(Stanford users can avoid this Captcha by logging in.)

  • Send to text email RefWorks EndNote printer

Bulletproof problem solving : the one skill that changes everything

Available online.

  • Safari Books Online

More options

  • Find it at other libraries via WorldCat
  • Contributors

Description

Creators/contributors, contents/summary.

  • Foreword ix
  • Introduction: Problem Solving for the Challenges of the Twenty-First Century xiii
  • Chapter 1 Learn the Bulletproof Problem Solving Approach 1 A straightforward seven-step process is the key to bulletproof problem solving.
  • Chapter 2 Define the Problem 31 Take time upfront to fully understand the problem and its context.
  • Chapter 3 Problem Disaggregation and Prioritization 49 Cleave the problem into manageable parts.
  • Chapter 4 Build a Great Workplan and Team Processes 87 Drive your workplans from hypotheses to action for efficient problem solving.
  • Chapter 5 Conduct Analyses 111 Start with summary statistics and heuristics to find simple answers to complex problems.
  • Chapter 6 Big Guns of Analysis 135 Employ sophisticated tools of analysis with confidence when they are needed.
  • Chapter 7 Synthesize Results and Tell a Great Story 179 Synthesize your analysis and turn it into a compelling narrative.
  • Chapter 8 Problem Solving with Long Time Frames and High Uncertainty 195 Add tools to address issues of long time frames and uncertainty.
  • Chapter 9 Wicked Problems 235 Unpick wicked problems to yield surprising insights.
  • Chapter 10 Becoming a Great Problem Solver 253 The magic of the bulletproof process is now yours.
  • Appendix: Blank Worksheets for You to Try 259
  • About the Authors 265
  • Acknowledgments 267
  • (source: Nielsen Book Data)

Bibliographic information

Stanford University

  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Non-Discrimination
  • Accessibility

© Stanford University , Stanford , California 94305 .

How to master the seven-step problem-solving process

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

Podcast transcript

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

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

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

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

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

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

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

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

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

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

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

Want to subscribe to The McKinsey Podcast ?

Simon London: So this is a concise problem statement.

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

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

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

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Both: Yeah.

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

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

Simon London: Right. Right.

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

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

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

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

Simon London: Would you agree with that?

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

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

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

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

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

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

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

Charles Conn: Yeah.

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Every step of the process.

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

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

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Absolutely.

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

Want better strategies? Become a bulletproof problem solver

Want better strategies? Become a bulletproof problem solver

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

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

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

Hugo Sarrazin: It was a pleasure. Thank you.

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

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

Explore a career with us

Related articles.

Want better strategies? Become a bulletproof problem solver

Strategy to beat the odds

firo13_frth

Five routes to more innovative problem solving

  • Sign-Up for Idea of the Month

Changing The Way We Think

IDEAS LIBRARY

IDEAS LIBRARY

Academic Research Summaries

PODCASTS & WEBINARS

PODCASTS & WEBINARS

with Leading Thinkers and Faculty

BUSINESS BOOK REVIEWS

BUSINESS BOOK REVIEWS

Leadership and Management titles

OUR BOOKS, PROGRAMS AND EVENTS

OUR BOOKS, PROGRAMS AND EVENTS

Online programs and Leader Prompts

IDEAS FOR LEADERS COMMUNITY

IDEAS FOR LEADERS COMMUNITY

From unbiased experts

DEVELOPING LEADERS QUARTERLY

DEVELOPING LEADERS QUARTERLY

Bulletproof problem solving, the one skill that changes everything.

mckinsey bulletproof problem solving

About Author/s:

Charles Conn is CEO of Oxford Sciences Innovation venture fund, he was a partner at McKinsey in the 1990s, and then Founding CEO of Ticketmaster-Citysearch a pioneering tech company that went public before the dot-com boom, and more recently has been CEO of the Rhodes Trust and Warden of Rhodes House at Oxford University until 2018; Robert Maclean is a Senior Adviser at McKinsey, who has led the Australian and New Zealand practice for eight years.

