Problem solving is for everyday life, too!

Felicia Jia

Felicia is a business analyst in our Hong Kong office. After graduating from Dartmouth College in 2016 with a double major in government and psychology, Felicia worked in sales and trading at JPMorgan for two years before joining McKinsey. She’s interested in exploring a variety of functions and industries, especially e-commerce, fintech, and digital transformation. Outside of work, Felicia enjoys horse riding, seeking out breathtaking views, and trying out new products from startups.

November 8, 2019 There are so many reasons to work at McKinsey. You can learn from smart people, explore a variety of different industries and functions, and receive excellent professional training. I understood and expected these experiences when joining McKinsey, but what surprised me is that the skills gained at work have substantially driven my personal growth as well.  Specifically, three behaviors I’ve picked up along the way—a can-do attitude, structured thinking, and mindful communication—have really helped me make sound decisions and build better relationships. First, I’ve realized that having a can-do attitude is a great start to any challenge. For example, my mother recently asked me whether we should sell the family apartment in Hong Kong. Without any experience in real estate, my initial reaction was one of bewilderment. However, I quickly realized that like any other problem, common sense goes a long way, and that I did have the critical thinking skills to put together a coherent analysis.

issue based problem solving mckinsey

Second, adding structure to my thoughts almost always bring additional clarity, and the tools we use to problem solve at McKinsey are versatile and applicable to all types of issues. One decision I’ve been struggling with is whether to apply to business school. I found myself easily swayed by others’ opinions, and so I decided to draw an issue tree (please see picture). An issue tree is a tool we use to structure problem solving, and it breaks the problem down into mutually exclusive and collectively exhaustive components. Putting together an issue tree helped me realize which specific matters are at stake and identify areas where I need to do a bit more research. Third, practicing mindful communication has helped me become a better friend. At McKinsey, we’re taught the iceberg metaphor, which is used to illustrate that people’s words or actions may be influenced by dynamics that are not immediately visible. It’s encouraged me to dig deeper when having a difficult conversation. The person in front of me may be saying something or behaving in a certain way that confuses me, but instead of getting frustrated, I try to push myself to understand his or her underlying thoughts, feelings, and beliefs at that point in time. Remembering the iceberg metaphor has helped me become a more understanding person, and probably saved me from a few interpersonal conflicts. Looking back at my McKinsey experience, I feel grateful and empowered to have learned these life lessons. Problem solving can be for everyday life, too! Felicia

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Crafting Cases

The Definitive Guide to Issue Trees

Introduction, issue trees: the secret to think like a mckinsey consultant and always have a clear, easy way to solve any problem.

Ask any McKinsey consultant what’s the #1 thing you should learn in order to solve problems like they do and you’re gonna get the same answer over and over again:

“You’ve gotta learn to create Issue Trees.”

Issue Trees (also known as “Logic Trees” and “Hypothesis Trees”) are THE most fundamental tool to structure and solve problems in a systematic way.

Mastering them is a requirement if you want to get a job in a top consulting firm, such as McKinsey, Bain and BCG.

But even if you’re not applying for a job at these firms, they’re a powerful tool for any job that requires you to solve problems .

In fact, Issue Trees are the main tool top management consultants use to solve the toughest multi-billion dollar problems their clients have.

This guide will teach you how to create and use Issue Trees.  

I will give a focus on case interviews  but you can use this skill in any other problem solving activity. I personally use it everyday at work.

(Which means what you’ll learn here is gonna be useful for far more than merely getting a job.)

About the author

issue based problem solving mckinsey

I’m Bruno Nogueira.

I’m an ex-McKinsey consultant and I have learned to think using issue trees the hard way.

There were no good resources to learn this back when I was applying for the job.

Even within McKinsey there was no formal training. People just expected you to “get it” on the job.

After leaving the Firm, I’ve spent a few years coaching people to get a job in consulting, and I learned to teach this skill the only way possible: by actually teaching it!

Along with my partner Julio, I have taught 1000’s of people to break down problems in a structured way using issue trees.

And today I’m gonna teach you  how to do this.

In this guide you'll learn:

issue based problem solving mckinsey

Issue Tree Fundamentals

issue based problem solving mckinsey

Three Techniques To Build Issue Trees

issue based problem solving mckinsey

Six Principles For AMAZING Issue Trees

issue based problem solving mckinsey

Issue Tree Examples

issue based problem solving mckinsey

Common Mistakes and Questions

issue based problem solving mckinsey

How To Practice Issue Trees

issue based problem solving mckinsey

BONUS CHAPTER

Applying Issue Trees On The Job

Issue trees are the blueprint of how McKinsey (and other) consultants think.

They make your thinking process more rigorous and much, much more clear.

Unfortunately they didn’t teach you this well enough (if at all) in school.

They don’t even teach this in most Business Schools.

But if you learn to harness their power, you’re set to case interview success (and a career where every problem can be easily solved).

issue based problem solving mckinsey

How I learned about Issue Trees

A bit of a personal story first…

I first learned about Issue Trees from a friend who was working in management consulting. It was back when I was applying for a job at McKinsey, Bain and BCG.

This friend told me Issue Trees were the #1 thing I had to learn in order to do well on the interview and land a top consulting job.

And so, the first thing I did was to look for examples of Issue Trees.

And I found stuff like this…

issue based problem solving mckinsey

Not exactly rocket science, right?

But then I thought… “Alright,  what if my problem is not a profit problem?  Or what if I need to dig a little deeper than that?”

It didn’t take me long to find people on the internet telling me that you could use Issue Trees to solve any  problem!

Here’s how they illustrated this important point:

issue based problem solving mckinsey

Let’s be honest with ourselves here… This is NOT the best way to teach something!

And so I kept looking around. 

I wanted to see realistic examples of real Issue Trees consultants use to solve their client’s problems.

And if I was lucky, I hoped to find some explanation on why each example was structured the way it was.

Here’s the kind of stuff I found looking up on Google again:

issue based problem solving mckinsey

And now I was left wondering how to get from Point A (the simple profit Issue Tree from the beginning of this orange box) to Point B (the behemoth you see above).

And I also wondered if getting to this behemoth was actually the kind of thing I wanted in the first place. Would it help me in a real interview?

So I gave up on the internet and decided to learn Issue Trees from those who know it best: real consultants. That’s who I learned to build Issue Trees from.

But I know that most people don’t have access to real consultants with the time to teach them things. 

And it never stopped bothering me the fact that the internet had no decent resource to teach people of a skill that I use multiple times a day (and even make a living out of).

This is why I wrote this guide.

The 4 things you need to "get" to understand Issue Trees

Before we jump into the nitty-gritty of how to create and use your Issue Trees, I want to give you a high-level view. This high-level view is what we’ll cover in this chapter.

I’m gonna show you four ways to look at Issue Trees so you can get an intuitive understanding of them.

And I’m gonna show you that through an example of a realistic Issue Tree. 

They are a "map" of your problem

The first thing you need to know about Issue Trees is that they’re nothing more than a “map” of the problem.

Not just any map, but a clear  and rigorous  map. 

We’re gonna achieve those two goals by using a principle called “MECE”. (Don’t worry about it now, we’re gonna get you covered later on).

So suppose you’re an executive in a Telecom Company in charge of B2C mobile services (that is, cell phone services for regular people like you and me).

Imagine you have a client retention problem. That means too many clients are unsubscribing for your services/plans. 

How would you figure out what’s causing this problem?

Well, a smart executive would build a “map” of all the possible things that might be going on. This map is your Issue Tree and “the things that might be going on” are your hypotheses.

I’ll show you one of these, but before I do that, I will ask you to do one 15-second task:

**Action step: grab a piece of paper and make a list of all the hypotheses that pop-up into your head of why customers might be unsubscribing for this Telco’s mobile services.**

Now, take a look at this Issue Tree.

If I did my job right, every hypothesis you had fits one of the “buckets” in this tree.

How do I know that?

Well, I used the MECE principle I mentioned above to build this tree. This means every “part” of the problem is here and that each “part” is different/independent from each other. 

We’re gonna get back to this later.

The second thing to notice is that there are probably whole categories of problems you didn’t even think of when you wrote out your list of hypotheses.

You’ve probably thought about customers hiring a competitor service because they hate us for a variety of reasons (unreliable service, poor customer service) and you’ve probably thought about them leaving us because they were lured by competition somehow (low prices, free phones).

And if you’re savvy on the telecom industry, you might have even though about customers moving to pre-paid services.

But if my intuition is good, you have probably forgotten about at least a couple of categories within the “They’re being forced out” branch. 

For example, you might’ve forgotten to think that they may be cancelling subscriptions on purpose because they’re leaving a market.

Simple – I’ve done thousands of cases with hundreds of candidates to consulting jobs and most people forget about those.

The third thing to notice is that I didn’t even mention any specific hypotheses that you might have written on your piece of paper, things such as:

  • We’ve increased our prices and our competitors have dropped theirs
  • There were failures in our billing provider and a bunch of people were overcharged and got mad at us
  • Our network was down for several days due to a problem within our IT systems, leaving people offline
  • A problem in the banking system caused us not to receive several payments, which triggered subscriptions to be cancelled automatically

But still, all of these hypotheses (and thousands of others) would fit into one of the eight categories at the right-end of the Issue Tree.

All of this is to say that an Issue Tree is a map of the problem you have to solve.

Just like a good map it covers the whole problem area (you wouldn’t want a map of just a part of the territory you’re exploring).

And just like a good map, it doesn’t go into the slightest details (the specific hypotheses), but focuses on the broad aspects of your problem  (the categories).

No adventurer should explore a territory without a good map.

And no smart problem solver should start solving a problem without a good Issue Tree.

Issue Trees are the tool for "dividing and conquering"

Issue Trees are more than a mere map. They’re a very useful one at that.

For those of you who are not warfare strategy geeks like me, “divide and conquer” is a military strategy based on attacking not the whole of the enemy’s forces at once, but instead, separating them and dealing with a part of their forces one at a time.

It’s much easier to deal with one cockroach a hundred times than with a hundred cockroaches at once (sorry for the nasty imagery for all cockroachofobics out there).

Anyway, this strategy goes back into the times of Sun Tzu (the ancient Chinese philosopher who wrote “Art of War”).

And it so happens that this “divide and conquer” strategy is not only good for dealing with military opponents, but also GREAT for dealing with Big, Hairy, Complex problems.

It’s very difficult to deal with a “customer retention problem” like our Telco Executive is facing right now without making this problem more specific first.

But if you try making it more specific without the help of an Issue Tree (or a “problem map”), you’re gonna end up with one of two things:

(1) An incomplete list of possible hypotheses (like the one you probably wrote down on your piece of paper)

(2) A HUGE list with hundreds, even thousands of hypotheses (which, at the end of the day, you don’t even know if it’s complete anyway)

Issue Trees allow you to divide the problem and work on it one part at a time.

Or, if you’re a Telco Executive like our friend from point #1, you can delegate this work to other people now that the problem is neatly divided.

Here’s an example of how you can divide the problem into tasks and delegate its parts:

issue based problem solving mckinsey

On the left side are the 8 buckets at the end of our Issue Tree. These are the eight potential problem areas.

And in orange are the six tasks our executive must do to know what’s causing the problem. 

Many of them are actually just requests to other people within the company because when you use “divide and conquer” you get to give work to other people (which by the way, it’s a great way to grow your career quickly).

Depending on what they find Task #1, you may be able to stop there. Or you may need to do all 6 tasks and then some more as you find new, unexpected information.

Now, I know that this Telco Executive doesn’t seem like a really good professional when I put the Issue Tree and the tasks that way. He doesn’t even know the basics about what’s going on in his company!

But let’s pretend for a second that he was just hired and he’s not at fault for not knowing his company’s basic numbers.

Or that he’s actually a management consultant instead of an executive, and that he was hired to give this company’s executives an unbiased perspective of why customers are leaving.

Now things make more sense!

But the point is that the Issue Tree allows you to create a plan to solve the problem, just like a map allows you to create a route to get from Point A to Point B.

Issue Trees are excellent for prioritization

Not only Issue Trees let you have a “map” of the problem and help you create a “route” on how to solve it, they also give you the ability to anticipate a lot of stuff that could happen along that route.

And anticipation = prioritization.

(Or 80/20, for those of you who love the buzzwords).

Because Issue Trees lay out the underlying structure  of your problem, they help you with two things:

(1) Get data structured in a way that helps you quickly find out where the problem is

(2) Anticipate what happened with a moderate to high degree of confidence even before you get data.

Let’s tackle each of these individually.

(1) Issue trees help you get data structured in a way that’s helpful to prioritize the problem.

Suppose you’re the Telco Executive and you’ve built your Issue Tree.

Remember how his Task #1 was to ask the Business Intelligence unit of his company for hard data about what’s going on?

Let’s assume they came back with the data below – how would you prioritize the problem?

issue based problem solving mckinsey

The way I see it:

Of the 6.5 thousand extra people who unsubscribed this year compared to last year, the vast majority came (4.5) from a system failure. This is not acceptable and this should be the area this executive should tackle first.

But there’s also another area that calls my attention: our biggest source of customer churn – them going to competitors – has increased from 7k per year to 10k per year.

This person (and the company) has two different problems, and getting data in a structured format via the Issue Tree makes this very clear.

(2) Issue Trees help you make a really good guess of what might be going on even before you get any data

Suppose this company’s Business Intelligence division is not that intelligent and has no data to provide.

In fact, suppose this company has such a problem with data gathering that they can’t get structured data for pretty much anything.

This would make this problem a nightmare to solve.

With no structured data, this exec (or his subordinates) would need to do a lot of legwork to test each category of hypotheses:

  • To know if customers are hiring a competitor service, we’d need to call a large sample of them and ask
  • To know if a problem in our processes caused customers’ subscriptions to be accidentally cancelled, we’d need to map out all our processes that could’ve caused that and evaluate each one individually

You get the idea!

But Issue Trees are a map of the problem. And as any good map, we can use it to see what parts of the terrain seem to be more important than others.

Here’s an example of how to do that even if you have no data:

issue based problem solving mckinsey

Obviously you need to use logical reasoning and a bunch of assumptions to prioritize one of these categories as more likely than others. 

But in the absence of data that’s actually the best way to work!

So if I were this executive and there was no data, I’d try to work smart and start testing the most likely hypotheses.

This means I’d give more priority to the ones related to customers leaving us willingly. 

It customers were being forced out we’d have crazy call centers full of customer complaints and the executive would probably know about it already. We’d probably have some lawsuits already!

I won’t go into the weeds of how to prioritize as we already cover that in our courses (including our free 7-day course on case interview fundamentals) but for now it’s cool to know that Issue Trees are the tool  that enables you to prioritize effectively because it gives you a clear map of the problem.

You can have "problem trees" and "solution trees"

Last thing about Issue Trees that you must know to grasp what they are even before we can go into the specifics on how to build them is that you can have “Problem Trees” and “Solution Trees”.

Or, as I like to call them, “Why Trees” and “How Trees” .

“Why Trees”, also known as “Hypothesis Trees” are the one we’ve been working with so far.

You have a PROBLEM and you want to know WHY it’s happening. Then you create a tree with all categories of HYPOTHESES of why it happened.

Just like we did with our executive trying to fix the customer retention problem he is facing.

(By the way, this is why you can call them “problem trees”, “why trees” or “hypotheses trees”.)

But you can also use Issue Trees to map out SOLUTIONS.

This makes them really useful.

A consultant who can figure out what’s causing a problem every single time is a pretty good asset to the team.

But to have a consultant that not only can do that, but who can also figure out the best solutions to those problems every single time  is even better!

So let me show you how a “Solution tree” or a “How tree” is different from a “Problem tree”. 

Suppose our Telco Executive character did NOT have a customer retention problem. Everything is fine and clients aren’t unsubscribing from this company’s services more than the normal rate.

But, naturally, they still have some level of customer churn.

Let’s say that they want to make that level even better than it is today.

And then the executive team gets together for a meeting to “brainstorm” some ideas on how to reduce customer churn rates so they can grow revenues more.

What most people in this meeting are doing is to throw ideas on a whiteboard.

  • “Hey, perhaps we can improve our customer service.”
  • “Hey, maybe we should offer faster internet.”
  • “Hey, what if we put people into long-term contracts?”

But our Telco Executive is smarter than that. He has learned how to make Issue Trees with his friend, a McKinsey consultant. And he puts his learnings into practice.

**Action step: grab a piece of paper and build an Issue Tree with the CATEGORIES of potential ideas/solutions  this company could have to improve their customer retention.**

Now, word of warning: this “solution Issue Tree” is NOT perfect.

If you try, you can probably come up with an idea that could improve customer retention that doesn’t fit any of these categories.

And the reason for that is that it’s much harder to map out all types of possible solutions to a problem than to map out all types of possible causes to a problem.

But in case you do come up with an idea that doesn’t fit any of these categories, you can easily abstract what “type” of solution is this and then create a category for it.

Now, you might be thinking – “Bruno, why do I want to use Issue Trees for mapping out types of solutions? Why not just Brainstorm freely?”

There are three reasons for that:

(1) Your ideas are gonna be way more organized

This helps you communicate your ideas with others.

And it also helps you organize everyone’s ideas into a coherent whole.

And then better prioritize those ideas and even “divide and conquer” the implementation of them. You know, all the good stuff Issue Trees allow you to do.

(2) Creativity from constraints

This is counter-intuitive, but bear with me.

There’s significant research showing that having some constraints make people MORE creative, not less. (You can see some of the core ideas here ,  here and here .)

And we know that intuitively!

Well, try to create a short story in your head.

Nothing comes to mind, right?

Now try to create a short story that involves an English guy, a French woman, a train trip and a few bottles of wine.

It’s actually easier  to do the second, even though there are many more constraints.

Now, if I ask you to generate ideas on how to improve customer retention in a Telco company you’ll probably be able to generate 5-7 ideas until they start to become scarce.

But if I ask you to generate ideas on how to improve customer service in a Telco you’ll also  be able to generate 5-7 ideas until they become scarce. Even though improving customer service is just a sub-set of the things you can do to improve customer retention.

And then I could ask you to generate ideas on how to make it financially costly to unsubscribe and you might be able to give me a few ideas as well.

Each of the last two questions was a branch of our issue tree from above.

And because our Issue Tree above has 7 different branches, if you’re able to generate 5 ideas for each, that’s 35 ideas!

I’ve never met a person that can generate that many ideas with just the prompt question (how to improve customer retention) and without building an Issue Tree first.

Our brains seem to get confused with that many ideas.

But if you add structure (forced constraints), you can think freely about each part without worrying about missing something.

Which leads me to the 3rd reason why you will want to use “solution Issue Trees” whenever you need to brainstorm ideas…

(3) They force you to see whole categories of ideas you wouldn’t have seen before.

This takes a bit of practice, but once you’re able to see how each category fits the whole, you might see parts of the whole that you weren’t even seeing before.

Take the “Make it costly to unsubscribe” category for example.

When I came up with it, I was thinking about financial costs. You know, contracts and stuff.

But when I saw the word “financial” coming up in my mind, I immediately noticed that there could also be “non-financial” costs, such as having to go to a physical retail store to cancel the service or losing your dear phone number that you had for 8 years and all your friends and business connections have.

I didn’t have these “non-financial costs” ideas before I create the category for them.

Which is another big advantage for using Issue Trees to come up with solutions for your problems. You can see the larger picture.

So, what’s our take away from all this?

Simple. Issue Trees are a “map” to your problem that help you prioritize what’s important and “divide and conquer” to solve it more effectively. 

And you can use them to map out solutions as well.

Oh, and by the way, I almost forgot…

One really powerful thing you can do is to use “Problem Trees” to find the problem and once you found it, use a “Solution Tree” on your newfound problem.

So, remember how we used a “Why Tree” to find out that one of our Telco Executive’s problems was that his customers were leaving to the competitor?

Now we could use a “How Tree” to figure out potential solutions to stop our customers from switching to the competitors even though they don’t really like us and the competitor is offering a better offer than we are.

I’ll leave this Issue Tree for you to build.

And you’ll be able to build it using the techniques you’ll learn in the next chapter!

Three Techniques to Build Issue Trees

You can have all the theory in the world, but if you don’t put it into practice you’re not gonna solve any of the world’s toughest problems (nor get a job offer at McKinsey, BCG or Bain).

In this chapter we’ll go deeply into the mechanics of how to build quality Issue Trees.

More specifically, we’ll go through three practical techniques that you will be able to apply in your next case interview or executive meeting to structure any problem.

issue based problem solving mckinsey

The structure of an Issue Tree

Issue Trees are a “problem structuring” tool.

That means you can structure problems using them.

But even Issue Trees have an underlying structure to them. It gets a bit “meta” and abstract, but the point is that every Issue Tree shares some similarities with other Issue Trees.

Knowing these common characteristics is the starting point to being able to successfully build them, so I’m gonna go over that in this short section.

And I’ll be quick, I promise.

(Note: I’m gonna give names to some stuff so that you and I can talk more effectively over the rest of the guide, but you don’t have to memorize those names nor use them in case interviews.)

So we seem to always keep coming to this MECE thing, don’t we?

We have a whole article series on that , and I highly recommend you to go through it. 

You can do so right now and then come back to this guide or you can read this guide first and then go there to understand how to make each part of your Issue Tree MECE.

