Complex problem solving is the core skill for 21st Century Teams Complex problem solving is at the very top of the list of essential skills for career progression in the modern world. But how problem solving is taught in our schools, universities, businesses and organisations comes up short. Our guest today shares the seven-step systematic approach to creative problem solving developed in top consulting firms that will work in any field or industry, turning you into a highly sought-after bulletproof problem solver who can tackle challenges that others balk at.
If you want to become a better problem solver, you can do so with only a modest amount of structure and numeric ability. Individuals make decisions that have lifetime consequences—such as career choice, where to live, their savings plan, or elective surgery—often without due consideration. These are among the examples you walk us through in the book to illustrate the value of a structured process to improve your prospects of better outcomes in your own life.
More about Charles here:
https://bulletproofproblemsolving.com/
Transcript:
Charles Conn – Final
[00:00:00] Charles Conn: [00:00:00] Stay hungry, stay foolish.
[00:00:13] Aidan McCullen: [00:00:13] Complex problem solving is the core skill for 21st century teams. Complex problem solving is at the very top of the list of essential skills for career progression in the modern world. But how problem solving is taught in our schools, universities, businesses and organizations comes up short. Our guest today shares the seven step systematic approach to creative problem solving developed in top consulting firms that will work in any field or industry turning you into a highly sought after Bulletproof.
[00:00:44] Problem-solver the problem solving technique outlined in today’s show is based on a highly visual logic tree method. That can be applied to everything from everyday decisions to strategic issues in business to global social challenges. Our [00:01:00] guests with decades of experience at McKinsey and company provides detailed real world examples.
[00:01:06] So you can see exactly how the technique works in action with this Bulletproof approach to defining on packing, understanding, and ultimately solving problems. You’ll have a personal superpower for developing compelling solutions in your workplace. If you want to become a better problem solver, you can do so with only a modest amount of structure and numeric ability individuals make decisions that have lifetime consequences, such as career choice, where to live their savings plan or elective surgery often without jus consideration.
[00:01:39] These are among the examples our guest walks us through in the book. To illustrate the value of a structured approach to improve your prospects of better outcomes in your own life. We welcome author of Bulletproof problem solving the one skill that changes everything. Charles Kahn, welcome to the show.
[00:01:59] Charles Conn: [00:01:59] It’s [00:02:00] really great to be here.
[00:02:00] Aidan McCullen: [00:02:00] It’s really great to have you on the show. And just a reminder, this show is brought to you by Microsoft for startups. I’m not sure if you remember, but in the foreword of the book written by former MD of McKinsey, your former colleague, Dominic Barton said the importance of gray problem solving has only grown as the pace of economic and technological change has accelerated in recent years and the scope and complexity of the problems that we need to address and increases alongside it.
[00:02:28] Today we are just as likely to be hired to help a country public health system prepare for the next Ebola outbreak as to develop a digital marketing strategy for a new consumer product as ever more data becomes available that bar on quality thinking rises. He said, we need Bulletproof. Problem-solvers.
[00:02:48] How prophetic for a book written back in 2018, particularly when you mentioned the pandemic.
[00:02:54] Charles Conn: [00:02:54] And it’s a perfect example of this too, where we get incredibly complex problems, where are the different [00:03:00] pieces of the problem actually act back on each other where there’s feedback loops and we’re human behavior apt to chain, and that’s the most difficult kind of problem.
[00:03:08] Sometimes called wicked problems.
[00:03:10] Aidan McCullen: [00:03:10] One of the interesting things is as you identified the world economic forum, labeled complex problem solving as the number one skill for the 21st century, an organizations everywhere are looking for this capability. And their talent recruiting above all else. But I have had HR professionals admit to me that they don’t know what it means.
[00:03:31] So let’s share your great definition of real problem solving actually means.
[00:03:35] Charles Conn: [00:03:35] And I think we should demystify this you’re a hundred percent, right? I think when people hear problem solving, especially complex problem solving, it sounds like it’s in the too hard category. It sounds like some nasty, but in calculus or trigonometry, but that really isn’t the case for us.
[00:03:51] Problem solving decision making. Where there’s complexity and uncertain either worlds out obvious answers, but also where there’s consequences that [00:04:00] make the work to get good answers. Or, and so it’s quite a simple definition and more and more businesses. And the roles that people are entering businesses are playing is actually just problem solving.
[00:04:13] Aidan McCullen: [00:04:13] And the problems are going to get faster. And at an exponential rate like this pandemic we were experiencing, when we go back to work, it’s not going to be. Back to normal. It’s gonna present loads of new complex problems for us to solve, but to highlight the importance of good problem solving and how it has the potential to save lives and change the fortunes of companies, nonprofits, and governments, and how on the other hand, mistakes in problem solving are often very costly and sometimes can cause great harm.
[00:04:42] Let’s share the tragic story. Of the space shuttle, challenger disaster.
[00:04:47] Charles Conn: [00:04:47] Yeah. I’d say that’s a really good example. And as you point out a sad example and one that they didn’t really not out until, of course, after it happened, when the scientists who were predicting launch conditions [00:05:00] did their work. They work with a smaller range of the data around O-rings and other critical components, rather than considering the full range of potential temperatures.
[00:05:10] And so they consider the risk of a failure about 100, a hundred thousand. When Richard Fineman, the fence assistant others, did the post-mortem. They put the rated Mark more like one in six, because the temperature range was so much slower on the day of the launch. And that’s just a bit of conditional probability thinking or Beijing probability thinking.
[00:05:31] And honestly, setting that problem up the right way could have saved all those lives.
[00:05:37] Aidan McCullen: [00:05:37] One of the things I mentioned, both from an HR perspective, you have HR directors and professionals and even CEOs of organizations. And they’re like, we need to hire a good problem solvers. They don’t know what it means, but equally we mentioned in the intro, it’s not taught in schools or universities on it.