The World Economic Forum has identified complex problem-solving as the key skill required of organizations in the 21t century, closely followed by critical thinking and creativity. However, the authors point out, none of these are ‘taught’ in the majority of standard formal education institutions, either at high school or universities. McKinsey, the leading strategy consultancy, has been using their Seven-Step Problem-Solving method internally to deliver client solutions for decades however, but it has never been explicitly shared externally. Charles Conn drafted the original internal paper on this 7 Easy Steps to Bulletproof Problem Solving during his time there back in the early 1990’s – and is now bringing it to a wider audience.

The authors quote Herb Simon, the Economics Nobel Laureate from Carnegie Mellon, who specialized in decision-making “solving a problem simply means representing it so as to make the solution transparent” – and this, at its heart, is what this book and the 7 Steps is about. Most of the problems we are faced with today are not ones of finding a new formula to cure a disease, but for navigating our way to a sensible decision. Executing the solution is another set of challenges, but often not as complex. 

The difficult part of solving-problems is not identifying the ‘what’ of the problem, but the ‘why’. At its simplest and most linear, if water is not running from your tap that is the ‘what’ of the problem, but the solution resides in why it is not flowing. Maybe the tap itself is faulty, maybe the pipe to the tap has burst, maybe there is no water flowing into the pipe. Without making the problem transparent the solution cannot be found. 

The problems this book concerns itself with are more complex and systemic, but no less personal often: should I invest in solar panels? Where should I live? What career should I choose? They apply to organizational problems too: pricing, airport capacity, bus routing, market share loss. And to societal issues as well: HIV in India, reducing overfishing, can obesity be reduced?

The Seven Steps are: 1.    Define the problem 2.    Disaggregate it (ie broken down into component parts or issues) 3.    Prioritize which of these elements has the biggest impact on the problem 4.    Build a workplan 5.    Conduct critical analysis (gather data) 6.    Synthesize findings (this is where team work makes a difference) 7.    Communicate a storyline

As a quick flip through the book shows, ‘logic trees’ (flowcharts) that map the questions, inputs and options lie at the heart of the approach – every case study is based on these.   

As with so many disciplines the essential core of this is not rocket science, and can be applied by anyone to almost any problem. The issue is the discipline to follow the methodology through and the opportunity to practice it sufficiently to get adept at it. When applied to problems which are largely or partly subjective, such as ‘where should I live?’ the weightings you give to the elements are open to personal preference and bias, but these biases can also appear in more structured, quantitative problems too. The authors briefly address the bias issues. The fact that McKinsey has successfully been employing this approach for over 30 years does indicate that it works, but one wonders how proficient a user of it you need to be to factor in the more subjective elements of the tree successfully, and come up with problem-solving solutions that are not based entirely on logic to the exclusion of the relational, human aspects.

BUY THIS BOOK

mckinsey bulletproof problem solving

Title: Bulletproof Problem Solving: The One Skill That Changes Everything

Author/s Name/s: Charles Conn and Robert McLean

Publisher:  Wiley

ISBN:  978-1-119553-02-1

Publishing Date:  March, 2019

Number of Pages:  320

Author Knowledge Rating:  1-5 (based on their years of experience, academic expertise in subject areas, and exposure to cross-functional thinking in the area)

https://www.ideasforleaders.com/sites/default/files/star_1.png

Readability:  1-5 score(1=dense and v academic; 5=frantic; page turner)

https://www.ideasforleaders.com/sites/default/files/star_2.png

Appropriate Length:  (1=could have been written in 25% of the length;5=could have been longer)

Core Idea Value:  (1=nonsense (or entirely esoteric); 5=game-changer)

Sign-Up to Receive Our Idea of the Month

Please select all the ways you would like to hear from IEDP Ideas for Leaders Ltd:

You can unsubscribe at any time by clicking the link in the footer of our emails. For information about our privacy practices, please visit our website.

We use Mailchimp as our marketing platform. By clicking below to subscribe, you acknowledge that your information will be transferred to Mailchimp for processing. Learn more about Mailchimp's privacy practices.

