#152 How Data can Enable Effective Leadership with Dr. Constance Dierickx, The Decision Doctor

Talent hits a target no one else can hit. Genius hits a target no one else can see. So if you want to become peerless as an organization and use your data to help you get there, you got a dream.

Hi, Constance. Thanks for joining us on the show today.

Oh, thank you for having me, Richie. I'm so looking forward to it. You are a. A person with great questions and a wicked sense of humor. So I'm looking forward to this.

Oh, well, yeah, flattery will get you everywhere.

So I just start with flattery. Right.

All right, so let's dive in. So your book is all about meta leadership. I think I'd really like to know what meta leadership is and how it's different from regular leadership.

Yeah, good question. So meta leadership is a phrase that I. I thought I coined it, but upon investigation, I realized others have used it, but they've used it in specific ways. Meta means above or beyond. It's from the Greek. I wanted to express the idea that really great leaders are distinct because they are able to turn their autopilot off in a very conscious way when they need to. When you want an autopilot on, it's great. But I had the joy of working with Delta Air Lines a few years ago, and I learned that those 777 pilots, they use the autopilot, but we need their good judgment to know when they have to turn it off and take control of the plane for our safety. So meta leaders are able to think consciously when they need to and use reflexive thinking when the risks are low. They understand the role of emotion, especially their own, and they are good students of human behavior and the habits of behavior. Each of these dimensions can operate on two levels and probably others. You'll tell me the other ones that I haven't thought of. One level is the individual leader or manager or just an ordinary human being, because we all make important decisions. The other is on a wider scale. So organizationally, collectively, what are we thinking? What are the ways that we think alike? What are the ruts that we get into with our thinking? What do we feel collectively and how do we act? What are our assumptions about the right way to act? Which a shorthand way to say that is organizational culture. This is a model. It's not a checklist or particularly a how to. It's a way to think differently and incorporate emotion and behavior. So you make great decisions.

That's brilliant. I like the idea that you have to be a little bit mindful about the decisions you're making rather than just doing everything on autopilot, it's very easy to get into that routine of just doing what you've done.

Yeah. And sometimes it's fine, you know, if you're standing in front of me in line at the ice cream store, please be on autopilot, make your choice, and move on.

Can you give me an example of how these methods, leadership ideas apply to data leadership?

Oh, absolutely. That's one of my favorite questions. So a client will say to me, well, we have our metrics and we have our experience data and our customer insight data and all of that. And I say to them, who chose the metrics? And there's usually a stunned silence, two or three. And the answer ends up being some version of, well, we got this advice, or this is the way we've done it, or we've been tracking this for years and we want the continuity for our data. These are not bad answers. But then I ask the leader, has anything changed in your business in the last 18 months? They say, oh, yeah, yeah, a bunch of stuff has changed. And I say, well, would it be a good idea to take a step back and think very deliberately about the data that you wish you had or the insights you wish you had? That's an act of meta leadership, because you're stepping back. You're not reflexively criticizing what is already being done, but you're saying, could we make it better? The beautiful thing about data is that you can always add or you can take away. The bad thing about data is we tend to reify the number. And there's a concept called subrogation, which means that we measure something and then we think that the measurement of the thing is the thing itself. So meta leadership requires us to always lay back and say, is that really. Is it the thing itself? Is the employee engagement number really telling us about employee engagement? It's a clue. It's a clue, but it's only a clue. It's not the thing itself.

I love the idea of saying, well, sometimes you need to sort of take a step back and when you're trying to update metrics, you don't say, or, this thing you're doing already is wrong. But actually, maybe you need to think about what's changed and how you might do things better. Because sometimes you can't get resistance to even these, like, little things like, oh, how's this thing calculated?

Exactly right, exactly right. And when you're working with a company or a leader that has a history of success, you can bank on the fact that they're going to defend what they've been doing. And you might hear that worn out phrase of if it ain't broke, don't fix it. And so as an advisor to leaders, I don't like to position myself as a problem solver or a fixer. I'm an optimizer and it's a much happier place to be.

Okay, so before you mentioned the idea that the things you calculate are not necessarily perfect, the representative of reality. So there's always some uncertainty involved in. Well, how does this metric play out in terms of how you interpret it, how it's going to affect your business? So can you talk me through some of the sort of pitfalls of what leaders make? What are the common mistakes leaders make when they're faced with uncertainty?