[00:05:54] It’s not taught in this more organic way. If you saw that on a list of. [00:06:00] Potential courses that you would take, it would put you off. And I think the presentation doesn’t match how easy it can be because you give it in a very, very simple way. But before we get into that seven step process, let’s share a little bit about your experience of the education experience.
[00:06:17] Charles Conn: [00:06:17] It’s perplexing, right? Because we learn all kinds of nuts and bolts skills, but the education system is really still set up with a almost 19th century model, which is. You’re going to focus in university on learning a body of knowledge that then you apply over the course of your career. So even people who do fancy training and accounting or, medicine or law are essentially learning an existing Canon, and then expected to present that cannon over time.
[00:06:46] Well, the world doesn’t work that way anymore with artificial intelligence and automation and all the other trends that are rapidly accelerating. The fact is in any kind of institution or business change is [00:07:00] happening so quickly that old model of learning a body of knowledge and applying it over time.
[00:07:05] It’s defunct, right? Mark Andreessen is famous for saying a few years ago that the internet is eating jobs, but of course now artificial intelligence is eating the internet. And so the only way to have a defensibility in your career is to be good at non-routine analytic skills. Working with people that means problem solving with people, all the routine jobs, whether they’re manual or cognitive are in decline.
[00:07:31] So even fancy jobs are being disintermediated by artificial intelligence. So think about people, for example, who used to read x-rays or echocardiograms, that’s all going away. So the only way you can build durability in your career, Just to be great at solving problems with real people,
[00:07:50] Aidan McCullen: [00:07:50] we covered a show on humidity is the new smart what ed has.
[00:07:53] And the whole concept there was, you need to be humble because your ideas aren’t written in [00:08:00] stone they’re hypothesis, because you can’t know for sure that the right. And when you couple that with complex problem solving as a skill. collaboration and communication, et cetera. There are the skills we need to be focused on.
[00:08:13] Not these linear logical skills that are from an, an old world where artificial intelligence will do way better than we can ever do it.
[00:08:21] Charles Conn: [00:08:21] Right? Anything that’s linear and analytic. The machines will do better than us. It’s how we work in teams, especially with creativity. And that creativity idea is really important.
[00:08:33] Is the only way that we’ll find jobs that are both interesting and meaningful
[00:08:38] Aidan McCullen: [00:08:38] before we launch into what good looks like Charles, you describe in the book, the most common pitfalls. And we mentioned there the tragic challenger crash, and you say that despite the increasing focus on problem solving and skills in universities, you find that there is a confusion about what good problem solving entails.
[00:08:57] So apart from focusing on a logical [00:09:00] approach, which is the smart method, That’s what most of us are. You need to have some smart goals. You share what the most common mistakes are.
[00:09:09] Charles Conn: [00:09:09] There’s a whole bunch of them. But as you know, from reading the work, for example of Daniel Conaman humans are inherently subject to all kinds of different biases.
[00:09:18] And those biases are the most common sources of pitfalls and problem solving, thinking. You’ve seen it before and then applying a model that actually doesn’t fit is probably the most important of those errors. Sometimes called the availability heuristic, and people often also have some cost bias. So if they’ve invested something that affects their decision making, when it shouldn’t affect their decision making, and those are just two areas where people consistently get problem solving wrong, you often get it in hierarchies.
[00:09:50] A and that’s where I see it the most, which is people have done something one way before, and especially where there’s strongly hierarchical teams. They tend to assert [00:10:00] this more senior people tend to a certain answer and more junior people go along with it. When the world is changing as fast as it is now, we need to look at everything fresh.
[00:10:09] Aidan McCullen: [00:10:09] This is why, oftentimes I get asked why on the innovation show, do I corporate leadership and organizational culture, et cetera, because they’re so intertwined. You need to have the right culture that accepts that the most junior member of your stuff can come up with the best idea. If you listen to them, Probably
[00:10:27] Charles Conn: [00:10:27] will, right.
[00:10:28] I mean, one of the interesting and it’s one of the four core values of McKinsey is called the obligation to dissent. It doesn’t mean the permission to descend. It means the obligation to descend even the most junior team member has to speak up when they disagree. And one of the things that I’ve always tried to do is make sure you let the most junior people speak first.
[00:10:50] Otherwise you get this heliotropic effect where the senior person says something and everyone changes their answer to accommodate that. Imagine a world where our teams didn’t have hierarchies [00:11:00] and fresher thinking was allowed to come to the fore. And it’s one of the reasons I think we should be inherently suspicious of experts because experts really just are knowledgeable about what the previous framing was and in a world where the framing changes quickly.
[00:11:16] Expertise can actually blind you to more creative solutions,
[00:11:19] Aidan McCullen: [00:11:19] beautifully pulled it. And this is the big problem. Isn’t it? That the pace of change is so rapid that we might’ve been right yesterday, but that could have changed today. And we need everybody in the organization. As Amy Edmondson said on the show.
[00:11:32] You need everybody to be a sensor who picks up data that you just can’t simply do because there’s too much data out there.
[00:11:40] Charles Conn: [00:11:40] Exactly.
[00:11:40] Aidan McCullen: [00:11:40] So before we go any further, let’s share the origin of your own story from your own young days. And this is the origin of the seven-step method that doesn’t require specialist skills or fancy mathematical talent, as you say, and it works on nearly any kind of problem.
[00:11:56] On you form this seven-step process during [00:12:00] an internship that you sought out in Japan.
[00:12:02] Charles Conn: [00:12:02] I worked for both the Boston consulting and McKinsey over the course of my career. And I learned an approach to problem solving. That’s common in consulting firms. I should say that there’s no, there’s no magic to it coming from consulting firms.
