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The McKinsey Mind: Understanding and Implementing the Problem-Solving Tools and Management Techniques of the World's Top Strategic Consulting Firm Hardcover – October 17, 2001
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The groundbreaking follow-up to the international bestsellera hands-on guide to putting McKinsey techniques to work in your organization
McKinsey & Company is the most respected and most secretive consulting firm in the world, and business readers just can't seem to get enough of all things McKinsey. Now, hot on the heels of his acclaimed international bestseller The McKinsey Way , Ethan Rasiel brings readers a powerful new guide to putting McKinsey concepts and skills into action The McKinsey Mind . While the first book used case studies and anecdotes from former and current McKinseyites to describe how "the firm" solves the thorniest business problems of their A-list clients, The McKinsey Mind goes a giant step further. It explains, step-by-step, how to use McKinsey tools, techniques and strategies to solve an array of core business problems and to make any business venture more successful.
Designed to work as a stand-alone guide or together with The McKinsey Way , The McKinsey Mind follows the same critically acclaimed style and format as its predecessor. In this book authors Rasiel and Friga expand upon the lessons found in The McKinsey Way with real-world examples, parables, and easy-to-do exercises designed to get readers up and running.
- Print length 272 pages
- Language English
- Publisher McGraw Hill
- Publication date October 17, 2001
- Dimensions 6.3 x 1.1 x 9.3 inches
- ISBN-10 0071374299
- ISBN-13 978-0071374293
- See all details
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From the publisher.
Ethan M. Rasiel was a consultant in McKinsey & Co.'s New York office. His clients included major companies in finance, telecommunications, computing, and consumer goods sectors. Prior to joining McKinsey, Rasiel, who earned an MBA from the Wharton School at the University of Pennsylvania, was an equity fund manager at Mercury Asset Management in London, as well as an investment banker.
Paul N. Friga worked for McKinsey & Co. in the Pittsburgh office after receiving his MBA from the Kenan-Flagler Business School at the University of North Carolina. He has conducted consulting projects relating to international expansion, acquisition and strategic planning, education, water, and other industries. He has also consulted for Price Waterhouse. He is currently pursuing his Ph.D. in Strategy at Kenan-Flagler and is Acting Director of the North Carolina Knowledge Management Center.
From the Back Cover
The First Step-by-Step Manual for Achieving McKinsey-Style Solutions--and Success
International bestseller The McKinsey Way provided a through-the-keyhole look at McKinsey & Co., history's most prestigious consulting firm. Now, the follow-up implementation manual, The McKinsey Mind , reveals the hands-on secrets behind the powerhouse firm's success--and discusses how executives from any field or industry can use those tactics to be more proactive and successful in their day-to-day decision-making.
Structured around interviews and frontline anecdotes from former McKinsey consultants--as well as the authors, themselves McKinsey alumni-- The McKinsey Mind explores how McKinsey tools and techniques can be applied to virtually any business problem in any setting. Immensely valuable in today's crisis-a-minute workplace, it discusses:
- Techniques for framing problems and designing analyses
- Methods for interpreting results and presenting solutions
The ability to think in a rigorous, structured manner--a McKinsey manner--is not a birthright. It can, however, be a learned behavior. Let The McKinsey Mind show you how to approach and solve problems with the skill of a McKinsey consultant and obtain the positive results that have been delivered to McKinsey clients for over a century.
McKinsey & Co. is renowned throughout the world for its ability to arrive at sharp, insightful analyses of its clients' situations then provide solutions that are as ingenious as they are effective. McKinsey succeeds almost as well as shielding its revolutionary methods from competitors' scrutiny.
Now, The McKinsey Mind pulls back the curtain to reveal the ways in which McKinsey consultants consistently deliver their magic and how those methods can be used to achieve exceptional results in companies from 10 employees to 10,000. Packed with insights and brainstorming exercises for establishing the McKinsey mind-set, this book is an in-depth guidebook for applying McKinsey methods in any industry and organizational environment.