Bulletproof Problem Solving

About the Authors

Rob McLean AM

Rob McLean AM

Rob is a Director Emeritus of McKinsey and Company. He led the Australian and New Zealand McKinsey practice for eight years and served on the firm’s global Director’s Committee. As Dean of the Australian Graduate School of Management (AGSM), Rob saw the growing need for stronger problem-solving capability for business leaders of the future. He is now an investor in mathematics education and data analytics software, alongside his philanthropic interests in conservation and social enterprise. He employs these techniques in his role as a Trustee of The Nature Conservancy in Australia and Asia to address water for wetlands, shellfish restoration and improving human health from urban green spaces. He is a director of the Paul Ramsay Foundation, Australia’s largest philanthropic Foundation. He is a graduate of the University of New England in Australia and the Columbia University Graduate School of Business. He became a member of the Order of Australia in 2010 for his contributions to business, social welfare and the environment.

✉ Contact Rob

Charles Conn

Charles Conn

Charles Conn is a seasoned cross-sector leader and entrepreneur. Charles is an experienced investor, and is co-founder and CEO of Monograph Capital, a life sciences venture firm based in London and San Francisco. Before that, he was CEO of Oxford Sciences, a £600m venture firm formed in partnership with Oxford to develop the University’s advanced science ideas. Charles has been a technology entrepreneur, and as founding CEO of Ticketmaster-Citysearch led the company through its IPO (NASDAQ TMCS) and acquisitions of Match.com, Evite, and other companies. He is also a nonprofit education and conservation leader, including a five year term as CEO of the Rhodes Trust, the organization that delivers the Rhodes Scholarships in Oxford. Earlier, Charles was senior advisor to the Gordon & Betty Moore Foundation, he sits or has sat on many company and nonprofit boards, including Patagonia and The Nature Conversancy European Council. He began his career at McKinsey & Company, where he was a Partner and a leader in the strategy practice. He is a graduate of Harvard Business School, Boston University, and Oxford University, where he was a Rhodes Scholar.

✉ Contact Charles

mckinsey bulletproof problem solving

Readingraphics

Book Summary – Bulletproof Problem Solving: The One Skill That Changes Everything

Home > Book Summaries > Book Summary - Bulletproof Problem Solving: The One Skill That Changes Everything

mckinsey bulletproof problem solving

The 7 Steps of Bulletproof Problem Solving

Now, let’s take a quick look at what the 7 steps entail. Do get our complete 16-page Bulletproof Problem Solving summary for a detailed breakdown of each step with examples.

Step 1: Define the Problem Clearly

Know what exactly you’re trying to solve in terms of the expected output and time frame. A well-defined problem provides a good starting point to save you lots of time later in the decision-making process. It must be concrete and measurable, yet leave enough room for creativity and unexpected developments.

You can get the steps and criteria for problem definition in the full Bulletproof Problem Solving summary.

Step 2: Disaggregate the Problem

Break the problem into its component parts or simpler issues, so you can form your hypotheses for testing.

One of the quickest and most effective ways to breakdown or cleave a problem is through logic trees. These are like mental maps of a problem to let you clearly visualize the problem. You can use logic trees to: • See all the component parts of the problem; • Identify possible paths or options; and • Isolate and prioritize the most important parts (step 3).

You can learn more about the principles of good logic trees, and when to apply different types of logic trees (including Factor Trees, Inductive Logic Trees, Deductive Logic Trees, Hypothesis Trees and Decision Tree) from our full summary.

Step 3: Prioritize—Prune the Logic Tree

Every organization has finite resources, and it won’t make sense to address every element in your logic tree. This step is about prioritizing the most important parts of the logic tree, to create the biggest impact with the least resources.

Your goal is to find the Critical Path that allows you to make the best use of your energy and resources. You must concurrently focus on your areas of priority and   discard or prune away the other branches:

Bulletproof Problem Solving summary - finding your critical path

And, ideally, brainstorm as a team to get a more comprehensive perspective.

Step 4: Develop a Workplan and Timetable

Now that you’ve identified and prioritized the key parts of the problem, you can create a workplan to assign specific tasks and resources to team members.

Do check out our complete Bulletproof Problem Solving summary for more insights on (i) what to look out for in developing your workplan, (ii) the ideal sequence of analysis, (iii) how to use “One Day Answers” to consolidate your understanding of a problem, and (iv) how to build sound structures and processes to problem-solve effectively as a team.

Step 5: Analyze the Problem Objectively

With a workplan in place, you can start to analyze the problem. To save time/effort, start with simpler tools (e.g. first‐cut heuristics and root cause thinking) for a quick initial diagnosis. Use complex tools only for the components that need more work. Learn more about these tools in our full summary!