[00:12:16] In fact, the origins of this approach to problem solving are really in the scientific method. Hypothesis driven problem solving. All we did was to break it into seven steps to make it easier to follow when I was working in Japan, for cannon many years ago, struggling as you do when you’re young. And of course I wasn’t fluent in the language.
[00:12:35] At that time, I was given a really difficult assignment, which is how would you know where to site new factory locations? And, you know, it was one of those things that sort of came to me as things that has things do for many of us were I realized that breaking the problem apart using a logic tree would help me see each of the elements that went into making good, factory siting [00:13:00] decisions and to separate them into determine which of those things were most important and what the shape of those relationships are.
[00:13:07] Essentially it takes something that looks like a complex, not. And you pull the nod apart by using the logic tree.
[00:13:14] Aidan McCullen: [00:13:14] And I wanted to share that for a couple of reasons. One is because it emphasized the importance of traveling. And I know you have kids as well, and we’ve done shows on the brain and dopamine in particular.
[00:13:25] And what I found fascinating was when you experienced new cultures like this, not only do you. Experience new information, new ways of doing things, et cetera, but your brain actually changes. And the chemistry of your brain changes because you’re more aware of what’s going on around you. I’d love have you shared this because you’re a experienced traveler with your career and with your family.
[00:13:47] Charles Conn: [00:13:47] Yeah. And you know, it’s funny. I think you’re so right. Our brains use all kinds of shorthands to allow us to interpret the world around us. So we only take in a small amount of the data that’s available and most of the [00:14:00] time that actually makes sense, but, but if you really want to learn, you have to actually be much more open to all the new sources of data.
[00:14:09] And you’re right. That happens when you’re traveled, because all of a sudden you’re thrown into unusual and uncertain situations where you don’t know how to interpret all the signals that are coming through to you. So you have to see them as they are. And I think the same is true when we try to learn languages.
[00:14:24] Or when we try to learn music or when we try to learn mathematics, for example, each of those things actually creates new brain cells and new pathways in our brains. And, it’s only when we put ourselves out like that, that we can see things fresh. And when you think about it, think of the best artists and the best poets.
[00:14:45] They caused us to see something in a new way, even things that are, common commonplace. Think about an artist like van Gogh, for example, who paints his own room, the paints, and in a way that allows you to see it in a way you never saw before
[00:14:59] Aidan McCullen: [00:14:59] you [00:15:00] mentioned your children. Cause you mentioned them in the book, but when you travel, I guess one of the first things I say to students who asked me for advice or whatever, cause I do lecturing.
[00:15:11] And I always say, if you can take an overseas assignment, go work in a somewhere overseas for a year before you go anywhere. I had an own my own experience of when I was in college. I took the Erasmus years where you can go and travel and experience a different college. And I took a year out and lived in France.
[00:15:28] Now my French was only average at the time, but. The experience of learning a different language. I went to particularly to a small town on purpose because I knew there wouldn’t be very many English speakers. So my brain bode changed because I had to listen, speak, communicate in a different language. And I had to survive in that world and I was learning differently.
[00:15:52] So the whole experience I came back, a totally different person on it’s like the lenses through which I saw the world [00:16:00] had entirely changed.
[00:16:01] Charles Conn: [00:16:01] Yeah. Your mind is literally blown. Right. And I, I think that’s what makes you open and awake two new ideas. And frankly, it’s the source of all creativity, which is the ability to see things differently.
[00:16:14] And that’s why I made the comment that I made about experts, which has expertise and creativity seldom go together because experts don’t see things fresh. They see things through the frames of. Whatever their learning framework.
[00:16:27] Aidan McCullen: [00:16:27] I was just thinking there’s some people scrambling to change their CVS and their LinkedIn profiles.
[00:16:34] Controller experts replaces blank. So,
[00:16:38] Charles Conn: [00:16:38] button instead though, I mean, I think CVS are changing and reference checking is changing and people are much more interested in learning. How do you work with others to get things done? Right. Not how not, how are you the boss of things, not how are you the expert of things, but how do you work with others to get good things done?
[00:16:59] And Silicon [00:17:00] Valley, where I spent a bunch of my career. It’s all about that. It’s not about what you did before. It’s not about who you’ve been the boss of. It’s how do you work with others to get things done?
[00:17:10] Aidan McCullen: [00:17:10] And we’re getting to that cause you do cover that in the seven part process as well, but let’s get into the seven step process because I’d love to share this.
[00:17:17] And I’m sure a lot of people have tuned in particularly to hear this. So the seven steps and let’s share them now and share some examples from the field at the end. And those examples from the field include personal examples. Where do I live? Which is an experience you went through. And even if we have time, I’d love if you chaired, what job or what employer should I join?
[00:17:37] And then we’re going to talk about startups as well, increasing prices. Well, before we get there, Let’s start with step one, which is about defining the problem in the first place.
[00:17:45] Charles Conn: [00:17:45] Yeah. And you know, one of the things you mentioned right at the beginning, which is, this is a very visual approach to problem solving.
[00:17:52] Humans are visual creatures and they’re storytellers. So working with pictures, really helps problem solving and where we’re [00:18:00] working just in this audio world. So maybe we can share some visuals with your audience, later. But if you could imagine a circle and there’s seven steps around the circle, the first step is defining the problem.
[00:18:15] And I know that sounds like a trivial thing, but, well, we found over many, many years of doing this in, in our personal lives, in the professional world of organizations and businesses. And in the policy sphere, particularly around environmentalism is. People often run off thinking they’ve got the idea what the problem is without actually really sitting down and thinking about it.
[00:18:40] And I love this quote from Einstein that we talk about in the book where he said, if he had an hour to solve a problem, he’d spend 55 minutes thinking about the problem and only five minutes thinking about solutions. I think about that for a second. What are you saying is making sure you get the shape of the problem.