Taking a step-by-step approach, The McKinsey Mind looks at the McKinsey mystique from every angle. Owners, executives, consultants, and team leaders can look to this comprehensive treatment for ways to:
- Follow McKinsey's MECE (mutually exclusive, collectively exhaustive) line of attack
- Frame business problems to make them susceptible to rigorous fact-based analysis
- Use the same fact-based analysis--in conjunction with gut instinct--to make strategic decisions
- Conduct meaningful interviews and effectively summarize the content of those interviews
- Analyze the data to find out the "so what"
- Clearly communicate fact-based solutions to all pertinent decision makers
Because organizational problems rarely exist in a vacuum, The McKinsey Mind discusses these approaches and more to help you arrive at usable and sensible solutions. It goes straight to the source--former McKinsey consultants now in leadership positions in organizations throughout the world--to give you today's only implementation-based, solution-driven look at the celebrated McKinsey problem-solving method.
" The McKinsey Mind provides a fascinating peek at the tools, practices, and philosophies that have helped this much-admired firm develop generations of bright young MBAs into trusted corporate advisors. But the book's practical, down-to-earth advice is not just for consultants. The disciplined way in which McKinsey consultants frame issues, analyze problems, and present solutions offers valuable lessons for any practicing or aspiring manager." --Christopher A. Bartlett, Daewoo Professor of Business Administration, Harvard Business School
"McKinsey and Co. rescues the biggest companies from disaster by addressing every problem with its own mixture of logic-driven, hypothesis-tested analysis. The McKinsey Mind helps everyone learn how to think with the same discipline and devotion to creating business success. According to the maxim, giving a man a fish may feed him for a day, but teaching him to fish will feed him for a lifetime. Paying McKinsey to solve your problem may help you for a day, but learning how they do it should help you for a lifetime." --Peter Wayner, Author of Free For All: How Linux and the Free Software Movement Undercut The High-Tech Titans
"The McKinsey Mind unlocks the techniques of the world's preeminent consulting firm and presents them in a format that is easy to understand and even easier to implement." --Dan Nagy, Associate Dean, The Fuqua School of Business, Duke University
About the Author
- Publisher : McGraw Hill; First Edition (October 17, 2001)
- Language : English
- Hardcover : 272 pages
- ISBN-10 : 0071374299
- ISBN-13 : 978-0071374293
- Item Weight : 15.8 ounces
- Dimensions : 6.3 x 1.1 x 9.3 inches
- #12 in Consulting
- #142 in Decision-Making & Problem Solving
- #470 in Business Management (Books)
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"The McKinsey Way" Book: A Comprehensive Summary
The McKinsey Way is a book by Ethan M. Rasiel , published in 1999, about what McKinsey&Company does, how McKinsey organizes and what working at McKinsey is like.
20 years after publication, the book still holds significant value, offering timeless insights into the world’s most prestigious management consulting firm: McKinsey&Company. In this article, we’ll provide a detailed summary of all the lessons and insights from The McKinsey way . We’ll re-organize the content and occasionally insert supporting insights to make it more friendly to the reader.
The McKinsey Way has 5 Parts (Sections) with 180 pages:
- Part 1: The Problem Solving Methodology of McKinsey
Part 2: Logistics of how a McKinsey project works
Part 3: insights into the actual works of consultants, part 4: how to excel as a junior consultant, part 5: exit opportunities and life after mckinsey, part 1: the mckinsey problem-solving methodology.
The McKinsey problem-solving process can be summarized in the 5 steps: define the problems, find the root cause, use “hypothesis-driven” process, analyze with “issue tree” and propose solutions.
1. Define the problem: Every consulting project revolves around a “problem”. But the “problem” is NOT always the problem!
One symptom may have different causes and we as doctors should never rely on the patient to diagnose.
So, always dig deeper. Get facts. Asks questions. Poke around. Challenge the client… until you find the real problem.
2. Find the root cause: Don’t jump straight to the solution, because you might just be fixing the symptoms. The problem will come back if the root cause is not properly dealt with.
3. Use “hypothesis-driven” process: Make educated guesses of possible root-cause A B C and test with data (a.k.a: facts). We’ll sometimes call this a fact-based process.
4. Break down and structure the analysis with the “ issue tree ” framework: A “hypothesis-driven” process may take forever as there are millions of possible root-causes. We need to test hypotheses from the top to the bottom of the issue tree – a top-down fashion. These issue trees need to be MECE.
5. Propose solutions: When the root causes are identified, consultants propose solutions targeting them directly.
A few notes when using this methodology
No.1: Don’t force the facts to say what you want.
