case studies on problem solving

Problem-Solving in Business: CASE STUDIES

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• PROBLEM-SOLVING DEFINED AND WHY IT IS IMPORTANT
• SKILLS AND QUALIFICATIONS NEEDED IN PROBLEM-SOLVING
• PROBLEM-SOLVING STEPS
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• Last Updated: Mar 23, 2024 4:47 PM
• URL: https://libguides.nypl.org/problem_solving_in_business

Problem-Solving

Problem-solving is a complex skill used in times where solutions are not readily available. It is defined as “the skill of finding solutions for difficult or complex issues.” Using problem-solving in our daily lives helps us think through what options are possible in difficult situations and also helps create new solutions to move past the issue at hand.

Learning in Observation

The following video case studies are a learning tool that helps students, families, and educators examine the context of the social problems that might arise for youth and young adults. Visual media gives everyone a common viewing experience and centralizes the discussion around making choices and decisions in situations where problems exist. The activities extend learning around problem-solving and help learners understand why many of the problems that exist in everyday life are more complex than we think.

Watch the high school video case study below and think about how the opportunities for problem-solving involve both advocacy and the ability to receive and listen to other people’s perspectives. Hand out Character Profile Cards to students or groups of students and have them watch the video from the perspective of that character.

Referencing the profile cards , facilitate a discussion after watching the video. Some questions for discussion may include:

• What does my character know that the other characters need to know?
• What do the other characters know that my character needs to know?
• What are some possible solutions to the problem?
• Who can support the solution to make sure it is effective?
• Who needs to be a part of the solution?

The following video case study takes place at home between two brothers. Similar to the case study above, use questions to reflect on the problem and the process of problem-solving taken up by the parents.

Use the following questions to guide small groups in discussion around problem-solving.

• Why does this approach work well to discover the truth around the problem?
• What are some things that the parents learned about their children in the process of working through the problem?
• As a parent, why would it be important to get both perspectives?
• As a child, why would it be important to be heard, but also to hear your sibling’s perspective?
• What are some complex or difficult issues that are addressed in this process?

Observation to Practice

It might seem easy to find solutions when we are outside of the situation, however, it can be hard to solve problems when they pop up in our daily lives. The following are steps you can take to start problem-solving.

• Identify the problem
• Invite others affected by the problem to help understand what happened
• With help, collect more information about what happened
• Using the collected information, consider what process is most appropriate for reaching positive solutions
• Use the process to collaborate with others and generate plans for moving towards a solution
• Act towards goals that will help bring about a solution

Try it out for yourself! Use the following link to practice problem-solving in real-life situations.

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Case-based Teaching and Problem-based Learning

Case-based teaching.

With case-based teaching, students develop skills in analytical thinking and reflective judgment by reading and discussing complex, real-life scenarios. The articles in this section explain how to use cases in teaching and provide case studies for the natural sciences, social sciences, and other disciplines.

Teaching with Case Studies (Stanford University)

This article from the Stanford Center for Teaching and Learning describes the rationale for using case studies, the process for choosing appropriate cases, and tips for how to implement them in college courses.

The Case Method (University of Illinois)

Tips for teachers on how to be successful using the Case Method in the college/university classroom. Includes information about the Case Method values, uses, and additional resource links.

National Center for Case Study Teaching in Science (National Science Teaching Association)

This site offers resources and examples specific to teaching in the sciences. This includes the “UB Case Study Collection,” an extensive list of ready-to-use cases in a variety of science disciplines. Each case features a PDF handout describing the case, as well as teaching notes.

The Michigan Sustainability Cases Initiative (CRLT Occasional Paper)

This paper describes the Michigan Sustainability Cases Initiative, including links to the full library of cases, and it offers advice both for writing cases and facilitating case discussions effectively.

The Case Method and the Interactive Classroom (Foran, 2001, NEA Higher Education Journal)

First-person account of how a sociology faculty member at University of California, Santa Barbara began using case studies in his teaching and how his methods have evolved over time as a professor.

Problem-based Learning

Problem-based learning (PBL) is both a teaching method and an approach to the curriculum. It consists of carefully designed problems that challenge students to use problem solving techniques, self-directed learning strategies, team participation skills, and disciplinary knowledge. The articles and links in this section describe the characteristics and objectives of PBL and the process for using PBL. There is also a list of printed and web resources.

Problem-Based Learning Network (Illinois Mathematics and Science Academy)

Site includes an interactive PBL Model, Professional Development links, and video vignettes to illustrate how to effectively use problem-based learning in the classroom. The goals of IMSA's PBLNetwork are to mentor educators in all disciplines, to explore problem-based learning strategies, and to connect PBL educators to one another.

Problem-Based Learning: An Introduction (Rhem, 1998, National Teaching and Learning Forum)

This piece summarizes the benefits of using problem-based learning, its historical origins, and the faculty/student roles in PBL. Overall, this is an easy to read introduction to problem-based learning.

Problem-Based Learning (Stanford University, 2001)

This issue of Speaking of Teaching identifies the central features of PBL, provides some guidelines for planning a PBL course, and discusses the impact of PBL on student learning and motivation.

Problem-Based Learning Clearinghouse (University of Delaware)

Collection of peer reviewed problems and articles to assist educators in using problem-based learning. Teaching notes and supplemental materials accompany each problem, providing insights and strategies that are innovative and classroom-tested. Free registration is required to view and download the Clearinghouse’s resources.

See also: The International Journal of Problem-Based Learning

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How to master the seven-step problem-solving process

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

Podcast transcript

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

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

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

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

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

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

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

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

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

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

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

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Simon London: So this is a concise problem statement.

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

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

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

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Both: Yeah.

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

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

Simon London: Right. Right.

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

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

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

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

Simon London: Would you agree with that?

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

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

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

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

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

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

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

Charles Conn: Yeah.

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Every step of the process.

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

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

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Absolutely.

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

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

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

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

Hugo Sarrazin: It was a pleasure. Thank you.

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

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

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Design Thinking has emerged as a powerful problem-solving approach that places empathy, creativity, and innovation at the forefront. However, if you are not aware of the power that this approach holds, a Design Thinking Case Study is often used to help people address the complex challenges of this approach with a human-centred perspective. It allows organisations to unlock new opportunities and drive meaningful change. Read this blog on Design Thinking Case Study to learn how it enhances organisation’s growth and gain valuable insights on creative problem-solving.

Table of Contents   

1) What is Design Thinking?

2) Design Thinking process   

3) Successful Design Thinking Case Studies

      a) Airbnb

      b) Apple

      c) Netflix

      d) UberEats

      e) IBM

       f) OralB’s electric toothbrush

      g) IDEO

      h) Tesla

       i) GE Healthcare

       j) Nike

3) Lessons learned from Design Thinking Case Studies

4) Conclusion    

What is Design Thinking ?

Before jumping on Design Thinking Case Study, let’s first understand what it is. Design Thinking is a methodology for problem-solving that prioritises the understanding and addressing of individuals' unique needs.

This human-centric approach is creative and iterative, aiming to find innovative solutions to complex challenges. At its core, Design Thinking fosters empathy, encourages collaboration, and embraces experimentation.

This process revolves around comprehending the world from the user's perspective, identifying problems through this lens, and then generating and refining solutions that cater to these specific needs. Design Thinking places great importance on creativity and out-of-the-box thinking, seeking to break away from conventional problem-solving methods.

It is not confined to the realm of design but can be applied to various domains, from business and technology to healthcare and education. By putting the user or customer at the centre of the problem-solving journey, Design Thinking helps create products, services, and experiences that are more effective, user-friendly, and aligned with the genuine needs of the people they serve.  

Design Thinking process

Design Thinking is a problem-solving and innovation framework that helps individuals and teams create user-centred solutions. This process consists of five key phases that are as follows:  

To initiate the Design Thinking process, the first step is to practice empathy. In order to create products and services that are appealing, it is essential to comprehend the users and their requirements. What are their anticipations regarding the product you are designing? What issues and difficulties are they encountering within this particular context?

During the empathise phase, you spend time observing and engaging with real users. This might involve conducting interviews and seeing how they interact with an existing product. You should pay attention to facial expressions and body language. During the empathise phase in the Design Thinking Process , it's crucial to set aside assumptions and gain first-hand insights to design with real users in mind. That's the essence of Design Thinking.

During the second stage of the Design Thinking process, the goal is to identify the user’s problem. To accomplish this, collect all your observations from the empathise phase and begin to connect the dots.

Ask yourself: What consistent patterns or themes did you notice? What recurring user needs or challenges were identified? After synthesising your findings, you must create a problem statement, also known as a Point Of View (POV) statement, which outlines the issue or challenge you aim to address. By the end of the define stage, you will be able to craft a clear problem statement that will guide you throughout the design process, forming the basis of your ideas and potential solutions.

After completing the first two stages of the Design Thinking process, which involve defining the target users and identifying the problem statement, it is now time to move on to the third stage - ideation. This stage is all about brainstorming and coming up with various ideas and solutions to solve the problem statement. Through ideation, the team can explore different perspectives and possibilities and select the best ideas to move forward with.

During the ideation phase, it is important to create an environment where everyone feels comfortable sharing their ideas without fear of judgment. This phase is all about generating a large quantity of ideas, regardless of feasibility. This is done by encouraging the team to think outside the box and explore new angles. To maximise creativity, ideation sessions are often held in unconventional locations.

It’s time to transform the ideas from stage three into physical or digital prototypes. A prototype is a miniature model of a product or feature, which can be as simple as a paper model or as complex as an interactive digital representation.

During the Prototyping Stage , the primary objective is to transform your ideas into a tangible product that can be tested by actual users. This is crucial in maintaining a user-centric approach, as it enables you to obtain feedback before proceeding to develop the entire product. By doing so, you can ensure that the final design adequately addresses the user's problem and delivers an enjoyable user experience.

During the Design Thinking process, the fifth step involves testing your prototypes by exposing them to real users and evaluating their performance. Throughout this testing phase, you can observe how your target or prospective users engage with your prototype. Additionally, you can gather valuable feedback from your users about their experiences throughout the process.

Based on the feedback received during user testing, you can go back and make improvements to the design. It is important to remember that the Design Thinking process is iterative and non-linear. After the testing phase, it may be necessary to revisit the empathise stage or conduct additional ideation sessions before creating a successful prototype.

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Successful Design Thinking Case Studies  

Now that you have a foundational understanding of Design Thinking, let's explore how some of the world's most successful companies have leveraged this methodology to drive innovation and success:

Case Study 1: Airbnb  

Airbnb’s one of the popular Design Thinking Case Studies that you can aspire from. Airbnb disrupted the traditional hotel industry by applying Design Thinking principles to create a platform that connects travellers with unique accommodations worldwide. The founders of Airbnb, Brian Chesky, Joe Gebbia, and Nathan Blecharczyk, started by identifying a problem: the cost and lack of personalisation in traditional lodging.

They conducted in-depth user research by staying in their own listings and collecting feedback from both hosts and guests. This empathetic approach allowed them to design a platform that not only met the needs of travellers but also empowered hosts to provide personalised experiences. 

Airbnb's intuitive website and mobile app interface, along with its robust review and rating system, instil trust and transparency, making users feel comfortable choosing from a vast array of properties. Furthermore, the "Experiences" feature reflects Airbnb's commitment to immersive travel, allowing users to book unique activities hosted by locals. 

Case Study 2.  Apple    

Apple Inc. has consistently been a pioneer in  Design Thinking, which is evident in its products, such as the iPhone. One of the best Design Thinking Examples from Apple is the development of the iPhone's User Interface (UI). The team at Apple identified the need for a more intuitive and user-friendly smartphone experience. They conducted extensive research and usability testing to understand user behaviours, pain points, and desires.   

The result? A revolutionary touch interface that forever changed the smartphone industry. Apple's relentless focus on the user experience, combined with iterative prototyping and user feedback, exemplifies the power of  Design Thinking in creating groundbreaking products.    

Apple invests heavily in user research to  anticipate what customers want before they even realise it themselves. This empathetic approach to design has led to groundbreaking innovations like the iPhone, iPad, and MacBook, which have redefined the entire industry.  

Case Study 3. Netflix  

Netflix, the global streaming giant, has revolutionised the way people consume entertainment content. A major part of their success can be attributed to their effective use of Design Thinking principles.

What sets Netflix apart is its commitment to understanding its audience on a profound level. Netflix recognised that its success hinged on offering a personalised, enjoyable viewing experience. Through meticulous user research, data analysis, and a culture of innovation, Netflix constantly evolves its platform. Moreover, by gathering insights on viewing habits, content preferences, and even UI, the company tailors its recommendations, search algorithms, and original content to captivate viewers worldwide.

Furthermore, Netflix's iterative approach to Design Thinking allows it to adapt quickly to shifting market dynamics. This agility proved crucial when transitioning from a DVD rental service to a streaming platform. Netflix didn't just lead this revolution; it shaped it by keeping users' desires and behaviours front and centre. Netflix's commitment to Design Thinking has resulted in a highly user-centric platform that keeps subscribers engaged and satisfied, ultimately contributing to its global success.  

Case Study 4. Uber Eats     

Uber Eats, a subsidiary of Uber, has disrupted the food delivery industry by applying Design Thinking principles to enhance user experiences and create a seamless platform for food lovers and restaurants alike.  

One of  UberEats' key innovations lies in its user-centric approach. By conducting in-depth research and understanding the pain points of both consumers and restaurant partners, they crafted a solution that addresses real-world challenges. The user-friendly app offers a wide variety of cuisines, personalised recommendations, and real-time tracking, catering to the diverse preferences of customers.  

Moreover,  UberEats leverages technology and data-driven insights to optimise delivery routes and times, ensuring that hot and fresh food reaches customers promptly. The platform also empowers restaurant owners with tools to efficiently manage orders, track performance, and expand their customer base. 

Case Study  5 . IBM    

IBM is a prime example of a large corporation successfully adopting Design Thinking to drive innovation and transform its business. Historically known for its hardware and software innovations, IBM recognised the need to evolve its approach to remain competitive in the fast-paced technology landscape.   