[00:18:59] Is really [00:19:00] critical understanding who the decision makers are, what forces are acting on them, what are the boundaries and constraints of the problem, including the timeframe, the resolution and the accuracy necessary. And then above all, what are the criteria or measures for successful effort really critical.
[00:19:17] So before you run off and start building some giant statistical or AI model, make sure you really know what you’re trying to do. The second step. Is this aggregating the problem. And I think it’s the most fun. How do you use a logic tree to take apart the problem at the beginning, when you don’t know much, maybe you could only chunk it out into factors or components as you get smarter about the problem, you might be able to form hypotheses or even set up a decision tree.
[00:19:45] All of which are different types of logic trees. The beauty of using logic trees is they help break the problem apart into smaller pieces. They help you make sure that you’ve got all of the pieces and they help you work with others to make sure that you [00:20:00] solve the most critical pieces. And in a way they also help you structure how to use frameworks and, theories as you’re solving problem solving, because you can use those as ways of taking problems apart.
[00:20:12] So that’s step two. Step three is really important, which is how do you determine what part to start first? So if you imagine a giant logic tree with all kinds of. Twigs on the end, each one of which is a particular analytic area. How do you, how do you know what to solve first? And we like to use a really simple two by two matrix.
[00:20:32] So imagine, on one access is how big an impact does it have on the problem that lever and on the other axis, how easy is it to move that lever? And we always start our problem solving where we’re working on the bits of the logic tree. Which have high impact on the problem, but we also can move them.
[00:20:55] So if you’re trying to save wild Pacific salmon, for example, ocean conditions turn out [00:21:00] to be really important, but it’s a lever you can move cause we can’t affect ocean conditions. Four step in problem solving, is getting a really great work plan and working well with your team. It’s another one that sounds boring, but it really isn’t great work planning means, you know, who’s doing what by when.
[00:21:17] And you’re working back from, again, pictures, again, working back from pictures of what you want the output to look like, so that nobody’s wasting their time. We often call it finding the critical path and problem solving, and we make sure that we’re not doing any analysis. That’s not on that critical path.
[00:21:33] Think of it as doing the knockout analysis first. And it’s in that stage, that forced stage where you can work with your team to avoid all of the typical cognitive biases that humans are subject to. When we said at the outset things like making sure that the junior people on your team speak first, making sure that your teams are diverse because diversity in backgrounds and genders, ethnicities.
[00:21:59] Actually [00:22:00] is empirically related to better problem solving Coke expose. It makes sense. Right? Which is if you have a team where everyone thinks the same, where’s the insight or creativity going to come from. Step five is analytics and lots of people listening are great analysts, analytic thinkers. But one of the things I just like to mention here is before you start building some giant AI model or some giant Monte Carlo model use heuristics and, and summary statistics before you get started.
[00:22:28]we see people all the time, run off and build a model before they really understand the shape of the problem. So use 80 20 thinking, credo thinking, you said Occam’s razor and it says the best solution is the one that requires the fewest assumptions use expected value or Basie and thinking like we mentioned at the beginning, so you can chunk up a sense of the problem before you start using fancy models and step six and seven, which is synthesizing your results.
[00:22:55] And then communicating them in a story are often neglected even by clever [00:23:00] people, maybe, especially by clever people, because they assume that their analytic results will stand on their own, but they don’t. We like to use just like journalists, a pyramid structure, where the bottom part of the pyramid are actual empirical findings, but then we summarize those into specific recommendations and that our overall governing thought, which is how people should change.
[00:23:21] And all problem solving ultimately is oriented toward the question. How should I change? So those seven steps that I’ve just described, you should think of them as something that you would iterate on every day. Not something you iterate on over months, every single day, you should be able to drive from hypotheses to do a complete loop.
[00:23:40] We often call it the one day answer or even the one hour answer. If you had to decide today, What’s the situation. What are your critical observations and what are the implications as best you understand them today? Great problem solvers are always doing that quick check in with a one day answer.
[00:23:58] Aidan McCullen: [00:23:58] What I find so [00:24:00] useful is that.
[00:24:02] When anybody even thinks of any problem, like even a personal problem and something that they keep putting off and off and off, it actually is stressful doing that because it’s there hanging around using open mental energy, so more in your head. And it’s the reason you can’t sleep well at Annette can feel like a mammoth task to take on a big problem.
[00:24:21] As the saying goes. You eat an elephant or a mammoth in this case, by eating it one bite at a time and you use the expression. What’s the one day answer. And I thought this was really, really helpful because where you reach a preliminary endpoint, you can repeat the process to draw out more insight for deeper understanding.
[00:24:42] So it helps crystallize the thinking from that day or that point and means it’s a knitter of Ezra to the process because it can feel on done. But if we go at the end of the day, where did we end today? What is our hypothesis today? And put that in [00:25:00] pencil and go, we’ll revisit it tomorrow. I thought that step was absolutely crucial because.
[00:25:06] You know, I envisaged doing a session with you and then hopping in the lift and then a junior member of staff or a senior member stuff asking me, so where are you guys are here? You’re doing a big strategy and I’m able to articulate it. And that’s a key step. That’s the key step. Isn’t it that’s overlooked.
[00:25:24] Charles Conn: [00:25:24] In fact, we often call it the elevator test for that reason, which is wherever you are at any moment in time, you should always be able to say that those three things, here’s our best understanding of the problem today. Here’s the insights that have emerged from our work so far and here, here’s what we think the implications are for how we should change.
[00:25:42] You should always have that. And it’s incredibly freeing to do that because most problems that are worth solving a really complicated and it’s easy to feel overwhelmed. And this gives you the license to surge, right to the end and problem solving, even though, you know, it’s not right yet. And when you dive into the data, [00:26:00] then.