When you propose or work extensively with a running hypothesis , it’s easy to get emotionally attached and turn the problem-solving process into a proving exercise. So keep an open mind and listen to what the data have to say.
No.2: Let the hypothesis come to you naturally.
You will not be able to form an initial hypothesis every time. The clients may not even know their problems. The scope of the project is often large and vague. So, dive in, gather facts, conduct analyses, and the hypotheses will show themselves.
No.3: Don’t reinvent the wheel.
Business problems often resemble each other more than they differ. With suitable techniques, you can apply what you and the firm learned from other projects. After all, one of the values consulting firms bring is to provide the “best practice” – what the top players in the game are doing
No.4: Make sure your solution fits your client.
The most brilliant solution is useless without proper implementation. So know your client’s weaknesses, strengths, and capabilities and tailor your solutions accordingly.
No.5: Be mindful of politics.
There are always politics in projects. Many times, McKinsey gets involved in fights between corporate factions. This creates friction that prevents you from doing your job (late data; rejected interviews, etc.).
So think about how your solutions affect the players in an organization and always build a consensus along the way. If consensus requires you to change your solution, try to compromise. It’s no good devising the ideal solution if the client refuses to accept it.
It’s highly recommended that you refer to the following video for a general view on how McKinsey organizes and a better understanding of the insights from this part.
There is a whole system behind how McKinsey solve a business problem. In this part of The McKinsey Way, Ethan Rasiel describes how the company sells their projects, builds a team and manages its hierarchy.
Selling a study/project
McKinsey typically does not sell. The firm does marketing through a constant stream of books, articles, and scholarly journals like the McKinsey Quarterly, etc. The Firm also invites organize press releases and generates quite some coverage by journalists.
These publications help McKinsey Partners build and nurture a vast network of informal contacts with potential clients. And when a problem arises, the client knows who to contact.
Assembling a team
Almost all projects need a full-time team of consultants. Typically, the process goes like this:
- The ED (a.k.a: Project Owner) signs a contract with the client
- The ED hires an EM from within the McKinsey network, from any offices (a.k.a: Project CEO)
- The EM then hires a group of staff, consisting of BAs (a.k.a: Business Analyst) and Associates.
It’s solely the EM’s responsibility to keep the team happy and functional. McKinsey projects have a few common practices to do so:
- A monthly “team-bonding”.
- A “team temperature” (a.k.a: morale) weekly survey.
The chain of command in McKinsey is very clear and strict. So is the responsibility funnel. In the ED’s eyes, the EM is responsible for everything in the project. In the EM eyes, the BA is responsible for everything within the assigned workstream. Even when a BA messes things up, to the ED, it’s not the BA’s fault, but the EM.
To provide the best solution for the clients, consultants need tons of skills in preparing presentations; conducting researchs and interviews; presenting the final products in a simple structure; communicating with clients; and brainstorming.
Making presentations, a.k.a: the final deliverable documents
Most consultants spend a big portion of their time making presentations (often in PowerPoint). Utilize the support team! Keep it structured, from top to bottom, from end to end.
Note that there are diminishing marginal returns to your effort, meaning that the last miles toward perfection are always much harder than the beginning. So, resist the temptation to tweak your presentation at the last minute. Try to assess its gains vs those of a good night’s sleep for you and the supporting cast.
Visualizing data with charts and exhibits
We subconsciously admire the people who talk in sophisticated language, so we make complex charts. However, simple and easy-to-follow charts go a long way in consulting. Charts are just a means of getting your messages across, not a Ph.D. project.
Also, don’t forget to:
- Write clear chart titles
- List out units of measurement in all axes
- Mark legends and side notes
- Provide data sources
Managing internal communications
- Over-communication is always better. Keep that information flowing. Make sure that your team is up to date with at least the broad outlines of your workstream and your boss up to date with your team’s progress. There are many channels for this: email, voicemail, messaging, small talks during cigarette breaks, meetings, etc.
- Keep your communication brief, yet comprehensive and structured.
- Look over your shoulder – always. You never know who is listening. Remember that your client’s confidentiality is a must.
Working with clients
This is a big one as the true hierarchy at McKinsey is “Client -> Firm -> and then You”. The client is your biggest boss.
There are many tips on client management, but the general principle is to bring the client to your side. You never win by opposing the client. Remind them about mutual benefits. Do it everyday!