Now, I don’t want to break your reading flow here…

So, before you open a new tab on your browser and get into another rabbit hole, let me explain what MECE is in simple terms.

MECE means Mutually Exclusive, Collectively Exhaustive and it is a basic principle of organizing ideas that was popularized by ex-McKinsey Barbara Minto (from the book on the Pyramid Principle, you might have heard of that) but  goes back to the ideas of Aristotle  (yes, the greek one!).

It basically means your reasoning has no gaps (Collectively Exhaustive, all parts together exhaust the whole) and no overlaps (Mutually Exclusive, one part is different and independent from the other).

issue based problem solving mckinsey

Easy, right?

Well, kind of. Most problems out there are harder than drawing rectangles. 

So, to give you a better idea of how to apply the MECE principle to a business problem, here’s an image from our article on  The 5 Ways to be MECE  of different MECE ways to break down the same problem:

issue based problem solving mckinsey

No need to worry about understanding this whole image right now, but the idea behind it is that (i) there are 5 types of ways to break down the problem in the image’s title (or any other problem) in a MECE way, and (ii) you can build different structures within each type.

An Issue Tree is built using a lot of these MECE structures. You also need to know how to pick among different options when you find more than one way to break down a problem..

I’m gonna link to the article on the 5 Ways to be MECE again  because it’s the best way to learn about MECE in a practical way. Instead of a bunch of theory, I show actual techniques you can apply right now to any problem in that article.

Anyway, enough with MECE. Let’s jump into the actual techniques to build Issue Trees.

Technique #1: Create a Math Tree

Math Equations are ALWAYS MECE.

Equations have no gaps and no overlaps (otherwise they wouldn’t be equations).

Which is why I used rectangles within rectangles to explain MECE above. Rectangles are huge in mathematics if I remember my high school math right.

Anyway, one easy way to create MECE trees is to take advantage of that and ALWAYS break down the next level using a math equation.

Obviously you can only do that if your problem is numerical.

But since most business problems are  numerical, we’re in luck!

I’m gonna show you how to do this in a “slideshow” kind of way because I wanna show you in a very step-by-step fashion, so be prepared to click on the arrow button more than a few times:

Creating math trees as a way to create Issue Trees isn’t hard at all once you get some practice.

But some of its nuances can be deceiving. Most people see them done and think they can easily do it, but it all goes downhill when they actually grab a piece of paper and attempt to do these trees.

So, here are four methods to actually create your “mini-equations” to break down each bucket:

#1. Use a proven formula

Most of the time you don’t need to reinvent the wheel.

If you know a formula that fits the problem well, just use it!

The most common one here is the classical Profits = Revenues – Costs, but there are others as you can see on the image below…

issue based problem solving mckinsey

You don’t need to memorize any formulas for your case interviews, as you can use the other methods and they will work.

But knowing some of these, especially the most basic ones does help a lot.

#2. The "Dimensional Analysis" method

This one’s my favorite!

Just find one direct “driver” of the variable you want to break down – a driver is a “fundamental cause” for that variable.

For example, one direct “driver” or “cause” of revenues is the “# of customers” you have. If you get more customers, these new customers  directly cause your revenues to increase.

Then, use dimensional analysis to find its mathematical complement. If you want “REVENUES” and you have “# OF CUSTOMERS”, you need to multiply that by REVENUE/CUSTOMER.

Just like in your high school physics class, customers on the numerator will cancel out with customers on the denominator and you’ll be left with REVENUES as a metric – exactly the one you’re aiming for.

This method is amazing because it lets you break down almost any metric into a formula really quickly – the only thing to be careful with is to not lose meaning in the process and end up with a formula that is mathematically right but doesn’t make any sense to actual human beings.

issue based problem solving mckinsey

#3. The Funnel method

This works wonders when the target metric is a percentage or is the end result of a funnel.

Take one example from e-commerce: Conversion Rate.

This is the % of visitors in your website that buy from you. How can you break that down?

Simple, you multiply the steps of the funnel from visitor to buyer.

issue based problem solving mckinsey

Funnels are everywhere: Sales, Product Development, Process Optimization. 

All you have to do is to find these funnels and then break them into stages.

#4. Use a sum of segments

This is my least favorite method because it doesn’t go too much into the structure of the problem, but simply slices it out.

However, it can be useful.

For example, if you’re working with a conglomerate and their profits are down, it might be useful to segment that conglomerate into its different businesses.

Or if you’re trying to understand a company’s market share drop in a certain category, it might be useful to just break it down into the market shares of its product lines.

If you’ve read  the article on the 5 Ways to be MECE  and you’ve been paying attention, you might have noticed that method #1, “Using a proven formula” and #2, “Dimensional Analysis” will get you an Algebra Structure. 

Method #3, “The Funnel Method” will get you a Process Structure. 

Finally, method #4, “Sum of segments” will get you a Segmentation type of structure.

If you haven’t read the article, don’t worry about these names – they are some of the ways to be MECE we teach there. I’m just helping the folks who did read it already to make the connections.

So, summing up. You can use any of these four methods to create a “mini equation” and you combine these “mini equations” to create a “Math Tree”, which is the first technique to build and Issue Tree.

And it’s a technique that works great with numerical variables, but doesn’t really work if you have a different type of problem to solve.

So, to tackle non-numerical problems – or even to make better  Issue Trees for numerical problems – let’s move on to the most powerful technique in your Issue Tree toolkit: layering the 5 Ways to be MECE.

Technique #2: Layering the 5 Ways to be MECE

Technique #1 works great because math is ALWAYS MECE and because creating equations isn’t too hard.

But not every problem is numerical and can be structured using equations alone.

And even to those problems that are numerical, doing a Math Tree isn’t always the best way to go about structuring them.

Here’s where Technique #2 comes in – instead of layering “mini equations” on top of each other, we’re gonna layer “mini MECE structures” on top of each other, regardless of them being equations or not.

Remember, we were confident to use math equations to build Issue Trees because they are always MECE. But from first principles what we need is MECE structure, not necessarily mathematical ones.

And where are we gonna find these “mini MECE structures”? 

Easy, with the 5 Ways to be MECE. These are 5 specific techniques we’ve developed that guarantee a MECE structure.

I’ll make your life easier in case you want to read about that now and link to  the article  we wrote about them.

But here’s a quick recap:

issue based problem solving mckinsey

The process of building Issue Trees by layering the 5 Ways to be MECE is itself very very similar to the process to create Math Trees.

Step #1: Define the problem specifically  (no need to be a numerical variable here).

Step #2: Break down the first layer using one of the 5 Ways to be MECE.

Step #3: Get to the 2nd (and 3rd, and 4th) layers by breaking down each bucket into another “mini MECE structure” that comes from the 5 Ways to be MECE as well.

I’ll show you the exact process to create an Issue Tree by layering the 5 Ways to be MECE through the example below:

Layering the 5 Ways to be MECE is my go-to method to create Issue Trees and break down problems or finding solutions.

I use it every day of my life, either on paper or just in my head.

And I used to use it everyday when I worked at McKinsey as well (even though I was doing it unconsciously – no one there had explicitly told me there were five  ways to be MECE).

Now, let me address one thing that comes up often… One thing that may have crossed your mind as you were going through the three steps above regarding the Issue Tree is “well, but this is so obvious” .

That thought may have crossed your head in each break-down of a bucket or just when looking at the whole Issue Tree.

And here’s my take on it: a well-structured problem SHOULD look obvious – at least in hindsight .

How Elon Musk changes the world structuring problems in "obvious" ways

(I swear to you it’s interesting, but you can skip this green box if you want and/or understand why MECE Issue Trees are super important even when they’re “obvious”)

You’ve probably heard of Elon.

In case you haven’t, he’s this guy…

issue based problem solving mckinsey

And he’s created these companies…

issue based problem solving mckinsey

So, the guy basically transformed the payments industry, the automotive industry, the aerospace industry and is transforming the tunneling and the solar power industry.

But how does he do that?

Well, anyone who does that much has many “secret sauces”, but one of the special things Musk has is to think things from first principles.

In this fantastic blog post  (from one of my favorite blogs), a guy who had access to Musk breaks down exactly how he thinks.

But let’s analyze one specific instance: how he came up with “The Boring Company”, a company that was created to dig tunnels more efficiently and solve the traffic problem in Los Angeles.

There are two underlying logics to the company:

issue based problem solving mckinsey

Simple logic, but a really strong reasoning about why tunnels are probably the best way to solve the traffic problem.

(And it actually is the only way that’s ever worked so far – demand for roads keep increasing no matter how many Uber rides people take, building more roads doesn’t seem to make a difference in most cities and no one’s ever been able to make flying cars… But most people in large cities take the subway/metro system every single day.)

Notice that we’re basically dividing the problem into supply and demand and then dividing “road” capacity into on ground, flying and underground. 

There’s no rocket science here (pun intended).

Alright, but there’s still a problem with tunnels: they’re expensive to make. So, is it possible to make them cheaper? Here comes Elon’s Logic #2 to build The Boring Company:

issue based problem solving mckinsey

Again, no rocket science here (although a bit of tunneling science).

If you want to understand better how Musk thinks, I recommend  this article  and  this TED Talk .

Now, onto what matters for us: 

(1) Most traffic specialists know that trying to reduce demand is an uphill battle and that expanding road capacity is mostly fruitless.

(2) Most people in the auto/aerospace industry know that flying cars are a very far away dream

(3) Most people in the tunneling industry understand the cost drivers of a tunnel.

And yet, no one looked at the big picture and questioned things from first principles.

You need an Issue Tree to do that, even if it’s an obvious one.

I’m not saying Elon Musk draws Issue Trees for a living, but I know  he has them in his head because he talks like he has one – I “took” both trees I showed you above from his own words.

Takeaway from the green box: Issue Trees are “obvious” because they’re drawn from first principles.

And this means if you want to think from first principles, draw Issue Trees.

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Technique #3: creating decision trees.

In the realm of Microsoft Excel, the most basic kind of logic you can do is using math operators. That is,  adding, subtracting, multiplying and dividing.

If you wanna go a step further you can use what they call “boolean operators”: AND functions, OR functions and so on.

And if you want to go a third step further, you can use “conditional operators”, the most famous of which are IF functions.

Decision Trees are basically regular Issue Trees with “conditional operators”, IF-THEN functions.

Now, let me translate into plain English for all the non-Excel nerds out there…

(Or should I say “future Excel nerds? I mean, this is a site for aspiring management consultants!)

When you do a Math Tree, the only way you have to relate the variables to each other is through math symbols. E.g.: Revenues = Price * Quantity. There is a mathematical relationship among everything in your Issue Tree.

It is great to have math because math is always MECE, but it is also limiting. What about everything that can’t fit an equation?

Enter Technique #2: Layering the 5 Ways to be MECE.

If you pay attention to it, everything that’s not in a mathematical relationship in that technique is joined logically by “AND” or “OR” relationships.

For example, we can find better employees ‘at the schools we already recruit in’ OR ‘in new schools’.

Another example, we can make new recruits better before their first project ‘by training them before they start’ AND/OR ‘as soon as they start working for us’.

Decision Trees are just like regular Issue Trees but they add another layer of logic to it: IF-THEN statements.

I won’t go into too much detail on how to build them because (1) it’s an advanced skill to be able to anticipate all the if-then logic required to take a decision before you even start exploring the problem, and (2) you don’t need to be able to do this to get a job at McKinsey, BCG or Bain if you can use the other two techniques well.

But I will give you a simple example below so you can see what I mean.

And if you want to learn more about this,  here’s a timeless article from Harvard Business Review on Decision Trees.

issue based problem solving mckinsey

There are also different types of decision trees.

For example, you can create a decision tree for an investment opportunity that considers the probabilities of different events to happen in order to calculate the expected value (there’s an example of this in the HBR article I’ve shared above).

Or you can create decision trees for WHY and HOW problems where you use IF-THEN statements to say where would you focus and prioritize if certain conditions applied.

(An example of the last phrase is this: in a case on “How should a restaurant grow revenues”, you can say that IF it has lines/too much demand, THEN you would focus on increasing capacity through expansion or increased productivity, and that IF if doesn’t have enough demand, THEN you would focus in customer acquisition and retention initiatives.)

Decision Trees can get really complicated even for simple decisions, so I would NOT recommend you to start learning with them. 

Focus on Techniques #1 and #2 to solve WHY and HOW problems.

For “decision-making”-type problems, we recommend you to learn Conceptual Frameworks first. We teach how to structure these problems using Conceptual Frameworks in our free course on case interview fundamentals.

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Six Principles for AMAZING Issue Trees

Man does not live by bread alone.

And Issue Trees need more than being “technically correct”

If Issue Trees had a “soul”, it would live in the six principles outlined in this short chapter.

In fact, if you follow the principles from this chapter, you don’t even need to use any of the three techniques I showed you on the last chapter.

And if you MASTER these principles, you might be able to come up with your own techniques. 

(And if you do come up with a “fourth technique”, please shoot me an e-mail telling me about it).

issue based problem solving mckinsey

Separate different problems early on

Some restaurants that want to grow revenues should work on getting more clients. Others have too much demand and should work on expanding their operations to handle that and sell more.

Most companies that have employee attrition problem have some problem that makes people wanna leave their jobs. Others are just firing too many people.

And a violence crisis in a country could be caused by criminals. But it could very well be caused by a really violent police system as well.

The common factor between the last three situations is that each one could be caused by two COMPLETELY DIFFERENT PROBLEMS.

Separate them early on your Issue Tree because trying to fix the two things together will only lead to confusion. Not good.

Build each part ONE AT A TIME

Most people who see a huge Issue Tree for the first time are overwhelmed.

Of course they are! 

They see this huge logical structure (that takes time to digest) and wonder if they’ll be able to do the same when they need to.

What they’re missing is that these trees are built one step at a time .

First you get the problem question and your only concern  is to define it well.

Then your only concern  is to break it down into a first layer.

Then you get each bucket from the first layer and your only concern  should be to break each down into a “mini MECE structure”.

One bite at a time, you will eat the whole metaphorical elephant.

Each part must be MECE

I’ve talked about MECE before in this article, but I’ll do it one last time.

ME = Mutually Exclusive =  No overlaps  between the parts of your structure = your structure is as clear as the blue sky for another person to understand.

CE = Collectively Exhaustive =  No gaps  in the way you break each part of your structure down = your structure is rigorously correct.

MECE is tough for most people, but you can use  the 5 Ways to be MECE  as a checklist of structures you can use to be MECE. 

That means it’s not gonna be as hard for you and you have more chances of getting the offer than the other people. Good for you!

Each part must be relevant and add INSIGHT to the problem

There are many MECE ways to break down any problem.

Choose the one that’s more relevant. The one that adds more insight to the problem.

For example, one of the Issue Trees from Chapter 2 was about improving the quality of new recruits in a consulting firm. Within “making the selection better”, I could’ve broken it down into “Stages 1, 2, 3” and so on of the selection process. 

That would’ve been “technically correct” and “MECE”, but it would bring absolutely no insight to the table. 

Because it wouldn’t be problem-specific .

Here are two resources to help you make your structures more insightful and problem-specific:

The first is  a Youtube video on how to make better revenue trees.  It shows how to create more insightful revenue trees but you can apply the same principles to any type of Issue Tree.

The second is “The Toothbrush Test”, a numerical measure so you can get a proxy of how insightful one structure is compared to another. You can watch the video  here  or read the article  here .

Each part must be eliminative and help you FOCUS to the problem

An Issue Tree that is built in a way that allows you to ELIMINATE all the non-problems and focus on the one thing that’s driving the issue is way more useful than one that does not allow you to do that.

Say you’re a soft drinks company concerned that you’re selling less soda.

Here are two ways to structure the first layer of that Issue Tree:

(1) Drop in general soda consumption OR Drop in market share

(2) Customers less willing to buy product OR Competition getting stronger OR Company doing poor marketing or supply chain OR Distribution channels not exposing our product

Which one’s better?

Well, according to this fifth principle, (1) is better because it allows you to get data and eliminate a whole branch (unless the problem comes from both, of course).

Eliminative Issue Trees help you FOCUS the problem and waste less time (that means more 80/20 for you).

The key to be eliminative is to make each bucket FALSIFIABLE. 

Falsifiable means you can find a test that, given a certain result , guarantees that the problem is not on that bucket.

This falsifiability is what makes Issue Trees “hypothesis testing” structures. If you want to be a hypothesis-driven problem solver you need to include falsifiability in your structures whenever you can.

However, this does not mean every single structure  you create must follow this principle.

There are times where falsifiability is impossible , and that means you should focus your efforts in being the most insightful as you can (Principle #4).

It is usually in these situations where you’ll want to use a qualitative, conceptual framework. You can learn more about this in the free course we offer on case interview fundamentals. In the Frameworks module of the course we will show you exactly when to use conceptual frameworks and how to create them.by 

Clarify what you need in each layer you build

You might be shy, but hey, overcome that shyness!

You don’t need to do guesswork to build your structures. You can ask first.

Actually, doing guesswork when you could’ve asked a simple question and eliminated confusion will harm your performance.

Say you’re breaking down how a consulting firm could hire better junior consultants. You’re trying to break down how they select candidates, but you’re not sure how their recruiting process is currently like…

Say to your interviewer: 

“Hey, I want to break it down into the stages of the selection process but I don’t know what those stages are. Here’s what’s on my mind… Does it make sense or did I miss something?”

If you’re doing Issue Trees to solve a problem in your work, this principle is even more important. You can’t structure what you don’t understand, so when in doubt ask questions and understand it better!

Sometimes these principles will enter in conflict with one another.

You might need to choose between being more eliminative and being more insightful.

You might feel in doubt of whether you should be fully exhaustive (MECE) or just add the relevant stuff.

And when principles enter in conflict, experience and judgement are here to save the day. 

Seeing real examples of real people that know what they’re doing making Issue Trees to solve case interview problems is invaluable to get that experience.

Which is why I will show you in-depth examples in the next chapter, including videos of me going through the thought process of building Issue Trees with you.

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When I was preparing for my case interview I looked for good Issue Tree examples all around.

I found none .

I don’t want you to go through the same, so here I’m gonna go all in and not only show you great Issue Trees but also show you, in video, how I think through each step of building them.

I’ll show you everything that goes through my mind as well as the specific nuances that make them great.

issue based problem solving mckinsey

I will use different examples so you can see how the principles and techniques apply to different types of situations.

And I will do exactly what I’d do in a real case interview on when solving a real problem at work.

The only thing I’ll avoid doing is using Decision Trees.

Because it’s much much harder to get to a MECE result using them, let alone explain why it’s MECE. I’d be only showing off instead of actually helping you learn how the principles apply and what makes a great Issue Tree. 

Not my style!

Example #1 - Airline fuel costs surge

This first example is of a fairly easy case question that would lead many well-prepared candidates to failure.

It’s funny how some problems can be easy  to real consultants and yet hard  even for candidates who have done 50+ cases.

Here’s why this happens: the business problem isn’t hard to solve from a first principles perspective (which is how good consultants tend to think) but they’re a bit unusual or too specific to an industry. 

Most candidates who haven’t internalized the principles of solving problems well feel overwhelmed when they get a case completely unrelated to anything they’ve seen before.

Even worse is when this problem doesn’t fit the half a dozen frameworks these candidates have memorized by heart.

Here’s a video of this first example. I highly recommend you to try to structure this Issue Tree by pausing the video right after I clarify the case question and then compare your structure and your thinking process with mine.

If you don’t have access to audio or can’t watch a video right now, you’ll be able to keep reading and grasp the main insights as well, although I highly recommend you come back to watch this later!

So, what’s interesting about this Issue Tree example is that I have structured the first two layers of the tree as a Math Tree (Technique #1) and then I used the “Opposite Words” technique and the “Conceptual Frameworks” technique to build layers 3 and 4.

You can do that too!

Here’s the whole Issue Tree if you weren’t able to watch the video: 

issue based problem solving mckinsey

There were three main take aways from this structure:

Takeaway #1: Break down a numerical problem mathematically as long as the math remains meaningful/insightful – then get more layers using qualitative “mini-MECE-structures”

As with most thing problem-solving related, this is not a rule written in stone.

There are a few numerical problems that are best structured with a qualitative structure. And you don’t always need to do the qualitative layers afterwards.

But usually the best way to break down a math problem initially is to break it down into an equation first, as you’ll be able to quantify how each driver contributed to the problem.

And usually the equation alone won’t be enough to bring you to the meaningful stuff. 

In this case, for example, if we were only mathematical in our structuring we would have missed important elements that show real world business intuition, such as “maintenance”, “aircraft weight” and “mix of aircraft in the fleet”.

Takeaway #2: Stop each branch when it can reasonably  explain the source of the problem

I have stopped some parts of my tree in Layer 2, other parts in Layer 3 and others in Layer 4.

How did I make this call?

A lot of people have asked me this in the past: how can I know that my Issue Tree is done? How many layers do I need?

The rule of thumb is to stop when your buckets can reasonably explain the problem.

For example, on Layer 2 you have a bucket which is “# of trips flown has risen”. This can reasonably explain why fuel costs might have risen. It’s pretty logical – if you fly more trips, your fuel costs will rise as well.