[00:26:00] If you iterate back, you’ll see that you’ll refine your problem statement. You’re refine your understanding of the context and you’ll refine your logic tree. That’s where it becomes playful Aiden, rather than burdensome, right? This doesn’t need to be like high school trigonometry. This should be fun.
[00:26:17] Working with other people, using the best knowledge we have at the moment to crack the problem as best as we can at the moment. Give yourself the permission to go all the way through to the end. And then use what you’ve learned to go back and refine what you’ve done. And obviously when we’re doing things like drug discovery, for example, we need to be incredibly precise.
[00:26:37] Yeah. Even at the beach, even on something as important as drug discovery and in an era of pandemics, we can use this kind of rapid hypothesis driven problem solving to quickly rule out avenues that are unlikely to be successful and to focus our attention where we’re likely to find that truffle.
[00:26:53] Aidan McCullen: [00:26:53] Going back to one of those skills that you mentioned is that the idea of teamworking and like in Silicon Valley, how are you going to get on with the [00:27:00] team?
[00:27:00] How are you going to work together? How are you going to communicate and collaborate thinking of that? And then thinking of that seventh step, if we articulate where we are today, it also aligns everybody. And I think that’s another step because oftentimes with these kind of strategy meetings, you have people who don’t agree.
[00:27:18] And if. Along the line somewhere. You have people who don’t agree or disagree in some way. They’re never going to execute that plan. They’re going to go along with it to tick the box. So I thought this step really Ahrens decreases
[00:27:32] Charles Conn: [00:27:32] early. That’s exactly right. And you know, you can surface descent. You can learn more about what the real boundaries are in your problem.
[00:27:40] You can test those boundaries because real creativity comes when you actually open up boundary areas. You never get there. If you wait until the end of a six month process or a three month process to say, here’s my results. Oh, I missed by a mile. You know, if you do this iterative approach you’ll know quickly, if you’re heading off in the wrong direction
[00:27:58] Aidan McCullen: [00:27:58] before we share it, like I mentioned [00:28:00] at the start, hopefully we’ll get in three case studies.
[00:28:02] I thought it’d be really useful to mention. Your extensive use of logic or issue trees, because you mentioned these, this helps us visualize. And as you said, desegregate problems. And I thought of that, like, if you do define the problem, it’s kind of like unbundling it down into component parts. And when you do that, visually you end up seeing things differently.
[00:28:23] Just like we mentioned about when you travel and the brain opens up to novelty, the brain acts totally different when you do this as well.
[00:28:31] Charles Conn: [00:28:31] Yeah. In fact, I usually try. And even when I think I’ve got the perfect logic tree for a particular problem, I always try and do two or three other logic trees to see what additional insight would I get.
[00:28:42] If I cut through this problem in a different way, like when you’re working in business, you often say supply and demand. And what about if you also said scale and scope, right? So that, that just blows your mind for a second. Oh, okay. What’s the breadth of my competitive space. As opposed to the depth of my [00:29:00] particular lines, that’s a different cut through our business problem and saying profit and loss or supply and demand.
[00:29:07] Each one of those is a, is a cleaving or cutting through the problem with a different set of insights or principal agent, for example. And each of those gives you a different insight. You
[00:29:18] Aidan McCullen: [00:29:18] just sparked a thought for me, which is, I’m just thinking of a CEO. I’m just thinking for me even personal experience that.
[00:29:25] If you try to do these type of this work, it’s very, very demanding on the brain. It’s very demanding on your energy. And you oftentimes need to get off site and get away from the home drum of today. You need to be given permission to not check your email, to not be working on day to day work, et cetera.
[00:29:45] And that’s a huge failure in so many businesses because they’re not given permission. They’re still under the pressure of quarterly or monthly earnings calls, et cetera, et cetera. And this is where business [00:30:00] really needs to change where we need to apportion time. To be brainstorming and working on problems in permanence, not in once a year and a strategy day where everybody goes and has a nice meal and a few drinks and stays in a nice hotel for the weekend.
[00:30:15] This has to be built into the process. What are you saying from the best examples of companies out there? How are they integrating this into their daily work practice?
[00:30:24] Charles Conn: [00:30:24] Yeah, well, and I think if you’ve just said it, I mean, you know, we used to create strategic plans that were done once a year and you know, we’re a hundred pages long and.
[00:30:32] Or were printed out and put on the back of the door that you hung your coat on. I mean, that way of thinking about strategy is out the window and the old world in which we went to work and we sat at a desk and our bosses judged her productivity by how long we sat at our desk, that’s out the window.
[00:30:49] Right? The only thing that matters now is creative solving of complex problems with teams. And I hope that this pandemic, you know, and it’s a terrible, terrible [00:31:00] thing. But if there’s some silver linings in it, it’s that we’ve let go completely. The 1950s mentality about work and that we understand that creative work can be done at any time.
[00:31:12] And sitting at your desk actually may be the least creative place that you said. And it’s working sensibly with our colleagues and teams, which, you know, as we’ve discovered, we can do quite effectively over zoom or Microsoft teams or many other mediums. And. That businesses now free us up to actually be our creative and collaborative best.
[00:31:35] And nobody’s going to go back to the old regimented approach to work because frankly, all of that stuff can be automated and will be automated. And I think, you know, we’ve seen just how much job destruction there’s been in the last 10 years, which is going to be massively accelerated by this terrible pandemic.
[00:31:57] So the silver lining is we won’t [00:32:00] go back to working the way we did. All of us will have to be creative problem solvers every day. None of us will ever do an 18 month strategic plan. Again,
[00:32:10] Aidan McCullen: [00:32:10] I mentioned these three case studies that we share and you share lots of 30 in the book and they are so well-worth.
[00:32:18] Reading and going through too, hone this skill. This is a skill that’s so essential. And what I love about it is the visual approach, how you break it down. So simply, and just for everybody out there, Charles and I are hoping to do a live version of this by video because it’s so visual and to share some examples.