IBM's Design Thinking journey began with a mission to reinvent its enterprise software solutions. The company transitioned from a product-centric focus to a user-centric one. Instead of solely relying on technical specifications, IBM started by empathising with its customers. They started to understand customer’s pain points, and envisioning solutions that genuinely addressed their needs. 

One of the key elements of IBM's Design Thinking success is its multidisciplinary teams. The company brought together designers, engineers, marketers, and end-users to collaborate throughout the product development cycle. This cross-functional approach encouraged diverse perspectives, fostering creativity and innovation. 

IBM's commitment to Design Thinking is evident in its flagship projects such as Watson, a cognitive computing system, and IBM Design Studios, where Design Thinking principles are deeply embedded into the company's culture. 

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Case Study 6. Oral-B’s electric toothbrush

Oral-B, a prominent brand under the Procter & Gamble umbrella, stands out as a remarkable example of how Design Thinking can be executed in a seemingly everyday product—Electric toothbrushes. By applying the Design Thinking approach, Oral-B has transformed the world of oral hygiene with its electric toothbrushes.  

Oral-B's journey with Design Thinking began by placing the user firmly at the centre of their Product Development process. Through extensive research and user feedback, the company gained invaluable insights into oral care habits, preferences, and pain points. This user-centric approach guided Oral-B in designing electric toothbrushes that not only cleaned teeth more effectively but also made the entire oral care routine more engaging and enjoyable.  

Another of Oral-B's crucial innovations is the integration of innovative technology into their toothbrushes. These devices now come equipped with features like real-time feedback, brushing timers, and even Bluetooth connectivity to sync with mobile apps. By embracing technology and user-centric design, Oral-B effectively transformed the act of brushing teeth into an interactive and informative experience. This has helped users maintain better oral hygiene.  

Oral-B's success story showcases how Design Thinking, combined with a deep understanding of user needs, can lead to significant advancements, ultimately improving both the product and user satisfaction.

Case Study 7. IDEO  

IDEO, a Global Design Consultancy, has been at the forefront of Design Thinking for decades. They have worked on diverse projects, from creating innovative medical devices to redesigning public services.

One of their most notable Design Thinking examples is the development of the "DeepDive" shopping cart for a major retailer. IDEO's team spent weeks observing shoppers, talking to store employees, and prototyping various cart designs. The result was a cart that not only improved the shopping experience but also increased sales. IDEO's human-centred approach, emphasis on empathy, and rapid prototyping techniques demonstrate how Design Thinking can drive innovation and solve real-world problems.   

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Case Study  8 .  Tesla  

Tesla, led by Elon Musk, has redefined the automotive industry by applying Design Thinking to Electric Vehicles (EVs). Musk and his team identified the need for EVs to be not just eco-friendly but also desirable. They focused on designing EVs that are stylish, high-performing, and technologically advanced. Tesla's iterative approach, rapid prototyping, and constant refinement have resulted in groundbreaking EVs like the Model S, Model 3, and Model X.    

From the minimalist interior of their Model S to the autopilot self-driving system, every aspect is meticulously crafted with the end user in mind. The company actively seeks feedback from its user community, often implementing software updates based on customer suggestions. This iterative approach ensures that Tesla vehicles continually evolve to meet and exceed customer expectations .   

Moreover, Tesla's bold vision extends to sustainable energy solutions, exemplified by products like the Powerwall and solar roof tiles. These innovations  showcase Tesla's holistic approach to Design Thinking, addressing not only the automotive industry's challenges but also contributing to a greener, more sustainable future.   

Case Study 9. GE Healthcare 

GE Healthcare is a prominent player in the Healthcare industry, renowned for its relentless commitment to innovation and design excellence. Leveraging Design Thinking principles, GE Healthcare has consistently pushed the boundaries of medical technology, making a significant impact on patient care worldwide.  

One of the key areas where GE Healthcare has excelled is in the development of cutting-edge medical devices and diagnostic solutions. Their dedication to user-centred design has resulted in devices that are not only highly functional but also incredibly intuitive for healthcare professionals to operate. For example, their advanced Medical Imaging equipment, such as MRI and CT scanners, are designed with a focus on patient comfort, safety, and accurate diagnostics. This device reflects the company's dedication to improving healthcare outcomes.  

Moreover, GE Healthcare's commitment to design extends beyond the physical product. They have also ventured into software solutions that facilitate data analysis and Patient Management. Their user-friendly software interfaces and data visualisation tools have empowered healthcare providers to make more informed decisions, enhancing overall patient care and treatment planning.

Case Study 10. Nike 

Nike is a global powerhouse in the athletic apparel and Footwear industry. Nike's journey began with a simple running shoe, but its design-thinking approach transformed it into an iconic brand.

Nike's Design Thinking journey started with a deep understanding of athletes' needs and desires. They engaged in extensive user research, often collaborating with top athletes to gain insights that inform their product innovations. This customer-centric approach allowed Nike to develop ground breaking technologies, such as Nike Air and Flyknit, setting new standards in comfort, performance, and style.

Beyond product innovation, Nike's brand identity itself is a testament to Design Thinking. The iconic Swoosh logo, created by Graphic Designer Carolyn Davidson, epitomises simplicity and timelessness, reflecting the brand's ethos.  

Nike also excels in creating immersive retail experiences, using Design Thinking to craft spaces that engage and inspire customers. Their flagship stores around the world are showcases of innovative design, enhancing the overall brand perception.

Lessons learned from Design Thinking Case Studies

The Design Thinking process, as exemplified by the success stories of IBM, Netflix, Apple, and Nike, offers valuable takeaways for businesses of all sizes and industries. Here are three key lessons to learn from these Case Studies:  

1)   Consider the b ig p icture   

Design Thinking encourages organisations to zoom out and view the big picture. It's not just about solving a specific problem but understanding how that problem fits into the broader context of user needs and market dynamics. By taking a holistic approach, you can identify opportunities for innovation that extend beyond immediate challenges. IBM's example, for instance, involved a comprehensive evaluation of their clients' journeys, leading to more impactful solutions.  

2)  Think t hrough a lternative s olutions   

One of the basic principles of Design Thinking is ideation, which emphasises generating a wide range of creative solutions. Netflix's success in content recommendation, for instance, came from exploring multiple strategies to enhance user experience. When brainstorming ideas and solutions, don't limit yourself to the obvious choices. Encourage diverse perspectives and consider unconventional approaches that may lead to breakthrough innovations.  

3)  Research e ach c ompany’s c ompetitors   

Lastly, researching competitors is essential for staying competitive. Analyse what other companies in your industry are doing, both inside and outside the realm of Design Thinking. Learn from their successes and failures. GE Healthcare, for example, leveraged Design Thinking to improve medical equipment usability, giving them a competitive edge. By researching competitors, you can gain insights that inform your own Design Thinking initiatives and help you stand out in the market.  

Incorporating these takeaways into your approach to Design Thinking can enhance your problem-solving capabilities, foster innovation, and ultimately lead to more successful results.  

Conclusion    

Design Thinking is not limited to a specific industry or problem domain; it is a versatile approach that promotes innovation and problem-solving in various contexts. In this blog, we've examined successful Design Thinking Case Studies from industry giants like IBM, Netflix, Apple, Airbnb, Uber Eats, and Nike. These companies have demonstrated that Design Thinking is a powerful methodology that can drive innovation, enhance user experiences, and lead to exceptional business success.   

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Frequently Asked Questions

Design Thinking Case Studies align with current market demands and user expectations by showcasing practical applications of user-centric problem-solving. These Studies highlight the success of empathetic approaches in meeting evolving customer needs.

By analysing various real-world examples, businesses can derive vital insights into dynamic market trends, creating innovative solutions, and enhancing user experiences. Design Thinking's emphasis on iterative prototyping and collaboration resonates with the contemporary demand for agility and adaptability.

Real-world examples of successful Design Thinking implementations can be found in various sources. For instance, you can explore several Case Study repositories on Design Thinking platforms like IDEO and Design Thinking Institute. Furthermore, you can also look for business publications, such as the Harvard Business Review as well as Fast Company, which often feature articles on successful Design Thinking applications.

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Our Leadership Training blogs covers a range of topics related to Design Thinking, offering valuable resources, best practices, and industry insights. Whether you are a beginner or looking to advance your Design Thinking skills, The Knowledge Academy's diverse courses and informative blogs have you covered.

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How the Case Method Works

• Read and analyze the case. Each case is a 10-20 page document written from the viewpoint of a real person leading a real organization. In addition to background information on the situation, each case ends in a key decision to be made. Your job is to sift through the information, incomplete by design, and decide what you would do.
• Discuss the case. Each morning, you’ll bring your ideas to a small team of classmates from diverse professional backgrounds, your discussion group, to share your findings and listen to theirs. Together, you begin to see the case from different perspectives, better preparing you for class.
• Engage in class. Be prepared to change the way you think as you debate with classmates the best path forward for this organization. The highly engaged conversation is facilitated by the faculty member, but it’s driven by your classmates’ comments and experiences. HBS brings together amazingly talented people from diverse backgrounds and puts that experience front and center. Students do the majority of the talking (and lots of active listening), and your job is to better understand the decision at hand, what you would do in the case protagonist’s shoes, and why. You will not leave a class thinking about the case the same way you thought about it coming in! In addition to learning more about many businesses, in the case method you will develop communication, listening, analysis, and leadership skills. It is a truly dynamic and immersive learning environment.
• Reflect. The case method prepares you to be in leadership positions where you will face time-sensitive decisions with limited information. Reflecting on each class discussion will prepare you to face these situations in your future roles.

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Case Study-Based Learning

Enhancing learning through immediate application.

By the Mind Tools Content Team

If you've ever tried to learn a new concept, you probably appreciate that "knowing" is different from "doing." When you have an opportunity to apply your knowledge, the lesson typically becomes much more real.

Adults often learn differently from children, and we have different motivations for learning. Typically, we learn new skills because we want to. We recognize the need to learn and grow, and we usually need – or want – to apply our newfound knowledge soon after we've learned it.

A popular theory of adult learning is andragogy (the art and science of leading man, or adults), as opposed to the better-known pedagogy (the art and science of leading children). Malcolm Knowles , a professor of adult education, was considered the father of andragogy, which is based on four key observations of adult learners:

• Adults learn best if they know why they're learning something.
• Adults often learn best through experience.
• Adults tend to view learning as an opportunity to solve problems.
• Adults learn best when the topic is relevant to them and immediately applicable.

This means that you'll get the best results with adults when they're fully involved in the learning experience. Give an adult an opportunity to practice and work with a new skill, and you have a solid foundation for high-quality learning that the person will likely retain over time.

So, how can you best use these adult learning principles in your training and development efforts? Case studies provide an excellent way of practicing and applying new concepts. As such, they're very useful tools in adult learning, and it's important to understand how to get the maximum value from them.

What Is a Case Study?

Case studies are a form of problem-based learning, where you present a situation that needs a resolution. A typical business case study is a detailed account, or story, of what happened in a particular company, industry, or project over a set period of time.

The learner is given details about the situation, often in a historical context. The key players are introduced. Objectives and challenges are outlined. This is followed by specific examples and data, which the learner then uses to analyze the situation, determine what happened, and make recommendations.

The depth of a case depends on the lesson being taught. A case study can be two pages, 20 pages, or more. A good case study makes the reader think critically about the information presented, and then develop a thorough assessment of the situation, leading to a well-thought-out solution or recommendation.

Why Use a Case Study?

Case studies are a great way to improve a learning experience, because they get the learner involved, and encourage immediate use of newly acquired skills.

They differ from lectures or assigned readings because they require participation and deliberate application of a broad range of skills. For example, if you study financial analysis through straightforward learning methods, you may have to calculate and understand a long list of financial ratios (don't worry if you don't know what these are). Likewise, you may be given a set of financial statements to complete a ratio analysis. But until you put the exercise into context, you may not really know why you're doing the analysis.

With a case study, however, you might explore whether a bank should provide financing to a borrower, or whether a company is about to make a good acquisition. Suddenly, the act of calculating ratios becomes secondary – it's more important to understand what the ratios tell you. This is how case studies can make the difference between knowing what to do, and knowing how, when, and why to do it.

Then, what really separates case studies from other practical forms of learning – like scenarios and simulations – is the ability to compare the learner's recommendations with what actually happened. When you know what really happened, it's much easier to evaluate the "correctness" of the answers given.

When to Use a Case Study

As you can see, case studies are powerful and effective training tools. They also work best with practical, applied training, so make sure you use them appropriately.

Remember these tips:

• Case studies tend to focus on why and how to apply a skill or concept, not on remembering facts and details. Use case studies when understanding the concept is more important than memorizing correct responses.
• Case studies are great team-building opportunities. When a team gets together to solve a case, they'll have to work through different opinions, methods, and perspectives.
• Use case studies to build problem-solving skills, particularly those that are valuable when applied, but are likely to be used infrequently. This helps people get practice with these skills that they might not otherwise get.
• Case studies can be used to evaluate past problem solving. People can be asked what they'd do in that situation, and think about what could have been done differently.

Ensuring Maximum Value From Case Studies

The first thing to remember is that you already need to have enough theoretical knowledge to handle the questions and challenges in the case study. Otherwise, it can be like trying to solve a puzzle with some of the pieces missing.

Here are some additional tips for how to approach a case study. Depending on the exact nature of the case, some tips will be more relevant than others.

• Read the case at least three times before you start any analysis. Case studies usually have lots of details, and it's easy to miss something in your first, or even second, reading.
• Once you're thoroughly familiar with the case, note the facts. Identify which are relevant to the tasks you've been assigned. In a good case study, there are often many more facts than you need for your analysis.
• If the case contains large amounts of data, analyze this data for relevant trends. For example, have sales dropped steadily, or was there an unexpected high or low point?
• If the case involves a description of a company's history, find the key events, and consider how they may have impacted the current situation.
• Consider using techniques like SWOT analysis and Porter's Five Forces Analysis to understand the organization's strategic position.
• Stay with the facts when you draw conclusions. These include facts given in the case as well as established facts about the environmental context. Don't rely on personal opinions when you put together your answers.