Now, one could ask “why has the # of trips flown risen” and if that’s the actual problem going on, I as a consultant would want to know that. But that’s getting granular, you don’t need to go that far unless the problem is proven to be there.

If I told my mom or someone on the street that an airline’s fuel costs have risen because the # of trips have risen, they’d accept the answer and probably not question it further (and they certainly would tell me I’m a weirdo for caring about an airline’s fuel costs).

Now, if I told my mom or a random guy on the street that fuel costs have risen because liters of fuel per km flown have risen they would: (1) think I’m really really weird, and (2) not take that answer as it is.

Even if I used more accessible language and said that this airline’s fuel efficiency was down, they’d still ask me “why is it down”? (That is, assuming my mom is actually interested about airlines).

If I had stopped that branch on the 2nd layer, I wouldn’t be telling the whole story. 

And so I went a level deeper.

Now, on the 3rd layer if I say that fuel efficiency is down because we’re using less efficient types of aircraft, most people would be satisfied with that answer. I can stop the Issue Tree here.

But in the case we’re flying the same aircraft, most people would NOT be satisfied. They’d be like “Hey, you’re telling me you’re less fuel efficient even though we’re flying the same aircraft? How come?”

And so we dig a level deeper on that one. Maybe the aircrafts are flying with more weight. Or we’re doing less maintenance. Or we’re flying at lower altitude and facing denser atmosphere. Or our pilots are changing speed all the time. 

Most people would take any of those as sufficient answer. Which means we don’t need to dig a level deeper.

Takeaway #3: You can still go deeper in the buckets you need

If the last take away gives you an idea on where to stop structuring the Issue Tree, this one gives you permission to dig deeper than that.

Say your interviewer tells you the problem is that this airlines is flying their planes heavier and asks why that might be. Well, weight was at the end of our tree, right? But we can still investigate the reasons behind that increased weight.

Here I would segment the things that add weight to airplanes into their categories: people, cargo, equipment, fuel itself (we may be flying with excess fuel and thus spending more fuel to carry fuel itself).

Or say that the interviewer tells you that fuel prices have gone up even though we’re buying the same product from the same supplier. 

Why that might be happening?

Well, either this supplier’s cost has gone up (because crude oil is up in price, for example) or their margins are higher (because we’re not negotiating as well, for example). We could dig deeper into each one of these factors if need be.

The point here is that even though you need somewhere to stop your Issue Tree (otherwise you’d spend the whole day building 15 layers), you also need to be aware that you can go as deep as you need to in the specific parts of your structure that the problem really is.

You find where the problem really is by getting data, numerical or not, for each part of your structure.

Example #2 - Overwhelmed consultant productivity

Real consultants have their own personal problems to solve as well.

And often time they will solve them with Issue Trees!

They’re a great way to see what your options are.

So before you look into this example, I want you to do an exercise:

**Action step: grab a piece of paper and write down all ideas you have to become more productive in case you were overwhelmed with work as a consultant**

What you’ll see from this exercise is that if you just “freely brainstorm” ideas to improve productivity on paper, you’ll end up with a huge list of (probably) unconnected action steps that are hard to estimate impact and to prioritize.

But if you had built an Issue Tree to organize those ideas , you’d get something much closer to an actual system to improve productivity.

Here’s what I mean by that:

This tree is solving a more qualitative problem than Example #1, but the techniques still work.

You define the problem really specifically at first.

And then you layer different “mini MECE structures” using the techniques from the 5 Ways to be MECE.

Here’s the final Issue Tree in case you couldn’t watch the video:

issue based problem solving mckinsey

Of course your tree can still be different than this one and still be correct.

How do you know if it’s correct or not?

Well, simple: are you adhering to the key principles? Are you using the techniques I have shown you in this guide?

If so, your Issue Tree is good to go!

Example #3 - Help a government solve illiteracy in children

This is an interesting example because it focuses specifically on Principle #1: Separating different problems early on.

In fact, the whole Issue Tree is built by separating different problems over and over again.

Because the problem to be solved has many different possible root-causes that are completely different from each other.

Once you watch the video, you’ll see that the way the Issue Tree is constructed in a very intuitive way. 

However, give this problem to most people and they aren’t able to structure it. They’ll spit out ideas and hypotheses without order nor an overarching logic.

Check it out how to help a government solve illiteracy in its children that go to public schools:

If you couldn’t watch the video, I’ll put an image of the Issue Tree bellow.

Notice how each layer is basically the previous bucket divided into two completely distinct problems.

The value of building Issue Trees like this is that you get a map of all types of possible root-causes. It’s also pretty easy to do so!

issue based problem solving mckinsey

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Common mistakes and questions.

I’ve helped hundreds of people learn to build Issue Trees.

In the process I’ve seen them making thousands of Issue Trees. And probably somewhere north of tens of thousands of mistakes.

Making mistakes if part of the learning process.

But you don’t have to make all those mistakes yourself because you can learn from theirs!

In this chapter I will show you the most common mistakes people make (with real Issue Trees, from real candidates) and also answer some of the most common questions that arise as you learn to build them.

issue based problem solving mckinsey

What you can learn from the key mistakes of real Issue Trees from real candidates

When I first wrote the  5 Ways to be MECE article  I had a little challenge in the end of it.

I challenged people to send me a structure for a specific business problem that could happen in a case interview: 

“Imagine you’re doing a project with Amazon and they’re complaining about a surge in theft in their warehouses – what could be causing this surge in theft?”

And so I got dozens and dozens of real Issue Trees from real candidates for the same problem.

What’s fascinating is that all these candidates had three things in common:

(1) They were having trouble with creating MECE structures for their cases (or else why would you read a huge guide on how to be MECE?).

(2) They had just read a huge guide with different techniques to be MECE and instructions on how to build Issue Trees using these techniques.

(3) They were dedicated enough to take my challenge, spend 10-20 minutes building their best Issue Trees and sending them to me.

Still, even with all those things going for them, most of their Issue Trees had mistakes. Mistakes you and I can learn from.

So in this section I’m gonna show you their trees, point out their key mistakes and show you the feedback I sent them.

#1 - Anastasia and the sin of ignoring problem definition

The first Issue Tree I wanna show you was sent by Anastasia.

Here it is:

Seems like a quite good Issue Tree, right? 

I mean, it describes quite well the process of a warehouse.

Well, not quite.

There are a few mistakes that this Issue Tree makes in terms of MECEness, some parts could be more insightful, etc. But the most important mistake here is that Anastasia ignored the specificity of the problem.

Much of this Issue Tree isn’t about theft – it is about losing items in general. So she’s talking about damage, negligence, machine mistake, etc.

Go back to the image above and click the right arrow to see all the areas of this tree that are not about theft at all.

Most of the tree is not talking about theft at all!

What that means is that she’s talking a lot about things unrelated to the problem and leaving a lot of important things out. It also implies that she wasn’t listening to the problem.

This is the #1 thing I’d tell Anastasia to focus on and the #1 thing I’d tell you to make sure you’re not messing up.

Now, Anastasia’s structure also has a #2 thing that I’d tell her to focus on if problem definition weren’t a problem: look for root causes. 

While she makes an excellent description of how the warehousing process is and thus is able to map out where  the problem might be, she never talks about the why.

You know, things like security systems and lack of penalties and having warehouses in areas with a lot of crime. The types of things you might expect for a WHY question…

#2 - How Anne messed up with layer ordering

This Issue Tree is actually quite good!

But it has three main mistakes. Can you guess what they are?

issue based problem solving mckinsey

Well, I gave you the main one in the title.

Anne’s first layer shouldn’t be a first layer. 

Because geographical location is not all that important. The different geographical areas of the problem aren’t the most relevant way to break it down.

What’s more, even if it were, why divide by continent? Why not small vs. big cities? Or low income vs. high income areas? Or high-crime vs. low-crime areas?

Anyway, I think it’s an excellent idea to mention that you’d like to see in which warehouses is the problem more prevalent. But what I would’ve done is to put that as a side note to an Issue Tree that actually digs into the potential causes of the problem, not as the main course.

She could’ve done an Issue Tree of causes for one  warehouse and then said at the end: “and then I’m gonna look at these causes for all warehouses we have, segmented by geographical area, warehouse size, how old they are, etc”.

And what would this Issue Tree that digs into the potential causes look like? 

Well, very much like Anne’s example Issue Tree for American warehouses (which I guess she would replicate for other continents as well).

Now, you might be thinking: what are the other two mistakes she made?

Well, one is that she offered solutions to each root-cause of the problem. That’s not a mistake in itself. In fact, I loved it. But the problem is that she was a bit too early on that – she should’ve gone a layer deeper into the why  each thing happened.

Keep in mind the case question was a WHY question and not a HOW question. 

And what she did was to suggest, for example, that if internal thieves who had the intention of stealing were responsible for the surge in theft, then they should run better checks.

What she should’ve done instead was to say that if that was the cause, then that caused happened because (a) they’ve stopped doing background checks, (b) background checks have worsened in quality or (c) background checks were never good at stopping that but that was never a problem beforehand. And then perhaps dig even deeper into the cause.

But she offered solutions before she got to the root cause, and that may hurt because she may be solving the wrong problem.

And the last mistake she did was one related to problem definition.

Everything she mentioned was related to the amount  of theft. But we don’t know if that’s the problem. It’s not clear on the case question (on purpose). Maybe the problem is the value  stolen.

So, she would’ve done much better by showing that in her structure. Maybe there are more thefts (in which case her issue tree is valid) and maybe the amount stolen per theft is higher (and because she didn’t consider this, she missed a whole part of the problem).

#3 - Guillaume and the "aggregator fallacy"

There are many problems with the Issue Tree below, for instance:

  • A regional segmentation early on when that’s not a really relevant factor to explain the problem (as in Mistake #2)
  • This regional segmentation isn’t even MECE (there are emerging countries in Europe and he forgot all developed countries in Asia)
  • A lack of $ value of theft (again, as in Mistake #2)
  • The way he breaks down a process structure to explain a surge in # of thefts per warehouse isn’t very insightful/relevant

But I want to call your attention to one other mistake which is related to causal effects. I call it “the aggregator fallacy”.

Can you spot it?

issue based problem solving mckinsey

Let me ask you one thing… If the number of gas stations raise in a city by 2X in a year, will sales of gas increase by 2X as well?

Will they even increase by 10 or 20%?

Not necessarily!

More gas stations don’t drive  more demand for fuel (unless there’s very few, high priced gas stations in town, but let’s leave extreme scenarios aside).

Yes, there might be 2X the number of gas stations because demand skyrocketed. But it could also be the case that gas stations were a really profitable business and entrepreneurs entered this market even thought there was no increase in demand. 

It could also be the case that some people who don’t know what they’re doing entered the market even though demand didn’t increase and profits weren’t that high (and everyone’s losing money now).

So if you were to find out if demand for gas increased in a town one MECE structure you could use is “# of gas stations * avg. amount of gas sold per station”, but that wouldn’t be the best one.

Because # of gas stations don’t drive  demand – more cars and more usage per car does.

The same thing is happening with Guillaume’s structure. 

More warehouses don’t drive more theft. They don’t cause  more theft.

Say, for example if Amazon had restructured their operations and they had switched from 10 huge warehouses to 100 smaller ones, with the goal of having faster delivery. Would it be ok for theft to increase 10X? Would it even be ok for it to increase by 50 or 100%?

Probably not, right? 

Amazon’s carrying the same number of items, they have roughly the same number of employees (considering internal theft) and if they have their security systems in place, they’re not necessarily more attractive to external burglars (if anything, it’s harder to steal a smaller warehouse than a huge one).

More warehouses shouldn’t cause more thefts. The warehouse is not a driver of stealing just as the gas station is not a driver of demand for gas.

The warehouse and the gas station are merely aggregators  of something. The warehouse aggregates products to be shipped (or stolen) and the gas station aggregates fuel to be sold (or not sold in case of a flat demand).

Which is why I call this mistake “the aggregator fallacy” – thinking that because the aggregator has increased that it has caused your problem.

Instead, try to build your Issue Trees with some causal relationship in mind. In the case of the gas station problem, that’d be “# of cars * fuel used per car”.

In the Amazon theft case, you could use “# of products in the warehouse * theft rate” if you assume that more products cause more demand for burglars or “avg. crime rate where Amazon warehouses are located * % of those crimes that are in Amazon’s warehouse” in case you assume that overall crime rate is a given and you can only control your exposure to it.

#4 - Jimi, the unMECE

Again many problems with this Tree. 

You can mistake-hunt later at your own pace, so I’ll just point out to the ONE FATAL MISTAKE YOU SHOULD NEVER MAKE:

issue based problem solving mckinsey

Jimi wasn’t MECE on the first layer of his Issue Tree.

In part because he insisted on using a conceptual framework (the hardest of the 5 Ways to be MECE) without needing to do it (as a theft problem is a numerical problem).

In part because he didn’t know how to create a MECE conceptual framework (as we teach in our courses).

And this would’ve gotten Jimi rejected from a real case interview at McKinsey, BCG, Bain or any other firm.

And it would probably get him fired if he was in charge of Amazon’s warehouses.

Don’t be like Jimi.

Always be MECE (and especially so on the first layer)!

#5 - Was Natalia rejected due to a simple mistake?

I actually like this Issue Tree quite a bit.

It’s well built, although there are a couple of problems.

And it’s interesting because Natalia, the lady who built this tree had been rejected from a Bain and a BCG final round before. She was preparing to try again. That means she was good enough to actually get to the final round but made some mistakes that prevented her to get the offer.

Maybe her mistakes were showing in her Issue Tree? 

Perhaps… Let’s take a look:

issue based problem solving mckinsey

There are two great mistakes with this tree.

One we’ve talked before – Natalia went for a conceptual structure to break down the “Warehouse facility factors” bucket and had trouble building it. There’s overlap between “Security” and “Information Confidentiality”. Also, there are many things not considered here (including theft caused by internal employees).

But the one mistake I wanna call your attention to is much less obvious. It’s more a nuance than a mistake.

It is on the first layer.

The way she build it is much better than many alternatives: there’s external factors (crime) and internal factors (the warehouse itself).

HOWEVER, it’s really really tough to test  which one is causing the surge in theft. These things look measurable but they’re not really.

Because measuring overall crime is a pain. And getting that data, an even higher pain.

Just to give you an example: what crime data should we consider to prove/disprove the fact that external crime has risen? Should it be overall criminal incidents? Thefts only? Warehouse thefts, specifically?

Also, how regional should the data be? Neighborhood? City? State?

And because you can’t measure “warehouse facility factors”, it’s hard to exclude a whole branch of the tree. Which means this tree is not very “eliminative”, because the factors in the first branch aren’t falsifiable.

Now, I’m being really picky here just to make a critical point to you. 

Maybe in a real interview Natalia would’ve been able to come up with a test that would reliably eliminate a whole branch. 

And maybe the problem could be solved without that kind of rigorous testing (e.g. maybe they completely switched their security personnel and had security holes in the process, so the cause would be obvious).

But if the situation was harder, more nuanced it would be tough to Natalia to actually diagnose the issue.

And whether she would be able to actually do it in real life is the #1 question in the interviewer’s mind.

Her first layer is not bad, but there are other MECE structures as insightful as this one that would also be more testable, more falsifiable.

And in a final round that could make all the difference.

Commonly Asked Questions

Learning from the mistakes of others is a great way to accelerate your learning curve!

But still, you might have some questions in your head.

Here are some of the questions I have been asked about Issue Trees throughout the years (and the best answers I have to those)…

Issue Trees are one structuring technique but they’re not the only one.

So there are actually two questions within this one: (1) How do I know if I should use a structure to solve the problem and (2) How do I know if I should use an Issue Tree or another technique.

Great questions!

Let’s start with #1…

You should use a structure to solve a problem, well, when you want to solve it in a structured way.

And when’s that? 

Well, whenever you want to be able to foresee the steps to the solution of the problem. 

That is, when you must have a due date of when the problem’s going to be solved (which is whenever you have a boss or a client, for example) or when you want to distribute the problem for other people to solve it (your employees or an outsourced company, for example).

That means almost always, especially in the professional world, where people have bosses, employees and clients.

Question #2 is a bit trickier to answer…

There are other structuring techniques – ways to break down the problem – that you can use. So, when to use Issue Trees and when to use the others?

Basically there are two scenarios: either you want to split the problem into components of the problem, or you want to look at the problem from different angles/points of view  without actually splitting it.

If the first, use an Issue Tree; if the last, use another tool (such as a conceptual framework, as we teach in our free course on case interviews).

How to know which one you want is a bit more complicated and would take an article on its own to explain. 

If you want the full details, check out our free course that you can find in our homepage or throughout this article, but here’s the long story short: if you want focus, efficiency and logic onto a well-defined problem use an Issue Tree and if you want awareness and insight onto a messy problem, use a tool like a conceptual framework.

A lot of people who teach case interviews say you should start with a hypothesis.

And they say that because MBB consulting firms (MBB stands for McKinsey, BCG and Bain) work in a hypothesis-driven approach. That means they come up with hypotheses and test them to find the truth (much like in the scientific method).

Being hypothesis-driven is tricky because you also have to be structured and MECE. 

So, how do you make your hypotheses MECE?

Well, one way some people figured out is to build a MECE tree and just throw the word hypothesis around. If it were in a case investigating why profits have fallen, this would sound something like this:

“My hypothesis if that profits have fallen because sales are down. To know if that’s true we need to look at sales and costs.”

Notice how there’s ZERO value add to using the word “hypothesis” in the phrase above. If the guy had just asked for sales and cost data he’d ask the same questions, do the same analysis and reach the same conclusion.

If you just want to use the word hypothesis like that, go for it, but there’s absolutely no need to do it. If your buckets are MECE and  testable with data, you can just lay out your Issue Tree with no “hypothesis” and test the buckets.

However if you can’t make your structure MECE/testable, you might need to use a hypothesis, but it’s a completely different type hypothesis than the one I’ve shown you above. Instead of being just a random guess with the word hypothesis on it, it must have a structure which we teach in the “Hypothesis Testing” module from our free course.

Great question, glad you asked that!

Clarifying questions are the questions you use to define the problem so you can create your structure / Issue Tree.

You use them to understand the problem better.

If the answer to a question you ask could potentially lead you to solve the problem then the question is a part of the structure of the problem and should be within your Issue Tree.

Drawing Issue Trees on paper is good practice whether you’re in a case interview, helping a client or solving your own problems.

The reason for that is that having it on paper makes it easier to communicate the ideas and frees up space in your mind so you can actually think about each part of the problem.

Not drawing the tree is kind of like memorizing a map – it’s helpful, but the whole purpose of the map is to be there when you need it without you having to know anything by heart.

But drawing does take a bit of time and in answering certain questions in case interviews, interviewers want you to be quick and may even ask you not to use paper . THIS DOES NOT MEAN YOU’RE ALLOWED TO BE UNSTRUCTURED.

It basically means they want to see if you can be structured and communicate your ideas in a structured way even when you don’t have a lot of time to think through a structure and draw it on paper.

Issue trees are a representation of how a consultant thinks. That means consultants think in Issue Trees . 

They communicate using these trees as the underlying structure of the ideas they’re thinking through.

So if you don’t have time at all to think, you don’t have to draw your Issue Tree on paper, but you still must communicate as if you were going through one.

This is a super common question, and a highly context dependent one.

If you’re in an interview and it’s a more conversational, back-and-forth style, you should use less layers and get data so you know where to focus on (and dig deeper on that one).

If you’re in a more structured rigid interview format without a lot of back-and-forth, you should use more layers and they may never give you data.

The first scenario will typically happen at BCG and the second at McKinsey. Other firms will depend more on office / interviewer.

But this is not a rule. I’ve gotten the first scenario at McKinsey (final rounds) and the second at BCG. This means you’ll have to feel the situation a bit, or even ask the interviewer what they prefer.

But there’s a rule of thumb: no less than 2 layers and no more than 5 layers, regardless of format.

Because with just one layer you’re not really structuring the problem. You’re not showing a map of the situation. And with more than 5 layers the time it takes to build each layer grows while the value each layer brings diminishes. Your interviewer can always ask you to dig deeper in a certain bucket if they want you to (and they often do).

That’s true!

Drivers are “underlying causes”, and Levers are “potential things you can do to fix the situation”.

You use drivers for WHY problems and Levers for HOW problems.

If you build a good WHY tree and a good HOW tree for the same problem you’ll see the similarities and differences between drivers and levers (and you can actually go back to Item #4 in Chapter 1, where I did just that).

Simple example: if costs in a factory have increased and you want to decrease them, “material costs” could be a driver of the problem AND a lever to solve it, “taxes” could be a driver but not a lever (because you can’t change it) and outsourcing could be a lever to solve it but not a driver of the problem.

Drivers must be potential causes to the problem and Levers should be under your control.

If each part is MECE, your structure is MECE.

To know if each part is MECE, read  the 5 Ways to be MECE .

And to know if your conceptual framework is MECE, check out our free course on case interview fundamentals.

Also, don’t obsess too much. There’s usually a bit  of overlap between areas and no framework is FULLY exhaustive. You want to aim for “as MECE as possible”, not perfection.

Take their hint and go do it!

Interviewers are there to help you. If they tell you the problem is elsewhere, it probably is.