Step 6: Synthesize Findings

Integrate the individual conclusions from the previous steps into a full, coherent picture, so you can test the accuracy of your conclusion and convince others that your solution is the best possible one. Often, this process unveils new insights that you may have missed when you were immersed in the details.

Step 7: Communicate your Findings

Create a compelling storyline that links the problem statement to the final conclusion. Present an overarching argument, supported by the situation-observation-conclusion  logic from your One-Day-Answers, and findings from the previous steps. More tips and examples/illustrations can be found in our full Bulletproof Problem Solving summary.

Dealing with Uncertain or Complex Problems

The 7-step Bullet Proof Problem-Solving Framework can be used for all types of problems. But what happens if you encounter problems with long timeframes and high levels of uncertainty?

For example, how do you address the impact of rising sea levels over the next 5 decades, or choose the right education/career given the uncertainty of the job market in 20-30 years? The McKinsey team divided uncertainty into 5 levels:

• Level 1 has the shortest timeframe with the lowest level of uncertainty, e.g. predicting sales for the next quarter.

• Level 2 involves alternative futures arising from specific events, e.g. Brexit or whether the UK would withdraw from the EU.

• Level 3 involves a range of possible futures and you can’t tell which ones are more likely, e.g. the role of fossil fuels compared to other energy sources in 15 years.

• Level 4 involves real uncertainty—situations where we can’t confidently foresee nor predict the outcomes, e.g. the Manhattan sea levels in 2050.

• Level 5 are the “unknown unknowns”. These are things we can’t possibly foresee (e.g. a meteorite hitting Earth) given our existing knowledge and technology.

You can still use the 7 steps to systematically work through potential strategies and find a resolution. The appropriate response will depend on (i) the nature and level of uncertainty and (ii) your own risk tolerance. For example, you can do nothing, try to buy time, purchase information to run complex modelling, buy hedges or insurance to protect yourself against risks, make moves that you won’t regret no matter the outcome, etc.

Do also check out our full summary for tips on how to deal with “wicked problems” which are extremely complex and hard to solve.

Getting the Most from “Bulletproof Problem Solving”

Bulletproof Problem Solving summary - Book Summary Bundle

This is an extremely comprehensive book to equip anyone with the skills and processes to become a good problem-solver. The authors explain the 7 steps in great detail, and present 30 real‐world case-studies complete with illustrations, tables, logic trees and charts to show how the framework can be applied. The examples cut across a range of individual, organizational and national scenarios, from airport capacity planning to education and setting the right prices for a business startup. The book also comes with other technical concepts, tips, suggested problems for you to try, and various worksheets (for defining your problem, prioritizing the key variables, developing your workplan and storyline). You can purchase the book here or visit bulletproofproblemsolving.com for more details and resources.

About the Authors of Bulletproof Problem Solving

Bulletproof Problem Solving: The One Skill That Changes Everything was written by Charles Conn and Robert McLean.

Charles R. Conn is a Canadian and American entrepreneur, investor, and author. He’s the co-founder of Monograph, a life sciences venture firm. Previously, he was the CEO of Oxford Sciences Innovation, Ticketmaster-Citysearch, and Rhodes Trust. Conn serves/served on many company and nonprofit boards. He began his career at McKinsey & Company as a Partner and leader in the strategy and energy practices. He is a graduate of Harvard Business School, Boston University, and Oxford University.

Robert McLean is a Director Emeritus of McKinsey and Company. He led the Australian and New Zealand McKinsey practice for 8 years and served on the firm’s global Director’s Committee. He was Dean of the Australian Graduate School of Management. He’s also an investor, and a director of the Paul Ramsay Foundation. He is a graduate of the University of New England in Australia and the Columbia University Graduate School of Business.

Bulletproof Problem Solving Quotes

“Our aim is simple: to enable readers to become better problem solvers in all aspects of their lives.”

“Good problem solvers are made not born.”

“A well-defined problem is a problem half-solved.”

“Good Problem solving is equal parts ‘What you do’ vs ‘What you don’t do’.”

“Problem solving done well translates into action that improves our circumstances.”

Download free summaries_banner

Master these 7 steps to solve any problem more effectively!