Writing a Case Study

You may have to write a case study yourself. These are complex documents that take a while to research and compile. The quality of the case study influences the quality of the analysis. Here are some tips if you want to write your own:

• Write your case study as a structured story. The goal is to capture an interesting situation or challenge and then bring it to life with words and information. You want the reader to feel a part of what's happening.
• Present information so that a "right" answer isn't obvious. The goal is to develop the learner's ability to analyze and assess, not necessarily to make the same decision as the people in the actual case.
• Do background research to fully understand what happened and why. You may need to talk to key stakeholders to get their perspectives as well.
• Determine the key challenge. What needs to be resolved? The case study should focus on one main question or issue.
• Define the context. Talk about significant events leading up to the situation. What organizational factors are important for understanding the problem and assessing what should be done? Include cultural factors where possible.
• Identify key decision makers and stakeholders. Describe their roles and perspectives, as well as their motivations and interests.
• Make sure that you provide the right data to allow people to reach appropriate conclusions.
• Make sure that you have permission to use any information you include.

A typical case study structure includes these elements:

• Executive summary. Define the objective, and state the key challenge.
• Opening paragraph. Capture the reader's interest.
• Scope. Describe the background, context, approach, and issues involved.
• Presentation of facts. Develop an objective picture of what's happening.
• Description of key issues. Present viewpoints, decisions, and interests of key parties.

Because case studies have proved to be such effective teaching tools, many are already written. Some excellent sources of free cases are The Times 100 , CasePlace.org , and Schroeder & Schroeder Inc . You can often search for cases by topic or industry. These cases are expertly prepared, based mostly on real situations, and used extensively in business schools to teach management concepts.

Case studies are a great way to improve learning and training. They provide learners with an opportunity to solve a problem by applying what they know.

There are no unpleasant consequences for getting it "wrong," and cases give learners a much better understanding of what they really know and what they need to practice.

Case studies can be used in many ways, as team-building tools, and for skill development. You can write your own case study, but a large number are already prepared. Given the enormous benefits of practical learning applications like this, case studies are definitely something to consider adding to your next training session.

Knowles, M. (1973). 'The Adult Learner: A Neglected Species [online].' Available here .

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Making Learning Relevant With Case Studies

The open-ended problems presented in case studies give students work that feels connected to their lives.

To prepare students for jobs that haven’t been created yet, we need to teach them how to be great problem solvers so that they’ll be ready for anything. One way to do this is by teaching content and skills using real-world case studies, a learning model that’s focused on reflection during the problem-solving process. It’s similar to project-based learning, but PBL is more focused on students creating a product.

Case studies have been used for years by businesses, law and medical schools, physicians on rounds, and artists critiquing work. Like other forms of problem-based learning, case studies can be accessible for every age group, both in one subject and in interdisciplinary work.

You can get started with case studies by tackling relatable questions like these with your students:

• How can we limit food waste in the cafeteria?
• How can we get our school to recycle and compost waste? (Or, if you want to be more complex, how can our school reduce its carbon footprint?)
• How can we improve school attendance?
• How can we reduce the number of people who get sick at school during cold and flu season?

Addressing questions like these leads students to identify topics they need to learn more about. In researching the first question, for example, students may see that they need to research food chains and nutrition. Students often ask, reasonably, why they need to learn something, or when they’ll use their knowledge in the future. Learning is most successful for students when the content and skills they’re studying are relevant, and case studies offer one way to create that sense of relevance.

Teaching With Case Studies

Ultimately, a case study is simply an interesting problem with many correct answers. What does case study work look like in classrooms? Teachers generally start by having students read the case or watch a video that summarizes the case. Students then work in small groups or individually to solve the case study. Teachers set milestones defining what students should accomplish to help them manage their time.

During the case study learning process, student assessment of learning should be focused on reflection. Arthur L. Costa and Bena Kallick’s Learning and Leading With Habits of Mind gives several examples of what this reflection can look like in a classroom: 

Journaling: At the end of each work period, have students write an entry summarizing what they worked on, what worked well, what didn’t, and why. Sentence starters and clear rubrics or guidelines will help students be successful. At the end of a case study project, as Costa and Kallick write, it’s helpful to have students “select significant learnings, envision how they could apply these learnings to future situations, and commit to an action plan to consciously modify their behaviors.”

Interviews: While working on a case study, students can interview each other about their progress and learning. Teachers can interview students individually or in small groups to assess their learning process and their progress.

Student discussion: Discussions can be unstructured—students can talk about what they worked on that day in a think-pair-share or as a full class—or structured, using Socratic seminars or fishbowl discussions. If your class is tackling a case study in small groups, create a second set of small groups with a representative from each of the case study groups so that the groups can share their learning.

4 Tips for Setting Up a Case Study

1. Identify a problem to investigate: This should be something accessible and relevant to students’ lives. The problem should also be challenging and complex enough to yield multiple solutions with many layers.

2. Give context: Think of this step as a movie preview or book summary. Hook the learners to help them understand just enough about the problem to want to learn more.

3. Have a clear rubric: Giving structure to your definition of quality group work and products will lead to stronger end products. You may be able to have your learners help build these definitions.

4. Provide structures for presenting solutions: The amount of scaffolding you build in depends on your students’ skill level and development. A case study product can be something like several pieces of evidence of students collaborating to solve the case study, and ultimately presenting their solution with a detailed slide deck or an essay—you can scaffold this by providing specified headings for the sections of the essay.

Problem-Based Teaching Resources

There are many high-quality, peer-reviewed resources that are open source and easily accessible online.

• The National Center for Case Study Teaching in Science at the University at Buffalo built an online collection of more than 800 cases that cover topics ranging from biochemistry to economics. There are resources for middle and high school students.
• Models of Excellence , a project maintained by EL Education and the Harvard Graduate School of Education, has examples of great problem- and project-based tasks—and corresponding exemplary student work—for grades pre-K to 12.
• The Interdisciplinary Journal of Problem-Based Learning at Purdue University is an open-source journal that publishes examples of problem-based learning in K–12 and post-secondary classrooms.
• The Tech Edvocate has a list of websites and tools related to problem-based learning.

In their book Problems as Possibilities , Linda Torp and Sara Sage write that at the elementary school level, students particularly appreciate how they feel that they are taken seriously when solving case studies. At the middle school level, “researchers stress the importance of relating middle school curriculum to issues of student concern and interest.” And high schoolers, they write, find the case study method “beneficial in preparing them for their future.”

7 Favorite Business Case Studies to Teach—and Why

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• Case Teaching
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FEATURED CASE STUDIES

The Army Crew Team . Emily Michelle David of CEIBS

ATH Technologies . Devin Shanthikumar of Paul Merage School of Business

Fabritek 1992 . Rob Austin of Ivey Business School

Lincoln Electric Co . Karin Schnarr of Wilfrid Laurier University

Pal’s Sudden Service—Scaling an Organizational Model to Drive Growth . Gary Pisano of Harvard Business School

The United States Air Force: ‘Chaos’ in the 99th Reconnaissance Squadron . Francesca Gino of Harvard Business School

Warren E. Buffett, 2015 . Robert F. Bruner of Darden School of Business

To dig into what makes a compelling case study, we asked seven experienced educators who teach with—and many who write—business case studies: “What is your favorite case to teach and why?”

The resulting list of case study favorites ranges in topics from operations management and organizational structure to rebel leaders and whodunnit dramas.

1. The Army Crew Team

Emily Michelle David, Assistant Professor of Management, China Europe International Business School (CEIBS)

“I love teaching  The Army Crew Team  case because it beautifully demonstrates how a team can be so much less than the sum of its parts.

I deliver the case to executives in a nearby state-of-the-art rowing facility that features rowing machines, professional coaches, and shiny red eight-person shells.

After going through the case, they hear testimonies from former members of Chinese national crew teams before carrying their own boat to the river for a test race.

The rich learning environment helps to vividly underscore one of the case’s core messages: competition can be a double-edged sword if not properly managed.

Executives in Emily Michelle David’s organizational behavior class participate in rowing activities at a nearby facility as part of her case delivery.

Despite working for an elite headhunting firm, the executives in my most recent class were surprised to realize how much they’ve allowed their own team-building responsibilities to lapse. In the MBA pre-course, this case often leads to a rich discussion about common traps that newcomers fall into (for example, trying to do too much, too soon), which helps to poise them to both stand out in the MBA as well as prepare them for the lateral team building they will soon engage in.

Finally, I love that the post-script always gets a good laugh and serves as an early lesson that organizational behavior courses will seldom give you foolproof solutions for specific problems but will, instead, arm you with the ability to think through issues more critically.”

2. ATH Technologies

Devin Shanthikumar, Associate Professor of Accounting, Paul Merage School of Business

“As a professor at UC Irvine’s Paul Merage School of Business, and before that at Harvard Business School, I have probably taught over 100 cases. I would like to say that my favorite case is my own,   Compass Box Whisky Company . But as fun as that case is, one case beats it:  ATH Technologies  by Robert Simons and Jennifer Packard.

ATH presents a young entrepreneurial company that is bought by a much larger company. As part of the merger, ATH gets an ‘earn-out’ deal—common among high-tech industries. The company, and the class, must decide what to do to achieve the stretch earn-out goals.

ATH captures a scenario we all want to be in at some point in our careers—being part of a young, exciting, growing organization. And a scenario we all will likely face—having stretch goals that seem almost unreachable.

It forces us, as a class, to really struggle with what to do at each stage.

After we read and discuss the A case, we find out what happens next, and discuss the B case, then the C, then D, and even E. At every stage, we can:

see how our decisions play out,

figure out how to build on our successes, and

address our failures.

The case is exciting, the class discussion is dynamic and energetic, and in the end, we all go home with a memorable ‘ah-ha!’ moment.

I have taught many great cases over my career, but none are quite as fun, memorable, and effective as ATH .”

3. Fabritek 1992

Rob Austin, Professor of Information Systems, Ivey Business School

“This might seem like an odd choice, but my favorite case to teach is an old operations case called  Fabritek 1992 .

The latest version of Fabritek 1992 is dated 2009, but it is my understanding that this is a rewrite of a case that is older (probably much older). There is a Fabritek 1969 in the HBP catalog—same basic case, older dates, and numbers. That 1969 version lists no authors, so I suspect the case goes even further back; the 1969 version is, I’m guessing, a rewrite of an even older version.

There are many things I appreciate about the case. Here are a few:

It operates as a learning opportunity at many levels. At first it looks like a not-very-glamorous production job scheduling case. By the end of the case discussion, though, we’re into (operations) strategy and more. It starts out technical, then explodes into much broader relevance. As I tell participants when I’m teaching HBP's Teaching with Cases seminars —where I often use Fabritek as an example—when people first encounter this case, they almost always underestimate it.

It has great characters—especially Arthur Moreno, who looks like a troublemaker, but who, discussion reveals, might just be the smartest guy in the factory. Alums of the Harvard MBA program have told me that they remember Arthur Moreno many years later.

Almost every word in the case is important. It’s only four and a half pages of text and three pages of exhibits. This economy of words and sparsity of style have always seemed like poetry to me. I should note that this super concise, every-word-matters approach is not the ideal we usually aspire to when we write cases. Often, we include extra or superfluous information because part of our teaching objective is to provide practice in separating what matters from what doesn’t in a case. Fabritek takes a different approach, though, which fits it well.

It has a dramatic structure. It unfolds like a detective story, a sort of whodunnit. Something is wrong. There is a quality problem, and we’re not sure who or what is responsible. One person, Arthur Moreno, looks very guilty (probably too obviously guilty), but as we dig into the situation, there are many more possibilities. We spend in-class time analyzing the data (there’s a bit of math, so it covers that base, too) to determine which hypotheses are best supported by the data. And, realistically, the data doesn’t support any of the hypotheses perfectly, just some of them more than others. Also, there’s a plot twist at the end (I won’t reveal it, but here’s a hint: Arthur Moreno isn’t nearly the biggest problem in the final analysis). I have had students tell me the surprising realization at the end of the discussion gives them ‘goosebumps.’

Finally, through the unexpected plot twist, it imparts what I call a ‘wisdom lesson’ to young managers: not to be too sure of themselves and to regard the experiences of others, especially experts out on the factory floor, with great seriousness.”

4. Lincoln Electric Co.

Karin Schnarr, Assistant Professor of Policy, Wilfrid Laurier University

“As a strategy professor, my favorite case to teach is the classic 1975 Harvard case  Lincoln Electric Co.  by Norman Berg.

I use it to demonstrate to students the theory linkage between strategy and organizational structure, management processes, and leadership behavior.

This case may be an odd choice for a favorite. It occurs decades before my students were born. It is pages longer than we are told students are now willing to read. It is about manufacturing arc welding equipment in Cleveland, Ohio—a hard sell for a Canadian business classroom.

Yet, I have never come across a case that so perfectly illustrates what I want students to learn about how a company can be designed from an organizational perspective to successfully implement its strategy.

And in a time where so much focus continues to be on how to maximize shareholder value, it is refreshing to be able to discuss a publicly-traded company that is successfully pursuing a strategy that provides a fair value to shareholders while distributing value to employees through a large bonus pool, as well as value to customers by continually lowering prices.

However, to make the case resonate with today’s students, I work to make it relevant to the contemporary business environment. I link the case to multimedia clips about Lincoln Electric’s current manufacturing practices, processes, and leadership practices. My students can then see that a model that has been in place for generations is still viable and highly successful, even in our very different competitive situation.”

5. Pal’s Sudden Service—Scaling an Organizational Model to Drive Growth

Gary Pisano, Professor of Business Administration, Harvard Business School

“My favorite case to teach these days is  Pal’s Sudden Service—Scaling an Organizational Model to Drive Growth .

I love teaching this case for three reasons:

1. It demonstrates how a company in a super-tough, highly competitive business can do very well by focusing on creating unique operating capabilities. In theory, Pal’s should have no chance against behemoths like McDonalds or Wendy’s—but it thrives because it has built a unique operating system. It’s a great example of a strategic approach to operations in action.

2. The case shows how a strategic approach to human resource and talent development at all levels really matters. This company competes in an industry not known for engaging its front-line workers. The case shows how engaging these workers can really pay off.

3. Finally, Pal’s is really unusual in its approach to growth. Most companies set growth goals (usually arbitrary ones) and then try to figure out how to ‘backfill’ the human resource and talent management gaps. They trust you can always find someone to do the job. Pal’s tackles the growth problem completely the other way around. They rigorously select and train their future managers. Only when they have a manager ready to take on their own store do they open a new one. They pace their growth off their capacity to develop talent. I find this really fascinating and so do the students I teach this case to.”

