of momentum.

The second example is a recent potential investment project in renewable energy that carried high reputational value for us, so there were emotional issues attached to winning the project. We were bidding for a wind park that was to be built, and the lowest bidder wins by offering the lowest electricity price. We knew it would be a very competitive auction for that project, and we had already decided in the run up to the decision making that we wanted to have a devil’s advocate involved.

We had the project team make the case first in the board meeting. Then we had the devil’s advocate put forward analysis of the risk–return trade-offs. All of this was in written form, so everybody had to read it before the meeting. This certainly helped our discussion a lot and made it much easier to have a nonemotional debate around the critical issues. And we came out of it with a different and I think better decision than we would have if we had just taken the proposal of our internal project team at face value.

The Quarterly : Now that these decision-making changes have taken hold, how do you see things running differently in the organization?

Bernhard Günther: Looking back at where we were three or four years ago, I’d say that this practice of awareness and debiasing has now become almost a part of our corporate decision-making DNA. But it’s something you have to constantly force yourself to practice again and again, because everyone at some point asks, “Do we really need to do it? Can’t we just decide?” It’s a very time-intensive process, which should be utilized only for the most important decisions of strategic relevance. About 30 percent of our board’s decisions fall into this category—for example, major resource-allocation decisions—and it’s similar elsewhere in the company.

Also, people’s general awareness of the complex set of issues around cognitive biases has grown dramatically. Before this, things easily degenerated into blaming exercises going both ways. The naysayers were critiquing the others for wanting to push their pet projects. And the people promoting these projects were saying that the naysayers were just narrow-minded financial controllers who were destroying the company by eternally killing good business ideas. But now there’s more mutual respect for these different roles that are needed to ultimately come up with as good a decision outcome as possible. It’s not just about debiasing; it’s given us a common language. It’s now routine for somebody to say in a meeting, “I think we need some debiasing here.” And then everybody can agree to this without any need to get emotional. When in doubt, we just go through the process.

The Quarterly : Do you have any recommendations for other senior leaders who might be reading this interview?

Bernhard Günther: I think when you read about these issues, it can seem a bit esoteric. You might say, “Well, maybe it’s just their problem, but not mine.” I think everyone should just do it; just start with it even on a pilot basis. You don’t have to start rolling it out across 1,000 people. You can start with your own board, with a few test examples, and see if you think it helps you. But if you do it, you have to do it right; you have to be serious about it. Looking back, there were a few key success factors for us. For one, top management has to set an example. That’s true of any kind of change, not just debiasing. If it’s not modeled at the very top, it’s unlikely to happen further down the hierarchy. Second, everyone has to be open to these ideas or it can be difficult to really make progress. At first glance, many of the tools might seem trivial to some, but we found them to have a very profound effect.

Bernhard Günther joined RWE in 1999 and served as the company’s chief financial officer from 2013 until the 2016 spin-off and IPO of Innogy, where he is now CFO. This interview was conducted by Sven Heiligtag , a partner in McKinsey’s Hamburg office, and Allen Webb, McKinsey Quarterly ’s editor in chief, who is based in the Seattle office.

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