Summary Preview

Get Powerful Insights with ReadinGraphics

mckinsey bulletproof problem solving

Includes: A one-page infographic in pdf A 16-page text summary in pdf An 39-min audio summary in mp3 Available for download or via web app

Get All Book Summaries

mckinsey bulletproof problem solving

Includes: Instant web-app access to 300+ summaries 3 monthly title downloads Cancel anytime Discounted rate for annual purchase

Get 2 Free Infographic Summaries

Get All Summaries

of summary infographics purchased every day

of minutes audio summaries accessed every day

summary pages purchased daily

mckinsey bulletproof problem solving

Leave a Reply Cancel Reply

Save my name, email, and website in this browser for the next time I comment.

  • Quick Feedback
  • Free Sample Summaries
  • Affiliate Programs
  • Reviews/Testimonials
  • Store (Buy individual summaries)
  • Gift All Summaries
  • Subscription Plans (Get all summaries)
  • List of Book Summaries

Customer Care

  • Suggest book titles
  • Privacy Policy
  • Disclaimers

© 2024 Readingraphics.

  • Business & Entrepreneurship
  • Business Strategy & Culture
  • Finance, Money & Wealth
  • Leadership & Management
  • Sales & Marketing
  • Health, Wellness & Spiritual Growth
  • Learning & Development
  • Technology & Innovation
  • Problem-Solving & Creativity
  • Personal Development & Success
  • Parenting & Relationships
  • Psychology, Economics, Sociology & General
  • View All Categories
  • Buy Summaries

mckinsey bulletproof problem solving

IMAGES

  1. Bulletproof Problem Solving: The One Skill That Changes Everything

    mckinsey bulletproof problem solving

  2. Bulletproof problem solving

    mckinsey bulletproof problem solving

  3. Book Summary

    mckinsey bulletproof problem solving

  4. 7 EASY STEPS TO BULLETPROOF PROBLEM SOLVING 解

    mckinsey bulletproof problem solving

  5. McKinsey's problem solving process: MindMapper mind map template

    mckinsey bulletproof problem solving

  6. Bulletproof Problem-Solving (Book Summary)

    mckinsey bulletproof problem solving

VIDEO

  1. Bulletproof Problem Solving: The One Skill That Changes Everything

  2. Bulletproof Problem Solving: The One Skill That Changes Everything

  3. Bulletproof Problem Solving: The One Skill That Changes Everything with Charles Conn

  4. Learn how to do effective Problem Solving from an ex Mckinsey Consultant

  5. Bulletproof Problem Solving: Sydney Airport Case Study

  6. McKinsey Problem Solving Game (Solve) Explained

COMMENTS

  1. Bulletproof problem solving

    Rob McLean: "Bulletproof problem solving" is an expression we used at McKinsey that meant that what you came up with to present to the client was ironclad. It really was a test of just how rigorously you'd gone about defining the problem, breaking it down, and doing the analysis.

  2. Bulletproof Problem Solving

    The Bulletproof Problem Solving online course is a comprehensive and interactive course that provides the user with key learnings from the best selling book, Bulletproof Problem Solving: The One Skill That Changes Everything. The online course provides insights from the Bulletproof Problem Solving authors, Conn and McLean.

  3. Problem solving doesn't have to be a puzzle

    a seven-step process for effective solutions different lenses for approaching problems Six problem-solving mindsets for very uncertain times How to master the seven-step problem-solving process Strategy to beat the odds Want better strategies? Become a bulletproof problem solver Five routes to more innovative problem solving From McKinsey Careers

  4. Bulletproof Problem Solving: The One Skill That Changes Everything

    In Bulletproof Problem Solving: ... This book should be read by students who consider working in management consultancy, describing the "McKinsey approved" 7-Step process of problem solving. Additionally, it will also be useful for readers who want to make an impact on complex organisations without getting distracted or caught in reiterative ...

  5. The McKinsey guide to problem solving

    The McKinsey guide to problem solving Become a better problem solver with insights and advice from leaders around the world on topics including developing a problem-solving mindset, solving problems in uncertain times, problem solving with AI, and much more.