6. The United States Air Force: ‘Chaos’ in the 99th Reconnaissance Squadron

Francesca Gino, Professor of Business Administration, Harvard Business School

“My favorite case to teach is  The United States Air Force: ‘Chaos’ in the 99th Reconnaissance Squadron .

The case surprises students because it is about a leader, known in the unit by the nickname Chaos , who inspired his squadron to be innovative and to change in a culture that is all about not rocking the boat, and where there is a deep sense that rules should simply be followed.

For years, I studied ‘rebels,’ people who do not accept the status quo; rather, they approach work with curiosity and produce positive change in their organizations. Chaos is a rebel leader who got the level of cultural change right. Many of the leaders I’ve met over the years complain about the ‘corporate culture,’ or at least point to clear weaknesses of it; but then they throw their hands up in the air and forget about changing what they can.

Chaos is different—he didn’t go after the ‘Air Force’ culture. That would be like boiling the ocean.

Instead, he focused on his unit of control and command: The 99th squadron. He focused on enabling that group to do what it needed to do within the confines of the bigger Air Force culture. In the process, he inspired everyone on his team to be the best they can be at work.

The case leaves the classroom buzzing and inspired to take action.”

7. Warren E. Buffett, 2015

Robert F. Bruner, Professor of Business Administration, Darden School of Business

“I love teaching   Warren E. Buffett, 2015  because it energizes, exercises, and surprises students.

Buffett looms large in the business firmament and therefore attracts anyone who is eager to learn his secrets for successful investing. This generates the kind of energy that helps to break the ice among students and instructors early in a course and to lay the groundwork for good case discussion practices.

Studying Buffett’s approach to investing helps to introduce and exercise important themes that will resonate throughout a course. The case challenges students to define for themselves what it means to create value. The case discussion can easily be tailored for novices or for more advanced students.

Either way, this is not hero worship: The case affords a critical examination of the financial performance of Buffett’s firm, Berkshire Hathaway, and reveals both triumphs and stumbles. Most importantly, students can critique the purported benefits of Buffett’s conglomeration strategy and the sustainability of his investment record as the size of the firm grows very large.

By the end of the class session, students seem surprised with what they have discovered. They buzz over the paradoxes in Buffett’s philosophy and performance record. And they come away with sober respect for Buffett’s acumen and for the challenges of creating value for investors.

Surely, such sobriety is a meta-message for any mastery of finance.”

More Educator Favorites

Emily Michelle David is an assistant professor of management at China Europe International Business School (CEIBS). Her current research focuses on discovering how to make workplaces more welcoming for people of all backgrounds and personality profiles to maximize performance and avoid employee burnout. David’s work has been published in a number of scholarly journals, and she has worked as an in-house researcher at both NASA and the M.D. Anderson Cancer Center.

Devin Shanthikumar  is an associate professor and the accounting area coordinator at UCI Paul Merage School of Business. She teaches undergraduate, MBA, and executive-level courses in managerial accounting. Shanthikumar previously served on the faculty at Harvard Business School, where she taught both financial accounting and managerial accounting for MBAs, and wrote cases that are used in accounting courses across the country.

Robert D. Austin is a professor of information systems at Ivey Business School and an affiliated faculty member at Harvard Medical School. He has published widely, authoring nine books, more than 50 cases and notes, three Harvard online products, and two popular massive open online courses (MOOCs) running on the Coursera platform.

Karin Schnarr is an assistant professor of policy and the director of the Bachelor of Business Administration (BBA) program at the Lazaridis School of Business & Economics at Wilfrid Laurier University in Waterloo, Ontario, Canada where she teaches strategic management at the undergraduate, graduate, and executive levels. Schnarr has published several award-winning and best-selling cases and regularly presents at international conferences on case writing and scholarship.

Gary P. Pisano is the Harry E. Figgie, Jr. Professor of Business Administration and senior associate dean of faculty development at Harvard Business School, where he has been on the faculty since 1988. Pisano is an expert in the fields of technology and operations strategy, the management of innovation, and competitive strategy. His research and consulting experience span a range of industries including aerospace, biotechnology, pharmaceuticals, specialty chemicals, health care, nutrition, computers, software, telecommunications, and semiconductors.

Francesca Gino studies how people can have more productive, creative, and fulfilling lives. She is a professor at Harvard Business School and the author, most recently, of  Rebel Talent: Why It Pays to Break the Rules at Work and in Life . Gino regularly gives keynote speeches, delivers corporate training programs, and serves in advisory roles for firms and not-for-profit organizations across the globe.

Robert F. Bruner is a university professor at the University of Virginia, distinguished professor of business administration, and dean emeritus of the Darden School of Business. He has also held visiting appointments at Harvard and Columbia universities in the United States, at INSEAD in France, and at IESE in Spain. He is the author, co-author, or editor of more than 20 books on finance, management, and teaching. Currently, he teaches and writes in finance and management.

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Case studies from Bulletproof Problem Solving

The book has more than 30 case studies. we show two simple ones here to pique your interest in learning more..

Exhibit 1.5

The company also evaluated whether it could achieve the same result by reducing its fixed overheads or taking manufacturing in-house. With few costs other than a lean staff and rent, the first was not an option. With limited current cash resources, investing in its own extremely expensive manufacturing presses and assembly also didn’t make sense (step 3). On balance a small price increase to restore unit margins was worth the risk (step 6 and 7).

This kind of financial tree is particularly useful for solving problems that involve monetary trade-offs of alternative strategies. You can use it to track almost any kind of business problem.

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How to Approach a Case Study in a Problem Solving Workshop

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• Help students effectively read problem solving case studies and prepare for problem solving class discussions and exercises.

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A Better Framework for Solving Tough Problems

Start with trust and end with speed.

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When it comes to solving complicated problems, the default for many organizational leaders is to take their time to work through the issues at hand. Unfortunately, that often leads to patchwork solutions or problems not truly getting resolved.

But Anne Morriss offers a different framework. In this episode, she outlines a five-step process for solving any problem and explains why starting with trust and ending with speed is so important for effective change leadership. As she says, “Let’s get into dialogue with the people who are also impacted by the problem before we start running down the path of solving it.”

Morriss is an entrepreneur and leadership coach. She’s also the coauthor of the book, Move Fast and Fix Things: The Trusted Leader’s Guide to Solving Hard Problems .

Key episode topics include: strategy, decision making and problem solving, strategy execution, managing people, collaboration and teams, trustworthiness, organizational culture, change leadership, problem solving, leadership.

HBR On Strategy curates the best case studies and conversations with the world’s top business and management experts, to help you unlock new ways of doing business. New episodes every week.

• Listen to the full HBR IdeaCast episode: How to Solve Tough Problems Better and Faster (2023)
• Find more episodes of HBR IdeaCast
• Discover 100 years of Harvard Business Review articles, case studies, podcasts, and more at HBR.org .

HANNAH BATES: Welcome to HBR On Strategy , case studies and conversations with the world’s top business and management experts, hand-selected to help you unlock new ways of doing business.

When it comes to solving complicated problems, many leaders only focus on the most apparent issues. Unfortunately that often leads to patchwork or partial solutions. But Anne Morriss offers a different framework that aims to truly tackle big problems by first leaning into trust and then focusing on speed.

Morriss is an entrepreneur and leadership coach. She’s also the co-author of the book, Move Fast and Fix Things: The Trusted Leader’s Guide to Solving Hard Problems . In this episode, she outlines a five-step process for solving any problem. Some, she says, can be solved in a week, while others take much longer. She also explains why starting with trust and ending with speed is so important for effective change leadership.

This episode originally aired on HBR IdeaCast in October 2023. Here it is.

CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Curt Nickisch.

Problems can be intimidating. Sure, some problems are fun to dig into. You roll up your sleeves, you just take care of them; but others, well, they’re complicated. Sometimes it’s hard to wrap your brain around a problem, much less fix it.

And that’s especially true for leaders in organizations where problems are often layered and complex. They sometimes demand technical, financial, or interpersonal knowledge to fix. And whether it’s avoidance on the leaders’ part or just the perception that a problem is systemic or even intractable, problems find a way to endure, to keep going, to keep being a problem that everyone tries to work around or just puts up with.

But today’s guest says that just compounds it and makes the problem harder to fix. Instead, she says, speed and momentum are key to overcoming a problem.

Anne Morriss is an entrepreneur, leadership coach and founder of the Leadership Consortium and with Harvard Business School Professor Francis Frei, she wrote the new book, Move Fast and Fix Things: The Trusted Leaders Guide to Solving Hard Problems . Anne, welcome back to the show.

ANNE MORRISS: Curt, thank you so much for having me.

CURT NICKISCH: So, to generate momentum at an organization, you say that you really need speed and trust. We’ll get into those essential ingredients some more, but why are those two essential?

ANNE MORRISS: Yeah. Well, the essential pattern that we observed was that the most effective change leaders out there were building trust and speed, and it didn’t seem to be a well-known observation. We all know the phrase, “Move fast and break things,” but the people who were really getting it right were moving fast and fixing things, and that was really our jumping off point. So when we dug into the pattern, what we observed was they were building trust first and then speed. This foundation of trust was what allowed them to fix more things and break fewer.

CURT NICKISCH: Trust sounds like a slow thing, right? If you talk about building trust, that is something that takes interactions, it takes communication, it takes experiences. Does that run counter to the speed idea?

ANNE MORRISS: Yeah. Well, this issue of trust is something we’ve been looking at for over a decade. One of the headlines in our research is it’s actually something we’re building and rebuilding and breaking all the time. And so instead of being this precious, almost farbege egg, it’s this thing that is constantly in motion and this thing that we can really impact when we’re deliberate about our choices and have some self-awareness around where it’s breaking down and how it’s breaking down.

CURT NICKISCH: You said break trust in there, which is intriguing, right? That you may have to break trust to build trust. Can you explain that a little?

ANNE MORRISS:  Yeah, well, I’ll clarify. It’s not that you have to break it in order to build it. It’s just that we all do it some of the time. Most of us are trusted most of the time. Most of your listeners I imagine are trusted most of the time, but all of us have a pattern where we break trust or where we don’t build as much as could be possible.

CURT NICKISCH: I want to talk about speed, this other essential ingredient that’s so intriguing, right? Because you think about solving hard problems as something that just takes a lot of time and thinking and coordination and planning and designing. Explain what you mean by it? And also, just  how we maybe approach problems wrong by taking them on too slowly?

ANNE MORRISS: Well, Curt, no one has ever said to us, “I wish I had taken longer and done less.” We hear the opposite all the time, by the way. So what we really set out to do was to create a playbook that anyone can use to take less time to do more of the things that are going to make your teams and organizations stronger.

And the way we set up the book is okay, it’s really a five step process. Speed is the last step. It’s the payoff for the hard work you’re going to do to figure out your problem, build or rebuild trust, expand the team in thoughtful and strategic ways, and then tell a real and compelling story about the change you’re leading.

Only then do you get to go fast, but that’s an essential part of the process, and we find that either people under emphasize it or speed has gotten a bad name in this world of moving fast and breaking things. And part of our mission for sure was to rehabilitate speed’s reputation because it is an essential part of the change leader’s equation. It can be the difference between good intentions and getting anything done at all.

CURT NICKISCH: You know, the fact that nobody ever tells you, “I wish we had done less and taken more time.” I think we all feel that, right? Sometimes we do something and then realize, “Oh, that wasn’t that hard and why did it take me so long to do it? And I wish I’d done this a long time ago.” Is it ever possible to solve a problem too quickly?

ANNE MORRISS: Absolutely. And we see that all the time too. What we push people to do in those scenarios is really take a look at the underlying issue because in most cases, the solution is not to take your foot off the accelerator per se and slow down. The solution is to get into the underlying problem. So if it’s burnout or a strategic disconnect between what you’re building and the marketplace you’re serving, what we find is the anxiety that people attach to speed or the frustration people attach to speed is often misplaced.

CURT NICKISCH: What is a good timeline to think about solving a problem then? Because if we by default take too long or else jump ahead and we don’t fix it right, what’s a good target time to have in your mind for how long solving a problem should take?

ANNE MORRISS: Yeah. Well, we’re playful in the book and talking about the idea that many problems can be solved in a week. We set the book up five chapters. They’re titled Monday, Tuesday, Wednesday, Thursday, Friday, and we’re definitely having fun with that. And yet, if you count the hours in a week, there are a lot of them. Many of our problems, if you were to spend a focused 40 hours of effort on a problem, you’re going to get pretty far.

But our main message is, listen, of course it’s going to depend on the nature of the problem, and you’re going to take weeks and maybe even some cases months to get to the other side. What we don’t want you to do is take years, which tends to be our default timeline for solving hard problems.

CURT NICKISCH: So you say to start with identifying the problem that’s holding you back, seems kind of obvious. But where do companies go right and wrong with this first step of just identifying the problem that’s holding you back?

ANNE MORRISS: And our goal is that all of these are going to feel obvious in retrospect. The problem is we skip over a lot of these steps and this is why we wanted to underline them. So this one is really rooted in our observation and I think the pattern of our species that we tend to be overconfident in the quality of our thoughts, particularly when it comes to diagnosing problems.

And so we want to invite you to start in a very humble and curious place, which tends not to be our default mode when we’re showing up for work. We convince ourselves that we’re being paid for our judgment. That’s exactly what gets reinforced everywhere. And so we tend to counterintuitively, given what we just talked about, we tend to move too quickly through the diagnostic phase.

CURT NICKISCH: “I know what to do, that’s why you hired me.”

ANNE MORRISS: Exactly. “I know what to do. That’s why you hired me. I’ve seen this before. I have a plan. Follow me.” We get rewarded for the expression of confidence and clarity. And so what we’re inviting people to do here is actually pause and really lean into what are the root causes of the problem you’re seeing? What are some alternative explanations? Let’s get into dialogue with the people who are also impacted by the problem before we start running down the path of solving it.

CURT NICKISCH: So what do you recommend for this step, for getting to the root of the problem? What are questions you should ask? What’s the right thought process? What do you do on Monday of the week?