That doesn’t mean there’s absolutely nothing  happening in the parts of the structure you were working on, but it does mean that they want to test your problem solving skills in the other part, not in the one you’re at.

If you got stuck, it’s either building  your issue tree or using  your issue tree.

If you got stuck building  your issue tree, that means you need more and better practice. There’s a whole section on how to practice in this guide (and it’s the part that’s coming next).

If you’re in the interview already, however, there’s no time left to practice. So, what do you do?

My advice: keep it simple.

Take a breath, rethink the case and create a very simple, down-to-earth structure that can solve the problem. Not a good time to be sophisticated and elaborate when you’re stuck.

Now, if you already have your tree and you got stuck using it, here’s what you should do:

Eliminate as many parts of your tree as possible and find out everything that is NOT a part of the problem .

It’s much easier to say something is not a problem than to say for certain that something else is.

Use this process of elimination to your favor. Doctors use it all the time to save people’s lives (they call it a differential diagnosis) and you can too to save your own butt in your interviews.

How to Practice Issue Trees

Practice makes perfect.

Or, as a teacher used to say, “Practice makes permanent”.

(Which means poor practice is worse than no practice).

You can have all the theory in the world, you can have seen all the examples and still not be able to perform when the time to use this tool comes.

Which means that reading this guide is useless if you don’t apply it into practice.

In this chapter, I’ll show you how.

issue based problem solving mckinsey

4 ways to practice Issue Trees

I could just tell you to go practice Issue Trees.

But then this chapter wouldn’t exist!

Just kidding 🙂

Here’s the thing, telling people to go practice Issue Trees is what we did when we started our case interview coaching practice.

But it didn’t really work.

Most people would just memorize  the common profit trees you see out there and try to apply them to different problems. The problem with that is that they weren’t building their ability to create  new trees for new problems.

Other people would feel stuck. They’d get bogged down into the details and be afraid to do it wrong and waste their time. Or they wouldn’t know where to start.

So what did we do?

Over time we created different techniques for people to practice trees. Each one has a different function and they’re synergistic – the more techniques you use, the more you’ll learn.

Here are my four favorite ones:

4waystopractice

As you can see there is a logic for the four types of practice I will suggest. (And yes, as a former consultant I can’t get over with 2×2 matrices.)

Case-specific practice  is important because this type of practice is very targeted to what you’ll find in your case interviews.

But you also need more generic day-to-day practice  because that will train your mind to always think in a structured way . Even when you’re in the bus. Even when you’re hanging out with your family. Even when the interviewer asks you that informal question about the time where you studied abroad.

On the vertical axis, you’ll find the type of problem you will be practicing with.

You need to practice with real problems you’ve tried to solve before  because you are (or were) emotionally invested in them. You know nuances about them that you wouldn’t know about a random problem and you care (or have cared) about solving them. That gives you the rigor and confidence to structure problems with all the nuances and details they need.

But you also need to practice with hypothetical problems , problems you’ve never considered before. Why? Because that gives you the flexibility and confidence to structure any  problem, even those you have never seen before! 

It helps you be more creative and trains you to face the unknown. What’s the point of learning to structure problems if you can’t face new problems, after all?

Using the four techniques I’ll show you, you will get all four types of practice. 

Actually, because this is a 2×2 matrix, practicing with three of these techniques should be enough to get you really good at this, so if you don’t like any of these, feel free to skip one of them if you want.

issue based problem solving mckinsey

Practice #1: Creating "deep trees"

The first type of practice is that of creating very deep Issue Trees for hypothetical problems, simulating one you would do in a case interview if you had 20-30 minutes to think or one you would do in a real project.

The process is rather simple:

(1) Think of a problem (business or public sector) that someone might have to solve. It could be a WHY problem or a HOW problem.

(2) Create a multilayered Issue Tree to solve the problem. Aim for at least 6 layers and try to create even more than that as you get more practice.

What you’ll notice is that the first few layers are going to be quite easy, especially if the problem you chose to structure is a common one.

However, as you go deeper you’ll find that it gets harder and harder.

Because when you get deep into your Issue Tree you must deal with much more specific problems, problems that you might have never considered in your life before.

The deepest layers are the ones that teach you the most.  

Everyone knows how to break down “profits” in a MECE way. Few people can break down “improving customer retention” in a MECE way. Even fewer can find a MECE structure on how to increase customer friction to leave to a competitor.

This exercise works wonders because most cases start really broad but they eventually get to really specific issues, such as “increasing customer friction to leave”, “outsourcing job tasks”, “reducing perceived purchase risks” and things like that.

Here’s an example of a “deep tree” for the “How to reduce costs in a widget manufacturing plant?” problem:

issue based problem solving mckinsey

Hey, I’m the first to say this tree isn’t perfect, especially in the last couple layers. It’s really hard to create MECE structures to “buying terms and conditions” and other specific things like that.

And I only covered the “material costs” part, otherwise it wouldn’t fit the screen.

But I wanted to show you one example just do you could see how deep you should go when doing this kind of practice.

issue based problem solving mckinsey

Practice #2: Restructuring past cases

Remember the last case you did? The one you messed up on the initial structure?

How much better would your structure be if you had 20-30 minutes to do it?

There’s a simple way to find out…

Restructure that case with as much time as you want!

This is a really good way to practice Issue Trees because (1) you internalize what you’ve learned in the case and (2) you can structure it with unlimited time and without being nervous.

Plus, let’s be honest, you keep telling yourself that your structures aren’t as good as they could be because you don’t have a lot of time to build them and you’re nervous.

But is that really the case?

Try it out!

This practice is as simple as the name suggests, but there is ONE NUANCE…

You will  feel tempted to overemphasize the parts of the case your interviewer directed you to and underemphasize other areas.

So, for example, if you had a profitability case and the case ended up being about cutting labor costs in a telecom company, you will tend to make your structure much more robust in the labor costs part than in the rest of the tree.

DON’T DO THAT.

Instead, build a robust tree all around.

Maybe this case was about labor costs, but the next one could be on infrastructure costs and the one after that could be on pricing. Build a robust structure all around that simulates what you would’ve done had the interview gone in any of those directions.

Be prepared for every situation.

issue based problem solving mckinsey

Practice #3: Solving real work problems

Got a problem at work?

Work like a consultant and build an Issue Tree first and foremost!

Have to hit a certain target in an organization you work at or collaborate with?

Break that metric down into an Issue Tree and find the best lever to focus on.

Have a school assignment?

Try to build an Issue Tree for it.

By doing these things you will incorporate Issue Trees in your daily work and study. 

Sometimes I even create them as I read a book to better organize its ideas. And as I do that, I end up with the whole structure and all the important ideas of a book in just one page.

issue based problem solving mckinsey

Practice #4: Creating "mental trees"

Remember I said you can do 3 out of the 4 types of practices in this chapter and still do fine?

Well, don’t skip this one.

Mental trees exercise a different muscle than the other practices, because it happens all in your head.

It’s kind of like mental math but for Issue Trees.

And it’s a skill that every consultant can do , and so should you.

So what are “mental trees”?

It’s simple. As you go through your day you will notice things. You will be curious about things. You will wonder how to fix certain problems or why they happen in the first place.

You’ll have questions such as:

  • “How could this restaurant generate more demand?”
  • “What could the city do to improve its transport system?”
  • “Why is the doctor always late for the appointment?”
  • “What will TV networks do to generate more revenue now that everyone’s on Youtube and Instagram?”

And as you have these questions, use these opportunities to create Issue Trees in your head.

Not huge ones, 2 or 3 layers is fine.

But do that and try to keep them in your head as you generate hypotheses for each bucket. At first this is gonna be really hard, but once you get the hang of it it will be a breeze.

And once it’s easy, you’ll be able to use Issue Trees whenever you need them.

This practice is especially important for final rounds because partners will often tell you to discuss a problem without using paper. (And they do expect you to structure it).

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Applying issue trees on the job.

If you’ve read this far, you’ve learned how to use the most versatile tool in solving business (and many other) problems.

And if you’re like me, you want to now maximize the value you got from learning this!

Issue Trees can help you be a better problem solver, but also to present your ideas better, to bring more and better insights and even to be a better manager.

In this chapter I’ll show you 5 direct, on-the-job applications of Issue Trees that you can use if you’re a consultant, if you work in industry and even if you have started your own business.

issue based problem solving mckinsey

Issue Trees can be used in every facet of your job

Before we even jump into examples of direct applications of how to use Issue Trees on the job, let me make a bold claim: Issue Trees can be used in every  facet of your job.

You know that saying about how everything looks like a nail to the guy who has a hammer?

Well, don’t think of Issue Trees as hammers. 

They’re more like Swiss army knives or Microsoft Excel. It’s a tool with many functions.

And you can use it as a consultant, but also as an executive, as an entrepreneur and more. I once taught my dad who is a doctor how to use it and he’s now better able to explain his thought process and diagnostics to his patients.

Why am I telling you all this?

Just so you know that the 5 on-the-job applications I’m about to show you are some  of the things you can do with Issue Trees. 

With a bit of creativity you can do much more.

Application #1 - As a map to solve a specific problem

If you’ve spent any time at all as a knowledge worker in your career (that’s most analyst and management positions at most companies), you know how it feels to be stuck with a problem.

Most business problems start with a very simple, almost trivial, question, but as you dig deeper you start seeing all the nuances you feel overwhelmed. 

It’s very different from the experience of solving a problem in business school, where all the information you’ll need (and all the info you’ll get) is in a neat 10-20 page case.

Anyway… When you feel overwhelmed, when you feel like there’s too much nuance to handle and when you feel like there’s so many directions to go what you need is a map. A high-level view of the problem with its distinct parts laid out in front of you so you can put numbers, hypotheses and plans to act in each part.

What you need is an Issue Tree.

Years ago I worked in a Venture Capital firm here in Brazil. They had just entered the market and wanted to invest in e-commerce.

My task was to figure out what types of e-commerce businesses would thrive in the country so they could invest well. Would it be auto-parts? Maybe fashion? Or perhaps food delivery?

It was an overwhelming task for me. There’s so many things you can do with e-commerce.

So what I did was to build two Issue Trees. One with our options and another with the high level criteria I’d want to see in each option for it to become a successful e-commerce.

Something like this:

issue based problem solving mckinsey

Now, the real trees I did were a bit more sophisticated than this. They had:

  • More layers and a more MECE structure for the verticals
  • Other criteria for success not shown here
  • Prioritization so we could find the most important information first and eliminate whole verticals quickly

But you can get the idea… I got both of these trees and put into a spreadsheet and now I had a map of the problem that I could work on.

Because I used Issue Trees to create this map, I assured that the thinking was clear and rigorous, that I would be able to work efficiently by eliminating bad options quickly and that I’d bring insight to the table.

It also removed all overwhelm and made my work much more efficient. I no longer had to consider all the factors at once in my head. All I had to do now was to fill out a table with the best information I could get and see the results.

Application #2 - As a guide to brainstorm solutions

Brainstorming solutions to common business problems is a nervous activity.

Everyone wants to show the best solution, and people want to show common sense AS WELL AS creativity. It’s a tough spot to be in.

On top of that, people typically brainstorm solutions to problems that are urgent and critical (why fix what’s not broken?) and this is usually done in meetings, which adds to the pressure.

But that’s not all… In most meetings, solution generation happens in a haphazard way – completely different ideas are mentioned in the spam of a few minutes and it’s hard to even evaluate which are the best ones.

The result? The best solutions rarely win and it’s common that people don’t even reach a consensus on which should be implemented.

So, what’s the antidote?

You guessed it: Issue Trees.

If you have a solution generating meeting (or if you’re doing it by yourself) and you can find a HOW tree that reaches consensus (not actual solutions, but the structure of the problem) at the beginning of the meeting, you can then lead the discussion forward, helping people generate solutions for each bucket of your tree and then prioritizing those in an organized fashion.

Also, doing it this way tends to bring out more, better ideas – for the same reason why dividing the problem brings more creativity in case interviews. It’s easier to get 5 ideas per bucket than 40 for the problem as a whole.

I’ve been to both kinds of solution-generating meetings. One feels like a pointless chaos and the other gives you certainty that the problem will be solved from minute one.

Application #3 - As a way to structure a presentation

Structuring a presentation is the kind of thing that gets most people CRAZY.

You have to consider your audience, how to capture and keep attention, storytelling, getting your point across quickly and being to the point and so many other conflicting goals.

But here’s a simple way to do it: use the Issue Tree of the problem as a basis to how your presentation is organized.

This works because your Issue Tree is a map of your problem. And maps are great ways to make people understand a complex thing with simplicity and accuracy.

Let me show you an example of how to do this…

Remember the Telco executive from Chapter 1 that had a problem because his customers were unsubscribing from their services? I’ll help you remember it, it’s been a while…

Now, imagine he had to present what’s happening to the executive committee. It needed to be a short and to the point presentation that was compelling as well.

Not a full solution to the problem, but a presentation showing what happened.

What would you do in his place?

Here’s what I’d do:

Slide 1: A chart showing the high level problem (overall unsubscriptions have raised from 10.5 to 17 thousand clients, with an increase of 2,000 from clients willing to unsubscribe and 4,500 from clients being forced out). 

I’d also add something that pointed out that the cause of the clients being forced out (the main problem) was a problem in the systems.

In other words, Slide 1 would be “High-level view” + “root-cause of main problem”. Everything the committee needs to understand the situation.

Slide 2: A chart detailing the root-cause of the main problem, with all details needed to understand why it happened. This would include numbers and qualitative things about that system problem.

Slide 3: A chart showing that even though we only lost 2,000 extra customers because they wanted out, we actually lost 3,000 to competition. I’d show the numbers (2nd Layer at “They wanted to unsubscribe” bucket) and show that there is potential there.

Slide 4: I’d turn back to the system’s problems and start talking about solutions. I’d show what was done, what is being done and what’s next to prevent it from happening again.

Slide 5: I’d show next steps to understand how to retain more customers vs. competition. This is a less urgent problem so I’d leave it at that.

That’s it, simple and straightforward.

And it all comes because I have a simple and straightforward Issue Tree that helps me solve and explain the problem in simple and straightforward ways.

Application #4 - As a guide to research best practices

We’ve all had that hurried boss that passes through your desk and casually mentions: “Hey, you should try to find some best practices around X”.

X can be anything he or she is concerned about: doing better presentations, sharing internal documents, improving productivity at work, getting more clients.

And the problem with that is that it’s really really hard to research that. If you just type “best practices for X” in google, chances are you’ll get some really generic, obvious tips.

One thing I’ve learned to do at McKinsey was to research best practices for each component  of X. So instead of looking for best practices around “getting more clients”, I could research best practices to “get more leads” and “increasing conversion rate”.

And then I could break down those components even further and look for best practices for each sub-component.

Guess what’s the tool you need to get all the components in a logical manner? Yes, Issue Trees!

A normal best practice for X’s sub-sub-component usually is a great insight to improve X, so by simply doing this exercise you will come off way ahead of your peers as the go-to person for insights on how to improve your company.

Application #5 - As a way to generate KPIs and indicators

In case you don’t know the lingo, KPIs are you “Key Performance Indicators”.

They’re a business’ dashboard. The numbers you have to look at to see how healthy your business is.

But how do you create KPIs?

Well, in three simple steps:

1) You define your goals

2) Your break down your goals into the sub-components that must be true for you to achieve them

3) You figure out indicators for each prioritized sub-component. (Without the “prioritized” part, these indicators wouldn’t be “Key”)

So for example,  if you’re studying for consulting interviews and you want to see how your preparation is going , here’s an example of how to create KPIs you can track:

issue based problem solving mckinsey

Each bullet point could be a KPI. Some of these are numbers to track, others are Yes/No KPIs.

I am not saying nor implying every candidate should use all these KPIs to prepare, but notice how nuanced you can get when you use a MECE Issue Tree to create KPIs.

Most candidates just track the # of cases they did, without even caring for the quality of those. 

No wonder why most get rejected. 

It’s like a company that just tracks how many products it has sold without concerning about margins, customer retention rates, customer satisfaction, quality control and so on.

You can get any Issue Tree from this article and transform it into a list of KPIs to track within each important bucket. 

There’s certainly an art on which ones are better to track (because you don’t want to end up with 35 different KPIs) but just generating them out of a MECE Issue Tree allows you to have at least one indicator to every important part of the problem, leaving no blind spots in your master dashboard.

What's next?

Issue Trees are one, but not the only  tool MBB consultants use to solve their client’s problems.

There are actually 6 types of questions interviewers ask in case interviews, to test on the 6 most important tasks consultants perform in real client work. 

You can learn about those questions and the specific tools, techniques and strategies management consultants from McKinsey, BCG and Bain use to solve business problems by joining our free course on case interviews!

issue based problem solving mckinsey

By joining our course, you’ll get access to:

  • Step-by-step methods to solve the 6 (and only six) types of questions you can get in case interviews
  • The “Landscape Technique” to create conceptual frameworks from scratch (this is the technique you need when Issue Trees fail to help you)
  • Tons of practice drills so you can apply your knowledge

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McKinsey Problem Solving: Six steps to solve any problem and tell a persuasive story

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The McKinsey problem solving process is a series of mindset shifts and structured approaches to thinking about and solving challenging problems. It is a useful approach for anyone working in the knowledge and information economy and needs to communicate ideas to other people.

Over the past several years of creating StrategyU, advising an undergraduates consulting group and running workshops for clients, I have found over and over again that the principles taught on this site and in this guide are a powerful way to improve the type of work and communication you do in a business setting.

When I first set out to teach these skills to the undergraduate consulting group at my alma mater, I was still working at BCG. I was spending my day building compelling presentations, yet was at a loss for how to teach these principles to the students I would talk with at night.

Through many rounds of iteration, I was able to land on a structured process and way of framing some of these principles such that people could immediately apply them to their work.

While the “official” McKinsey problem solving process is seven steps, I have outline my own spin on things – from experience at McKinsey and Boston Consulting Group. Here are six steps that will help you solve problems like a McKinsey Consultant:

Step #1: School is over, stop worrying about “what” to make and worry about the process, or the “how”

When I reflect back on my first role at McKinsey, I realize that my biggest challenge was unlearning everything I had learned over the previous 23 years. Throughout school you are asked to do specific things. For example, you are asked to write a 5 page paper on Benjamin Franklin — double spaced, 12 font and answering two or three specific questions.

In school, to be successful you follow these rules as close as you can. However, in consulting there are no rules on the “what.” Typically the problem you are asked to solve is ambiguous and complex — exactly why they hire you. In consulting, you are taught the rules around the “how” and have to then fill in the what.

The “how” can be taught and this entire site is founded on that belief. Here are some principles to get started:

Step #2: Thinking like a consultant requires a mindset shift

There are two pre-requisites to thinking like a consultant. Without these two traits you will struggle:

  • A healthy obsession looking for a “better way” to do things
  • Being open minded to shifting ideas and other approaches

In business school, I was sitting in one class when I noticed that all my classmates were doing the same thing — everyone was coming up with reasons why something should should not be done.

As I’ve spent more time working, I’ve realized this is a common phenomenon. The more you learn, the easier it becomes to come up with reasons to support the current state of affairs — likely driven by the status quo bias — an emotional state that favors not changing things. Even the best consultants will experience this emotion, but they are good at identifying it and pushing forward.

Key point : Creating an effective and persuasive consulting like presentation requires a comfort with uncertainty combined with a slightly delusional belief that you can figure anything out.

Step #3: Define the problem and make sure you are not solving a symptom

Before doing the work, time should be spent on defining the actual problem. Too often, people are solutions focused when they think about fixing something. Let’s say a company is struggling with profitability. Someone might define the problem as “we do not have enough growth.” This is jumping ahead to solutions — the goal may be to drive more growth, but this is not the actual issue. It is a symptom of a deeper problem.

Consider the following information:

  • Costs have remained relatively constant and are actually below industry average so revenue must be the issue
  • Revenue has been increasing, but at a slowing rate
  • This company sells widgets and have had no slowdown on the number of units it has sold over the last five years
  • However, the price per widget is actually below where it was five years ago
  • There have been new entrants in the market in the last three years that have been backed by Venture Capital money and are aggressively pricing their products below costs

In a real-life project there will definitely be much more information and a team may take a full week coming up with a problem statement . Given the information above, we may come up with the following problem statement:

Problem Statement : The company is struggling to increase profitability due to decreasing prices driven by new entrants in the market. The company does not have a clear strategy to respond to the price pressure from competitors and lacks an overall product strategy to compete in this market.

Step 4: Dive in, make hypotheses and try to figure out how to “solve” the problem

Now the fun starts!

There are generally two approaches to thinking about information in a structured way and going back and forth between the two modes is what the consulting process is founded on.

First is top-down . This is what you should start with, especially for a newer “consultant.” This involves taking the problem statement and structuring an approach. This means developing multiple hypotheses — key questions you can either prove or disprove.

Given our problem statement, you may develop the following three hypotheses:

  • Company X has room to improve its pricing strategy to increase profitability
  • Company X can explore new market opportunities unlocked by new entrants
  • Company X can explore new business models or operating models due to advances in technology

As you can see, these three statements identify different areas you can research and either prove or disprove. In a consulting team, you may have a “workstream leader” for each statement.