[00:32:37] So please do subscribe to the innovation show newsletter on the innovation show.io, where I can keep you updated on that or just on LinkedIn or. Instagram or whatever social challenges you have on also, Charles is share where we can find out more about his work at the end of the show, but moving onto these three examples.
[00:32:59] Rather than going [00:33:00] really deep on businesses. I wanted to go both on personal examples. And then that startup example, I mentioned that this started, this is I show this first one was based on your own personal experience of moving house and deciding where to live. And here you involved your whole family in the decision.
[00:33:18] Charles Conn: [00:33:18] Yeah. I mean, you know, it’s funny cause taking my company public and you know, it was trying to decide, okay, what’s next in life. And how do you think about where you’d want to live? And it was really interesting, you know, having used that kind of framework that we talked about, in business problems, I wondered, could we use this kind of framework to solve a personal problem?
[00:33:39] And it worked really well. In fact, it’s really akin to the first example we talked about, which is, back when I was working in Japan many years ago for Canon, how, where would you decide to put a factory? But I use the same kind of logic, which is sat down with a family with a whiteboard. I know this sounds crazy, but it really works and [00:34:00] said what’s important to everybody.
[00:34:02] And you know, some, some things emerge very quickly just sitting there with your kids, which is, kids need great schools. We all need a clean environment and lots of fun things to do when we have time off, everyone wants to live in a cool, friendly town. And, you know, I always want to know the answer to the question.
[00:34:19] Can you make a living? And so if you said those are the four things that are important, then you’d say, well, what, what is it, what are the good schools look like? And then you might say, well, okay. And you can see a tree. Aiden is starting to emerge here, like, okay, here’s a branch it’s called school. And the twigs off that branch are, let’s be in a place where there’s great teachers, small class sizes, and good taxpayer support for education.
[00:34:46] And then the next branch is, well, we said we liked environment. We could measure water quality. We can measure number of sunny day. You could measure great hikes nearby, and you can start to see that, that part of the tree [00:35:00] emerging. What does it mean to have a cool friendly town? You know, you want to have a walkable town center.
[00:35:05] Do you want to have arts theaters in libraries? You want to make sure that there’s not too much traffic and maybe a university town. So those start to look like twigs. Or leaves off the end of that branch and similarly on and on for whether you could make a living and whether you can get to other parts of the world.
[00:35:23] And that actually, you know, and I know that sounds funny, but that kind of family problem solving then leads to a simple tree and you can start to figure out what the data is. You could collect against that and really good schools. Well, one thing you can do is look at something that’s published called the achievement index.
[00:35:43] Or you can look at student teacher ratio. And similarly, I started collecting data on snowfall and number of sunny days, and what’s called the comfort index, which is based on, heat and humidity. And very quickly I had a little spreadsheet and you just normalize each one of those bits of [00:36:00] data between zero and a hundred.
[00:36:02] And then everyone in the family could agree what the waiting should be. And all of a sudden you can start to say, Oh, maybe here’s 10 cities that we should have a closer look at. And that’s exactly what we did. And they ended up taking the family to do physical visits, to place like Boulder, Colorado, or Steamboat Springs, Colorado, or bend Oregon, or Healdsburg, California.
[00:36:23] Eventually we ended up in Ketchum, Idaho. And that way of thinking, which is, you know, you could say it’s systematic, but it’s also just fun. And it means that everyone’s bought into it. And when you make a decision everyone’s aligned around it, You could say it’s silly. Cause that’s just a family example, but the same thing works in organizations.
[00:36:42] Imagine if you brought your whole team along by getting them engaged in saying, what are the important variables for success in our business and how would we measure that? And if everyone’s bought in, then you’ve already got alignment amongst your team, which is the single biggest thing, keeping most businesses from achieving their highest [00:37:00] tax.
[00:37:00] I
[00:37:00] Aidan McCullen: [00:37:00] think that’s the thing that’s so overlooked is that alignment, because if you’re feel like you were part of the strategy or the direction of the business, you’re going to be so much more behind it because you don’t feel like a cog in the machine. You feel like actually. This machine is aligned and everybody’s pointing in the same direction.
[00:37:20] I often think of coherent energy when, when energy is coherent, it’s so powerful or the rays of the sun that when they’re dispersed, they’re, you know, you might get sunburn. It depends on the heat, but when they’re aligned, they become like a laser beam and you can do amazing things when that
[00:37:38] Charles Conn: [00:37:38] happens. Yeah.
[00:37:39] And you know, that’s so again, it’s we talk about just a few minutes ago, which is the whole world is dead. In the old world, there were some guy up front telling us what to do. So that guy said, here’s what we’re going to do. And you said, yes, there are. How do I do it? Well, that, that world’s gone. Now. All of us need to be involved and engaged in deciding [00:38:00] what to do and how we’re going to do it.
[00:38:02] And it means that there’s much less requirement for hierarchy than there used to be. And organizations are much flatter and titles are much simpler. Because if you can empower everybody to be good at creative solving of complex problems. We don’t need all fashion hierarchies. We don’t need to look like military organizations.
[00:38:21] Aidan McCullen: [00:38:21] And again, people feel more empowered and they bring more discretionary effort to work. They don’t feel like they’re just shown up for a paycheck, but one of the criticisms you pointed out with this system, and I love that you do this as well. Is that with a systematic approach like this, some people point out that it’s a phony process to confirm the bias you had any way to get to the end points you want.
[00:38:45] Anyway, and this. Isn’t the case at all. And that wasn’t the case for your own experience with ending open catch on, because it wasn’t even on the list in the first place.
[00:38:54] Charles Conn: [00:38:54] That’s right. You know, obviously this is this question of fighting cognitive biases and [00:39:00] this stuff only works if you do it with integrity.