Biggest pitfall of all is not recognizing how much change is happening in the environment. So sometimes we as humans, we experience, and I'm going right to the emotion section of the book, we experience uncertainty in the external world through subtle cues in ourselves. So we feel queasy, our stomach flips over, we get sweaty palms. Whatever it happens to be. Feelings are. We call feelings emotions, but feelings are really the physiological things that happen to us first. So leaders, great leaders, use those as input, as clues. It's not information, it's a clue. So when faced with uncertainty, the thing to do is to lean out, not lean in. That phrase, lean in has been very worn out, is to lean out and look for novel sources of information, which I call data. I like to think that qualitative data is data. It's not very organized, it's messy. But quantitative data is very neat. You could put it in spreadsheets and it's super valuable. So looking for novel sources of input, and this is when gathering, having a conversation with people who aren't in your usual suspect group can be extremely helpful because every leader I've worked with that's in a crisis will tell you in hindsight they saw faint signals early that something was brewing and they dismissed it. And in fairness to leaders, they get a lot of faint signals. So separating signal from noise is not always super obvious, but having an external touchstone or two is really helpful.

And you mentioned that this is often like a very emotional reaction. So you have uncertainty, you don't know how to deal with it. How do you move from thinking or from feeling emotionally to thinking about this logically?

Yes. So this is where Amy Edmondson's concept of psychological safety is very profound. And we know from her research and subsequent research from academics and scholars that psychologically safe organizations are More profitable, they're more innovative. So if you're having those feelings and you're in an unsafe environment, I would say you'd be nuts to tell anybody what you're feeling. That's just crazy, right? But look for a place that is where you can explore. You could say. So I worked with. I'll give you an example. I worked with a CEO years ago who was running a company outside the US they were based in Miami, but all of their operations were outside the United States. So he had very remote. He was very remote, and he had a lot of data. But he said to me one day, he goes, something funny is going on in Mexico. I don't know what it is. Now he's telling me with his office door closed me, who is not going to tell him he's crazy or I don't know what he's talking about? And I said, what are your indicators that something's not right? And he described to me a lot of behavior. He was very behavioral in his description. The general manager was sort of slow with his reporting. He was cagey with his answers. Those are big clues. That's not a faint signal. That's like a red flag in front of a bull. So, long story short, he sent me to Mexico. I went to Mexico City three or four times, and I came back and said, indeed, something is wrong, and it's wrong in finance. And he looked at me and he said, well, you're not an accountant. Like, how would you know that? And I said, by the behavior I'm seeing. So we talked fast forward a few months. The CFO and the controller of this company were in cahoots, and it cost them $14 million that they had to write off. So what he did was he shared his concern, his feeling, his discomfort with someone that wasn't going to laugh at him. And we figured out together what we could do to explore it. And then I came back to him. I will tell you that he didn't want to believe me at first. They had just had an audit that was clean. And I said to him, you know, if you're CFO and you're a controller, have some sort of agreement, it's harder to detect. And so then he took a closer look. That was very, very unfortunate. So find a safe place to express your concern and allow someone to help you walk through. Because when we have a feeling, there's always some event or something someone said there's something that's causing that response. And once you start to sort out the specifics, then your Brain gets a bit more engaged. Your brain is never not engaged, but you want to use the emotion and the brain simultaneously as best you can. It's hard.

That's a really interesting story, and I find it fascinating that this is a thing that came out about because of people's behavior. And we talk a lot in the podcast about making decisions from data, but perhaps sometimes it shows up in that sort of human aspect first. And so do you have any advice on how you go from these sort of behavioral instincts into making decisions with data? Is there a way to reconcile the two?

Yes. Yes. First of all, it's to not be dismissive, qualitative or behavioral data, but rather use it as a clue, hold it as a hypothesis. Does this mean anything? What might this mean? I think it might mean this. And then you test it with your data. You say, I saw this, I observed this. What is the data telling me? Are the things I'm observing predictive of behavior that shows up in data? You know, when people borrow money, make payments on a credit card? Those are behaviors that show up in data. When we search online and we're scrolling and we stop at the ad for whatever, you know, we all know that's not private, right? Somebody's capturing all this metadata. So the best way to describe it, I think, is with an example. Would that be of interest? Of course. Okay. So I had a client a few years ago that acquired a company for their technology. It was primarily a technology move, and they needed the technology. This company had amazing technology. They were running their customer platform on mobile devices. This was before that was as common as it is now. And I. They appointed an executive to, you know, bring that company into the fold, if you will. And I was his. He called me his flight engineer. Like, I was with him. You know, I saw. I was looking through the same windshield, I was seeing what he was saying. And I was in his ear, saying, a little to the left. And this guy's a great leader. It's a great. Really good. This, this acquisition turned out way better than the. Than the investment thesis. That's pretty rare, right? So as we got to know the company, they were in the financing business, and we. I started asking the president, who are your best account reps? And he. He said, well, you know, these guys won the president's award or whatever. And so he's looking at the data, right? And I said, can I meet with and talk to these high performers? There were five. And I met and I talked to them, and I asked them, how do you know when A customer is starting to get in financial trouble that could lead them to default. And they told me. They told me all kinds of behaviors. You know, I go in to talk to the customer. We have an appointment, but they're not there. I look around the business, and it's unkempt. There are fewer employees there. The offices, well, I said unkempt. It's a mess. They're not doing the things they're supposed to do quite as well as they did before. It's very much like American Express. If you pay your amex bill in a certain way, and then one month, you pay it one day late, you know, flares go up. Right. Because that's behavior. So what I learned was that the best account managers or reps were the ones that saw these early signs. Oh, another one told me was when I park, I park at the very edge of their parking lot so that I can walk through the parking lot because I want to see if there's garbage. That's a behavior. Right. But it's indicative of an ethos, of a culture. You can see the signs of decline. In the best case, one of these account reps warned the risk manager early that one of their customers was in trouble, and indeed, they ended up going out of business. But my client, or the client of my client, rather, the acquisition of my client was very prepared for it, and they took action sooner than they might have otherwise. So you gather that data by talking to people. It's not complicated, but it does require really good listening.