Once you establish the structure you you may shift to the second type of analysis: a bottom-up approach . This involves doing deep research around your problem statement, testing your hypotheses, running different analysis and continuing to ask more questions. As you do the analysis, you will begin to see different patterns that may unlock new questions, change your thinking or even confirm your existing hypotheses. You may need to tweak your hypotheses and structure as you learn new information.

A project vacillates many times between these two approaches. Here is a hypothetical timeline of a project:

Strategy consulting process

Step 5: Make a slides like a consultant

The next step is taking the structure and research and turning it into a slide. When people see slides from McKinsey and BCG, they see something that is compelling and unique, but don’t really understand all the work that goes into those slides. Both companies have a healthy obsession (maybe not to some people!) with how things look, how things are structured and how they are presented.

They also don’t understand how much work is spent on telling a compelling “story.” The biggest mistake people make in the business world is mistaking showing a lot of information versus telling a compelling story. This is an easy mistake to make — especially if you are the one that did hours of analysis. It may seem important, but when it comes down to making a slide and a presentation, you end up deleting more information rather than adding. You really need to remember the following:

Data matters, but stories change hearts and minds

Here are four quick ways to improve your presentations:

Tip #1 — Format, format, format

Both McKinsey and BCG had style templates that were obsessively followed. Some key rules I like to follow:

  • Make sure all text within your slide body is the same font size (harder than you would think)
  • Do not go outside of the margins into the white space on the side
  • All titles throughout the presentation should be 2 lines or less and stay the same font size
  • Each slide should typically only make one strong point

Tip #2 — Titles are the takeaway

The title of the slide should be the key insight or takeaway and the slide area should prove the point. The below slide is an oversimplification of this:

Example of a single slide

Even in consulting, I found that people struggled with simplifying a message to one key theme per slide. If something is going to be presented live, the simpler the better. In reality, you are often giving someone presentations that they will read in depth and more information may make sense.

To go deeper, check out these 20 presentation and powerpoint tips .

Tip #3 — Have “MECE” Ideas for max persuasion

“MECE” means mutually exclusive, collectively exhaustive — meaning all points listed cover the entire range of ideas while also being unique and differentiated from each other.

An extreme example would be this:

  • Slide title: There are seven continents
  • Slide content: The seven continents are North America, South America, Europe, Africa Asia, Antarctica, Australia

The list of continents provides seven distinct points that when taken together are mutually exclusive and collectively exhaustive . The MECE principle is not perfect — it is more of an ideal to push your logic in the right direction. Use it to continually improve and refine your story.

Applying this to a profitability problem at the highest level would look like this:

Goal: Increase profitability

2nd level: We can increase revenue or decrease costs

3rd level: We can increase revenue by selling more or increasing prices

Each level is MECE. It is almost impossible to argue against any of this (unless you are willing to commit accounting fraud!).

Tip #4 — Leveraging the Pyramid Principle

The pyramid principle is an approach popularized by Barbara Minto and essential to the structured problem solving approach I learned at McKinsey. Learning this approach has changed the way I look at any presentation since.

Here is a rough outline of how you can think about the pyramid principle as a way to structure a presentation:

pyramid principle structure

As you build a presentation, you may have three sections for each hypothesis. As you think about the overall story, the three hypothesis (and the supporting evidence) will build on each other as a “story” to answer the defined problem. There are two ways to think about doing this — using inductive or deductive reasoning:

deductive versus inductive reasoning in powerpoint arguments

If we go back to our profitability example from above, you would say that increasing profitability was the core issue we developed. Lets assume that through research we found that our three hypotheses were true. Given this, you may start to build a high level presentation around the following three points:

example of hypotheses confirmed as part of consulting problem solving

These three ideas not only are distinct but they also build on each other. Combined, they tell a story of what the company should do and how they should react. Each of these three “points” may be a separate section in the presentation followed by several pages of detailed analysis. There may also be a shorter executive summary version of 5–10 pages that gives the high level story without as much data and analysis.

Step 6: The only way to improve is to get feedback and continue to practice

Ultimately, this process is not something you will master overnight. I’ve been consulting, either working for a firm or on my own for more than 10 years and am still looking for ways to make better presentations, become more persuasive and get feedback on individual slides.

The process never ends.

The best way to improve fast is to be working on a great team . Look for people around you that do this well and ask them for feedback. The more feedback, the more iterations and more presentations you make, the better you will become. Good luck!

If you enjoyed this post, you’ll get a kick out of all the free lessons I’ve shared that go a bit deeper. Check them out here .

Do you have a toolkit for business problem solving? I created Think Like a Strategy Consultant as an online course to make the tools of strategy consultants accessible to driven professionals, executives, and consultants. This course teaches you how to synthesize information into compelling insights, structure your information in ways that help you solve problems, and develop presentations that resonate at the C-Level. Click here to learn more or if you are interested in getting started now, enroll in the self-paced version ($497) or hands-on coaching version ($997). Both versions include lifetime access and all future updates.

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Resources >

Mckinsey approach to problem solving.

McKinsey and Company is recognized for its rigorous approach to problem solving. They train their consultants on their seven-step process that anyone can learn.

This resource guides you through that process, largely informed by the McKinsey Staff Paper 66. It also includes a PowerPoint Toolkit with slide templates of each step of the process that you can download and customize for your own use.

You can click any section to go directly there:

Overview of the McKinsey Approach to Problem Solving

Problem solving process.

  • Problem Definition & Problem Statement Worksheet

Stakeholder Analysis Worksheet

Hypothesis trees, issue trees, analyses and workplan, synthesize findings, craft recommendations, distinctiveness practices, harness the power of collaboration, sources and additional reading, download the umbrex toolkit on the mckinsey approach to problem solving.

Problem solving — finding the optimal solution to a given business opportunity or challenge — is the very heart of how consultants create client impact, and considered the most important skill for success at McKinsey.

The characteristic “McKinsey method” of problem solving is a structured, inductive approach that can be used to solve any problem. Using this standardized process saves us from reinventing the problem-solving wheel, and allows for greater focus on distinctiveness in the solution. Every new McKinsey associate must learn this method on his or her first day with the firm.

There are four fundamental disciplines of the McKinsey method:

1. Problem definition

A thorough understanding and crisp definition of the problem.

2. The problem-solving process

Structuring the problem, prioritizing the issues, planning analyses, conducting analyses, synthesizing findings, and developing recommendations.

3. Distinctiveness practices

Constructing alternative perspectives; identifying relationships; distilling the essence of an issue, analysis, or recommendation; and staying ahead of others in the problem-solving process.

4. Collaboratio n

Actively seeking out client, customer, and supplier perspectives, as well as internal and external expert insight and knowledge.

Once the problem has been defined, the problem-solving process proceeds with a series of steps:

  • Structure the problem
  • Prioritize the issues
  • Plan analyses
  • Conduct analyses
  • Synthesize findings
  • Develop recommendations

Not all problems require strict adherence to the process. Some steps may be truncated, such as when specific knowledge or analogies from other industries make it possible to construct hypotheses and associated workplans earlier than their formal place in the process. Nonetheless, it remains important to be capable of executing every step in the basic process.

When confronted with a new and complex problem, this process establishes a path to defining and disaggregating the problem in a way that will allow the team to move to a solution. The process also ensures nothing is missed and concentrates efforts on the highest-impact areas. Adhering to the process gives the client clear steps to follow, building confidence, credibility, and long-term capability.

Problem Definition & Problem Statement Worksheet

The most important step in your entire project is to first carefully define the problem. The problem definition will serve the guide all of the team’s work, so it is critical to ensure that all key stakeholders agree that it is the right problem to be solving.

Problem Statement Worksheet

This is a helpful tool to use to clearly define the problem. There are often dozens of issues that a team could focus on, and it is often not obvious how to define the problem. In any real-life situation, there are many possible problem statements. Your choice of problem statement will serve to constrain the range of possible solutions.

  • Use a question . The problem statement should be phrased as a question, such that the answer will be the solution. Make the question SMART: specific, measurable, action-oriented, relevant, and time-bound. Example: “How can XYZ Bank close the $100 million profitability gap in two years?”
  • Context . What are the internal and external situations and complications facing the client, such as industry trends, relative position within the industry, capability gaps, financial flexibility, and so on?
  • Success criteria . Understand how the client and the team define success and failure. In addition to any quantitative measures identified in the basic question, identify other important quantitative or qualitative measures of success, including timing of impact, visibility of improvement, client capability building required, necessary mindset shifts, and so on.
  • Scope and constraints . Scope most commonly covers the markets or segments of interest, whereas constraints govern restrictions on the nature of solutions within those markets or segments.
  • Stakeholders . Explore who really makes the decisions — who decides, who can help, and who can block.
  • Key sources of insight . What best-practice expertise, knowledge, and engagement approaches already exist? What knowledge from the client, suppliers, and customers needs to be accessed? Be as specific as possible: who, what, when, how, and why.

The problem definition should not be vague, without clear measures of success. Rather, it should be a SMART definition:

  • Action-oriented

Example situation – A family on Friday evening

Scenario: A mother, a father, and their two teenage children have all arrived home on a Friday at 6 p.m. The family has not prepared dinner for Friday evening. The daughter has lacrosse practice on Saturday and an essay to write for English class due on Monday. The son has theatre rehearsal on both Saturday and Sunday and will need one parent to drive him to the high school both days, though he can get a ride home with a friend. The family dog, a poodle, must be taken to the groomer on Saturday morning. The mother will need to spend time this weekend working on assignments for her finance class she is taking as part of her Executive MBA. The father plans to go on a 100-mile bike ride, which he can do either Saturday or Sunday. The family has two cars, but one is at the body shop. They are trying to save money to pay for an addition to their house.

What is the problem definition?

A statement of facts does not focus the problem solving:

It is 6 p.m. The family has not made plans for dinner, and they are hungry.

A question guides the team towards a solution:

1. What should the family do for dinner on Friday night?

2. Should the family cook dinner or order delivery?

3. What should the family cook for dinner?

4. What should the family cook for dinner that will not require spending more than $40 on groceries?

5. To cook dinner, what do they need to pick up from the supermarket?

6. How can the family prepare dinner within the next hour using ingredients they already have in the house?

In completing the Problem Statement Worksheet, you are prompted to define the key stakeholders.

As you become involved in the problem-solving process, you should expand the question of key stakeholders to include what the team wants from them and what they want from the team, their values and motivations (helpful and unhelpful), and the communications mechanisms that will be most effective for each of them.

Using the Stakeholder Analysis Worksheet allows you to comprehensively identify:

  • Stakeholders
  • What you need from them
  • Where they are
  • What they need from you

The two most helpful techniques for rigorously structuring any problem are hypothesis trees and issue trees. Each of these techniques disaggregates the primary question into a cascade of issues or hypotheses that, when addressed, will together answer the primary question.

A hypothesis tree might break down the same question into two or more hypotheses. 

Example: Alpha Manufacturing, Inc.

Problem Statement: How can Alpha increase EBITDA by $13M (to $50M) by 2025?

The hypotheses might be:

  • Alpha can add $125M revenues by expanding to new customers, adding $8M of EBITDA
  • Alpha can reduce costs to improve EBITDA by $5M

These hypotheses will be further disaggregated into subsidiary hypotheses at the next level of the tree.

The aim at this stage is to structure the problem into discrete, mutually exclusive pieces that are small enough to yield to analysis and that, taken together, are collectively exhaustive.

Articulating the problem as hypotheses, rather than issues, is the preferred approach because it leads to a more focused analysis of the problem. Questions to ask include:

  • Is it testable – can you prove or disprove it?
  • It is open to debate? If it cannot be wrong, it is simply a statement of fact and unlikely to produce keen insight.
  • If you reversed your hypothesis – literally, hypothesized that the exact opposite were true – would you care about the difference it would make to your overall logic?
  • If you shared your hypothesis with the CEO, would it sound naive or obvious?
  • Does it point directly to an action or actions that the client might take?

Quickly developing a powerful hypothesis tree enables us to develop solutions more rapidly that will have real impact. This can sometimes seem premature to clients, who might find the “solution” reached too quickly and want to see the analysis behind it.

Take care to explain the approach (most important, that a hypothesis is not an answer) and its benefits (that a good hypothesis is the basis of a proven means of successful problem solving and avoids “boiling the ocean”).

Often, the team has insufficient knowledge to build a complete hypothesis tree at the start of an engagement. In these cases, it is best to begin by structuring the problem using an issue tree.

An issue tree is best set out as a series of open questions in sentence form. For example, “How can the client minimize its tax burden?” is more useful than “Tax.” Open questions – those that begin with what, how, or why– produce deeper insights than closed ones. In some cases, an issue tree can be sharpened by toggling between issue and hypothesis – working forward from an issue to identify the hypothesis, and back from the hypothesis to sharpen the relevant open question.

Once the problem has been structured, the next step is to prioritize the issues or hypotheses on which the team will focus its work. When prioritizing, it is common to use a two-by-two matrix – e.g., a matrix featuring “impact” and “ease of impact” as the two axes.

Applying some of these prioritization criteria will knock out portions of the issue tree altogether. Consider testing the issues against them all, albeit quickly, to help drive the prioritization process.

Once the criteria are defined, prioritizing should be straightforward: Simply map the issues to the framework and focus on those that score highest against the criteria.

As the team conducts analysis and learns more about the problem and the potential solution, make sure to revisit the prioritization matrix so as to remain focused on the highest-priority issues.

The issues might be:

  • How can Alpha increase revenue?
  • How can Alpha reduce cost?

Each of these issues is then further broken down into deeper insights to solutions.

If the prioritization has been carried out effectively, the team will have clarified the key issues or hypotheses that must be subjected to analysis. The aim of these analyses is to prove the hypotheses true or false, or to develop useful perspectives on each key issue. Now the task is to design an effective and efficient workplan for conducting the analyses.

Transforming the prioritized problem structure into a workplan involves two main tasks:

  • Define the blocks of work that need to be undertaken. Articulate as clearly as possible the desired end products and the analysis necessary to produce them, and estimate the resources and time required.
  • Sequence the work blocks in a way that matches the available resources to the need to deliver against key engagement milestones (e.g., important meetings, progress reviews), as well as to the overall pacing of the engagement (i.e., weekly or twice-weekly meetings, and so on).

A good workplan will detail the following for each issue or hypothesis: analyses, end products, sources, and timing and responsibility. Developing the workplan takes time; doing it well requires working through the definition of each element of the workplan in a rigorous and methodical fashion.

This is the most difficult element of the problem-solving process. After a period of being immersed in the details, it is crucial to step back and distinguish the important from the merely interesting. Distinctive problem solvers seek the essence of the story that will underpin a crisp recommendation for action.

Although synthesis appears, formally speaking, as the penultimate step in the process, it should happen throughout. Ideally, after you have made almost any analytical progress, you should attempt to articulate the “Day 1” or “Week 1” answer. Continue to synthesize as you go along. This will remind the team of the question you are trying to answer, assist prioritization, highlight the logical links of the emerging solution, and ensure that you have a story ready to articulate at all times during the study.

McKinsey’s primary tool for synthesizing is the pyramid principle. Essentially, this principle asserts that every synthesis should explain a single concept, per the “governing thought.” The supporting ideas in the synthesis form a thought hierarchy proceeding in a logical structure from the most detailed facts to the governing thought, ruthlessly excluding the interesting but irrelevant.

While this hierarchy can be laid out as a tree (like with issue and hypothesis trees), the best problem solvers capture it by creating dot-dash storylines — the Pyramid Structure for Grouping Arguments.

Pyramid Structure for Grouping Arguments

  • Focus on action. Articulate the thoughts at each level of the pyramid as declarative sentences, not as topics. For example, “expansion” is a topic; “We need to expand into the European market” is a declarative sentence.
  • Use storylines. PowerPoint is poor at highlighting logical connections, therefore is not a good tool for synthesis. A storyline will clarify elements that may be ambiguous in the PowerPoint presentation.
  • Keep the emerging storyline visible. Many teams find that posting the storyline or story- board on the team-room wall helps keep the thinking focused. It also helps in bringing the client along.
  • Use the situation-complication-resolution structure. The situation is the reason there is action to be taken. The com- plication is why the situation needs thinking through – typically an industry or client challenge. The resolution is the answer.
  • Down the pyramid: does each governing thought pose a single question that is answered completely by the group of boxes below it?
  • Across: is each level within the pyramid MECE?
  • Up: does each group of boxes, taken together, provide one answer – one “so what?” – that is essentially the governing thought above it?
  • Test the solution. What would it mean if your hypotheses all came true?

Three Horizons of Engagement Planning

It’s useful to match the workplan to three horizons:

  • What is expected at the end of the engagement
  • What is expected at key progress reviews
  • What is due at daily and/or weekly team meetings

The detail in the workplan will typically be greater for the near term (the next week) than for the long term (the study horizon), especially early in a new engagement when considerable ambiguity about the end state remains.

It is at this point that we address the client’s questions: “What do I do, and how do I do it?” This means not offering actionable recommendations, along with a plan and client commitment for implementation.

The essence of this step is to translate the overall solution into the actions required to deliver sustained impact. A pragmatic action plan should include:

  • Relevant initiatives, along with a clear sequence, timing, and mapping of activities required
  • Clear owners for each initiative
  • Key success factors and the challenges involved in delivering on the initiatives

Crucial questions to ask as you build recommendations for organizational change are:

  • Does each person who needs to change (from the CEO to the front line) understand what he or she needs to change and why, and is he or she committed to it?
  • Are key leaders and role models throughout the organization personally committed to behaving differently?
  • Has the client set in place the necessary formal mechanisms to reinforce the desired change?
  • Does the client have the skills and confidence to behave in the desired new way?

Great problem solvers identify unique disruptions and discontinuities, novel insights, and step-out opportunities that lead to truly distinctive impact. This is done by applying a number of practices throughout the problem-solving process to help develop these insights.

Expand: Construct multiple perspectives

Identifying alternative ways of looking at the problem expands the range of possibilities, opens you up to innovative ideas, and allows you to formulate more powerful hypotheses. Questions that help here include:

  • What changes if I think from the perspective of a customer, or a supplier, or a frontline employee, or a competitor?
  • How have other industries viewed and addressed this same problem?
  • What would it mean if the client sought to run the company like a low-cost airline or a cosmetics manufacturer?

Link: Identify relationships

Strong problem solvers discern connections and recognize patterns in two different ways:

  • They seek out the ways in which different problem elements – issues, hypotheses, analyses, work elements, findings, answers, and recommendations – relate to one another.
  • They use these relationships throughout the basic problem-solving process to identify efficient problem-solving approaches, novel solutions, and more powerful syntheses.

Distill: Find the essence

Cutting through complexity to identify the heart of the problem and its solution is a critical skill.

  • Identify the critical problem elements. Are there some issues, approaches, or options that can be eliminated completely because they won’t make a significant difference to the solution?
  • Consider how complex the different elements are and how long it will take to complete them. Wherever possible, quickly advance simpler parts of the problem that can inform more complex or time-consuming elements.

Lead: Stay ahead/step back

Without getting ahead of the client, you cannot be distinctive. Paradoxically, to get ahead – and stay ahead – it is often necessary to step back from the problem to validate or revalidate the approach and the solution.

  • Spend time thinking one or more steps ahead of the client and team.
  • Constantly check and challenge the rigor of the underlying data and analysis.
  • Stress-test the whole emerging recommendation
  • Challenge the solution against a set of hurdles. Does it satisfy the criteria for success as set out on the Problem Statement Worksheet?

No matter how skilled, knowledgeable, or experienced you are, you will never create the most distinctive solution on your own. The best problem solvers know how to leverage the power of their team, clients, the Firm, and outside parties. Seeking the right expertise at the right time, and leveraging it in the right way, are ultimately how we bring distinctiveness to our work, how we maximize efficiency, and how we learn.

When solving a problem, it is important to ask, “Have I accessed all the sources of insight that are available?” Here are the sources you should consider:

  • Your core team
  • The client’s suppliers and customers
  • Internal experts and knowledge
  • External sources of knowledge
  • Communications specialists

The key here is to think open, not closed. Opening up to varied sources of data and perspectives furthers our mission to develop truly innovative and distinctive solutions for our clients.

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McKinsey Solve

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McKinsey’s Solve assessment has been making candidates sweat ever since it was initially trialled at the firm’s London office back in 2017 - and things have gotten even more difficult since a new version launched in Spring 2023, adding the Redrock case study.

More recently, in Summer 2023, we have seen a new iteration of that Redrock case, as we continue to interview test takers to keep you updated. This replaces the case study about optimising wolf pack populations across Redrock Island with one about boosting the overall plant biodiversity on the same island.

Since its initial roll-out, the Solve assessment has definitely been the most idiosyncratic, but also the most advanced, of the screening tests used by the MBB firms.

It can be hard to understand how an ecology-themed video game can tell McKinsey whether you’ll make a good management consultant, let alone know how to prepare yourself to do well in that game. When you consider that McKinsey are potentially cutting 70%+ of the applicant pool based on this single test, you can hardly blame applicants for being worried.

Matters are definitely not helped by the dearth of reliable, up-to-date information about what could very well be - with a top-tier consulting job on the line - the most important test you will take over your entire career. This was already true with the version of Solve that had been around for a few years, let alone the new iterations.