ANNE MORRISS: In our experience of doing this work, people tend to undervalue the power of conversation, particularly with other people in the organization. So we will often advocate putting together a team of problem solvers, make it a temporary team, really pull in people who have a particular perspective on the problem and create the space, make it as psychologically safe as you can for people to really, as Chris Argyris so beautifully articulated, discuss the undiscussable.

And so the conditions for that are going to look different in every organization depending on the problem, but if you can get a space where smart people who have direct experience of a problem are in a room and talking honestly with each other, you can make an extraordinary amount of progress, certainly in a day.

CURT NICKISCH: Yeah, that gets back to the trust piece.

ANNE MORRISS: Definitely.

CURT NICKISCH: How do you like to start that meeting, or how do you like to talk about it? I’m just curious what somebody on that team might hear in that meeting, just to get the sense that it’s psychologically safe, you can discuss the undiscussable and you’re also focusing on the identification part. What’s key to communicate there?

ANNE MORRISS: Yeah. Well, we sometimes encourage people to do a little bit of data gathering before those conversations. So the power of a quick anonymous survey around whatever problem you’re solving, but also be really thoughtful about the questions you’re going to ask in the moment. So a little bit of preparation can go a long way and a little bit of thoughtfulness about the power dynamic. So who’s going to walk in there with license to speak and who’s going to hold back? So being thoughtful about the agenda, about the questions you’re asking about the room, about the facilitation, and then courage is a very infectious emotion.

So if you can early on create the conditions for people to show up bravely in that conversation, then the chance that you’re going to get good information and that you’re going to walk out of that room with new insight in the problem that you didn’t have when you walked in is extraordinarily high.

CURT NICKISCH: Now, in those discussions, you may have people who have different perspectives on what the problem really is. They also bear different costs of addressing the problem or solving it. You talked about the power dynamic, but there’s also an unfairness dynamic of who’s going to actually have to do the work to take care of it, and I wonder how you create a culture in that meeting where it’s the most productive?

ANNE MORRISS: For sure, the burden of work is not going to be equitably distributed around the room. But I would say, Curt, the dynamic that we see most often is that people are deeply relieved that hard problems are being addressed. So it really can create, and more often than not in our experience, it does create this beautiful flywheel of action, creativity, optimism. Often when problems haven’t been addressed, there is a fair amount of anxiety in the organization, frustration, stagnation. And so credible movement towards action and progress is often the best antidote. So even if the plan isn’t super clear yet, if it’s credible, given who’s in the room and their decision rights and mandate, if there’s real momentum coming out of that to make progress, then that tends to be deeply energizing to people.

CURT NICKISCH: I wonder if there’s an organization that you’ve worked with that you could talk about how this rolled out and how this took shape?

ANNE MORRISS: When we started working with Uber, that was wrestling with some very public issues of culture and trust with a range of stakeholders internally, the organization, also external, that work really started with a campaign of listening and really trying to understand where trust was breaking down from the perspective of these stakeholders?

So whether it was female employees or regulators or riders who had safety concerns getting into the car with a stranger. This work, it starts with an honest internal dialogue, but often the problem has threads that go external. And so bringing that same commitment to curiosity and humility and dialogue to anyone who’s impacted by the problem is the fastest way to surface what’s really going on.

CURT NICKISCH: There’s a step in this process that you lay out and that’s communicating powerfully as a leader. So we’ve heard about listening and trust building, but now you’re talking about powerful communication. How do you do this and why is it maybe this step in the process rather than the first thing you do or the last thing you do?

ANNE MORRISS: So in our process, again, it’s the days of the week. On Monday you figured out the problem. Tuesday you really got into the sandbox in figuring out what a good enough plan is for building trust. Wednesday, step three, you made it better. You created an even better plan, bringing in new perspectives. Thursday, this fourth step is the day we’re saying you got to go get buy-in. You got to bring other people along. And again, this is a step where we see people often underinvest in the power and payoff of really executing it well.

CURT NICKISCH: How does that go wrong?

ANNE MORRISS: Yeah, people don’t know the why. Human behavior and the change in human behavior really depends on a strong why. It’s not just a selfish, “What’s in it for me?” Although that’s helpful, but where are we going? I may be invested in a status quo and I need to understand, okay, if you’re going to ask me to change, if you’re going to invite me into this uncomfortable place of doing things differently, why am I here? Help me understand it and articulate the way forward and language that not only I can understand, but also that’s going to be motivating to me.

CURT NICKISCH: And who on my team was part of this process and all that kind of stuff?

ANNE MORRISS: Oh, yeah. I may have some really important questions that may be in the way of my buy-in and commitment to this plan. So certainly creating a space where those questions can be addressed is essential. But what we found is that there is an architecture of a great change story, and it starts with honoring the past, honoring the starting place. Sometimes we’re so excited about the change and animated about the change that what has happened before or what is even happening in the present tense is low on our list of priorities.

Or we want to label it bad, because that’s the way we’ve thought about the change, but really pausing and honoring what came before you and all the reasonable decisions that led up to it, I think can be really helpful to getting people emotionally where you want them to be willing to be guided by you. Going back to Uber, when Dara Khosrowshahi came in.

CURT NICKISCH: This is the new CEO.

ANNE MORRISS: The new CEO.

CURT NICKISCH: Replaced Travis Kalanick, the founder and first CEO, yeah.

ANNE MORRISS: Yeah, and had his first all-hands meeting. One of his key messages, and this is a quote, was that he was going to retain the edge that had made Uber, “A force of nature.” And in that meeting, the crowd went wild because this is also a company that had been beaten up publicly for months and months and months, and it was a really powerful choice. And his predecessor, Travis was in the room, and he also honored Travis’ incredible work and investment in bringing the company to the place where it was.

And I would use words like grace to also describe those choices, but there’s also an incredible strategic value to naming the starting place for everybody in the room because in most cases, most people in that room played a role in getting to that starting place, and you’re acknowledging that.

CURT NICKISCH: You can call it grace. Somebody else might call it diplomatic or strategic. But yeah, I guess like it or not, it’s helpful to call out and honor the complexity of the way things have been done and also the change that’s happening.

ANNE MORRISS: Yeah, and the value. Sometimes honoring the past is also owning what didn’t work or what wasn’t working for stakeholders or segments of the employee team, and we see that around culture change. Sometimes you’ve got to acknowledge that it was not an equitable environment, but whatever the worker, everyone in that room is bringing that pass with them. So again, making it discussable and using it as the jumping off place is where we advise people to start.

Then you’ve earned the right to talk about the change mandate, which we suggest using clear and compelling language about the why. “This is what happened, this is where we are, this is the good and the bad of it, and here’s the case for change.”

And then the last part, which is to describe a rigorous and optimistic way forward. It’s a simple past, present, future arc, which will be familiar to human beings. We love stories as human beings. It’s among the most powerful currency we have to make sense of the world.

CURT NICKISCH: Yeah. Chronological is a pretty powerful order.

ANNE MORRISS: Right. But again, the change leaders we see really get it right, are investing an incredible amount of time into the storytelling part of their job. Ursula Burns, the Head of Xerox is famous for the months and years she spent on the road just telling the story of Xerox’s change, its pivot into services to everyone who would listen, and that was a huge part of her success.

CURT NICKISCH: So Friday or your fifth step, you end with empowering teams and removing roadblocks. That seems obvious, but it’s critical. Can you dig into that a little bit?

ANNE MORRISS: Yeah. Friday is the fun day. Friday’s the release of energy into the system. Again, you’ve now earned the right to go fast. You have a plan, you’re pretty confident it’s going to work. You’ve told the story of change the organization, and now you get to sprint. So this is about really executing with urgency, and it’s about a lot of the tactics of speed is where we focus in the book. So the tactics of empowerment, making tough strategic trade-offs so that your priorities are clear and clearly communicated, creating mechanisms to fast-track progress. At Etsy, CEO Josh Silverman, he labeled these projects ambulances. It’s an unfortunate metaphor, but it’s super memorable. These are the products that get to speed out in front of the other ones because the stakes are high and the clock is sticking.

CURT NICKISCH: You pull over and let it go by.

ANNE MORRISS: Yeah, exactly. And so we have to agree as an organization on how to do something like that. And so we see lots of great examples both in young organizations and big complex biotech companies with lots of regulatory guardrails have still found ways to do this gracefully.

And I think we end with this idea of conflict debt, which is a term we really love. Leanne Davey, who’s a team scholar and researcher, and anyone in a tech company will recognize the idea of tech debt, which is this weight the organization drags around until they resolve it. Conflict debt is a beautiful metaphor because it is this weight that we drag around and slows us down until we decide to clean it up and fix it. The organizations that are really getting speed right have figured out either formally or informally, how to create an environment where conflict and disagreements can be gracefully resolved.

CURT NICKISCH: Well, let’s talk about this speed more, right? Because I think this is one of those places that maybe people go wrong or take too long, and then you lose the awareness of the problem, you lose that urgency. And then that also just makes it less effective, right? It’s not just about getting the problem solved as quickly as possible. It’s also just speed in some ways helps solve the problem.

ANNE MORRISS: Oh, yeah. It really is the difference between imagining the change you want to lead and really being able to bring it to life. Speed is the thing that unlocks your ability to lead change. It needs a foundation, and that’s what Monday through Thursday is all about, steps one through four, but the finish line is executing with urgency, and it’s that urgency that releases the system’s energy, that communicates your priorities, that creates the conditions for your team to make progress.

CURT NICKISCH: Moving fast is something that entrepreneurs and tech companies certainly understand, but there’s also this awareness that with big companies, the bigger the organization, the harder it is to turn the aircraft carrier around, right? Is speed relative when you get at those levels, or do you think this is something that any company should be able to apply equally?

ANNE MORRISS: We think this applies to any company. The culture really lives at the level of team. So we believe you can make a tremendous amount of progress even within your circle of control as a team leader. I want to bring some humility to this and careful of words like universal, but we do think there’s some universal truths here around the value of speed, and then some of the byproducts like keeping fantastic people. Your best people want to solve problems, they want to execute, they want to make progress and speed, and the ability to do that is going to be a variable in their own equation of whether they stay or they go somewhere else where they can have an impact.

CURT NICKISCH: Right. They want to accomplish something before they go or before they retire or finish something out. And if you’re able to just bring more things on the horizon and have it not feel like it’s going to be another two years to do something meaningful.

ANNE MORRISS: People – I mean, they want to make stuff happen and they want to be around the energy and the vitality of making things happen, which again, is also a super infectious phenomenon. One of the most important jobs of a leader, we believe, is to set the metabolic pace of their teams and organizations. And so what we really dig into on Friday is, well, what does that look like to speed something up? What are the tactics of that?

CURT NICKISCH: I wonder if that universal truth, that a body in motion stays in motion applies to organizations, right? If an organization in motion stays in motion, there is something to that.

ANNE MORRISS: Absolutely.

CURT NICKISCH: Do you have a favorite client story to share, just where you saw speed just become a bit of a flywheel or just a positive reinforcement loop for more positive change at the organization?

ANNE MORRISS: Yeah. We work with a fair number of organizations that are on fire. We do a fair amount of firefighting, but we also less dramatically do a lot of fire prevention. So we’re brought into organizations that are working well and want to get better, looking out on the horizon. That work is super gratifying, and there is always a component of, well, how do we speed this up?

What I love about that work is there’s often already a high foundation of trust, and so it’s, well, how do we maintain that foundation but move this flywheel, as you said, even faster? And it’s really energizing because often there’s a lot of pent-up energy that… There’s a lot of loyalty to the organization, but often it’s also frustration and pent-up energy. And so when that gets released, when good people get the opportunity to sprint for the first time in a little while, it’s incredibly energizing, not just for us, but for the whole organization.

CURT NICKISCH: Anne, this is great. I think finding a way to solve problems better but also faster is going to be really helpful. So thanks for coming on the show to talk about it.

ANNE MORRISS:  Oh, Curt, it was such a pleasure. This is my favorite conversation. I’m delighted to have it anytime.

HANNAH BATES: That was entrepreneur, leadership coach, and author Anne Morriss – in conversation with Curt Nickisch on HBR IdeaCast.

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• J Microbiol Biol Educ
• v.19(3); 2018

A Systematic Approach to Teaching Case Studies and Solving Novel Problems †

Carolyn a. meyer.

1 Department of Biomedical Sciences, Colorado State University, Fort Collins, CO 80523

Heather Hall

Natascha heise, karen kaminski.

2 School of Education, Colorado State University, Fort Collins, CO 80523

Kenneth R. Ivie

Tod r. clapp, associated data.

Both research and practical experience in education support the use of case studies in the classroom to engage students and develop critical thinking skills. In particular, working through case studies in scientific disciplines encourages students to incorporate knowledge from a variety of backgrounds and apply a breadth of information. While it is recognized that critical thinking is important for student success in professional school and future careers, a specific strategy to tackle a novel problem is lacking in student training. We have developed a four-step systematic approach to solving case studies that improves student confidence and provides them with a definitive road map that is useful when solving any novel problem, both in and out of the classroom. This approach encourages students to define unfamiliar terms, create a timeline, describe the systems involved, and identify any unique features. This method allows students to solve complex problems by organizing and applying information in a logical progression. We have incorporated case studies in anatomy and neuroanatomy courses and are confident that this systematic approach will translate well to courses in various scientific disciplines.

INTRODUCTION

There is increasing emphasis in pedagogical research on encouraging critical thinking in the classroom. The specific mental processes and behaviors involved require the individual to engage in reflective and purposeful thinking. Critical thinking encompasses the ability to examine ideas, make decisions, and solve problems ( 1 , 2 ). The skills necessary to think critically are essential for learners to evaluate multiple perspectives and solve novel problems in the classroom and throughout life. Career success in the 21st century requires a complex set of workforce skills. Current labor market assessments indicate that by the year 2020, the majority of occupations will require workers to display cognitive skills such as active listening, critical thinking, and decision making ( 3 , 4 ). In particular, current studies show that the US economy is impacted by a deficit of skilled workers able to solve problems and transfer learning to any unique situation ( 3 ).

