The following is a conversation between Charles Conn, Co-Author of Bulletproof Problem Solving: The One Skill That Changes Everything, and Denver Frederick, the Host of The Business of Giving.
Denver: The World Economic Forum lists complex problem solving as the number one skill for jobs in 2020. But how many of us, faced with a difficult problem, just dive right in looking for a solution. My next guest says there’s a better way, a much better way by using a simple seven-step approach. He is Charles Conn, the Co-Author of Bulletproof Problem Solving: The One Skill That Changes Everything.
Welcome to The Business of Giving, Charles!
Charles: Thanks, Denver. It’s really a pleasure to be here.
… problem solving is simply decision-making when there’s uncertainty or complexity that makes the answers not obvious. That’s it. And typically, we would add where the consequences are substantial enough that it’s worth putting some process against it.
Denver: When people hear about complex problem solving, it can be a little intimidating. So make it a bit less so by giving us your definition of problem-solving.
Charles: Yes, You’re right. And I think there’s that group of people who love Sudoku or other problems, and the rest crosswords, and the rest of the world that doesn’t. And I think that we’re trained somehow, maybe it’s early in our mathematics training, to fear problems.
For us, problem-solving is simply decision-making when there’s uncertainty or complexity that makes the answers not obvious. That’s it. And typically, we would add where the consequences are substantial enough that it’s worth putting some process against it. We’re trying to demystify problem-solving.
Denver: That’s a very accessible definition. I mentioned just a moment ago that this is the number one skill for the 21st century World Economic Forum and a whole bunch of others. And that’s ahead of things like critical thinking and people management and creativity. What makes it so?
Charles: You know what? I think it’s the world that we’re in, which is really different from the world that we grew up in. The world we grew up in was still a learning model where the idea was you would learn a body of knowledge in school or in university — and whether you were at the sort of lawyer or doctor end, or you were at the engineering or apprenticeship end — and then you’d apply that over the course of a career.
Well, we know that era has passed, and nowadays, all of us need to expect that we’ll work in multiple jobs, in multiple industries. And what it means is we can’t carry with us a body of knowledge to apply. The only thing we can really carry with us is that ability to crack difficult problems, ideally working in teams. So I like putting those two things together.
The truth is, and it’s an awful truth, but many, many industries are going to be impacted by artificial intelligence and automation. Any tasks that are routine, even tasks today that are high-cognitive tasks — like reading x-rays, for example — are being automated better by the combination of artificial intelligence and robotics. That means what’s left for humans is what we can do with creative problem-solving.
Denver: So with that being said, is problem-solving being taught anywhere in universities or in schools?
Charles: I wish I could say it was. It’s a shock, and it’s enormously surprising to us that it’s not a standard part of people’s learning experience. Some people who go through engineering programs learn about engineering problem-solving. Some people who go through hard sciences hear about the scientific method. Sometimes people who go through graduate schools in marketing learn about design thinking. Each of which are approaches to problem-solving very consistent with the one that we talk about in the book. Most people are not exposed to systematic processes for problem-solving.
Denver: Charles, what are some of the most common mistakes people make in problem-solving?
Charles: And you said one right at the very beginning. Lots of people run off into problem-solving before they’ve really sat down and thought about: Can I really describe the parameters of the problem that I’m working on? Do I know what are the boundaries — what’s in, what’s out? How quickly do I need an answer? How accurate does the answer need to be? Do the decision-makers I’m working with agree with that definition of problem-solving? That’s one of the biggest ones. The others, you can read about in Daniel Kahneman’s wonderful book Thinking Slow and Fast, which I’m sure you’re familiar with. But as humans, we tend to make a couple of critical mistakes.
One of which is confirmation bias, where our first instinct on what the answer is becomes the thing that we then try to prove, and we know from the scientific method, we should be trying to disprove our hypothesis. And then the second most important error of these heuristic biases is availability bias. Meaning, if we have a hammer, we think every problem looks like a nail. So, for a statistician, we’re going to pull out some fancy statistical package and that’s how we approach the problem. Those are the three biggest mistakes that humans make when they start problem-solving.