What information is available online is then often contradictory. For a long time, there was huge disagreement as to whether it is actually possible to meaningfully prepare for the Solve assessment - before you’ve even considered how to go about that preparation. There is also a lot of confusion and inaccuracy around the new Redrock case - largely as it is such a recent addition, and individual test takers tend to misremember details.

Luckily, we at MCC have been interviewing test takers both before and after the Redrock case rollout and have been following up to see which strategies and approaches actually work to push individuals through to interview.

Here, we’ll explain that it is indeed possible to prepare effectively for both versions of Solve and give you some ideas for how you can get started. Understanding how the Solve assessment works, what it tests you for and how is critical for all but the most hurried preparations.

This article makes for a great introduction to the Solve assessment. However, if you are going to be facing this aptitude test yourself and want full information and advice for preparation, then you should ideally get our full PDF guide:

Master the Solve Assessment

What is the mckinsey solve assessment.

In simple terms, the McKinsey Solve assessment is a set of ecology-themed video games. In these games, you must do things like build food chains, protect endangered species, manage predator and prey populations, boost biodiversity and potentially diagnose diseases within animal populations or identify natural disasters.

Usually, you will be given around 70 minutes to complete two separate games, spending about the same amount of time on each.

Until recently, these games had uniformly been Ecosystem Building and Plant Defence. However, since Spring 2023, McKinsey has been rolling out a new version across certain geographies. This replaces the Plant Defence game with the new Redrock case study. Some other games have also been run as tests.

We’ll run through a little more on all these games below to give you an idea of what you’ll be up against for both versions and possible new iterations.

An important aspect that we'll cover in more detail here is that the Solve games don't only score you on your answers (your "product score"), but also on the method you use to arrive at them (your "process score") - considerably impacting optimal strategy.

In the past, candidates had to show up to a McKinsey office and take what was then the Digital Assessment or PSG on a company computer. However, candidates are now able to take the re-branded Solve assessment at home on their own computers.

Test takers are allowed to leverage any assistance they like (you aren’t spied on through your webcam as you would be with some other online tests), and it is common to have a calculator or even another computer there to make use of.

Certainly, we strongly advise every candidate to have at least a pen, paper and calculator on their desk when they take the Solve assessment.

Common Question: Is the Solve assessment the same thing as the PSG?

In short, yes - “Solve” is just the newer name for the McKinsey Problem Solving Game.

We want to clear up any potential confusion right at the beginning. You will hear this same screening test called a few different things in different places. The Solve moniker itself is a relatively recent re-branding by McKinsey. Previously, the same test was known as either the Problem Solving Game (usually abbreviated to PSG) or the Digital Assessment. You will also often see that same test referred to as the Imbellus test or game, after the firm that created the first version.

You will still see all these names used across various sites and forums - and even within some older articles and blog posts here on MyConsultingCoach. McKinsey has also been a little inconsistent on what they call their own assessment internally. Candidates can often become confused when trying to do their research, but you can rest assured that all these names refer to the same screening test - though, of course, folk might be referring to either the legacy or Redrock versions.

How and why does McKinsey use the Solve assessment?

It’s useful to understand where the Solve assessment fits into McKinsey’s overall selection process and why they have felt the need to include it.

Let’s dive right in…

How is the Solve Assessment used by McKinsey?

McKinsey's own account of how the Solve assessment is used in selection can be seen in the following video:

Whilst some offices initially stuck with the old PST, the legacy Solve assessment was soon rolled out globally and given universally to candidates for roles at pretty well every level of the hierarchy. Certainly, if you are a recent grad from a Bachelor’s, MBA, PhD or similar, or a standard experienced hired, you can expect to be asked to complete the Solve assessment.

Likewise, the new Redrock case study versions seem to be in the process of being rolled out globally - though at this point it seems you might be given either (especially as McKinsey has been having significant technical problems with this new online case study) and so should be ready for both.

At present, it seems that only those applying for very senior positions, or perhaps those with particularly strong referrals and/or connections, are allowed to skip the test. Even this will be office-dependent.

As noted above, one of the advantages of the Solve assessment is that it can be given to all of McKinsey’s hires. Thus, you can expect to be run into the same games whether you are applying as a generalist consultant or to a specialist consulting role - with McKinsey Digital , for example.

The takeaway here is that, if you are applying to McKinsey for any kind of consulting role, you should be fully prepared to sit the Solve Assessment!

Where does the Solve assessment fit into the recruitment process?

You can expect to receive an invitation to take the Solve assessment shortly after submitting your resume.

It seems that an initial screen of resumes is made, but that most individuals who apply are invited to take the Solve assessment.

Any initial screen is not used to make a significant cut of the candidate pool, but likely serves mostly to weed out fraudulent applications from fake individuals (such as those wishing to access the Solve assessment more than once so they can practice...) and perhaps to eliminate a few individuals who are clearly far from having the required academic or professional background, or have made a total mess of their resumes.

Your email invitation will generally give you either one or two weeks to complete the test, though our clients have seen some variation here - with one individual being given as little as three days.

Certainly, you should plan to be ready to sit the Solve assessment within one week of submitting your resume!

Once you have completed the test, McKinsey explain on their site that they look at both your test scores and resume (in more detail this time) to determine who will be invited to live case interviews. This will only be around 30% of the candidates who applied - possibly even fewer.

One thing to note here is that you shouldn’t expect a good resume to make up for bad test scores and vice versa. We have spoken to excellent candidates whose academic and professional achievements were not enough to make up for poor Solve performance. Similarly, we don’t know of anyone invited to interview who hadn’t put together an excellent resume.

Blunty, you need great Solve scores and a great resume to be advanced to interview.

Your first port of call to craft the best possible resume and land your invitation to interview is our excellent free consulting resume guide .

Why does this test exist?

Screenshot of an island from the McKinsey Solve assessment

As with Bain, BCG and other major management consulting firms, McKinsey receives far far more applications for each position than they can ever hope to interview. Compounding this issue is that case interviews are expensive and inconvenient for firms like McKinsey to conduct. Having a consultant spend a day interviewing just a few candidates means disrupting a whole engagement and potentially having to fly that consultant back to their home office from wherever their current project was located. This problem is even worse for second-round interviews given by partners.

Thus, McKinsey need to cut down their applicant pool as far as possible, so as to shrink the number of case interviews they need to give without losing the candidates they actually want to hire. Of course, they want to accomplish this as cheaply and conveniently as possible.

The Problem Solving Test (invariably shortened to PST) had been used by McKinsey for many years. However, it had a number of problems that were becoming more pronounced over time, and it was fundamentally in need of replacement. Some of these were deficiencies with the test itself, though many were more concerned with how the test fitted with the changing nature of the consulting industry.

The Solve assessment was originally developed and iterated by the specialist firm Imbellus ( now owned by gaming giant Roblox ) to replace the long-standing PST in this screening role and offers solutions to those problems with its predecessor.

We could easily write a whole article on what McKinsey aimed to gain from the change, but the following few points cover most of the main ideas:

  • New Challenges: Previously, candidates were largely coming out of MBAs or similar business-focussed backgrounds and the PST’s quickfire business questions were thus perfectly sufficient to select for non-technical generalist consulting roles. However, as consulting projects increasingly call for a greater diversity and depth of expertise, McKinsey cannot assume the most useful talent – especially for technical roles – is going to come with pre-existing business expertise. A non-business aptitude test was therefore required.
  • Fairness and the Modern Context: The covid pandemic necessitated at-home aptitude testing. However, even aside from this, online testing dramatically reduces the amount of travel required of candidates. This allows McKinsey to cast a wider net, providing more opportunities to those living away from hub cities, whilst also hugely reducing the carbon footprint associated with the McKinsey selection process.
  • Gaming the System: More pragmatically, the Solve assessment is a much harder test to “game” than was the PST, where highly effective prep resources were available and readily allowed a bad candidate with good preparation to do better than a good candidate. The fact that game parameters change for every individual test taker further cuts down the risk of candidates benefitting from shared information. The recent move towards the Redrock version then also helps McKinsey stay ahead of those developing prep resources for the legacy Solve assessment.
  • Cost Cutting: A major advantage of scrapping the old pen-and-paper PST is that the formidable task of thinning down McKinsey’s applicant pool can be largely automated. No test rooms and invigilation staff need to be organised and no human effort is required to devise, transport, catalogue and mark papers.

Impress your interviewer

Group of blue fish in a coral reef

There has been a bit of variation in the games included in the Solve assessment/PSG over the years and what specific form those games take. Imbellus and McKinsey had experimented with whole new configurations as well as making smaller, iterative tweaks over time. That being said, the new 2023 Redrock case studies (seemingly added by McKinsey themselves without Imbellus) are by far the largest change to Solve since that assessment's genesis back in 2017.

Given that innovation seems to continue (especially with the lengthy feedback forms some candidates are being asked to fill in after sitting the newest iteration), there is always the chance you might be the first to receive something new.

However, our surveys of, and interviews with, those taking the Solve assessment - both before and after recent changes - mean we can give you a good idea of what to expect if you are presented with either the legacy or one of the Redrock versions of Solve.

We provide much more detailed explanation of each of the games in our Solve Assessment PDF Guide - including guidance on optimal scenarios to maximise your performance. Here, though, we can give a quick overview of each scenario:

Ecosystem Building

Screenshot showing the species data from the ecosystem building game

In this scenario, you are asked to assemble a self-sustaining ecosystem in either an aquatic, alpine or jungle environment (though do not be surprised if environments are added, as this should be relatively easy to do without changing the underlying mechanics).

The game requires you to select a location for your ecosystem. Several different options are given, all with different prevailing conditions. You then have to select a number of different plant and animal species to populate a functioning food chain within that location.

In previous versions of the game, you would have had to fit as many different species as possible into a functioning food chain. However, newer iterations of the Solve assessment require a fixed number of eight or, more recently, seven species to be selected.

Species selection isn’t a free-for-all. You must ensure that all the species you select are compatible with one another - that the predator species you select are able to eat the prey you have selected for them etc. All the species must also be able to survive in the conditions prevailing at the location you have selected.

So far, this sounds pretty easy. However, the complexity arises from the strict rules around the manner and order in which the different species eat one another. We run through these in detail in our guide, with tips for getting your food chain right. However, the upshot is that you are going to have to spend some significant time checking your initial food chain - and then likely iterating it and replacing one or more species when it turns out that the food chain does not adhere to the eating rules.

Once you have decided on your food chain, you simply submit it and are moved on to the next game. In the past, test takers were apparently shown whether their solution was correct or not, but this is no longer the case.

Test takers generally report that this game is the easier of the two, whether it is paired with the Plant Defence game in the legacy Solve or the Redrock case study in the new version. Candidates will not usually struggle to assemble a functioning ecosystem and do not find themselves under enormous time pressure. Thus, we can assume that process scores will be the main differentiator between individuals for this component of the Solve assessment.

For ideas on how to optimise your process score for this game, you can see our PDF Solve guide .

Plant Defence

Screenshot showing the plant defence game in progress

As mentioned, this game has been replaced with the Redrock case study in the new newer version of the Solve assessment, rolled out from Spring 2023 and further iterated in Summer 2023. However, you might still be asked to sit the legacy version, with this game, when applying to certain offices - so you should be ready for it!

This scenario tasks you with protecting an endangered plant species from invasive species trying to destroy it.

The game set-up is much like a traditional board game, with play taking place over a square area of terrain divided into a grid of the order of 10x10 squares.

Your plant is located in a square near the middle of the grid and groups of invaders - shown as rats, foxes or similar - enter from the edges of the grid before making a beeline towards your plant.

Your job then is to eliminate the invaders before they get to your plant. You do this by placing defences along their path. These can be terrain features, such as mountains or forests, that either force the invaders to slow down their advance or change their path to move around an obstacle. To actually destroy the invaders though, you use animal defenders, like snakes or eagles, that are able to deplete the groups of invaders as they pass by their area of influence.

Complication here comes from a few features of the game. In particular:

  • You are restricted in terms of both the numbers of different kinds of defenders you can use and where you are allowed to place them. Thus, you might only have a couple of mountains to place and only be allowed to place these in squares adjacent to existing mountains.
  • The main complication is the fact that gameplay is not dynamic but rather proceeds in quite a restricted turnwise manner. By this, we mean that you cannot place or move around your defences continuously as the invaders advance inwards. Rather, turns alternate between you and invaders and you are expected to plan your use of defences in blocks of five turns at once, with only minimal allowance for you to make changes on the fly as the game develops.

The plant defence game is split into three mini-games. Each mini-game is further split into three blocks of five turns. On the final turn, the game does not stop, but continues to run, with the invaders in effect taking more and more turns whilst you are not able to place any more defences or change anything about your set-up.

More and more groups of invaders pour in, and your plant will eventually be destroyed. The test with this “endgame” is simply how many turns your defences can stand up to the surge of invaders before they are overwhelmed.

As opposed to the Ecosystem Building scenario, there are stark differences in immediate candidate performance - and thus product score - in this game. Some test takers’ defences will barely make it to the end of the standard 15 turns, whilst others will survive 50+ turns of endgame before they are overwhelmed.

In this context, as opposed to the Ecosystem Building game typically preceding it, it seems likely that product score will be the primary differentiator between candidates.

We have a full discussion of strategies to optimise your defence placement - and thus boost your product score - in our Solve guide .

Redrock Case Study

Pack of wolves running through snow, illustrating the wolf packs central to the Redrock case study

This is the replacement for the Plant Defence game in the newest iteration of Solve.

One important point to note is that, where the Solve assessment contains this case study, you have a strict, separate time limit of 35 minutes for each half of the assessment. You cannot finish one game early and use the extra time in the other, as you could in the legacy Solve assessment.

McKinsey has had significant issues with this case study, with test takers noting several major problems. In particular:

  • Glitches/crashes - Whilst the newest, Summer 2023 version seems to have done a lot to address this issue, many test takers have had the Redrock case crash on them. Usually, this is just momentary and the assessment returns to where it was in a second or two. If this happens to you, try to just keep calm and carry on. However, there are reports online of some candidates having the whole Solve assessment crash and being locked out as a result. If this happens, contact HR.
  • Poor interface - Even where there are no explicit glitches, users note that several aspects of the interface are difficult to use and/or finicky, and that they generally seem poorly designed compared to the older Ecosystem Building game preceding it. For example, test takers have noted that navigation is difficult or unclear and the drag and drop feature for data points is temperamental - all of this costing precious time.
  • Confusing language - Related to the above is that the English used is often rather convoluted and sometimes poorly phrased. This can be challenging even for native English speakers but is even worse for those sitting Solve in their second language. It can make the initial instructions difficult to understand - compounding the previous interface problem. It can also make questions difficult, requiring a few readings to comprehend.
  • Insufficient time - Clearly, McKinsey intended for Redrock to be time pressured. Whilst the newest, Summer 2023 iteration of the Redrock case seems slightly more forgiving in this regard, time is still so scarce that many candidates don't get through all the questions. This is plainly sub-optimal for McKinsey - as well as being stressful and disheartening for candidates. We would expect further changes to be made to address this issue in future.

McKinsey are clearly aware of these issues, as even those sitting the new version of Redrock have been asked to complete substantial feedback surveys. Do note, then, that this raises the likelihood of further changes to the Redrock case study in the near term - meaning you should always be ready to tackle something new.

For the time being, though, we can take you through the fundamentals of the current version of the Redrock case study. For more detail, see our freshly updated PDF Guide .

The Scenario

Whilst changes to the details are likely in future, the current Redrock case study is set on the Island of Redrock. This island is a nature reserve with populations of various species, including wolves, elk and several varieties of plant.

In the original Redrock case, it is explained that the island's wolves are split into four packs, associated with four geographical locales. These packs predate the elk and depend upon them for food, such that there is a dynamic relationship between the population numbers of both species. Your job is to ensure ecological balance by optimising the numbers of wolves in the four packs, such that both wolves and elk can sustainably coexist.

In the newer iteration of the case, first observed in Summer 2023, you are asked to assess which, if any, of three possible strategies can successfully boost the island's plant biodiversity by a certain specified percentage. Plants here are segmented into grasses, trees and shrubs.

The Questions

The Redrock case study's questions were initially split into three sections, but a fourth was added later. These sections break down as follows:

  • Investigation - Here, you have access to the full description of the case, with all the data on the various animal populations. Your task is to efficiently extract all the most salient data points and drag-and-drop them to your "Research Journal" workspace area. This is important, as you subsequently lose access to all the information you don't save at this stage.
  • Analysis - You must answer three numerical questions using information you saved in the Investigation section. This can include you dragging and dropping values to and from an in-game calculator.
  • Report - Formerly the final section, you must complete a pre-written report on the wolf populations or plant biodiversity levels, including calculating numerical values to fill in gaps and using an in-game interface to make a chart to illustrate your findings. You will leverage information saved in the Investigation section, as well as answers calculated in the Analysis section.
  • Case Questions - This section adds a further ten individual case questions. These are wolf-themed, so are thematically similar to the original Redrock case, but are slightly incongruous with the newer, plant-themed version of Redrock. In both instances, though, these questions are entirely separable from the main case preceding them, not relying on any information from the previous sections. The ten questions are highly quantitative and extremely time pressured. Few test takers finish them before being timed out.

This is a very brief summary - more detail is available in our PDF Guide .

Other Games - Disease and Disaster Identification

Screenshot of a wolf and beaver in a forest habitat from the Solve assessment

There have been accounts of some test takers being given a third game as part of their Solve assessment. At time of writing, these third games have always been clearly introduced as non-scored beta tests for Imbellus to try out potential new additions to the assessment. However, the fact that these have been tested means that there is presumably a good chance we’ll see them as scored additions in future.

Notably, these alternative scenarios are generally variations on a fairly consistent theme and tend to share a good deal of the character of the Ecosystem Building game. Usually, candidates will be given a whole slew of information on how an animal population has changed over time. They will then have to wade through that information to figure out either which kind of natural disaster or which disease has been damaging that population - the commonality with the Ecosystem Building game being in the challenge of dealing with large volumes of information and figuring out which small fraction of it is actually relevant.

Join thousands of other candidates cracking cases like pros

What does the solve assessment test for.

Chart from Imbellus showing how they test for different related cognitive traits

Whilst information on the Solve assessment can be hard to come by, Imbellus and McKinsey have at least been explicit on what traits the test was designed to look for. These are:

Diagram showing the five cognitive traits examined by the Solve Assessment

  • Critical Thinking : making judgements based on the objective analysis of information
  • Decision Making : choosing the best course of action, especially under time pressure or with incomplete information
  • Metacognition : deploying appropriate strategies to tackle problems efficiently
  • Situational Awareness : the ability to interpret and subsequently predict an environment
  • Systems Thinking : understanding the complex causal relationships between the elements of a system

Equally important to understanding the raw facts of the particular skillset being sought out, though, is understanding the very idiosyncratic ways in which the Solve assessment tests for these traits.

Let's dive deeper:

Process Scores

Perhaps the key difference between the Solve assessment and any other test you’ve taken before is Imbellus’s innovation around “process scores”.

To explain, when you work through each of the games, the software examines the solutions you generate to the various problems you are faced with. How well you do here is measured by your “product score”.

However, scoring does not end there. Rather, Solve's software also constantly monitors and assesses the method you used to arrive at that solution. The quality of the method you used is then captured in your “process score”.

To make things more concrete here, if you are playing the Ecosystem Building game, you will not only be judged on whether the ecosystem you put together is self-sustaining. You will also be judged on the way you have worked in figuring out that ecosystem - presumably, on how efficient and organised you were. The program tracks all your mouse clicks and other actions and will thus be able to capture things like how you navigate around the various groups of species, how you place the different options you select, whether you change your mind before you submit the solution and so on.

You can find more detail on these advanced aspects of the Solve assessment and the innovative work behind it in the presentation by Imbellus founder Rebecca Kantar in the first section of the following video:

Compared to other tests, this is far more like the level of assessment you face from an essay-based exam, where the full progression of your argument towards a conclusion is marked - or a maths exam, where you are scored on your working as well as the final answer (with, of course, the major advantage that there is no highly qualified person required to mark papers).

Clearly, the upshot of all this is that you will want to be very careful how you approach the Solve assessment. You should generally try to think before you act and to show yourself in a very rational, rigorous, ordered light.

We have some advice to help look after your process scores in our PDF Guide to the McKinsey Solve Assessment .

A Different Test for Every Candidate

Another remarkable and seriously innovative aspect of the Solve assessment is that no two candidates receive exactly the same test.

Imbellus automatically varies the parameters of their games to be different for each individual test taker, so that each will be given a meaningfully different game to everyone else’s.

Within a game, this might mean a different terrain setting, having a different number of species or different types of species to work with or more or fewer restrictions on which species will eat which others.

Consequently, even if your buddy takes the assessment for the same level role at the same office just the day before you do, whatever specific strategy they used in their games might very well not work for you.

This is an intentional feature designed to prevent test takers from sharing information with one another and thus advantaging some over others. At the extreme, this feature would also be a robust obstacle to any kind of serious cheating.

To manage to give every candidate a different test and still be able to generate a reliable ranking of those candidates across a fundamental skillset, without that test being very lengthy, is a considerable achievement from Imbellus. At high level, this would seem to be approximately equivalent to reliably extracting a faint signal from a very noisy background on the first attempt almost every time.