The critical thinking skills necessary to tackle novel problems can best be addressed in higher education institutions ( 5 , 6 ). Throughout education, and specifically in college courses, students tend to be required to regurgitate knowledge through a myriad of multiple-choice exams. Breaking this habit and incorporating critical thinking can be difficult for students. While the ability to recite information is helpful for establishing base knowledge, it does not prepare students to tackle novel problems. Ideally, the objective of any course is to encourage students to move beyond recognition of knowledge into its application ( 7 ). Considering this, the importance of critical thinking is widely accepted; however, there has been some debate in educational research regarding how to teach these skills ( 8 ). Research has demonstrated that students show significant improvements in critical thinking as a result of explicit methods of instruction in related skills ( 9 , 10 ). Explicit instruction provides a protocol on how to approach a problem. By establishing the necessary framework to work through unfamiliar details, we enable students to independently solve complex problems.

These skills, which are important in every facet of the workforce, are vital for students in the sciences ( 10 , 11 ). Here, we discuss a specific process that teaches students a systematic approach to solving case studies in the anatomical sciences. Case studies are a popular method to encourage critical thinking and engage students in the learning process ( 12 ). While the examples described here are specifically designed to be implemented in anatomy and neuroanatomy courses, this platform lends itself to teaching critical thinking skills across scientific disciplines. This four-step approach encourages students to work through four separate facets of a problem:

• Define unfamiliar terms
• Create a timeline associated with the problem
• Describe the (anatomical) systems involved
• Identify any unique features associated with the case

Often, students start by trying to plug in memorized facts to answer a complicated question quickly. With the four-step approach, students learn that before “solving” the case study, they must analyze the information presented in the case. The case studies implemented are anatomically-based case studies that emphasize important structural relationships. The case may include terminology with which the students are not familiar. They therefore begin by identifying and defining unfamiliar terms. They then specify the timeline in which the problem occurred. Establishing a timeline and narrowing the focus can be critical when considering the relevant pathology. Students must then describe the anatomical systems involved (e.g., musculoskeletal or circulatory), and finally list any additional unique features of the case (e.g., lateral leg was struck or patient could not abduct the right eye). By dissecting the details along the lines of these four categories, students create a clear roadmap to approach the problem. Case studies with a clinical focus are complex and can be overwhelming for unpracticed students. However, teaching students to follow this systematic approach gives them the tools to begin to carefully dismantle even the most convoluted problem.

Intended audience

This approach to solving case studies has been applied in undergraduate courses, specifically in the sciences. This curriculum is currently utilized in both human gross anatomy and functional neuroanatomy capstone courses. While it is ideal to implement this process in a course that runs in parallel with a lecture-heavy course, it can also be utilized with case studies in a typical lecture class.

Anatomy-based case studies lend themselves well to this problem-solving approach due to the complexities of clinical problems. However, we believe with an appropriately designed case study, this model of teaching critical thinking can easily be expanded to any discipline. This activity encourages critical thinking and engages students in the learning process, which we believe will better prepare them for professional school and careers in the sciences.

Prerequisite student knowledge

Required previous student knowledge only extends to that which students learn through the related course taken previously or concurrently. Application of this approach in different classroom settings only requires that students have a basic understanding of the material needed to solve the case study. As such, the case study problem and questions should be built around current topics being studied in the classroom.

Using unfamiliar words teaches students to identify important information. This encourages integration of information and terminology, which can be critical for understanding anatomy. Simple terms, like superficial or deep, guide discussions about anatomical relationships. While students may be able to recite the definitions of these concepts, applying that information to a case study requires integrating the basic definition with an understanding of the relevant anatomy. Specific prerequisite knowledge for the sample case study is detailed in Appendix 1 .

Learning time

This process needs to be learned and practiced over the course of a semester to ensure long-term retention. With structured and guided attempts, students will be able to implement this approach to solving case studies in one 50-minute class period ( Table 1 ). The course described in this study is a capstone course that meets once weekly. Each 50-minute class period centers around working through a case study. As some class sessions are reserved for other activities, students complete approximately 10 case studies during the semester. Students begin to show increased confidence with this method within a few weeks and ultimately are able to integrate this approach into their critical thinking skillset by the end of the semester. Presentation of the case study, individual or small group work, and class discussion are all achieved in one standard class session ( Table 1 ). The current model does not require student work prior to the class meeting. However, because this course is taken concurrently with a related, content-heavy lecture component, students are expected to be up to date on relevant material. Presenting the case study in class to their peers encourages students to work through the systematic approach we describe here. Each case study is designed to correlate with current topics from the lecture-based course. Following the class period, students are expected to complete a written summary of the discussed case study. The written summary should include a detailed explanation of the approach they utilized to solve the problem, as well as a definitive solution. Written summaries are to be completed two days after the original class period.

Anticipated in-class time to implement this model.

Learning objectives

This model for teaching a systematic approach to solving case studies provides a framework to teach students how to think critically and how to become engaged learners when given a novel problem. By mastering this technique, students will be able to:

• Recognize words and concepts that need to be defined before solving a novel problem
• Recall, interpret, and apply previous knowledge as it relates to larger anatomical concepts
• Construct questions that guide them through which systems are affected, the timeline of the pathologies, and what is unique about the case
• Formulate and justify a hypothesis both verbally and in writing

As a faculty member, it can be challenging to create appropriate case studies when developing this model for use in a specific classroom. There are resources that provide case studies and examples that can be tailored to specific classroom needs. The National Center for Case Study Teaching in Science (University at Buffalo) can be a useful tool. The ultimate goal of this model is to teach an approach to problem solving, and a properly designed case study is crucial to success. To build an effective case study, faculty must include sufficient information to provide students with enough base knowledge to begin to tackle the problem. This model is ideal in a course that pairs with a lecture-heavy component, utilized in either a supplementary course or during a recitation. The case study should be complex and not quickly solved. An example of a simplified case study utilized in Human Gross Anatomy is detailed in Appendix 1 .

This particular case study encourages students to think through the anatomy of the lateral knee, relevant structures in this area, and which muscle compartments may be affected based on movement disabilities within the case. While more complex case studies can certainly be developed for the Neuroanatomy course through Clinical Case Studies, this case study provides a good example of a problem to which students cannot immediately provide the answer. They must think critically through the four-step process to identify the “diagnosis” for this patient.

This approach to solving case studies can be integrated into the classroom with no special materials. However, we use a Power-Point presentation and personal whiteboards (2.5’ × 2’) to both improve delivery of the case study and facilitate small group discussion, respectively. The Power-Point presentation is utilized by faculty to assist in leading the classroom discussion, prompting student responses and projecting relevant images. As the faculty member is presenting the case study during the first five minutes of class ( Table 1 ), the wording of the case study can be displayed on the PowerPoint slide as a reference while students take notes.

Faculty instructions

It is helpful to first present an overview of the approach and to solve a case study together as a class. We recommend giving students a lecture describing the benefits of a systematic approach to case studies and emphasizing the four-step approach outlined in this paper. Following this lecture, it is imperative that faculty walk the students through the first case study. This helps to familiarize students with the approach and lays out expectations on how to break down the individual components of the case. During the initial case study, faculty must heavily moderate the discussion, leading students through each step of the approach using the provided Case Study Handout ( Appendix 2 ). In subsequent weeks, students can be expected to show increasing independence.

Following initial presentation of the case study in class, students begin work that is largely independent or done in small groups. This discussion has no grades assigned. However, following the in-class discussion and small group work, students are asked to detail their approach to solving the case study and their efforts are graded according to a set rubric ( Appendix 3 ). This written report should document each step of their thought process and detail the questions they asked to reach the final answer, providing students with a chance for continual self-evaluation on their mastery of the method.

Implementing this model in the classroom should focus not only on the individual student approach, but also on creating an encouraging classroom environment and promoting student participation. Student questions may prompt other student questions, leading to an engaging discussion-based presentation of the case study, which is crucial to increasing confidence among students, as has been seen with the data represented in this paper. When moderating the discussion, it is important that faculty emphasize to students that the most critical goal of the exercise is to learn how to ask the next most appropriate question. The questions should begin with broad concepts and evolve to discussing specific details. Efforts to quickly arrive at the answer should be discouraged.

Students should be randomly assigned to groups of two to three individuals as faculty members moderate small group discussion during class. Randomly assigning students to different groups each week encourages interaction between all students in the class and promotes a collaborative environment. Within their small groups, students should work through the systematic four-step process for solving a novel problem. Students are not assigned specific roles within the group. However, all group members are expected to contribute equally. During this process, it can be beneficial to provide students with a template to follow ( Appendix 2 ). This template guides their discussion and encourages them to use the four-step process. Additionally, each small group is given a white board that they can use to facilitate their small group discussions. Specifically, asking students to write down details of each of the four facets of the problem (definitions, timeline, systems involved, unique features) and how they arrived at these encourages them to commit to their answers. This also ensures they have concrete evidence to support their “diagnosis” and that they have confidence in presenting it to the class. Two or three small groups are chosen randomly each week to present their hypothesis to the class using their whiteboard.

Suggestions for determining student learning

The cadence of the in-class discussion can provide an informal gauge of how students are progressing with their ability to apply the systematic approach. The discussion for the initial case studies should be largely faculty led. Then, as the semester progresses, faculty should step back into a facilitator role, allowing the dialogue to be carried by the students.

Additionally, requiring students to write a detailed summary of their approach to the problem provides a strong measure of student learning. While it is important for students to document their final “diagnosis” or solution to the problem, the focus of this assignment is primarily on the process and the series of relevant questions the student used to arrive at the answer. These assignments are graded according to a set rubric ( Appendix 3 ).

Sample data

The following excerpt is from a student who showed marked improvement over the course of the semester in implementing this approach to solving case studies. The initial submission for the case study write-up was rudimentary, did not document the thought process through appropriate questions, and lacked an in-depth explanation to demonstrate any critical thinking. By the end of the semester, this student documented a logical thought progression through this four-step approach to solving the case study. This student, additionally, detailed the questions that led each stage of critical thinking until a “diagnosis” was reached (complete sample data are available in Appendix 4 ).

Initial sample

“Given loss of sensory and motor input to left lower limb, right anterior cerebral artery ischemia caused the sensory and motor cortices of the contralateral (left) lower limb to be without blood flow for a short amount of time (last night). The lack of flow led to a fast onset of motor and sensory paresis to limb.”

Final sample

“…the left vestibular nuclei which explains the nystagmus, and the left cerebellar peduncles which carry information that aids in coordinating intention movements. My next question was where in the brainstem are all of these components located together? I narrowed this to the left caudal pons. Finally, I asked which artery supplies the area that was damaged by the lesion? This would be the left anterior inferior cerebellar artery.”

Safety issues

There are no known safety issues associated with implementing this approach to solving case studies.

The primary goal of the model discussed here is to give students a method that uses critical reasoning and helps them incorporate facts into a complete story to solve case studies. We believe that this model addresses the need for teaching the specific skill set necessary to develop critical thinking and engage students in the learning process. By encouraging critical thinking, we begin to redirect the tendency to simply recite a memorized answer. This four-step approach to solving case studies is ideal for the college classroom, as it is easily implemented, requires minimal resources, and is simple enough that students demonstrate mastery within one semester. While it was designed to be used in anatomy and neuroanatomy courses, this platform can be used across scientific disciplines. Outside of the classroom, in professional school and future careers, this approach can help students to break down the details, ask appropriate questions, and ultimately solve any complex, novel problem.

Field testing

This model has been implemented in several courses in both undergraduate and graduate settings. The data and approach detailed here are specific to an undergraduate senior capstone course with approximately 25 students. The lecture-based course, which is required to be taken concurrently or as a prerequisite, provides a strong base of information from which faculty can develop complex case studies.

Evidence of student learning

Student performance on written case study summaries improved over approximately ten weeks of practicing the systematic four-step approach ( Fig. 1 ). As indicated by the data, scores improve and begin to plateau around five weeks, indicating a mastery of the approach. In the spring 2016 semester, a marked drop in scores was observed at week 8. We believe that this reflects a particularly difficult case study that was assigned that week. After observing the overall trend in scores, instructional format was adjusted to provide students with more guidance as they worked through this particular case study.

Grade performance in case study written summaries as measured with the grading rubric throughout the semester. A) Mean (with SD) grade performance in case study write-ups in the spring semester of 2016. B) Mean (with SD) grade performance in case study write-ups in the spring semester of 2017. Overall grade performance in case study written summaries improved throughout the 10 weeks in which this method was implemented in the classroom. Written summaries are graded based on a set rubric ( Appendix 3 ) that assigned a score between 0 and 1 for five different categories. Data represent the mean of students’ scores and the associated standard deviation. Improved student performance throughout the semester indicates progress in successful incorporation of this method to solve a complex novel problem.

After the class session, students were asked to provide a written summary of their findings. A set rubric ( Appendix 3 ) was used to assess students on their ability to apply basic anatomical knowledge as it relates to the timeline, systems involved, and what is unique in each case study. Students were also asked to describe the questions that they had asked in order to reach a diagnosis for the case study. The questions formulated by students indicate their ability to bring together previous knowledge to larger anatomical concepts. In this written summary, students were also required to justify the answer they arrived at in each step of the process. In addition to these four steps, students were assessed on the organization of their paper and whether their diagnosis is well supported.

Although class participation was not formally assessed, the improvements demonstrated in the written assignments were mirrored in student discussions in the classroom. While it is difficult to accurately assess how well students think critically, students demonstrated success in learning this module, which provides the necessary framework for approaching and solving a novel problem.

Student perceptions

Students were asked to answer the open response question, “Describe the process you use to figure out a novel problem or case study.” Responses were anonymized, then coded based on frequency of responses. Responses were collected at the start of the semester, prior to any instruction in the described systematic approach, and again at the end of the semester ( Figs. 2 and ​ and3). 3 ). Overall, student comments indicated that mastering this four-step approach greatly increased their confidence in tackling a novel problem. Below are some sample student responses.

Student responses to a survey regarding their approach to solving a novel problem. Data were collected prior to and following the completion of the spring semester of 2016. A) Student approach to solving a novel problem at the beginning of the semester. B) Student approach to solving a novel problem at the end of the semester. Student responses indicate that following a semester of training in using this method, students prefer to use this four-step systematic approach to solve a novel problem.