[00:39:02] And I end authenticity, which means leaders, so-called leaders actually have to be open to everybody’s genuine input. And the more you can empower your teams. To feel like they have agency in this, the more likely it is you’ll have that kind of alignment that we discussed a minute ago. And the less likely it is that you’ll just pick something that you already meant to do.
[00:39:25] Building
[00:39:25] Aidan McCullen: [00:39:25] on the idea of moving home and keeping it on a personal level. One of the things that happens with the show is that so many of the brilliant guests, I have inspire people to make the brave decision, to leave a job that they’re not connected to, or they’re totally disengaged from, or a company that competes with their values.
[00:39:44] And you say we can use similar process again, the seven step process, very aligned to the idea of moving home to moving employer. Or deciding to leave a job in the first place. I’d love if you give an overview of how people would approach this one.
[00:39:59] Charles Conn: [00:39:59] Yeah. [00:40:00] And, you know, I think it’s slightly more complicated than the question about where to live, but really uses the same kind of thinking.
[00:40:05] And you know what I often say to people when we’re talking about career stuff is how do you find the intersection of three things, which is what does the world need? What am I good at? And what do I love doing. And you can do a bit of research on that. Again, I think it’s this kind of systematic research.
[00:40:23] So what does the world need? So I think you’d want to look at data about current, the current labor market. And as you know, from my introduction, I would probably break things into what are cognitive and non-cognitive jobs and what’s W which are routine jobs and which are non-routine jobs. I know that when you look for growth, Almost all of the growth is occurring in jobs that are non routine and both cognitive and manual.
[00:40:52] Actually it turns out contracting is one of those things that’s actually growing. So I do a bit of research on what parts of the economy look like. They’re [00:41:00] generating jobs. And then I shift my attention and I’d say, what do I love? And what am I good at? And so you might start with a simple set of things.
[00:41:09] In fact, I did this with one of the road scholars who I was working with on the book. and she had studied architecture and it studied business. And so she filled out, she created a grid herself, which said down one side are in design, is this in finance, health and human services and so on. And then she created some, some simple columns.
[00:41:31] What’s the economic projection for this sector. What’s my personal strength. And do I love this? And then she added a fourth column that I think is really interesting, which is what’s her ability to take risks. Right? Cause career is one of these things where it’s not just what, but how risky is it? Right.
[00:41:50] And we use those two pieces of work. Just that little bit of research on what are the areas of the economy that are actually likely to be growing. And then what do I love and [00:42:00] what am I good at as well as where am I willing to take risks, to create a simple decision tree that we show in the book? Right.
[00:42:08] And I’ll take you to the front end of that, which is, you know, . So she asked herself are my strengths, risk tolerance, and interests aligned with, economic opportunity and, you know, the answer for her was not yet. And so then she asked, can I make a no regrets move? where I pursue a basic level of education in a new field, like design and in her case, she felt like the answer was, yes.
[00:42:36] Right. And so could she gain employment in that field, with her current skillset or would she need a little bit more investment in her case she needed a bit more investment. She ended up doing an internship in an architectural firm, and now she’s actually been selected to be a partner in that same architectural firm.
[00:42:55] So that kind of thinking, you know, cause in her case, she’s, she’s got [00:43:00] this very fancy Oxford education. People were pushing her to do a particular kind of businessy thing or a particular kind of social policy thing. And she used this framework instead to choose a career in architecture and design, which, which is a place where her kind of skills were, valued and needed, where there were growth in jobs, in that space and a field in which she had enormous passion.
[00:43:26] So same kind of relative. And again, I don’t want anyone to think this is over complicated. It requires really fancy math skills in most cases. It doesn’t.
[00:43:35] Aidan McCullen: [00:43:35] No, it’s so good. It’s so helpful, man. And I think, I think there’s covered, locked down. We’ll probably give people a chance to reflect and kind of
[00:43:43] Charles Conn: [00:43:43] think.
[00:43:45] I
[00:43:45] Aidan McCullen: [00:43:45] don’t, I don’t think my job has given me any fulfillment or any purpose. And if that can’t be fixed, life is too short to be staying in those roles. And I, I know that sounds easy, but I have, I’ve moved and it’s [00:44:00] very difficult to do so because it’s particularly when you have a family, when you have people relying on you, when you’re married, when you’re mortgage, all those kind of things.
[00:44:07] But it’s so worth it because life is too short to be miserable. And you know, how many people do you see who go through life, working in careers that they hate. They get to the end, they retire and then they catch some disease and they don’t even enjoy the retirement because you’re somebody who has had the bravery, but also use this logic.
[00:44:29] To make these decisions for yourself, including selling your business.
[00:44:32] Charles Conn: [00:44:32] The world is full of people who were 40 years old or 50 year old, 50 years old, and they hate what they do, right. We should never be in that situation. People feel like they’ve made choices that close off other choices. And in the future, like all of us are going to have three or four or five different careers, and we’re going to have 10 or 15 different jobs.
[00:44:52] We should move away again from that 1950s or 1970s model that. We’re going to learn a bunch of things in [00:45:00] university and then apply it over career and get a gold watch. Those people died. Anyway, they died sitting on the couch two years after they retired.
[00:45:07] Aidan McCullen: [00:45:07] That’s so true, man. And I think that I’d love if you shared that piece, because I say the same thing to people that my father worked in one company for 20 years or 30 years, you know, he moved, but that was rare in his era.
[00:45:21] I will work for maybe five companies in my lifetime. Our children will probably work for five companies concurrently in honey one year. And yeah, you’ve seen this firsthand. You work as a contractor, you’ve worked in the big consulting firms. What is your advice to those people making decisions now?
[00:45:39] Charles Conn: [00:45:39] And I think it said it’s very much aligned with the case example we just gave, which is the constantly be thinking about what does the world need, because that is shifting at a faster and faster rate.