(Note that we are yet to confirm to what extent and how this also happens with the new Redrock case studies, but it seems to be set up to allow for easy changes to be made to the numerical values describing the case, so we assume there will be similar, widespread of variation.)

Preparation for the McKinsey Solve assessment

Understanding what the Solve assessment tests for immediately begs the question as to whether it is possible to usefully prepare and, if so, what that preparation should look like.

Is it Really Possible to Prepare for the McKinsey Solve Assessment?

Clown fish swimming in a coral reef

In short, yes you can - and you should!

As noted previously, there has been a lot of disagreement over whether it is really possible to prep for the Solve assessment in a way that actually makes a difference.

Especially for the legacy version, there has been a widespread idea that the Solve assessment functions as something like an IQ test, so that preparation beyond very basic familiarisation to ensure you don’t panic on test day will not do anything to reliably boost your scores (nobody is going to build up to scoring an IQ of 200 just by doing practice tests, for example).

This rationale says that the best you can do is familiarise yourself with what you are up against to calm your nerves and avoid misunderstanding instructions on test day. However, this school of thought says there will be minimal benefit from practice and/or skill building.

The utility of preparation has become a clearer with the addition of the Redrock case study to the new version of Solve. Its heavily quantitative nature, strong time pressure and structure closely resembling a traditional business case make for a clearer route to improvement.

However, as we explain in more detail in our PDF guide to the Solve assessment, the idea that any aspect of either version of Solve can't be prepared for has been based on some fundamental misunderstandings about what kind of cognitive traits are being tested. Briefly put, the five key skills the Solve assessment explicitly examines are what are known as higher-order thinking skills.

Crucially, these are abilities that can be meaningfully built over time.

McKinsey and Imbellus have generally advised that you shouldn’t prepare. However, this is not the same as saying that there is no benefit in doing so. McKinsey benefits from ensuring as even a playing field as possible. To have the Solve test rank candidates based purely on their pre-existing ability, they would ideally wish for a completely unprepared population.

How to prep

Two stingrays and a shark swimming in blue water, lit from above

We discuss how to prep for the Solve assessment in full detail in our PDF guide . Here, though, we can give you a few initial pointers to get you started. In particular, there are some great ways to simulate different games as well as build up the skills the Solve assessment tests for.

Playing video games is great prep for the legacy Solve assessment in particular, but remains highly relevant to the new Redrock version.

Contrary to what McKinsey and Imbellus have said - and pretty unfortunately for those of us with other hobbies - test takers have consistently said that they reckoned the Problem Solving Game, and now the Solve assessment, favours those with strong video gaming experience.

If you listened when your parents told you video games were a waste of time and really don’t have any experience, then putting in some hours on pretty much anything will be useful. However, the closer the games you play are to the Solve scenarios, the better. We give some great recommendations on specific games and what to look for more generally in our Solve guide - including one free-to-play game that our clients have found hugely useful as prep for the plant defence game!

PST-Style Questions

The inclusion of the Redrock case studies in the new version of Solve really represents a return to something like a modernised PST. Along with the similar new BCG Casey assessment, this seems to be the direction of travel for consulting recruitment in general.

Luckily, this means that you can leverage the wealth of existing PST-style resources to your advantage in preparation.

Our PST article - which links to some free PST questions and our full PST prep resources - is a great place to start. However, better than old-fashioned PDF question sets are the digital PST-style questions embedded in our Case Academy course . Conducted online with a strict timer running, these are a much closer approximation of the Solve assessment itself. These questions are indeed a subset of our Case Academy course, but are also available separately in our Course Exercises package .

Quick Mathematics With a Calculator and/or Excel

Again, specifically for the Redrock assessment, you will be expected to solve math problems very quickly. The conceptual level of mathematics required is not particularly high, but you need to know what you are doing and get through it fast using a calculator nand/or Excel, if you are already comfortable with that program.

Our article on consulting math is a great place to start to understand what is expected of you throughout the recruiting process, with our consulting math package (a subset of our Case Academy course) providing more in-depth lessons and practice material.

Learn to Solve Case Studies

With the Redrock case studies clearly being ecology-themed analogues to standard business case studies, it's pretty obvious that getting good at case studies will be useful.

However, the Solve assessment as a whole is developed and calibrated to be predictive of case interview performance, so you can expect that improving your case solving ability will indirectly bring up your performance across the board.

Of course, this overlaps with your prep for McKinsey's case interviews. For more on how to get started there, see the final section of this article.

Learning About Optimal Strategies for the Games

The first thing to do is to familiarise yourself with the common game scenarios from the Solve assessment and how you can best approach them to help boost your chances of success.

Now, one thing to understand is that, since the parameters for the games change for each test taker, there might not be a single definitive optimal strategy for every single possible iteration of a particular game. As such, you shouldn’t rely on just memorising one approach and hoping it matches up to what you get on test day.

Instead, it is far better to understand why a strategy is sensible in some circumstances and when it might be better to do something else instead if the version of the game you personally receive necessitates a different approach.

In this article, we have given you a useful overview of the games currently included in the Solve assessment. However, a full discussion with suggested strategies is provided in our comprehensive Solve guide .

With the limited space available here, this is only a very brief sketch of a subset of the ways you can prep.

As noted, what will help with all of these and more is reading the extensive prep guidance in our full PDF guide to the Solve assessment...

The MCC Solve Assessment Guide

Preparing for the Solve assessment doesn’t have to be a matter of stumbling around on your own. This article is a good introduction. From here, though our new, updated PDF guide to the McKinsey Solve assessment is your first stop to optimise your Solve preparation.

This guide is based on our own survey work and interviews with real test takers, as well as iterative follow-ups on how the advice in previous editions worked out in reality.

Does it make sense to invest in a guide?

Short answer: yes. If you just think about the financials, a job at McKinsey is worth millions in the long run. If you factor in experience, personal growth and exit opportunities, the investment is a no-brainer.

How our guide can help you ace the test

Don't expect some magic tricks to game the system (because you can't), but rather an in-depth analysis of key areas crucial to boost your scores. This helps you to:

As noted, the guide is based on interviews with real recent test takers and covers the current games in detail. Being familiar with the game rules, mechanics and potential strategies in advance will massively reduce the amount of new information you have to assimilate from scratch on test day, allowing you to focus on the actual problems at hand.

Despite the innovative environment, the Solve assessment tests candidates for the same skills evaluated in case interviews, albeit on a more abstract level. Our guide breaks these skills down and provides a clear route to develop them. You also benefit from the cumulative experience of our clients, as we have followed up to see which prep methods and game strategies were genuinely helpful.

A clear plan of how to prepare is instrumental for success. Our guide includes a detailed, flexible preparation strategy, leveraging a whole host of diverse prep activities to help you practice and build your skills as effectively as possible. Importantly, our guide helps you prioritise the most effective aspects of preparation to optimise for whatever timeframe you have to work in.

Overall, the MyConsultingCoach Solve guide is designed to be no-nonsense and straight to the point. It tells you what you need to know up front and - for those of you in a hurry - crucial sections are clearly marked to read first to help you prep ASAP.

For those of you starting early with more time to spare, there is also a fully detailed, more nuanced discussion of what the test is looking for and how you can design a more long-term prep to build up the skills you need - and how this can fit into your wider case interview prep.

Importantly, there is no fluff to bulk out the page count. The market is awash with guides at huge page counts, stuffed full of irrelevant material to boost overall document length. By contrast, we realise your time is better spent actually preparing than ploughing through a novel.

If this sounds right for you, you can purchase our PDF Solve guide here:

McKinsey Solve Assessment Guide

  • Full guide to both the legacy version of the Solve assessment and the newer Redrock Case Study versions
  • In-depth description of the different games and strategies to beat them
  • Preparation strategies for the short, medium and long-term prep
  • No fluff - straight to the point, with specific tips for those without much time
  • Straight to your inbox
  • 30 days money-back guarantee, no questions asked. Simply email us and we will refund the full amount.

The Next Step - Case Interviews

Male interviewer with laptop administering a case study to a female interviewee

So, you pour in the hours to generate an amazing resume and cover letter. You prepare diligently for the Solve assessment, going through our PDF guide and implementing all the suggestions. On test day, you sit down and ace Solve. The result is an invitation to a live McKinsey case interview.

Now the real work begins…

Arduous as application writing and Solve prep might have seemed, preparing for McKinsey case interviews will easily be an order of magnitude more difficult.

Remember that McKinsey tells candidates not to prepare for Solve - but McKinsey explicitly expects applicants to have rigorously prepared for case interviews .

The volume of specific business knowledge and case-solving principles, as well as the sheer complexity of the cases you will be given, mean that there is no way around knuckling down, learning what you need to know and practicing on repeat.

If you want to get through your interviews and actually land that McKinsey offer, you are going to need to take things seriously, put in the time and learn how to properly solve case studies.

Unfortunately, the framework-based approach taught by many older resources is unlikely to cut it for you. These tend to falter when applied to difficult, idiosyncratic cases - precisely the kind of case you can expect from McKinsey!

The method MCC teaches is based specifically on the way McKinsey train incoming consultants. We throw out generic frameworks altogether and show you how to solve cases like a real management consultant on a real engagement.

You can start reading about the MCC method for case cracking here . To step your learning up a notch, you can move on to our Case Academy course .

To put things into practice in some mock interviews with real McKinsey consultants, take a look at our coaching packages .

And, if all this (rightfully) seems pretty daunting and you’d like to have an experienced consultant guide you through your whole prep from start to finish, you can apply for our comprehensive mentoring programme here .

Looking for an all-inclusive, peace of mind program?

Our comprehensive packages.

Get our Solve guide for free if you purchase any of the following packages. Just email us with your order number and we will send the guide straight to your inbox.

Access to our Case Academy and to coaching will help you prepare for Solve and for the following rounds!

The MCC bundle

  • All Case Interview Course Videos
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Bridge to Consulting

  • 5 one-hour sessions with ex-MBB (McKinsey/Bain/BCG) coach of your choice
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Case Interview Course

  • 16+ hours of lectures  covering  all aspects of the case interview
  • Introduction to the consulting interview
  • Case Interview foundations section 
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MECE Framework McKinsey

  “MECE,” pronounced “me see,” an acronym for “mutually exclusive and collectively exhaustive,” is a popular mantra at McKinsey. If you manage to get a position at McKinsey, or at any other MBB for that matter, you are likely to have to handle huge amounts of data. Chances are that your boss will ask you to ensure that you organize your data in an “MECE manner.” “Be more ‘MECE’ in your approach,” she might say. In fact, even at your case interview, you likely used the MECE principle. You might not have got the green signal if you hadn’t.  

Introduction and definition

MECE is a method of grouping information into elements that are mutually exclusive (ME) and collectively exhaustive (CE). In other words, it is a process by which information—ideas, topics, issues, solutions—is arranged or, put in “MECE buckets,” with no overlapping between buckets and with each item having a place in one bucket only (ME), and with the buckets including all possible items relevant to the context.

A simple example of the MECE principle would be the classification of the population into age groups. Here, dividing the population into two groups, one group of people above, say, 60, and another group below 60, would be based on the MECE principle. The entire population would be either above or below 60 (ME, with no overlapping between the two buckets) and with all people included in one or the other bucket (CE).

However, a categorization of the population into one group of, say, people below 60 and another of people between 50 and 70 would not be based on MECE. People between 50 and 60 would be in both “buckets” (not ME) and some people would not be in either bucket (so not CE).  

How is it used?

Strategy consultants use the MECE framework (Issue Tree, Decision Tree, Hypothesis Tree) to segregate a client’s problems into logical data categories that can be analyzed systematically and minutely by their staff involved with the project. The framework is notably used at McKinsey, where data from clients’ businesses is organized on the basis of MECE. Well-known frameworks, such as Cost-Benefit Analysis, 4Cs, and Porter’s Five Forces have the MECE principle at their core.

Let’s discuss three popular MECE frameworks.  

How is the MECE framework used to solve clients’ issues at consultancies? One method consultants use is to create an “issue tree” to arrange all the information that they have and divide this information into all possible issues and sub-issues.

An issue tree is particularly helpful for solving large and complex problems as it facilitates splitting them up into smaller, solvable problems. “Issue trees” get their names from their structure—narrow at the top with the problem statement, and wider towards the bottom, even as each level accommodates more specific sub-issues or smaller problems. However, some “trees” are also created left to right, but the principle remains the same.

A common type of cases in which a MECE issue tree is used is profitability cases. Suppose the problem statement is “My restaurant is not profitable.” An issue tree is created, starting with the problem statement at the treetop.

The various sub-levels of the tree would answer the question “How to make the restaurant profitable?” in broad, intuitive ways: “Increase revenue” and “Reduce costs.” The lower levels would also answer the question “How?”

The second level, with sub-issues of the first level, would answer the questions “How to increase revenue?” (under “Increase revenue”) on the one hand and “How to reduce costs?” on the other. The answers under “Increase revenue” would be “Increase the number of orders” and “Increase the prices of items.” The answers under “Reduce costs” would be “Reduce salary expenditure,” “Reduce rental,” and “Reduce raw material expenses.”

On the third level, the issue tree would tackle the question “How to Increase the number of orders?” One way to increase orders would be to shift the restaurant to a busier area and another would be to launch a marketing campaign so that the restaurant becomes more widely known. On the other main branch, under “reduce salary expenditure,” options such as “fire redundant workers” could be mentioned, as also “shift to a less expensive locality” under “reduce rental”, and “change the vendors,” under “reduce raw material expenses.”

How does an issue tree help? It enables consultants to consider all options separately and exclusively and suggest the best option to the client. It helps create a common understanding among team members about the problem-solving framework and focus team efforts. It smoothens work distribution among team members.

Often, consultants who create an issue tree may need to “trim branches,” which means doing away with options that are not worth pursuing after a detailed initial consideration. In the example of the issue tree, given above, about how to increase the profitability of a restaurant, increasing prices may not be an option for various reasons, and that “branch” of the issue tree may be left out or “trimmed.”

Issue Tree

Decision tree

A decision tree is a tree-shaped graphical representation of decisions and potential outcomes of those decisions, and is used to determine a course of action. A decision tree helps users understand the comparative advantages and disadvantages of each decision and outcome.

A decision tree is often drawn from left to right. It starts with a specific decision denoted by a small square. “Branches,” or lines, are drawn to the right from the square, representing each potential option. If the option is a new decision, a square is drawn, and from it, new branches are drawn, representing new options. At the end of each branch, a circle is drawn if the result of the option is unclear. If the option leads to a decision that helps bring about a solution, the branch is left blank. A triangle is also used to signify the end of a branch or path to a potential solution.

Like an issue tree, a decision tree is exhaustive in its inclusion of decision, outcomes, options, and scenarios. A user of a decision tree looks at each of them and chooses the best option.

Decision Tree

Hypothesis tree

Another method to structure a problem is to develop a hypothesis tree, which is the graphical representation of all MECE hypothesis that elucidates the problem. It is, in a way, similar to an issue tree, where a problem is broken down into its components, which makes identifying and solving it easier. But while an issue tree splits up each problem into issues and sub-issues, a hypothesis tree organizes a problem around hypotheses, and often offers a more direct approach than an issue tree.

Hypothesis Tree

Developing MECE hypotheses

First, understand the problem thoroughly. What are you trying to solve?

Second, write down the problem statement. Take care to ensure clarity in the statement so that there is no ambiguity.

Third, list the options to solve the problem, using a MECE tree. See that the options do not overlap (that they are mutually exclusive) and that no option has been left out (that they are collectively exhaustive).

Fourth, consider each option individually. Consider the pros and cons. Leave out those that are illogical and include any new insight as an option as you understand the problem better.

Fifth, select the best option and present it to the client.  

Clarity pays

Good management consultants use the MECE structure for problem-solving. A piece of advice they like to give to aspiring consultants is to learn to use the MECE principle for not only structuring problems but also communicating solutions, whether they are attending a case interview at MBB or sitting across the desk from a client.

Creating a MECE hypothesis helps clarifies a problem. It’s like having a road map when you are lost in unknown territory. If your approach to structuring a problem is “not MECE,” “it is probably messy,” as they say.   Found this lesson useful? You’re going to love our online Mini MBA certificate course. It covers other important strategy concepts (including powerful frameworks), as well as the wider range of super-essential business topics.

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  Resources: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14

Can AI help you solve problems?

May 21, 2023 AI technology has revolutionized the way organizations do business; now, with proper guardrails in place, generative AI promises to not only unlock novel use cases for businesses but also speed up, scale, or otherwise improve existing ones. “Companies across sectors, from pharmaceuticals to banking to retail, are already standing up a range of use cases to capture value creation potential,” write Michael Chui , Roger Roberts , Tanya Rodchenko, Alex Singla , Alex Sukharevsky , Lareina Yee , and Delphine Zurkiya  in a new article . Generative AI is nascent, but as it develops and becomes increasingly, and more seamlessly, incorporated into business, its problem-solving potential will intensify. Check out these insights to understand how both AI and generative AI can help your organization solve complex problems, transform operations, improve products, and realize new revenue streams.

What every CEO should know about generative AI

Generative AI is here: How tools like ChatGPT could change your business

What is generative AI?

Exploring opportunities in the generative AI value chain

AI-powered sales and marketing reach new heights with generative AI

Smart scheduling: How to solve workforce-planning challenges with AI

Author Talks: In the ‘age of AI,’ what does it mean to be smart?

The potential value of AI—and how governments could look to capture it

How AI can accelerate R&D for cell and gene therapies

How AI can assist in Asia’s net-zero transition

Evolving institutional finance with AI

Generative AI: Unlocking the future of fashion

MORE FROM MCKINSEY

Legal innovation and generative AI: Lawyers emerging as ‘pilots,’ content creators, and legal designers

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The Ultimate Guide to Acing the McKinsey Case Interview (Problem-Solving Interview)

the image is the cover for the mckinsey case interview or problem solving interview article

Last Updated on September 13, 2023

The McKinsey case interview, also called the Problem-Solving Interview by the firm, is a crucial and defining element of the consulting recruitment process for one of the world’s most prestigious management consulting firms. This unique type of interview assesses a candidate’s analytical, problem-solving, and communication skills, as well as their ability to think critically under pressure. With a reputation for being challenging and rigorous, the McKinsey case interview is often seen as a significant hurdle for aspiring consultants to overcome. Forbes ranked McKinsey’s interview process as the most difficult across all firms globally and the case plays a crucial role in that evaluation, besides the Personal Experience Interview .

Recognizing the importance of thorough preparation, this article aims to become the go-to resource for candidates worldwide who are seeking to excel in the McKinsey case interview and want to kickstart their McKinsey careers. By providing comprehensive insights, practical tips, and concrete examples, our goal is to equip you with the knowledge and confidence required to stand out in the competitive world of management consulting.

As former McKinsey consultants and interview experts, we have specialized in helping our candidates to effectively tackle this part of the McKinsey assessment. We found that the information on the McKinsey application process and specifically the case interviews is often wrong, outdated, or assumed to be the same as for every other consulting firm, and written by ‘experts’, who have never conducted an interview at McKinsey or even seen a McKinsey office from the inside.

As a consequence, the advice given can be detrimental to your recruiting success with the firm. In this article, we want to shed some light on this mysterious, often-talked-about, even more often misunderstood interview.

McKinsey’s Interview Process

Overview of the recruitment process.

The McKinsey recruitment process typically consists of the following stages:

  • Application submission: Candidates submit their resume, cover letter, and academic transcripts online.
  • Online assessments: Selected candidates may be invited to complete an online assessment, the McKinsey Solve Game (previously known as the Imbellus test, or Problem Solving Game/PSG)
  • First-round interviews: Successful candidates progress to first-round interviews, which typically involve two separate interviews, each consisting of a Personal Experience Interview (PEI) and a case interview.
  • Final-round interviews: Candidates who excel in the first round are invited to final-round interviews, which usually consist of two to three separate interviews with more senior McKinsey consultants or partners, again featuring a PEI and a case interview in each session.
  • Offer decision: Following the final round, the firm makes a decision on whether to extend an offer to the candidate.

the image provides an overview of the mckinsey interview process

The Personal Experience Interview (PEI)

The Personal Experience Interview (PEI) is a critical component of McKinsey’s interview process. During the PEI, the interviewer will ask the candidate to share a specific example from their past experiences that demonstrates one of McKinsey’s core values, such as leadership, personal impact, or the ability to deal with change. Candidates should prepare concise and compelling stories that highlight their achievements, challenges faced, and the lessons learned. The PEI aims to assess the candidate’s interpersonal skills, self-awareness, and overall fit with McKinsey’s culture.

The Case Interview (Problem-Solving Interview)

The case interview is the centerpiece of McKinsey’s interview process. In this interview, the candidate is presented with a real-life or hypothetical business problem, which they must analyze and solve. The interviewer will assess the candidate’s ability to structure the problem, analyze data, generate insights, and communicate recommendations effectively. During the case interview, candidates should exhibit strong problem-solving, analytical, and communication skills, as well as the ability to think critically under pressure. Preparing for the case interview involves practicing a variety of cases, developing essential skills, and understanding the McKinsey case interview framework (more on that below).

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Understanding the McKinsey Case Interview

What is a case interview.