Student responses to a survey regarding their approach to solving a novel problem. Data were collected prior to and following the completion of spring semester of 2017. A) Student approach to solving a novel problem at the beginning of the semester. B) Student approach to solving a novel problem at the end of the semester. Student responses indicate that students overwhelmingly utilize this systematic approach when solving a novel problem.

“Rather than being intimidated with a set of symptoms I can’t explain, I’m now able to break them down into simpler questions that will lead me down a path of understanding and accurate explanation.” “I now know how to address an exam question or life problem by considering what is needed to solve it. This knowledge will help me to address each problem efficiently and calmly. As a future nurse, I will benefit from developing a logical and stereotypical approach to solving problems. I have learned to assess my thinking and questioning and modify my approach to problem-solving. While the problems may be different in the future, I am confident that I will be able to efficiently learn from my successes and setbacks and continually improve.” “I’m sure I’ll use this approach when I’m faced with any other novel problem, whether it’s scientific or not. Stepping back and establishing what I know and what I need to find out makes difficult problems a lot more approachable.” “Before, I would look at all the information presented and try to find things that I recognized. Then I would simply ask myself if I knew the answer. Even if I did actually know the answer, I had no formula to make the information understandable, cohesive, or approachable. I now feel far more confident when dealing with novel problems and do not become immediately overwhelmed.”

This approach encourages students to quickly sort through a large amount of information and think critically. Although students can find the novel nature of this method cumbersome in the initial implementation in the classroom, once they become familiar with the approach, it provides a valuable platform for attacking any novel problem in the future. The ability to apply this approach to critical thinking in any discipline was also demonstrated, as is evidenced by the two following student responses.

“When I first thought about this question and when solving case studies I tried to find the answer immediately. I’m good at memorizing information and spitting it back out but not working through an issue and having a method. I definitely have a more successful way to think through complex problems and being patient and coming up with an answer.” “I already use it in many of my other classes and life cases. When I take an exam that is asking a complicated question or is in a long format, I work to break it down like I did in this class and try to find the base question and what the answer may be. It has actually helped significantly.”

Possible modifications

Currently, students are randomly assigned to groups each week. In future semesters, we could improve small group work by utilizing software that helps to identify individual student strengths and assign groups accordingly. Additionally, while students are given flexibility within their small groups, if groups struggle with equality of workload we could assign specific roles and tasks.

We are also using this model in a large class (100 students) and assessing understanding of the case study through instant student response questions (ICLICKER). While this model does not allow for the valuable in-depth classroom discussions, it still presents the approach to students and allows them to begin to implement it in solving complex problems. Preliminary data from these large classes indicate that students initially find the method difficult and cumbersome. Further development and testing of this model in a large classroom will improve its use for future semesters.

SUPPLEMENTAL MATERIALS

Appendix 1: sample case study, appendix 2: case study handout, appendix 3: case study grading rubric, appendix 4: student writing sample, acknowledgments.

Use of anonymized student data and student responses to surveys was approved by the Institutional Review Board at Colorado State University. The authors declare that there are no conflicts of interest.

† Supplemental materials available at http://asmscience.org/jmbe

• Spencer Greenberg
• 14 min read

Problem-Solving Techniques That Work For All Types of Challenges

Essay by Spencer Greenberg, Clearer Thinking founder

A lot of people don’t realize that there are general purpose problem solving techniques that cut across domains. They can help you deal with thorny challenges in work, your personal life, startups, or even if you’re trying to prove a new theorem in math.

Below are the 26 general purpose problem solving techniques that I like best, along with a one-word name I picked for each, and hypothetical examples to illustrate what sort of strategy I’m referring to.

Consider opening up this list whenever you’re stuck solving a challenging problem. It’s likely that one or more of these techniques can help!

1. Clarifying

Try to define the problem you are facing as precisely as you can, maybe by writing down a detailed description of exactly what the problem is and what constraints exist for a solution, or by describing it in detail to another person. This may lead to you realizing the problem is not quite what you had thought, or that it has a more obvious solution than you thought.

Life Example

“I thought that I needed to find a new job, but when I thought really carefully about what I don’t like about my current job, I realized that I could likely fix those things by talking to my boss or even, potentially, just by thinking about them differently.”

Startup Example

“we thought we had a problem with users not wanting to sign up for the product, but when we carefully investigated what the problem really was, we discovered it was actually more of a problem of users wanting the product but then growing frustrated because of bad interface design.”

2. Subdividing

Break the problem down into smaller problems in such a way that if you solve each of the small problems, you will have solved the entire problem. Once a problem is subdivided it can also sometimes be parallelized (e.g., by involving different people to work on the different components).

“My goal is to get company Z to become a partner with my company, and that seems hard, so let me break that goal into the steps of (a) listing the ways that company Z would benefit from becoming a partner with us, (b) finding an employee at company Z who would be responsive to hearing about these benefits, and (c) tracking down someone who can introduce me to that employee.”

Math Example

“I want to prove that a certain property applies to all functions of a specific type, so I start by (a) showing that every function of that type can be written as a sum of a more specific type of function, then I show that (b) the property applies to each function of the more specific type, and finally I show that (c) if the property applies to each function in a set of functions then it applies to arbitrary sums of those functions as well.”

3. Simplifying

Think of the simplest variation of the problem that you expect you can solve that shares important features in common with your problem, and see if solving this simpler problem gives you ideas for how to solve the more difficult version.

“I don’t know how to hire a CTO, but I do know how to hire a software engineer because I’ve done it many times, and good CTOs will often themselves be good software engineers, so how can I tweak my software engineer hiring to make it appropriate for hiring a CTO?”

“I don’t know how to calculate this integral as it is, but if I remove one of the free parameters, I actually do know how to calculate it, and maybe doing that calculation will give me insight into the solution of the more complex integral.”

4. Crowd-sourcing 

Use suggestions from multiple people to gain insight into how to solve the problem, for instance by posting on Facebook or Twitter requesting people’s help, or by posting to a Q&A site like Quora, or by sending emails to 10 people you know explaining the problem and requesting assistance.

Business Example

“Do you have experience outsourcing manufacturing to China? If so, I’d appreciate hearing your thoughts about how to approach choosing a vendor.”

Health Example

“I have trouble getting myself to stick to doing exercise daily. If you also used to have trouble getting yourself to exercise but don’t anymore, I’d love to know what worked to make it easier for you.”

5. Splintering

If the problem you are trying to solve has special cases that a solution to the general problem would also apply to, consider just one or two of these special cases as examples and solve the problem just for those cases first. Then see if a solution to one of those special cases helps you solve the problem in general.

“I want to figure out how to improve employee retention in general, let me examine how I could have improved retention in the case of the last three people that quit.”

“I want to figure out how to convince a large number of people to become customers, let me first figure out how to convince just Bill and John to become customers since they seem like the sort of customer I want to attract, and see what general lessons I learn from doing that.”

Read the books or textbooks that seem most related to the topic, and see whether they provide a solution to the problem, or teach you enough related information that you can now solve it yourself.

Economics Example

“Economists probably have already figured out reasonable ways to estimate demand elasticity, let’s see what an econometrics textbook says rather than trying to invent a technique from scratch.”

Mental Health Example

“I’ve been feeling depressed for a long time, maybe I should read some well-liked books about depression.”

7. Searching

Think of a similar problem that you think practitioners, bloggers or academics might have already solved and search online (e.g., via google, Q&A sites, or google scholar academic paper search) to see if anyone has done a write-up about how they solved it.

Advertising Example

“I’m having trouble figuring out the right advertising keywords to bid on for my specific product, I bet someone has a blog post describing how to approach choosing keywords for other related products.”

Machine Learning Example

“I can’t get this neural network to train properly in my specific case, I wonder if someone has written a tutorial about how to apply neural networks to related problems.”

8. Unconstraining

List all the constraints of the problem, then temporarily ignore one or more of the constraints that make the problem especially hard, and try to solve it without those constraints. If you can, then see if you can modify that unconstrained solution until it becomes a solution for the fully constrained problem.

“I need to hire someone who can do work at the intersection of machine learning and cryptography, let me drop the constraint of having cryptography experience and recruit machine learning people, then pick from among them a person that seems both generally capable and well positioned to learn the necessary cryptography.”

Computer Science Example

“I need to implement a certain algorithm, and it needs to be efficient, but that seems very difficult, so let me first figure out how to implement an inefficient version of the algorithm (i.e., drop the efficiency constraint), then at the end I will try to figure out how to optimize that algorithm for efficiency.”

9. Distracting

Fill your mind with everything you know about the problem, including facts, constraints, challenges, considerations, etc. and then stop thinking about the problem, and go and do a relaxing activity that requires little focus, such as walking, swimming, cooking, napping or taking a bath to see if new ideas or potential solutions pop into your mind unexpectedly as your subconscious continues to work on the problem without your attention.

“For three days, I’ve been trying to solve this problem at work, but the solution only came to me when I was strolling in the woods and not even thinking about it.”

Example from mathematician Henri Poincaré

“The incidents of the travel made me forget my mathematical work. Having reached Coutances, we entered an omnibus to go someplace or other. At the moment when I put my foot on the step, the idea came to me, without anything in my former thoughts seeming to have paved the way for it, that the transformations I had used to define the Fuchsian functions were identical with those of non-Euclidean geometry.”

10. Reexamining

Write down all the assumptions you’ve been making about the problem or about what a solution should I look like (yes – make an actual list). Then start challenging them one by one to see if they are actually needed or whether some may be unnecessary or mistaken.

Psychology Example

“We were assuming in our lab experiments that when people get angry they have some underlying reason behind it, but there may be some anger that is better modeled as a chemical fluctuation that is only loosely related to what happens in the lab, such as when people are quick to anger because they are hungry.”

“I need to construct a function that has this strange property, and so far I’ve assumed that the function must be smooth, but if it doesn’t actually need to be then perhaps I can construct just such a function out of simple linear pieces that are glued together.”

11. Reframing

Try to see the problem differently. For instance, by flipping the default, analyzing the inverse of the problem instead, thinking about how you would achieve the opposite of what you want, or shifting to an opposing perspective.

If we were building this company over again completely from scratch, what would we do differently in the design of our product, and can we pivot the product in that direction right now?”

“Should move to New York to take a job that pays $20,000 more per year? Well, if I already lived in New York, the decision to stay there rather than taking a $20,000 pay cut to move here would be an easy one. So maybe I’m overly focused on the current default of not being in New York and the short term unpleasantness of relocating.”

Marketing Example

“If I were one of our typical potential customers, what would I do to try to find a product like ours?”

12. Brainstorming

Set a timer for at least 5 minutes, and generate as many plausible solutions or ideas that you can without worrying about quality at all. Evaluate the ideas only at the end after the timer goes off.

“I’m going to set a timer for 5 minutes and come up with at least three new ways I could go about looking for a co-founder.”

“I’m going to set a timer for 20 minutes and come up with at least five possible explanations for why I’ve been feeling so anxious lately.”

13. Experting

Find an expert (or someone highly knowledgeable) in the topic area and ask their opinion about the best way to solve the problem.

“Why do you think most attempts at creating digital medical records failed, and what would someone have to do differently to have a reasonable chance at success?”

“What sort of optimization algorithm would be most efficient for minimizing the objective functions of this type?”

14. Eggheading

Ask the smartest person you know how they would solve the problem. Be sure to send an email in advance, describing the details so that this person has time to deeply consider the problem before you discuss it.

“Given the information I sent you about our competitors and the interviews we’ve done with potential customers, in which direction would you pivot our product if you were me (and why)?”

Research Example

“Given the information I sent you about our goals and the fact that our previous research attempts have gotten nowhere, how would you approach researching this topic to find the answer we need?”

15. Guessing

Start with a guess for what the solution could be, now check if it actually works and if not, start tweaking that guess to see if you can morph it into something that could work.

“I don’t know what price to use for the product we’re selling, so let me start with an initial guess and then begin trying to sell the thing, and tweak the price down if it seems to be a sticking point for customers, and tweak the price up if the customers don’t seem to pay much attention to the price.”

“My off the cuff intuition says that this differential equation might have a solution of the form x^a * e^(b x)for some a or b, let me plug it into the equation to see if indeed it satisfies the equation for any choice of a and b, and if not, let me see if I can tweak it to make something similar work.”

“I don’t know what the most effective diet for me would be, so I’ll just use my intuition to ban from my diet some foods that seem both unhealthy and addictive, and see if that helps.”

16. Comparing

Think of similar domains you already understand or similar problems you have already solved in the past, and see whether your knowledge of those domains or solutions to those similar problems may work as a complete or partial solution here.

“I don’t know how to find someone to fix things in my apartment, but I have found a good house cleaner before by asking a few friends who they use, so maybe I can simply use the same approach for finding a person to fix things.”

“This equation I’m trying to simplify reminds me of work I’m familiar with related to Kullback-Leibler divergence, I wonder if results from information theory could be applied in this case.”

17. Outsourcing

Consider whether you can hire someone to solve this problem, instead of figuring out how to solve it yourself.

“I don’t really understand how to get media attention for my company, so let me hire a public relations firm and let them handle the process.”

“I have no fashion sense, but I’d like to look better. Maybe I should hire someone fashionable who works in apparel to go shopping with me and help me choose what I should wear.”

18. Experimenting

Rapidly develop possible solutions and test them out (in sequence, or in parallel) by applying cheap and fast experiments. Discard those that don’t work, or iterate on them to improve them based on what you learn from the experiments.

“We don’t know if people will like a product like the one we have in mind, but we can put together a functioning prototype quickly, show five people that seem like they could be potential users, and iterate or create an entirely new design based on how they respond.”

“I don’t know if cutting out sugar will help improve my energy levels, but I can try it for two weeks and see if I notice any differences.”

19. Generalizing

Consider the more general case of the specific problem you are trying to solve, and then work on solving the general version instead. Paradoxically, it is sometimes easier to make progress on the general case rather than a specific one because it increases your focus on the structure of the problem rather than unimportant details.

“I want to figure out how to get this particular key employee more motivated to do good work, let me construct a model of what makes employees motivated to do good work in general, then I’ll apply it to this case.”