[00:45:52] What am I good at? And what do I love doing? And then making sure that each job you build on, what am I [00:46:00] good at? And I like to say to the, to the students that I advise stay only as long in each job where you learned what you came to learn, right? That’s how you avoid getting trapped in something that you hate, just because you’re good at it.
[00:46:16] And especially lucrative jobs are like that. Right? To be free means walking away from great lucrative jobs. Once you’ve learned what you came to learn.
[00:46:27] Aidan McCullen: [00:46:27] I love us and maybe I’d park the ego because, you know, anytime I’ve made a call or decision based on ego for a brand name, it wasn’t usually for myself, it’s usually to look good externally and that always comes back and bites in the ass.
[00:46:44] But
[00:46:45] Charles Conn: [00:46:45] when I quit McKinsey, I was 34 years old and I had just made partner and everybody said, what are you insane? Like you finally got the brass ring. Yeah. But they’re brass handcuffs.
[00:46:58] Aidan McCullen: [00:46:58] That is when you need to go, [00:47:00] man. And it’s such an important message that, and I know it’s easy for certain people.
[00:47:04] Everybody has different brain structures, everybody’s different dopamine levels. So we all make these decisions differently. So I just wanted to say that I know this is a difficult choice for people, but there’s a final case study that is so relevant for the show and a great way to mention our sponsors, which is Microsoft for startups.
[00:47:21] And this case involves making pricing decisions in a startup company, which is hugely relevant for your work as an investor, mentor and advisor for startups, Charles. In your own companies, cash is even more critical than in established ones. And this is a dilemma, so many startups face, which you call. And in this particular case, you call the business truck gear based on a friend of yours startup.
[00:47:45] And basically they were asking if the marketplace would react negatively to price increases, growth would slow and perhaps even drop in unit sales, which would be a death blow for a startup. And I’d love a future, how they dealt with [00:48:00] this challenge or this dilemma.
[00:48:01] Charles Conn: [00:48:01] Yeah. And you know, and this is a real company and this is a real mate of mine who I’ve known for years and he’s incredibly brilliant guy, but you know, it’s, it’s so characteristic, which is when you’re buried in the day to day of business, it’s really hard to get clarity, to make difficult decisions like this.
[00:48:18] The company is growing 50% a year. Is profitable already, which is amazing for a startup, but all of a sudden it starts to get margin pressure because it’s a materials and variable manufacturing costs are going up, it outsources manufacturing. And so what do you do? Do you, do you try and cut costs to save margin or you raise price?
[00:48:41] And as you said, it’s a super scary decision. And so what we did is we just sat down with a whiteboard and we created a really simple. Profit lever tree. You could also create a more sophisticated version of this, where you use assets too, called a return on invested capital tree, but let’s just stick with this very simple tree.
[00:49:00] [00:49:00] Imagine a tree which is just got cash profit at the origin and has revenue and costs as the two big trunks. And then you can break revenue out into average price per unit times units sold, and your break costs out into variable costs and fixed costs. And variable costs break out into units sold and variable cost per unit.
[00:49:20] And what you could see really quickly was once we put in his numbers for those things, that if you could raise, prices by only 7%, you too double the cash profitability of the business, removing all that margin pressure. And so we knew we had to answer one question, which is. Would customers stop purchasing the product?
[00:49:44] If it went up, if it’s price went up by 7%? Well, we got on the phone, we call it, we called 40 recent customers and we ask them about the product features that led them to make the purchase. And no case was priced. One of those defining features. And so we were able to [00:50:00] experiment and because the company had multiple channels that could start just in one channel, which was the online channel.
[00:50:06] We experimented by raising the prices and we discovered at that price level. There was a low price elasticity of demand. So people didn’t stop purchasing just because it went up by 50 bucks and in that case, we’re able to double the profitability of a fast growing business, very confidently. whereas before that, we weren’t sure what to do later on the business was able to bring manufacturing in house so that it had stronger control over that variable manufacturing costs.
[00:50:36] So we were able to drive that down as well. But it just showed like a little bit of discipline problem solving with a very simple logic tree and barely any mathematics, just literally, you know, addition, subtraction, division. We’re able to get a good answer for a young business and give it the confidence to move ahead.
[00:50:54] I
[00:50:54] Aidan McCullen: [00:50:54] was thinking about doing a live visual version of this and how we would do it. I don’t know [00:51:00] quite yet how to do it. I’d probably need to use the seven step process to figure it out, but we’ll brainstorm that between ourselves. But I think maybe doing this, or maybe even crowdsourcing, a real challenge might be a good way of doing it.
[00:51:12] Or perhaps it’s a career move for somebody or. I dunno, a new business idea or something like that we might do. So please do to our audience, do get in touch on those channels. The innovation show that I always subscribed there to newsletter and I’ll share when we’re going to do it, Charles, where can people find out when we’re going to do it and how we’re going to do it?
[00:51:30] And also the amount of knowledge that you do share where, where can people find that
[00:51:34] Charles Conn: [00:51:34] if you go to Bulletproof problem solving.com, you can find some worked out examples, including the graphics, because I know sometimes it’s hard to imagine. What does a logic tree look like? And it makes it sound harder than it is.
[00:51:46] You can also go on YouTube where we’ll show some examples. The first video is up already, and several other videos will be posted the next couple of weeks where you can see us working through problems step by step, because all this stuff again, [00:52:00] it’s, it makes it sound like math class, but it isn’t. It’s meant to be fun and it’s meant to be collaborative.
[00:52:04] So go to Bulletproof problem, solving.com or check out YouTube, and you can see examples worked out
[00:52:10] Aidan McCullen: [00:52:10] author of Bulletproof problem solving the one skill that changes everything. Charles Kahn, thank you for joining us.
[00:52:16] Charles Conn: [00:52:16] And it was such a pleasure.