Some of the client members can be “liabilities”. There are 2 types of them:
- the merely “useless”.
- the hostile ones.
With both types, the number 1 option is to subtly trade them out of your realm. When that is not possible, the next best option is to play ignorant. Leak out information only with the right “secret audience”.
No matter what, engage the client members in the process. The more they feel everybody is on the same boat, the more they would support you.
You should also get buy-ins throughout the organization along the process. Every important party has to agree with you. Ideally, the final document has already been discussed many times through many rounds with the client before the official presentation.
Don’t reinvent the wheel! Whatever you are doing, chances are that someone, somewhere has done something similar. Building upon someone’s work is the best way to save time and energy while achieving the highest standard.
Besides, here are some research tips:
- Start with the annual report. All public companies have them available on their website.
- Look for abnormal patterns (things that are especially good or bad). That’s where all the insights lie.
- Last but not least, look for the best practice. Find out what the best performers in the field are doing and learn from them.
This is one of the most effective ways to gather qualitative facts during a project. You will find yourself interviewing multiple industry and function experts as well as key client leaders.
Here are a few tips:
- Be prepared. Know exactly what you want to get out of it. Know as much as you can about the interviewee. Writing an interview brief for yourself is not a bad idea.
- If possible, have the interviewee’s boss set up the meeting.
- Start with some general and open-ended questions then move on to specific ones. Let the content flow naturally.
- Sometimes, it’s useful to use the indirect style. Take time to make the interviewee comfortable with you and the interview process.
- Include some questions you know the answer to. This gives insights into the interviewee’s style, knowledge, and honesty.
- Don’t ask too much. Focus on what you really need (what you prioritize in the interview brief).
- Listen and let the interviewee know you are doing so.
- Paraphrase what you hear in your own words. Confirm whether you understand correctly. This also gives chances for the interviewee to add or amplify important points.
- Near the end, use this last trick to flush out any possible missing insights: “Is there anything else you would like to tell or any question I forgot to ask…?”.
- Adopt the Columbo tactic. Wait until a day or two passes, then drop by the interviewee’s office. “I was just passing by and remembered a question I forgot to ask”. This is a less threatening way to keep the conversation going.
- Lastly, always write a thank-you note. A short and sincerely one always does the work.
Brainstorming at McKinsey
In McKinsey, we often use the word “Problem-Solving” interchangeably with brainstorming sessions. It’s a very topic-focus meeting within the McKinsey team, consisting of the consultant in-charge, the EM, and sometimes even the ED and experts.
Before the session, prepare in advance as much supporting data as possible. It will come handy in the process.Inside the White room: Start with tabula rasa — a clean slate. When you get your team into the room, leave your preconceptions at the door. Bring in only the facts, and find new ways of looking at them.
Management consulting is an interesting yet challenging job. To survive and thrive at McKinsey, here are some advices for you:
Tip 1: Find your own mentor
At McKinsey, every consultant is officially assigned a mentor, who may not be in the same office. How much you benefit from the official mentor is pretty much a matter of luck. If you want great guidance, you have to go out and get your own. Get a few too, don’t stick to just one.
Tip 2: Survive the road
Business travel can be exhausting and difficult, here are some note you can take to deal with it:
- Look at business travel as an adventure.
- Do proper planning. These simple logistics can make a big difference
- Treat everyone with tremendous respect
Tip 3: Have a list of items to bring when traveling
Here is the list:
- Clothing: extra shirts or blouses, spare ties, spare shoes, casual clothes, cashmere sweaters
- Tools: writing pad, copy of whatever you send to the client, calculator
- Personal care Items
- Things to keep you organized and in touch
Tip 4: Treat your assistant well
Having a good assistant is a lifeline. Treat them well. Be clear about what you want. Give them room to grow. Take time to train them well. Answering their questions and showing them the ropes.
Tip 5: Have boundaries to keep your life balance
Since you have a large amount of work to cover as a consultant, there is almost no work-life balance. However, if you want a life, lay down some rules. For example:
- Make one day a week to be completely free of work, both physically and mentally. Tell your boss about it! He/she will respect it. And so should you.
- Don’t take work home. When you are home, you are home!
- Plan long ahead, especially when you travel.
Tip 6: The 80 / 20 Rule
80% of the wealth is owned by just 20% of the population. 80% of the output can be produced by 20% of the effort. 20% of the problems can cause 80% of the trouble.