Denver: Everything goes right to my core competency, so why not exercise that muscle? I’ve really built it up. You started this journey that led to the seven-step process during an internship you had in Japan. Share with us that story.
Charles: And it’s one of those times when you feel like a fish out of water, and I think it’s a very good mindset to cultivate. When you’re in a country where you basically don’t speak the language and you don’t know the cultural practices, but all of a sudden, I’m in a business setting. I was working for Canon, the photocopier and camera people, and I was assigned to a really difficult problem of: How should we think about siting our factories around the world? And I had to figure out in this strange cultural context how to work with a team of people very different for me to come up with an answer.
And that’s when I used this very structured approach that you could actually put on one page, and was a visual approach to solving that problem that made sense to my colleagues and, ultimately, my bosses in Japan who were English-as-a-second-language folks.
Remember that humans are visual thinkers, and they’re storytellers. And if you can’t tell your story in a really compelling way, it doesn’t matter how smart you are, you won’t get people to change.
Denver: So without further ado, Charles, run us through the seven-step process.
Charles: Let me be super brief on it. The seven steps are very straightforward. And again, I want people to think that this is easy to embrace. It doesn’t require fancy mathematics. It doesn’t require fancy degrees. Anybody can do this and you can do it on the little problems like: Should I put solar panels on my roof?…which is a problem from the book. Or big problems like: Should I support the death penalty? Or how should I think about legalizing drugs?
The seven steps are straightforward. First of all, define the problem. And as I mentioned, that sounds boring, but it’s the most critical starting point. Disaggregate the problem. We like to use “logic trees” so that we can visually take apart the elements of the problem. Prioritize the problems. So that means make sure I know which are the two or three things that if I work on them first, the answer is most likely to fall out from those. I like to prioritize based on what has the biggest impact on the problem, but a lever that I can change.
The fourth one is: How do I plan to do the work with others? And how do I set up my team process so that I avoid those heuristic biases? The fifth is the analytic stage. That’s where you get to apply those big guns of problem-solving. We like you to start with simple statistics and heuristics first. And then the last two steps are: How do I synthesize that analytic work? And tell a great story.
And the smartest problem-solvers often fall short on this last step. Remember that humans are visual thinkers, and they’re storytellers. And if you can’t tell your story in a really compelling way, it doesn’t matter how smart you are, you won’t get people to change. And the whole reason to do problem-solving is to help organizations change.
Typically, two or three levers on your problem disaggregation are going to give you 80% of the answer. Find those levers, and you’ll have a nice life.
Denver: Even problem solvers have to be salespeople; otherwise, it doesn’t go anywhere. Now, given that you cannot skip any one of these seven steps, what would you think is the most critical of the seven?
Charles: As I mentioned already, I’m partial to getting problem definition really right and then iterating on that. As I learn more, I like to go back and check again to make sure I’ve got the right problem. And if I’m working with other decision-makers like clients or bosses, to make sure I revisit it with them, too…. so that I don’t get to the end and show a solution and they say, “That’s not what I asked you to look at.”
And then I’d say the second most important one is that prioritization step. Boy, it’s easy to — and young people do this all the time — just work 18 hours a day solving a problem because you didn’t stop and ask: What’s that critical path? What are the two or three elements of that problem disaggregation that are likely to give me the biggest bang in solving that problem?
There’s a famous Italian economist called Vilfredo Pareto who noticed this 80-20 relationship that you hear all the time. Typically, two or three levers on your problem disaggregation are going to give you 80% of the answer. Find those levers, and you’ll have a nice life.
Denver: That’s a mantra that McKinsey, where you worked, and Bain and Boston Consulting Group — it’s “be more 80-20. “I think every new consultant hears that once or twice.
Charles: You got it. And when you figure that out, you don’t work 18 hours a day, just 15.
Denver: Although this is a very familiar technique to consulting firms, I don’t think most people use a hypothesis and then bring forth arguments to either disprove it or to support it. Tell us the benefits of that approach.