  6. 7 Steps to Bulletproof Problem Solving

    That's where Bulletproof Problem Solving comes in. McKinsey alums Charles Conn and Rob McLean teach us how to be bulletproof problem solvers using a simple 7-steps approach. The approach has its foundation in the hypothesis-driven structure of the scientific method.

  7. Bulletproof Problem Solving: The One Skill That Changes…

    In Bulletproof Problem Solving: The One Skill That Changes Everything you'll learn the seven-step systematic approach to creative problem solving developed in top consulting firms that will work in any field or industry, turning you into a highly sought-after bulletproof problem solver who can tackle challenges that others balk at.

  8. Bulletproof Problem Solving: The One Skill That Changes Everything

    Bulletproof Problem Solving: The One Skill That Changes Everything | Wiley The problem-solving technique outlined in this book is based on a highly visual, logic-tree method that can be applied to everything from everyday decisions to strategic issues in business to global social challenges.

  9. Online Course

    The Bulletproof Problem Solving online course is a comprehensive and interactive course that provides the user with key learnings from the best selling book, Bulletproof Problem Solving: The One Skill That Changes Everything. The online course provides insights from the Bulletproof Problem Solving authors, Conn and McLean.

  10. Articles

    Click Here to read the McKinsey Quarterly article for September 15, 2020 written by Bulletproof Problem Solving authors Charles Conn and Robert McLean. Follow Bulletproof Problem Solving now on YouTube

  11. Wiley Bulletproof Problem Solving: The One Skill That Changes

    this bulletproof approach to defining, unpacking, understanding, and ultimately solving problems, you'll have a personal superpower for developing compelling solutions in your workplace. Discover the time-tested 7-step technique to problem solving that top consulting professionals employ

  12. Bulletproof Problem Solving: The One Skill... by Charles Conn

    In Bulletproof Problem Solving: ... This book should be read by students who consider working in management consultancy, describing the "McKinsey approved" 7-Step process of problem solving. Additionally, it will also be useful for readers who want to make an impact on complex organisations without getting distracted or caught in reiterative ...

  13. Bulletproof problem solving : the one skill that changes everything in

    Chapter 1 Learn the Bulletproof Problem Solving Approach 1 A straightforward seven-step process is the key to bulletproof problem solving. ... with decades of experience at McKinsey and Company, provide 30 detailed, real-world examples, so you can see exactly how the technique works in action. With this bulletproof approach to defining ...

  14. How to master the seven-step problem-solving process

    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.

  15. Bulletproof Problem Solving

    The Seven Steps are: 1. Define the problem 2. Disaggregate it (ie broken down into component parts or issues) 3. Prioritize which of these elements has the biggest impact on the problem 4. Build a workplan 5. Conduct critical analysis (gather data) 6. Synthesize findings (this is where team work makes a difference) 7. Communicate a storyline

  16. About the Authors

    Rob is a Director Emeritus of McKinsey and Company. He led the Australian and New Zealand McKinsey practice for eight years and served on the firm's global Director's Committee. As Dean of the Australian Graduate School of Management (AGSM), Rob saw the growing need for stronger problem-solving capability for business leaders of the future.

  17. Book Summary

    The Bullet Proof Problem-Solving framework was developed by McKinsey & Company, renowned management consulting firm. This framework is a complete problem-solving process that can be used at an individual, organizational or even social/government level.

  18. Bulletproof Problem Solving: The One Skill That Changes Everything

    But how problem solving is taught in our schools, universities, businesses, and organizations comes up short. In Bulletproof Problem Solving: ... This book should be read by students who consider working in management consultancy, describing the "McKinsey approved" 7-Step process of problem solving. Additionally, it will also be useful for ...

  19. Book Review:《The McKinsey Problem-Solving Method》( Bulletproof Problem

    However, "The McKinsey Problem-Solving Process" book provides numerous case studies that can serve as guidelines and references for those currently or in the future dealing with problem ...

  20. Wiley Bulletproof Problem Solving: The One Skill That Changes

    Bulletproof Problem Solving: The One Skill That Changes Everything Charles Conn, Robert McLean E-Book 978-1-119-55303-8 March 2019 $18.00 Paperback 978-1-119-55302-1 March 2019 $29.95 ... Previously, he was a Partner at McKinsey & Company, led a technology start-up to its IPO, and was an early team lead at the Gordon & Betty Moore Foundation in ...