A case interview is a unique type of job interview that tests a candidate’s ability to analyze, solve, and communicate complex business problems. During a case interview, the interviewer presents a real-life or hypothetical business scenario, and the candidate is expected to analyze the situation, identify the key issues, and propose a strategic solution. The case interview format allows the interviewer to evaluate a candidate’s problem-solving, analytical, and interpersonal skills, which are essential for a successful career in management consulting.

Why does McKinsey use case interviews?

McKinsey & Company uses case interviews as a key component of its recruitment process for several reasons. First, the case interview format closely simulates the work environment and tasks that consultants face daily, providing the firm with a more accurate assessment of a candidate’s potential performance. Second, case interviews allow McKinsey to evaluate a candidate’s ability to think critically, structure complex problems, and communicate effectively under pressure—skills that are crucial for consultants who must deliver high-quality solutions to clients. Lastly, case interviews serve as a consistent and objective measure of a candidate’s capabilities, enabling the firm to compare candidates from diverse backgrounds fairly and accurately.

What is different in McKinsey’s interview format?

The McKinsey Problem Solving Interview is a typical case interview as it is employed by most consulting firms to test the analytical capabilities and communication skills of applicants. However, it comes with a twist. The interview simulates a client situation, where you are tasked to solve a specific business problem that they are facing. You will have to answer a succession of several questions rather than driving the case yourself as would be the case in other consulting firms. Within the interview, which is a dialogue between you and the interviewer, you need to structure problems, propose concrete ideas, gather information, spot insights in data and charts, solve quantitative problems, and communicate in a professional and calm manner.

The case is the hardest part for most candidates since it involves a number of different skills that need to be demonstrated consistently across all questions and across multiple cases in succession. Depending on the office, applicants need to go through four to six case interviews before receiving an offer. They need to convince the interviewers in all cases to start their McKinsey careers.

Types of cases you may encounter

During a McKinsey case interview, candidates may encounter a variety of case types that cover different industries, functions, and challenges. The following is just a selection of potential case problems that you would need to solve.

  • Market entry: Evaluating the attractiveness of entering a new market or launching a new product or service.
  • Growth strategy: Identifying opportunities for a company to grow its revenue, market share, or profitability.
  • Mergers and acquisitions: Assessing the feasibility and potential value of merging with or acquiring another company.
  • Cost reduction: Identifying areas for cost savings and efficiency improvements in a company’s operations or supply chain.
  • Pricing strategy: Determining the optimal pricing structure for a product or service to maximize revenue or profit.
  • Organizational restructuring: Evaluating changes to a company’s organizational structure or management processes to improve performance.
  • Operational improvements: Figure out and improve operational issues.

While the specifics of each case may differ, the core skills required to tackle these cases—such as structuring, data analysis, and problem-solving—remain consistent across all case types.

On top of that, McKinsey cases have become much more creative over the last couple of years, hence, using memorized and established frameworks will never serve you well . Rather it is important to approach every McKinsey case from a first-principles approach.

For instance, consider the following real McKinsey case example.

You are working with an operator of a specific type of machines. They break down at different rates at different locations. What factors can you think of why that would happen? Example of a McKinsey Case Interview Structure Questions

There is not a single memorized framework bucket that would work here. Let us look at an example answer for this prompt.

issue based problem solving mckinsey

Less than 1% of candidates make it through the recruiting filters of McKinsey. You want to provide insights that the interviewer has not heard before and not be just like the other 99% that fail to impress.

What is the format of the McKinsey case?

A typical McKinsey case follows the PEI in a one-hour interview session. It lasts for 25 to 30 minutes in an interviewer-led format , meaning that the interviewer takes the lead and guides you through the case. Your role as the interviewee is to answer the questions asked by the interviewer before they will move on to the next question. While it is the interviewer’s responsibility to provide hints and move you through the different questions, you should take the lead within each question.

Depending on your performance and speed, you will be asked three to six questions . Only receiving three questions is actually a positive sign since the interviewer was happy with your answers to each question. Going above three questions usually happens when the interviewer wants to dig deeper into a specific question type to see if the quality of a previous answer to a similar question was just an outlier or can be confirmed with a second question. Most candidates need more than three questions to convince the interviewer, so don’t be scared when your case gets a little bit longer and consists of more than three questions.

Some offices also offer a McKinsey phone case interview as a first screening device, which follows the same structure as an in-person interview.

Is the McKinsey case interview different from a BCG or Bain interview?

While there are many similarities in McKinsey interviews and interviews with other firms, McKinsey interviews are interviewer-led, while other firms employ a candidate-led format .

McKinsey, BCG, and Bain cases have certain things in common:

  • The elements of the cases are the same. You will have to structure problems, interpret exhibits, and work through some calculations, come up with recommendations or implications, etc.
  • The skills that are assessed are the same. You need to exhibit strong problem-solving skills, creativity, ability to work under pressure, top-down communication, etc.

However, there is one key difference:

  • In interviewer-led cases, you take ownership of every question and go into greater detail here, while the interviewer guides you from question to question. In the interviewee-led case, you drive the whole case and have to move along, get the correct information to work with by asking the right questions, and analyze the problem to then deduct a recommendation

In a McKinsey case, the interviewer will guide you through a series of connected questions that you need to answer, synthesize, and develop recommendations from. There are clear directions and a flow of questions, which you need to answer with a hypothesis-driven mindset . These are arguably easier to prepare for and to go through since the flow and types of questions will always be the same.

For McKinsey case interview examples, check the available interviewer-led cases  here .

In a candidate-led BCG case interview or Bain case interview, due to the nature of your role as an investigator, it is much easier to get lost, walk down the wrong branch of the issue tree, and waste a ton of time. While the interviewers will try to influence you to move in the right direction (pay attention to their hints), it is still up to you what elements of the problem you would like to analyze. Each answer should lead to a new question (hypothesis-driven) on your quest to find the root cause of the problem to come up with a recommendation on how to overcome it.

What are the questions of a McKinsey case interview?

In the McKinsey interview you will have to answer  three different questions types  – broadly speaking:

  • Structuring (includes creating frameworks and brainstorming questions)
  • Exhibit Interpretation

Structuring

Structuring includes both the framework creation at the beginning of a case as well as answering brainstorming questions (usually at a later stage of the case).

A case interview structure is used to break the problem you are trying to solve for the client down into smaller problems or components. It is the roadmap you establish at the beginning of the interview that will guide your problem-solving approach throughout the case. A strong initial structure should cover all elements of the situation AND allow you to understand where the problem is coming from. Read more about case interview structure and frameworks here .

A common question would be:

What factors would you look at to understand the problem better? McKinsey framework question

Brainstorming has you come up with specific ideas around a certain topic (in a structured m anner). Read more about brainstorming here .

What ideas do you have that could decrease customer check-out time? McKinsey brainstorming question

Data interpretation

For chart or data interpretation , you are tasked to find the key insights of 1-2 PowerPoint slides and relate them back to the case question and the client situation at hand. Read more about exhibit interpretation here .

Case math questions have you analyze a problem mathematically before qualitatively investigating the particular reason for the numerical result or deriving specific recommendations from the outcome. Read more on how to ace case math here .

Now for  structure and exhibit interpretation , there is no right or wrong answer in a McKinsey interview. Some answers are better than others because they are

  • hypothesis-driven
  • follow strong communication (MECE, top-down, signposted)

That being said, there is no 100% that you can reach or a one-and-only solution/ answer. It is important that your answers display the characteristics specified above and are supported well with arguments.

As for  math questions , usually, there are answers which are correct (not always 100% the same since some candidates simplify or round differently – which is ok), and others that are wrong, either due to the

  • calculation approach
  • calculation itself

Now, for the interviewer, the overall picture counts. Mistakes in one area need to be balanced by a strong performance in other areas. McKinsey wants to see spikes in performance in certain areas and a good enough performance in other areas.

The most common example we see almost every day: You can be strong in structure and exhibit, yet make a small mistake in the math section – overall as you might consider 80% – and still pass on to the next round.

Be aware that in 99% of cases, there is no recommendation question in the end. The case just ends with the last case question. This is something many candidates are surprised by when they get out of their McKinsey interviews.

Mastering the McKinsey Case Interview Framework

In the sequence of questions that you receive, you need to demonstrate that you are able to

  • identify the ask;
  • structure the problem to investigate it;
  • analyze data related to it;
  • generate insight and recommendations;
  • communicate effectively.

Problem identification

The first step in tackling a McKinsey case interview is to identify the core problem or question that needs to be addressed. Carefully listen to the case prompt and take notes, ensuring that you understand the client’s objectives, the scope of the problem, and any constraints. Clarify any uncertainties with the interviewer before moving forward.

Structuring the problem

Once you have identified the problem, develop a structured approach to address it. Break down the problem into smaller, more manageable components using logical frameworks. Tailor the chosen framework to the specific case, incorporating any unique factors or considerations. Present your structure to the interviewer, explaining your rationale and seeking their input or approval.

Data analysis and interpretation

As you proceed with your structured approach, you may be provided with additional data or information by the interviewer. Analyze the data, using quantitative techniques, such as calculating growth rates, market shares, or breakeven points, to draw meaningful insights. Be prepared to make assumptions or estimates if necessary but ensure they are reasonable and well-justified.

Generating insights and recommendations

Based on your data analysis, develop actionable insights and recommendations that address the client’s objectives. Consider the potential impact, feasibility, and risks associated with each recommendation. Think creatively and strategically, incorporating both qualitative and quantitative factors into your decision-making process.

Synthesis and communication

Finally, synthesize your findings and recommendations into a clear and concise conclusion. Use the “top-down” communication style, starting with your main recommendation, followed by the supporting evidence and insights. Demonstrate strong communication skills by articulating your thought process and recommendations persuasively and confidently. Be prepared to answer any follow-up questions from the interviewer and engage in a discussion to defend or refine your conclusions.

  • Pyramid principle communication
  • How to communicate in a case interview

In this format, McKinsey assesses in a case interview six skills that you need to demonstrate consistently in every case interview.

What skills are assessed by McKinsey?

  • Problem-solving: Are you able to derive a MECE (mutually exclusive, collectively exhaustive) framework, breaking a problem down into smaller problems, and accurately covering all aspects of the problem?
  • Analytical rigor and logical thinking: Can you link the structure to creative thinking? Are you using a hypothesis-driven approach to your problem solving, i.e. have a clear picture of where you think the solution of the case is buried most likely? Do you qualify your thinking, follow your structure, tackle (likely) high-impact issues first, lead the interviewer, and ask the right questions?
  • Mental math and basic calculus : Are you able to structure quantitative problems and comfortably perform calculations? Can you derive the correct approach to calculate the desired outcome variable? Can you plug in the numbers and perform the calculations, relying on basic pen-and-paper math, shortcuts, and mental math?
  • Creativity: Do you think about a problem holistically, offering broad, deep, and insightful perspectives? Are you able to come up with different angles to the problem (breadth) and draft rich descriptions that qualify why these areas are important to investigate (depth)?
  • Communication: Are you able to communicate like a consultant? Are you following a top-down communication approach similar to the Pyramid Principle taught by Minto? Do all of your statements add value and do you guide the interviewer through your thinking?
  • Maturity and presence: Are you leading the conversation or are merely getting dragged along by the interviewer? Are you confident and mature? Are you comfortable with silence while taking time to structure your thinking?
  • Business sense and intuition : Are you able to quickly understand the business and the situation of the client? Can you swiftly interpret data, charts, exhibits, and statements made by the interview? Are you asking the right questions? Are you able to make sense of new information quickly and interpret it properly in the context of the case?

Now, these skills are assessed in a very specific interviewing format, which is not natural for most applicants and needs significant practice to become second nature.

the image shows a case interview evaluation sheet

Key Strategies to Excel in a McKinsey Case Interview

Using the mece principle.

MECE (Mutually Exclusive, Collectively Exhaustive) is a problem-solving principle that helps ensure your analysis is both comprehensive and well-organized. Apply the MECE principle when structuring your approach to a case by breaking down the problem into distinct, non-overlapping components while ensuring that all relevant aspects are covered. This method allows you to maintain a clear and logical structure throughout the case and reduces the likelihood of overlooking critical factors.

Applying the 80/20 rule

The 80/20 rule, also known as the Pareto Principle, suggests that 80% of the effects come from 20% of the causes. In the context of a case interview, this means focusing on the most critical issues or factors that will have the most significant impact on the client’s objectives. By prioritizing your analysis and recommendations, you can work more efficiently and effectively, demonstrating your ability to identify and address the most pressing concerns for the client.

Hypothesis-driven approach

Using a hypothesis-driven approach means forming an initial hypothesis or educated guess about the potential solution to the problem and then testing it using data and analysis. By starting with a hypothesis, you can guide your problem-solving process more efficiently, focusing your efforts on collecting evidence that supports or refutes your hypothesis. Throughout the case, be prepared to revise or refine your hypothesis as new information emerges.

Incorporating creativity and business intuition

While frameworks and structured approaches are essential, it’s also crucial to demonstrate creativity and business intuition during a McKinsey case interview. This means thinking beyond the standard frameworks and considering innovative solutions or unique factors that may be relevant to the specific case. Use your knowledge of industry trends, best practices, and real-world business challenges to inform your analysis and recommendations. By combining structured thinking with creative problem-solving, you can showcase your ability to deliver well-rounded, impactful solutions for clients.

Preparing for the McKinsey Case Interview

Most candidates prepare using generic frameworks. Alternatively, they are looking for a McKinsey case book PDF or a case study interview questions and answers PDF with the hope that the cases will be the same across interviewers and interviews.

Do not learn case-specific frameworks by heart , expecting them to work for every case you will encounter. There is no specific McKinsey case study framework or McKinsey case study book. It is much more important to learn the right approach that will help you tackle all types of cases. This is even more relevant for McKinsey interviews.

What you need to do is to study each individual question type and the associated skills in a case interview and learn how to approach it, regardless of the client situation, the context of the case, the industry, or function. Your goal should be to learn how to build issue trees, interpret charts, and perform math no matter the context, industry, or function of the case and follow our McKinsey case interview tips.

Many candidates ask if there is a specific McKinsey implementation case interview, McKinsey operation case interview, or McKinsey digital case interview. In fact, the cases are usually a mix of cases in a domain-relevant context as well as cases set in a completely different context to the role you are applying for.

Be aware that frameworks were applicable in the 2000 years, the era of Victor Cheng and Case in Point. McKinsey has long caught up on this and the cases you will get during the interviews are tailored in a way to test your creativity and ability to generate insights on the spot, not remember specific frameworks.

In fact, it will hurt you when you try to use a framework on a case that calls for a completely different approach. Also, it gives a false sense of security that will translate to stress once you figure out how your approach won’t work during the real interview – We have seen this way too often…

Developing the right mindset

Success in the McKinsey case interview starts with cultivating the right mindset. Being mentally prepared involves:

  • Embracing a growth mindset: Recognize that your skills can improve with consistent practice and effort. Stay open to feedback and learn from your mistakes.
  • Building resilience: Understand that case interviews are challenging, and you may face setbacks during your preparation. Stay persistent and maintain a positive attitude.
  • Adopting a client-first perspective: Approach each case as if you were a consultant working on a real client engagement, focusing on delivering value and actionable insights.

Learning the essential skills

To excel in the McKinsey case interview, it’s crucial to develop the following skills:

  • Problem structuring: Break down complex problems into smaller, more manageable components using frameworks and logical structures.
  • Qualitative and quantitative analysis: Interpret and analyze data to draw meaningful insights and make informed decisions.
  • Hypothesis-driven thinking: Develop and test hypotheses to guide your problem-solving approach efficiently.
  • Communication: Clearly articulate your thought process, insights, and recommendations in a concise and persuasive manner.

Studying relevant materials and resources

Leverage various resources to enhance your understanding of case interviews and management consulting:

  • Books: The most effective and exhaustive case interview preparation book is The 1%: Conquer Your Consulting Case Interview (shameless plug). It goes much deeper than the usual suspects which are outdated and provide faulty advice on case interviews.
  • Websites and blogs : Websites like StrategyCase.com offer the latest case interview tips, practice cases, and industry insights. You can check out more free articles covering consulting applications and interviews here .
  • Online courses: Enroll in case interview preparation courses to gain structured guidance and access to a wealth of practice materials. We have created several high-quality courses for all elements of the McKinsey interview (see below)

We are the highest ranked and most successful case coaches on the web and have helped 100s of candidates break into McKinsey. As former McKinsey consultants and interview experts, we have specialized in getting our candidates into the firm. We can help you by

  • tailoring your resume and cover letter to meet McKinsey’s standards
  • showing you how to pass the McKinsey Imbellus Solve Game
  • showing you how to ace McKinsey interviews and the PEI with our video academy
  • coaching you in our 1-on-1 sessions to become an excellent case solver and impress with your fit answers (90% success rate after 5 sessions)
  • preparing your math to be bulletproof for every McKinsey case interview
  • helping you structure creative and complex McKinsey cases
  • teaching you how to interpret McKinsey charts and exhibits
  • providing you with cheat sheets and overviews for 27 industries .

Reach out to us if you have any questions! We are happy to help and offer a tailored program.

the image is the cover of a case interview industry overview

Practicing with case partners

Regular practice with case partners is essential for honing your case interview skills:

  • Find practice partners: Connect with fellow candidates through online forums, social media groups, or local consulting clubs.
  • Set a practice schedule: Aim to practice at least a few cases per week, gradually increasing the difficulty and variety of cases.
  • Seek feedback: After each practice case, discuss your performance with your partner, and identify areas for improvement.
  • Alternate roles: Take turns playing the role of the interviewer and the interviewee to develop a deeper understanding of the case interview process.

Common Pitfalls and How to Avoid Them

Common mistakes.

  • Insufficient structure: Failing to break down the problem into manageable components can lead to a disorganized analysis and an inability to identify key issues.
  • Overlooking the big picture: Becoming too focused on the details and losing sight of the overall objective or client’s needs can hinder the development of effective recommendations.
  • Ignoring qualitative factors: Relying solely on quantitative data without considering qualitative aspects may result in an incomplete understanding of the problem.
  • Ineffective communication: Struggling to articulate your thought process, insights, or recommendations in a clear and persuasive manner can undermine the value of your analysis.
  • Failing to adapt: Sticking to a preconceived framework or hypothesis despite conflicting evidence may indicate a lack of flexibility and critical thinking.

Tips to prevent these mistakes

  • Practice structuring: Develop your ability to structure problems effectively by practicing with a wide range of cases and familiarizing yourself with common frameworks.
  • Stay focused on the objective: Periodically remind yourself of the client’s goals and priorities, ensuring that your analysis remains aligned with their needs.
  • Balance quantitative and qualitative factors: Recognize the importance of both quantitative data and qualitative insights in forming a well-rounded understanding of the problem.
  • Hone your communication skills: Practice speaking clearly, concisely, and persuasively, ensuring that your message is easily understood and well-received.
  • Embrace adaptability: Be open to revising your approach, framework, or hypothesis in response to new information or feedback, demonstrating your ability to think critically and flexibly.

McKinsey Interview Course

Unlock the Secrets to Acing McKinsey Interviews with Our Comprehensive Training Program

Are you eager to dive deep into mastering the McKinsey interviews? Look no further than our extensive 40-part Ready-for-McKinsey Interview Academy . This exceptional video program features simulated McKinsey-specific case studies and in-depth coverage of all Personal Experience Interview (PEI) dimensions and stories. Our Interview Academy is the ultimate resource to prepare you for success in your McKinsey case interviews.

We take pride in our results: an impressive 9 out of 10 candidates who complete our one-on-one Ready-for-McKinsey Interview Coaching program receive an offer. This track record has earned us consistent recognition as the best McKinsey and MBB coaches on several platforms.

Don’t leave your McKinsey interview success to chance—invest in your future by exploring our top-rated Interview Academy and coaching services today.

the image is the cover for the florian smeritschnig case coaching program, the best on the internet

In summary, acing the McKinsey case interview requires a deep understanding of the interview process, mastery of essential skills, and the ability to apply effective problem-solving strategies. By embracing the MECE principle, applying the 80/20 rule, adopting a hypothesis-driven approach, and incorporating creativity and business intuition, you will be well-equipped to tackle any case interview challenge.

Remember to invest time in preparing for both the Personal Experience Interview and the case interview itself, using the wealth of resources and practice materials available. Focus on developing a structured approach, honing your analytical and communication skills, and staying adaptable throughout the interview process.

As you embark on your McKinsey case interview journey, stay confident and persistent in your efforts. By applying the tips and strategies shared in this article, you will be one step closer to achieving your consulting career aspirations. We wish you the best of luck in your journey toward success at McKinsey.

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issue based problem solving mckinsey

Florian spent 5 years with McKinsey as a senior consultant. He is an experienced consulting interviewer and problem-solving coach, having interviewed 100s of candidates in real and mock interviews. He started StrategyCase.com to make top-tier consulting firms more accessible for top talent, using tailored and up-to-date know-how about their recruiting. He ranks as the most successful consulting case and fit interview coach, generating more than 500 offers with MBB, tier-2 firms, Big 4 consulting divisions, in-house consultancies, and boutique firms through direct coaching of his clients over the last 3.5 years. His books “The 1%: Conquer Your Consulting Case Interview” and “Consulting Career Secrets” are available via Amazon.

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