Charles: It is counterintuitive, isn’t it? Because we don’t want to have that confirmation bias problem, and by making a hard hypothesis, you might be at risk of confirming your hypothesis. This is where you have to remember the discipline of the scientific method, which says, “I want something that is, if you will, a firm statement, something that I can attack.” And creating something that is an attackable statement, that is a strong hypothesis, makes it easier for the team to coalesce not only positive data that would confirm that but negative data that would challenge it. And that’s why we like to work with strong hypotheses rather than wishy-washy statements.
Denver: It really does provide focus as opposed to just getting more and more information and not really having any idea where it would go. And as you go along that road, you also talk about in the book the one-day answer, or maybe even the one-hour answer. What is that?
Charles: It’s the same kind of idea behind hypothesis-driven problem solving, which is: those seven steps are an iterative loop, not something that you do over six months, something you do over 60 minutes if you can. And what we’d like people to do, is once they’ve got a good problem definition, is to very quickly run through all seven steps and say, “If I had to answer today, what’s my best guess at an answer?” Again, not falling in love with my original hypothesis. Sometimes — you’ve heard this before in consulting firms, we’d like to call this the “elevator answer” because you inevitably step into the elevator and there’s your senior client or your client’s boss, and that client says, “Hey, how’s it going?” And you think, “Shoot! I don’t know the answer.”
Denver: Actually, what I do is I get off on the next floor.
Charles: Smart. And of course, at the beginning of a project, you don’t know the answer. And what we like to do is that structure of a one-minute or one-hour answer where we’d say, “Well, I don’t know for sure, ma’am, but here’s what I know. Here’s the set-up of the situation,” I like to call that situation, “Here’s what we know so far,” complication,” and” If I had to guess today, here’s what I think the answer is, but we’re still working on proving that up.”
And so, that one-hour answer, it helps me identify what are the weak points in my story so far, and it gets me in that storytelling orientation right at the beginning.
Denver: And with these short timeframes and these feedback loops, which seem to be very tight, it would seem that these work plans then are not the long, extended kind but are also relatively short. Would that be right?
Charles: You read the book. Yes, and boy, oh, boy, did I ever learn this the hard way! Early in my career, when I first discovered Microsoft Project, I found that you could plan a six-month project. And then I worked all night to do that and inflicted that on my teams.
What we discovered, of course, as soon as we got into that analytic phase when everyone started going off and diving into the data and doing their initial modeling and thinking, was that we did get on the critical path, and the first two or three analyses we did shone light on our problem and then made the rest of that work plan obviated. And so, nowadays we like to work with two- or three-week work plans, no more than that.
Denver: Very smart.
Charles: And then we use–yes. And then we use what we call study plans, which is, again, chart format to keep track of that six months you might have to work with, but then constantly iterate that work plan with the team.
Denver: So a little bit of that … I spoke to David Marquet. And he was, in “Turn the Ship Around!” he was talking about blue work and red work. So it seems like your work plan is the blue work, and then you do that two weeks of red work, but get right back to the blue work so you’re not going too far down the wrong alley, and that’s a great way to talk about it.
I want to get into a couple of examples shortly, but I do want to ask you one last thing about this process, and that is the disaggregation piece of it and logic trees. Talk about those.
Charles: And I think that’s another one of these things that look scary to people, but the logic tree is just a way of keeping track of the pieces of your problem. You don’t have to do it in the structure of a trunk and major branches and minor branches and twigs, but it does help you see a hierarchy in the relationship between things.
So if I were to tell you that the profitability of a company is made up a revenue less costs, and I were to tell you that cost is made up of fixed costs and variable costs, and I were to tell you that fixed costs are made up of occupancy costs and, let’s say, insurance, that would make a ton of sense to you, right?
All the logic tree does is help show me in a physical way that set of relationships. And it helps me keep track of: I’ve assigned to Sally to work on lowering fixed costs, and I’ve assigned to Rob to work on addressing variable costs. It’s a visual way of keeping track of my problem and helping to identify which things are more likely to lead to a bigger part of the answer.
Denver: And on these branches, they need to be — what do you call it — MECE?
Charles: MECE. Yes. it’s that one that catches people out.
Denver: I should’ve gotten the audio version.