I love this idea of having these subtle behaviors as being really strong signals of indication. And I suppose in some ways this is how a lot of marketing works, is you try and quantify human behavior and get some data out of that.

Precisely. Precisely. But I'm not good at marketing, so it's hard to talk about that. I appreciate it, but I'm not that.

All right, we'll not talk about marketing then. What I would like to talk about is a related idea of biases, because we often think, okay, I'm a rational decision maker, but there are many sort of common biases that these particularly are prone to. Can you talk me through what some of these common sort of thinking biases are?

Yes, but first I want to say that cognitive biases, or, you know, our tendency to step into invisible decision traps, as I like to call them, is human. This is not something that dumb people do. And, you know, we're smart and rational, so we're not going to make these mistakes. We all make them. And if the risks are Low, you learn and move on. If the risks are high, that is when you slow down and ask yourself the most common one that I see. Someone was interviewing me on a podcast about mergers and acquisitions and they said, name the top five reasons why they fail. And I said, there's only one. They said, what are you going to tell me? Yes, it's overconfidence. Your overconfidence in your projection. You're overconfident in your data. You're overconfident that progress in a business will be more or less linear. That might be true, it might not be true. These are the metacognition questions that leaders ask. Overconfidence. There's an overconfidence self test in my first book, High Stakes Leadership, and actually I should probably turn it into a PDF. If I send that to you, maybe your readers would be interested in it and you could offer it to them. Let me make a note to do that. What we know is that people are overconfident. Humans are overconfident, wildly. And there doesn't seem to be a whole lot we can do about it other than be forewarned. But knowing about biases is not preventative because knowing is in our head. It's knowledge. What drives behavior more is emotion. I know data. People don't like to hear that. In fact, leaders don't like to hear it. I think another one that that trips people up is this notion of sunk costs. Well, we've already invested this much, so we have to keep going because why do people do that? They don't want to be wrong. We don't want to be wrong. I will include myself. I had to go downstairs yesterday. I was in my office where I am right now, and I was thinking about a conversation I'd had with my husband. And he said something and I was like, no. So I had to. I left my office, I went downstairs and I said I was wrong. I was wrong about that. You were right. And here's how I learned that you are right. There are very few things more restorative to an important relationship than admitting when we are wrong. But human beings don't like to do that. And I'm not perfect at it. So this notion of sunk cost gets particularly enlarged in an organization. Let's imagine you've set up a new IT system that's going to improve your data collection, your analyses and your insights. You know, a business bi sort of a thing. And you've spent a million and a half dollars, or probably more like a hundred million. You Tell me. But you realize that there's a very important fundamental flaw in it. It's very hard to pull the plug. And you can understand that, right? Like, it makes sense, but it's powerful and it's emotional. So we have to manage that in ourselves.

I have to say, certainly admitting you're wrong is one of the biggest challenges of working in life in general. But, yeah, useful advice if you can pull it off. So one of the things in your book that I found very interesting was that you talk about all these sort of pairs of sort of opposite dimensions, things that you need to worry about. One of the ideas was around the difference between strategy and tactics. And I'm wondering, do you find data to be more useful for business strategy or business tactics is like preference of one over the other?