So if you wanna save time and effort. Always try to find those 20% and act upon them!
Tip 7: Don’t try to analyze everything
If you don’t take shortcuts, there is simply too much to do. Be selective. Find the key drivers. Focus on the core problem, then apply analysis. This helps avoid going down blind alleys and boiling the ocean.
Tip 8: The Elevator Test
Concise communication is crucial in consulting. Anytime the EM asks you for your workstream status, you have to be able to give him a 30 seconds summary. Short yet insightful. This skill takes practice. Try doing it every day in various contexts!
Tip 9: Pluck the Low-Hanging Fruit
Solving only part of the problem can still mean increased profits. Those little wins help you and your customers. Try to see such opportunities and grab them first.
Tip 10: Hit singles
Get your job and only your job done, don’t try to do the work of the whole team.
It’s impossible to do everything yourself all the time. Even if you manage to pull it off once, you raise unrealistic expectations and once you fail, it is difficult to get back credibility.
Tip 11: Look at the big picture
When you are feeling swamped, take a step back, figure out what you are trying to achieve, and then look at what you are doing. “Does this really matter?”
Probably not! All of these troubles will go away!
Tip 12: Just say “I don’t know”
The firm pounds the concept of professional integrity: Honesty. If you don’t know something, just say “I DON’T KNOW” in an empowering fashion. Admitting that is a lot less costly than bluffing.
“Leaving McKinsey is never a question of whether—it’s a question of when”
There are not many people who stay with McKinsey for their whole career life. In the last part of The McKinsey Way , Ethan Rasiel and other ex-McKinsey consultants share their valuable lessons and memories from working at the company.
- “Structure, structure, structure. MECE, MECE, MECE. Hypothesis-driven, Hypothesis-driven, Hypothesis-driven.” – Former associate in Dusseldorf and San Francisco offices
- “The quality of the people. In the corporate world, the average-caliber employee is far below McKinsey’s least intelligent.” – Wesley Sand
- “What stays with me is the rigorous standard of information and analysis, the proving and double-proving of every recommendation, combined with the high standard of communication both to clients and within the Firm.” – Former associate in the Boston and New York offices
- “When faced with an amorphous situation, apply structure to it.” – Kristin Asleson, New York office, 1990-93; now working in Silicon Valley
- “Execution and implementation are the key. A blue book is just a blue book, unless you do something with it. Getting things done is the most important thing.” – Former EM in the New York office
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The scoring mechanism in the McKinsey Digital Assessment
McKinsey Comprehensive Package
Unlock all materials helping you land the next job in McKinsey!
Management consulting is an industry providing expensive and professional advice to organizations to boost their overall performance through better management
“An engaging collection of often novel and excellent advice for business leaders, which draws on the wisdom of long experience and on many memorable examples of decisions and their consequences. Imperfectionism is a powerful idea.” – Professor Daniel Kahneman, Nobel Laureate
“Under today’s conditions, the authors argue that real-time problem solving should be the heart of strategy development rather than theoretical frameworks, and they present a framework for this approach.” In Uncertain Times, Embrace Imperfectionism
The world is changing faster and faster, with increasing uncertainty and threat of disruption in every business and nonprofit segment. Conventional approaches to strategy development no longer work.
In this prequel to their Amazon-bestseller, Bulletproof Problem Solving, Conn and McLean introduce a novel approach to strategic problem solving in times of high uncertainty. Based on a decade of research and 45 new case studies, The Imperfectionists posits a dynamic approach to developing organizational direction under uncertainty based on harnessing six reinforcing strategic mindsets.
Imperfectionists are curious, they look at problems from several perspectives, and gather new data and approaches, including from outside their current industry. They deliberately step into risk, proceeding through trial and error, utilizing nimble low consequence and reversible moves to deepen their understanding of the unfolding game being played, and to build capabilities. Imperfectionists succeed with dynamic, real time strategic problem solving, confidently moving forward while others wait for certainty or make impetuous and foolish bets.