Charles: Yes. It’s that one. It catches people out. It’s mutually exclusive and collectively exhaustive. And I think the second part of that is easier for people to understand, which is you want to make sure that you’ve got all the branches. It’s collectively exhaustive. You also want to make sure that the branches don’t cross and therefore, that they are mutually exclusive. And that’s a harder concept for people to get their head around, but that you don’t have little bits and pieces of the same thing on different branches. Ideally, you want those branches to be clean and separate.
Denver: Well, speaking about exhaustive, your book is exhaustive in terms of the number of case studies you present. It must be 30 or so. And I think people would like to hear about a couple of them.
Let me start with The Rhodes Trust, where you were the CEO, and that organization in itself has a pretty complicated history. And you know we’re in a period now where people are debating historic statues — Should they be allowed to stand? Which ones need to come down? Because, obviously, things in that person’s life are now looked upon as being abhorrent, and people think those statues should come down. Talk about this method a little bit as to how you would think about that problem.
Charles: I’m glad you started with that example because it does show how you actually can start to construct trees. I sat there with a group of really bright graduate philosophy students in a room with a whiteboard, and we were thinking about this problem, which is: How do you think about historical legacies? Because when we think about people in the past, like Teddy Roosevelt, for example, or Thomas Jefferson, we know they did great things, and we also know they believed different things from what we believe today… in fact, things that we think are abhorrent. But how would we make decisions therefore about whether we would keep, for example, the Jefferson monument, or whether we would want to placard the Jefferson monument, keep it, but put a sign out front that says, “Thomas Jefferson is revered for what he did here, but he also kept slaves.”
And so, we wanted a framework for thinking about that, and what we started to do was to write down things that we noticed. For example, how long ago things are matters, whether people are still being harmed matters, what the extent or nature of the harm is matters. If I were to tell you that the Romans marched into the UK in 42 A.D., and that they oppressed the local Picts, would you feel outraged?
Denver: First, I’d fact-check you, OK?
Charles: You can fact-check me. My guess is that you probably wouldn’t feel outraged because it’s–
Denver: Absolutely right. Yes.
Charles: — you can’t identify those people anymore, and you don’t know what the nature of the harm is. So distance from the past actually matters a little bit.
And what we did, working “inductively,” which is one of these terms that we use with logic trees, is to begin to pull out, to tease out some principles from these examples. Why do we feel differently about Gandhi than we do about other historical characters of that period? So, Gandhi’s life overlapped with that of Adolf Hitler. We feel very differently about Adolf Hitler than we do Gandhi, but we also know that Gandhi had said some racist things, and his relationship with women was different from the relationship with women that we would think is appropriate today.
And so, we started to tease out those principles and then wrote them down in the form of a decision tree, and that decision tree is in the book. And that helped us think about: If there’s a portrait of someone whose views we no longer believe, is that something that we should take down, or should we put a sign up? And it helped us, at least in the context of this old university, Oxford University, how to think about a place, which is just literally everything around you is an indication of that ancient history, much of which reflects values that are different from those we have today. All of which we don’t want to take down, but some of which we may want to take down.
Denver: It certainly seems that this approach would do an awful lot for the political discourse we’re having today, where as you begin to get some of the emotion out — not that emotion isn’t good to a certain degree — but logically just break it down and have a discussion about it might just advance our civilization at the moment a little bit.
Charles: I sure agree with that. And I personally try and listen to all different perspectives in the political spectrum, and I especially like to listen to people that I don’t agree with because that’s the only way I’m going to learn something different.
And I do believe that if we could sit down with people that we, on the surface, don’t agree with and begin to find common ground — I like to use logic trees there, too — whether we’re talking about tax policy or things like capital punishment, and figure out why is it that we may disagree on the surface? And what are the common areas? I think that idea of problem disaggregation makes a ton of sense, especially when it’s hot, not just when it’s rational.
Denver: More of a solutions orientation as opposed to a debate because debates get you absolutely nowhere. You just get everybody locked in to their point of view.
I can see how this could be used in a problem like that. What about something like climate change? Or let’s say, the case of Pacific salmon; maybe you could speak about that.