“I want to solve this specific differential equation, but it’s clearly a special case of a more general class of differential equations, let me study the general class and see what I can learn about them first and then apply what I learn to the specific case.”

20. Approximating

Consider whether a partial or approximate solution would be acceptable and, if so, aim for that instead of a full or exact solution.

“Our goal is to figure out which truck to send out for which delivery, which theoretically depends on many factors such as current location, traffic conditions, truck capacity, fuel efficiency, how many hours the driver has been on duty, the number of people manning each truck, the hourly rate we pay each driver, etc. etc. Maybe if we focus on just the three variables that we think are most important, we can find a good enough solution.”

“Finding a solution to this equation seems difficult, but if I approximate one of the terms linearly it becomes much easier, and maybe for the range of values we’re interested in, that’s close enough to an exact solution!”

21. Annihilating

Try to prove that the problem you are attempting to solve is actually impossible. If you succeed, you may save yourself a lot of time working on something impossible. Furthermore, in attempting to prove that the problem is impossible, you may gain insight into what makes it actually possible to solve, or if it turns out to truly be impossible, figure out how you could tweak the problem to make it solvable.

“I’m struggling to find a design for a theoretical voting system that has properties X, Y, and Z, let me see if I can instead prove that no such voting system with these three properties could possibly exist.”

“My goal has been to prove that this property always applies to this class of functions, let me see if I can generate a counterexample to prove that this goal is actually impossible.”

Physics Example

“I was trying to design a physical system with certain properties, but I now realize that if such a system could be realized, then it would allow for perpetual motion, and therefore it is impossible to build the sort of system I had in mind.”

22. Modeling

Try to build an explicit model of the situation, including what elements there are and how they related to each other. For instance, try drawing a diagram or flow chart that encapsulates your understanding of all the important information that relates to the problem.

“I’ve noticed that there are certain situations that cause me to freak out that would not bother other people. So what are the common elements when this happens, and how do they seem to relate to each other and to the way I end up feeling? Let me see if I can draw a diagram of this on paper.”

“What are all the different groups (e.g., providers, payers, patients) involved in the healthcare system, and if we diagram how they interact with each other, will that give us ideas for how we can sell our healthcare product?”

23. Brute forcing

One-by-one, consider every possible solution to the problem until you’ve found a good one or exhausted them all.

Startup example

“We’re not sure the order that these four parts of the user registration process should go in, so let’s make a list of all 24 possible orderings, and examine them one by one to see which makes the most sense.”

“It’s not clear how to pick which of these machine learning methods to use on this problem, but since we have lots of data, we can just try each of the algorithms and see which makes the most accurate predictions on data we’ve held to the side for testing.”

24. Refocusing

Forget about trying to solve the problem, and instead consider why you are trying to solve it. Then consider if there is a different problem you can work on that is aimed at producing the same sort of value in a different way.

Startup Example 1

“Maybe instead of trying increasingly hard to figure out how to get this type of consumer to buy, we need to switch our focus to the problem of how to sell to businesses, since what we actually care about is selling it, not selling it to one particular group.”

Startup Example 2

“I’ve been banging my head against the wall trying to implement this extremely complex feature, but there are lots of features that users would find just as valuable that are much easier to implement, maybe I should focus on those instead.”

25. Sidestepping

Consider whether you really want to spend more time trying to solve this problem and whether you can avoid the problem by instead working on totally different problems that you also care about.

“We’ve tried selling our solution to replace Excel for 12 months without much success, maybe we should go back to the drawing board and consider designing a totally new product. Our assumptions about customer needs seem to simply have been wrong.”

“I’ve spent six months on this math problem with little progress, but there are two other math problems I’m equally excited about, so maybe I should spend some time investigating whether one of those may be more tractable.”

26. Aggregating

Consider whether multiple problems you’re now experiencing might, in fact, be caused by the same source of difficulty, rather than being independent problems.

“I seem to be having conflict with a few different friends right now – could it be that I’m doing something without realizing it that is increasing my chance of conflict with all of them?”

“Three employees have quit in the last month. Perhaps the primary problem isn’t really about convincing this one important employee to stay, which is how I was framing it, but rather, about identifying why people keep leaving more generally.”

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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• Mastering Prolog for Engineering Problem-Solving: A Comprehensive Guide

Solving Complex Engineering Problems with Prolog: A Student's Guide

In the dynamic landscape of engineering, the ability to efficiently address complex problems is a hallmark of success for professionals. Imagine a scenario where engineers are tasked with designing a state-of-the-art system, navigating a labyrinth of intricacies and interdependencies. It is precisely in these challenging situations that Prolog, a declarative programming language celebrated for its prowess in handling complex logic, emerges as an indispensable tool for students. This comprehensive guide takes you on a journey, exploring the multifaceted ways in which students can harness the capabilities of Prolog to dissect and conquer the intricate challenges inherent in engineering problems. As we delve into its applications, Prolog becomes more than just a programming language; it transforms into a strategic companion, empowering students to unravel the complexities of real-world engineering scenarios and gain a profound understanding of their applications. Whether modeling logic-based systems, optimizing solutions for maximum efficiency, or navigating constraint satisfaction problems, Prolog proves to be a versatile and indispensable asset. This guide not only equips students with the technical skills needed to leverage Prolog effectively but also fosters a mindset that embraces the power of logical reasoning and declarative problem-solving – essential attributes for success in the ever-evolving field of engineering. If you need help with your Prolog assignment , this guide is here to provide the support and insights necessary for mastering this powerful tool.

Understanding Prolog Basics

Embarking on the journey of utilizing Prolog for engineering problem-solving necessitates a foundational comprehension of its fundamental principles. Prolog, derived from "Programming in Logic," stands as a high-level programming language meticulously crafted for symbolic reasoning and manipulation. Its strength lies in its unique ability to adeptly represent and solve problems entwined with intricate relationships and logic. Before unraveling the intricacies of Prolog's applications in engineering, establishing a robust understanding of its basics becomes the crucial first step. This section serves as a gateway to the logic-driven realm of Prolog, laying the groundwork for students to grasp the language's syntax, rules, and core components. As we delve into the nuances of Prolog's fundamental principles, the stage is set for a comprehensive exploration of its applications in tackling the multifaceted challenges posed by complex engineering problems.

Prolog Syntax and Fundamentals

Navigating the landscape of Prolog demands a deep dive into its distinctive syntax and fundamental principles. Setting itself apart from conventional imperative programming languages, Prolog operates on a unique set of rules and facts. The intricacies of Prolog's syntax form the bedrock of its strength, providing a nuanced framework for logical problem-solving. A thorough understanding of fundamental components like predicates, facts, and rules emerges as a pivotal requirement for effective utilization. This section serves as a gateway to deciphering the language's syntax intricacies, offering insights into the rules that govern Prolog's logical structure. As students delve into the syntax and fundamentals, they unlock the key to harnessing Prolog's full potential in tackling complex engineering problems. The mastery of Prolog's unique syntax becomes a cornerstone for students seeking to leverage its declarative power in building robust and efficient solutions within the realm of engineering problem-solving.

Solving Engineering Problems with Prolog

Embarking on the realm of solving engineering problems with Prolog unveils a transformative journey of logical prowess and declarative efficiency. This section delves into the practical application of Prolog, exploring its capabilities in dissecting and resolving intricate challenges within the engineering domain. As students immerse themselves in the art of problem-solving, Prolog emerges as a powerful ally, adept at modeling and navigating complex logic-based systems. Whether unraveling the intricacies of circuit analysis, optimizing solutions for maximum efficiency, or navigating the constraints of real-world engineering scenarios, Prolog's versatile applications take center stage. This section serves as a guide through practical case studies and examples, providing students with a hands-on understanding of how Prolog can be harnessed as a strategic tool in the arsenal of an aspiring engineer. The journey of solving engineering problems with Prolog is not just about mastering a programming language; it's about acquiring a mindset that thrives on logical reasoning and efficient problem-solving—a skill set poised to make a lasting impact in the dynamic and ever-evolving field of engineering.

Applying Prolog to Logic-Based Systems

Prolog's prowess in handling intricate logic-based systems opens up a realm of possibilities for students grappling with complex engineering challenges. The application of Prolog in logic-based systems is not just a theoretical exercise but a practical approach to problem-solving. As students delve into the world of Prolog, they discover a tool uniquely tailored for modeling and solving engineering problems that demand rigorous logical reasoning. The language's inherent ability to represent relationships, combined with its rule-based system, makes it an invaluable asset in tackling multifaceted issues within the engineering domain. In this section, we will embark on a journey to explore various examples showcasing how Prolog can be effectively applied to diverse problem domains such as circuit analysis, optimization, and constraint satisfaction.

Case Study: Circuit Analysis

Delving deeper into Prolog's application, let's consider a scenario involving the analysis of a complex electronic circuit—a common challenge in the field of electrical engineering. Electronic circuits often consist of multiple components intricately connected through pathways, presenting a daunting challenge for analysis. In this case study, we'll witness how Prolog's rule-based system becomes a beacon of clarity in navigating the complexities of such circuits. Students will be guided through the process of formulating Prolog rules to represent and analyze the intricate relationships between various circuit elements. Through this hands-on exploration, the practical application of Prolog in real-world engineering scenarios comes to life, showcasing its effectiveness in problem-solving. This case study serves not only as an illustration of Prolog's capabilities but also as a valuable learning experience for students seeking to apply their knowledge to tangible, engineering challenges.

Utilizing Prolog for Optimization Problems

In the intricate landscape of engineering, many challenges revolve around optimization—finding the most effective solution from a myriad of possibilities. Prolog, with its inherently declarative nature, emerges as a powerful ally in expressing and efficiently solving optimization problems. This section unravels the symbiotic relationship between Prolog and optimization, demonstrating how students can leverage its capabilities across various domains. From resource allocation scenarios, where efficiency is paramount, to the intricate intricacies of project scheduling, Prolog's flexibility in articulating and solving optimization challenges becomes evident. By exploring real-world examples, students gain insights into the versatility of Prolog, establishing it not only as a programming language but as a strategic tool for optimizing engineering solutions.

Prolog in Constraint Satisfaction Problems

The engineering landscape is rife with constraint satisfaction problems (CSPs), presenting complex scenarios where solutions must adhere to a set of constraints. Prolog's innate ability to express and solve CSPs positions it as an invaluable asset for students navigating problems laden with multiple constraints. This section plunges into the principles of CSPs, unraveling the intricacies of constraint-based problem-solving. Through relevant examples, Prolog's application in designing efficient networks, orchestrating seamless logistics planning, and conquering multifaceted engineering challenges comes to the forefront. Students are guided through the strategic implementation of Prolog in deciphering and resolving constraint satisfaction problems, fostering a deep understanding of its applicability across a spectrum of real-world engineering scenarios. As students grapple with these examples, they not only enhance their Prolog proficiency but also cultivate a problem-solving mindset tailored for the intricate constraints prevalent in the dynamic field of engineering.

Challenges and Tips for Mastering Prolog

Navigating the intricacies of Prolog comes with its unique set of challenges, requiring students to unravel complexities in logic and overcome hurdles inherent in its declarative nature. This section delves into the potential stumbling blocks that learners may encounter on their journey to mastering Prolog. From understanding the nuances of backtracking to effectively handling negation and optimizing code for performance, each challenge presents an opportunity for growth. Alongside these challenges, invaluable tips and strategies are shared to guide students through the learning curve, providing insights into best practices for efficient Prolog programming. The goal is not just proficiency but a mastery that empowers students to apply Prolog confidently and strategically in real-world scenarios. As learners grapple with challenges and implement recommended strategies, they embark on a transformative path toward mastering Prolog—an essential skill for success in the dynamic landscape of programming and problem-solving.

Overcoming Common Challenges

While Prolog stands as a potent tool for problem-solving, mastering its unique paradigm may present students with specific challenges. This section is dedicated to addressing these common hurdles head-on, ensuring that students can navigate the intricacies of Prolog with confidence. Understanding backtracking, a fundamental aspect of Prolog's logic-based approach, can be initially perplexing for learners. Likewise, grappling with the intricacies of handling negation and optimizing code for performance requires a nuanced understanding of Prolog's inner workings. This section aims to demystify these challenges by offering in-depth explanations and practical strategies. Through insights and expert guidance, students will not only overcome these obstacles but also gain a deeper appreciation for Prolog's distinctive features, transforming potential stumbling blocks into valuable learning experiences that contribute to their overall mastery of the language.

Best Practices for Efficient Prolog Programming

To harness the full potential of Prolog in engineering problem-solving, adhering to best practices is indispensable. This section delves into a comprehensive exploration of techniques that elevate Prolog programming to a level of clarity, efficiency, and effectiveness. From the fundamental aspects of code organization to advanced debugging strategies and optimization tips, students receive a wealth of knowledge to enhance their Prolog proficiency. By incorporating these best practices, students not only produce code that is clear, maintainable, and robust but also develop a strategic mindset for approaching complex challenges. Empowered with the ability to write efficient Prolog code, students gain a competitive edge in the dynamic field of engineering, equipped to tackle intricate problems with precision and innovation. Through the integration of these best practices, Prolog becomes more than a language; it transforms into a strategic tool, empowering students to navigate the complexities of real-world engineering scenarios with confidence and proficiency.

In conclusion, Prolog emerges as a indispensable asset for engineering students, serving as a beacon for those in search of effective solutions to intricate problems. The language's distinctive logic-based approach, complemented by its rule-based systems, positions it as a powerful tool for modeling and solving complex engineering scenarios. This comprehensive exploration of Prolog's applications, spanning logic-based systems, optimization problems, and constraint satisfaction, provides students with a profound understanding of its versatile capabilities. Engaging with Prolog becomes more than a mere educational pursuit; it becomes a transformative journey. As students navigate through the challenges presented by complex problems and implement best practices in Prolog programming, they embark on a path toward mastery. This journey not only hones their technical skills but instills in them a strategic mindset for logical problem-solving. In the ever-evolving landscape of engineering, where adaptability and innovation are paramount, mastering Prolog equips students with a skill set that transcends the confines of traditional programming languages. Armed with the ability to navigate intricate scenarios and the insights gained from overcoming challenges, students emerge from this transformative Prolog journey well-prepared for success in the dynamic and demanding field of engineering.

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