McLean and Conn’s The Imperfectionists is a breath of fresh air among books on business strategy. They correctly take problem-solving as the most crucial skill in the strategist’s toolkit and explore six different ways of thinking about difficult uncertain situations. If your company is struggling with “strategies” that are just three-year budgets, get this book as quickly as you can. It will open your mind to powerful ways of dealing with uncertainty and complexity. – Professor Richard Rumelt, author Good Strategy, Bad Strategy and The Crux
Introducing the Bulletproof Problem Solving online course
Complex problem solving is the core skill for the 21st Century , the only way to keep up with rapid change. But systematic problem solving is not taught in most universities and graduate schools. The online course covers the seven-step approach to creative problem solving developed in leading consulting firms. It employs a highly visual, logic-tree method that can be applied to almost any problem, from strategic business decisions to global social challenges. Conn and McLean, with decades of experience at McKinsey, start-up companies, and environment-focused foundations, provide a toolkit with detailed, real-world examples.
For current students: Lost password? Reset it here at Go1.
Bulletproof Problem Solving 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.
The online course is a self guided, highly interactive course with 4-6 hours of content. The course is designed for people to work at their own pace and develop the problem solving skills employed at leading management consulting firms. There are many worked example problems to practice the 7-step process, as well as a bonus workbook to help solve problems from your own organisation.
Bulletproof Problem Solving
The one skill that changes everything.
Charles Conn & Robert McLean
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.
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.
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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Complex problem solving is the core skill for 21st Century Teams
Complex problem solving is at the very top of the list of essential skills for career progression in the modern world. But how problem solving is taught in our schools, universities, businesses and organizations comes up short. 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.
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. The authors, 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, 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
- Learn how a simple visual system can help you break down and understand the component parts of even the most complex problems
- Build team brainstorming techniques that fight cognitive bias, streamline workplanning, and speed solutions
- Know when and how to employ modern analytic tools and techniques from machine learning to game theory
- Learn how to structure and communicate your findings to convince audiences and compel action
The secrets revealed in Bulletproof Problem Solving will transform the way you approach problems and take you to the next level of business and personal success.
Table of contents
- Problem Solving Capability
- Education Gaps
- The Seven‐Steps Process
- High Stakes
- Pitfalls and Common Mistakes
- What's in Store?
- The Bulletproof Problem Solving Cycle
- Prepare for an Avalanche of Trees!
- Let's Start with Some Case Studies
- Case 1: Does Sydney Airport Have Adequate Capacity?
- Case 2: Should Rob Install Solar Panels on His Roof Now?
- Case 3: Where Should I Move?
- Case 4: Making Pricing Decisions in a Start‐up Company
- Case 5: Should Charles Support the Local School Levy?
- Chapter 1 Takeaways
- Problems to Try on Your Own
- Design Thinking and Seven Steps
- Chapter 2 Takeaways
- Types of Logic Trees: Getting Started
- Step 3: Prioritization—Pruning Your Logic Trees
- Advanced Class: Using Cleaving Frames to Take Apart Problems
- Team Processes in Problem Disaggregation and Prioritization
- Chapter 3 Takeaways
- Workplanning and Project Management
- One‐Day Answers
- Great Team Processes for Workplanning and Analysis
- Chapter 4 Takeaways
- Heuristics and Rules of Thumb
- Question‐Based Problem Solving
- Chapter 5 Takeaways
- Firepower Availability
- Sequence Your Thinking
- Which Big Gun to Choose?
- Case Studies for Employing the Big Guns
- Synthesis of Findings
- From One‐Day Answers to Pyramid Structure
- Telling Compelling Stories
- Chapter 7 Takeaways
- Levels of Uncertainty
- Logic Trees to Deal with Uncertainty
- Case Examples of Long Time Frames and Uncertainty
- Case Study: How Should I Choose My Career?
- Case Study: Will My Retirement Savings Last?
- Case Study: How to Make Really Long‐Term Investments
- Case Study: Building New Businesses with Strategic Staircases
- Case Study: Managing a Long‐Term Strategy Portfolio, Pacific Salmon Example
- Chapter 8 Takeaways
- Obesity as a Wicked Problem
- Overfishing: The Quintessential Wicked Problem
- Chapter 9 Takeaways
- Chapter Ten: Becoming a Great Problem Solver
- Appendix: Blank Worksheets for You to Try
- About the Authors
- End User License Agreement
- Title: Bulletproof Problem Solving
- Author(s): Charles Conn, Robert McLean
- Release date: March 2019
- Publisher(s): Wiley
- ISBN: 9781119553021
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