Charles: Sure! I said early on that I thought this kind of approach to problem-solving is really like an accordion. You can use it for quite simple problems: Should I have arthroscopic knee surgery or put solar panels on my roof? Right through to these most difficult kinds of problems. And those are sometimes called wicked problems after a 1970s article that defined a set of problems that were particularly complex, especially ones where there was multiple causations, multiple reinforcement loops, and where people’s behavior has to change. Topics like climate change or saving endangered species often fall into that category. So do questions like: How would we fight homelessness?
These kinds of problems, the biggest policy problems that society faces, are also amenable to logical disaggregation. And if we were to take just something like: How do you save wild salmon? You could note right off the top of the bat that salmon live in rivers when they’re little, and then they go to the ocean when they’re older. And they face one set of threats when they’re babies living in freshwater ecosystems. Those threats include predators, but they also include threats like the runoff from farming or the impacts of forestry or road building. And then when they leave the freshwater environment and go into the estuaries and sea, another set of factors threaten them. And that includes human catch. That’s the commercial fisheries, aboriginal and sport fisheries.
And even just that simple thing I just said right now helps give you a bit of a framework for knowing what the levers are that affects them. So some of it’s habitat; some of it’s how fish are caught. Some of it’s the impact of hatcheries and fish farms. And pretty quickly, you can see I’ve got a structure. And then with a little bit of research, I can tell you which of those things has a big impact on the fish, and I can tell you which of those things you’re likely to be able to have to change. If I told you that ocean conditions were a big impact on salmon, you wouldn’t be surprised, but if I told you that we can’t affect ocean conditions very much, you also wouldn’t be surprised.
Denver: I’d be surprised if you said if you could.
Charles: Right. But if I told you that habitat mattered a hell of a lot in freshwater habitat, and we can affect that by how we build roads and how we cut down trees and how we farm, that would make sense to you. And if I told you that how we caught fish commercially in the ocean has a big impact, that would make sense to you, too.
And we could hone in pretty quickly on policy changes that we could actually make, that would give a better chance that future generations will also enjoy salmon, both as food and for their ecosystem benefits.
Charles: So I hope that’s not too long an answer to using this approach. You can tackle even tough stuff.
Denver: No. Absolutely. I can see how this can work. You mentioned personal problems or personal challenges. Give us an example.
Charles: So, my coauthor, Rob McLean, is an avid runner– both of us are– and he had knee problems, increasing knee problems a couple of years ago — some kind of an issue with his meniscus. And Rob being Rob, took it apart in a tree, and he asked himself the question: Is this something that can be fixed? Yes or no. If it is something that can be fixed, are there invasive and non-invasive approaches? It turns out that there are. There’s both physiotherapy and surgery. And then he asked himself: Does it look like there’s new science that might provide better approaches to solving this meniscus problem using, for example, synthetic meniscus. And what he discovered is that yes, in fact, there were some new therapies that were just on the horizon.
And so, using the probabilities associated with each one of those things, he worked out that it made sense for him to wait and do a combination of physiotherapy and gentle training before these more advanced technologies became developed. It doesn’t sound like a silly example. Rob had a real problem. He wants to stay healthy, but he also wanted to make a reasoned and reasonable decision about whether he should wait for these more advanced interventions.
Denver: Charles, a complex problem that is plaguing all of us right now is COVID-19. It’s dominating our lives. It’s dominating this entire generation’s memory of where they were and what happened during this time. What are some of the ways we should be addressing that problem?
Charles: And I think this is a — we talked about it a little bit before we started the show today — is that this novel pandemic is a perfect example of where you need bulletproof problem-solving. This is something we haven’t seen before, but we know that this virus is a member of a family of viruses that we do know something about.
And very quickly, we can begin to bucket this into elements of the problem. How can we avoid people catching the virus before we get therapies? And so that’s where questions like: Will social distancing work? How important are touching surfaces in transmission of the disease? And does masking help us in addition?
And then you could look at another branch, which would be: If we do get sick, are there therapies that could assist us in making it less likely that we die, or shortening or lessening the severity of the impact on us? And then there’s a third branch, which is: How could we move toward various forms of herd immunity, either by careful exposure of the people who are less likely to die or of development of vaccines that mimic the impacts in the population of herd immunity?
And so, you can see the very same things that are debated often in a fact-free way, I’m afraid, in media are very much amenable to science looking at each of those three buckets or branches.
Denver: And it also, I think, underscores the importance of synthesis and presentation because if you begin to think if our leaders didn’t tell us what we needed to do but actually walked us through a logic tree so we were part of that process and could be engaged with it, you just wonder if the public response would be dramatically different than what it is right now.
Charles: Well, I’m laughing. It’s not the electoral choices we face on November 3 as Americans, but if Anthony Fauci were running for president, how do you think he’d do and why? And I think it very much — and I say this slightly tongue-in-cheek, and I say this in a nonpartisan way — part of the reason why many people in the world today trust Anthony Fauci is he does do us the decency of taking us through those arguments.
One is, if your problem isn’t exactly the same as the problem that the experts developed their techniques on, they could easily miss the mark…
…a lot of times, when we go straight to an expert solution, we lose the ability to add additional creativity; and great problem solving is good, but creative problem solving is better.
Denver: Exactly right. But, I will add, you have also said that sometimes we should be suspicious of experts, right?
Charles: You’re exactly right! You really did read the book. Yes, and there’s a reason for that. I know this will sound counterintuitive at first, but experts are people who’ve seen a particular problem before and developed a particular solution to that problem.
Two things I would say about it. One is, if your problem isn’t exactly the same as the problem that the experts developed their techniques on, they could easily miss the mark — back to my example of someone with a hammer thinking everything looks like a nail. And the second thing I’d say is slightly more subtle, but a lot of times, when we go straight to an expert solution, we lose the ability to add additional creativity; and great problem solving is good, but creative problem solving is better.
If we can loosen — and it’s one of the reasons I care so much about problem definition — if we can loosen the structures or boundaries on problems, we can come up with novel ways of solving them, and experts often don’t lead to novel solutions. That’s why I’m not suspicious, but I’m careful with the use of experts.
Denver: That makes sense. Finally, Charles, you conclude by sharing or reiterating what it takes to become a great problem solver, and you say they can be made, not necessarily born. What are some of those final tips you’d like to leave us with?
Charles: Yes. And it’s funny, my co-author Rob and I have been thinking a lot about this lately and thinking about the mindsets that would go along with this formal structured process. And let me just say a couple of those, Denver, that really stand out to me.
One is to cultivate a childlike curiosity rather than that sort of adult decisiveness and to really allow yourself to see things with those fresh eyes the way that a 4-year-old who asked the question “why?” thinks about.
The second one I’d like to talk about is being an experimentalist. And that means rather than just relying on third-party data, wherever you can, to collect your own data by doing little experiments. The internet has made that much easier than ever in the past to try two different versions of something to see which thing works, for example, which is called AB testing, to use focus groups of your friends and family and others wherever possible, to dive into the world of experiencing yourself rather than just relying on other people’s data.
And then I guess the third thing I’d say — I’ll say a fourth, too — but the third thing I’d say is to be tolerant of ambiguity. We call it being an imperfectionist, and to accept that the world is full of uncertainty
…the gray is usually where that beautiful, unseen answer is to be found.
Denver: I like to say: “Embrace the gray.”
Charles: A hundred percent. Because the gray is usually where that beautiful, unseen answer is to be found.
And then I’ll just come back at the end to the childhood analogy and say, “Don’t forget to do show and tell.”
Denver: That’s right. In front of the class. It’s coming up. You better be prepared. And I love the idea about experimenting, too, because I think about that a lot, and I say to myself, “Almost everything I believe, someone has told me, and I’ve never seen it firsthand.” And the idea of trying to get in there and getting your hands dirty a little bit and finding out for yourself can really change the way you view the world and how you approach it.
The book is titled Bulletproof Problem Solving: The One Skill That Changes Everything. So if one of your problems is problem-solving, this is the book to read that will help solve that problem.
Thanks, Charles. It was just a delight to have you on the show.
Charles: It was an enormous pleasure, Denver. My pleasure entirely.
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