Yes and yes. And data is very important to setting a strategic direction for a company or a strategy for a business unit or a team, because strategy defines. This is where we're headed. This is what we're going to do, this is what we're not going to do. And therefore our resources are going to go here. Strategy that does not inform resource allocation decision decisions is not a strategy. It's a business plan. And a lot of strategies that have strategy written on them are really operating plans or business plans or financial plans, all of which are useful. But when it comes down to competing priorities for resources, people, space, money, technology, the deciding factor needs to be, what is it we're trying to do here? Where are we going? Tactics require data. And so let me think. Can I use a clinical example for your audience? Okay, so anyone who's ever had an issue like chronic pain, for example, I used to work in a behavioral medicine clinic when I was a resident, because that's my background is actually clinical psychology. Although everyone thinks I'm an industrial psychologist, I wear a good disguise, I suppose. So I saw a lot of patients with pain, knee pain, back pain, chronic headaches, et cetera. And we would use biofeedback mechanisms. Well, what is biofeedback? It's data from your body. It's your hand temperature, it's the tension in your arm. It's some physiological measure that is then compared to your pain level. And people get a visual representation of this biometric and they begin to understand, somewhat unconsciously. Oh, when I am like this, you know, that little donut is less filled up and my pain is less. So that is a continuous feed of data around a tactic. And there are a lot of examples, I think, in customer experience, for example, in marketing where you get these very minute and real time pieces of data that companies use to test a tactic. You know, everybody wants to grow revenue, sales and margin, Right. But if you invest in a move to the left, you want to know as fast as you can and you want to amass as much data that's relevant to say, yeah, we should keep doing that, or well, that didn't work. You know, fail fast, cheap and often is the idea. And you need to test your tactics and use data.

Okay, I mean, that sounds pretty cool. Data is actually useful for both the strategy side of things and the tactical side of things.

It's not binary. Used it everywhere, which is the whole point of the book, is that meta leaders need to be synthesizers and say, we need to use data strategically when we're choosing strategy in this way. And it's probably a longer process, but we also need to use it to test to see if the tactics we're employing are actually doing what we'd hope.

So on that related idea, talking about synthesis. So one of the bits in your book I really liked was the idea that you have to synthesize size, your analytical side and your creative side. I think a lot of data roles, people get labels. Oh, yeah, you're an analytical person, data analyst, the sort of the clues on the job title. But actually.

Yeah, right, that's a big clue.

Yeah, yeah. But actually you do need some level of creativity there as well.

Yes.

So can you tell me where the creativity comes into working with data?

Yes, well, creativity comes in. Well, let me, let me back up. I want to say something about this first. When leaders refer to people as you're this kind of a person rather than this is the job you're doing or the task you're doing, they're limiting absolutely everybody, they're limiting themselves because they'll miss seeing what else that person can do. And most of us are not monolithic, although we have a strong tendency to have identities as well. I'm an introvert, therefore, blah, blah, blah. That's not true. So when leaders limit their own ability to see, they also limit the person themselves from being able to see. Oh, they're really good at this other thing that's not really analytical. What would you call that? Oh, maybe it's creative or maybe it's, you know, whatever words you want to put on it. So where creativity comes into play is in the design phase. Designing what sort of data set you want to end up with requires bigger thinking. Data collection requires a lot of technology. It requires accuracy, requires that the data Go through the right funnel and end up in the right place so it can be utilized. But the creative process. And there's a wonderful book that, that I love, actually, I have it right here because I love it that much. I'm gonna show it to you and your. The people that are viewing this on video. It's called Life. You love design the life you love. Now, don't be fooled by the life you love. Just think of it as this. Think of this as design thinking. The author is Ayshe Bursel, A Y S E Burel. She's an internationally known designer. She works with Herman Miller and Toto and big companies. She just did a whole big confab at Amazon and she shows all of us the process of setting your vision. What do you want? And then before you create your plan about how you're going to get there, you do some other steps that are really pretty fun. And you. She takes you through a process of deconstructing and then reconstructing within that. I discovered. I did the exercises in the book, which I never do in a book. I read them and I go, that's stupid. I'm not doing it. Her book is very different, but you have to come to it with an open mind. What she teaches you is a process that you can apply anywhere. You could say, we want to be able to make these decisions in our company, and immediately we think, what data do we need? It's like, whoa, wait a second. Back up. Spend 30 minutes, 45 minutes doing this process that she recommends and see what you come up with. I would describe it for you, except it'll just take time. And she describes it better than I do. But I've used it personally and I've used it in my business, and it's terrific. We find that most people are able to create when they're given the opportunity or sometimes when the situation requires it. You think about, you know, the gosh Apollo, you know, the one that got stranded. Gosh, I grew up. Thank you. I grew up near the Cape. I'm supposed to know this. I supposed to have this in my memory that, you know, you got a bunch of engineers and literal rocket scientists and they put a bunch of stuff on the table and said, this is what they have on board. We have to help them fix this using these materials. And. And they did it. You wouldn't call those guys creative, but they were.

There's such a sort of great real life story, the Apollo 13.

Thank you for bailing me out.

And I do like the idea of there being from the book, you mentioned the idea there's a sort of process for creativity in a lot of cases. I'm curious as to if you have any examples of how you go about mixing the analytical side of things and the creative side of things when it comes to making decisions, particularly around data driven decision making.

Well, I think creativity is the aspect of identifying options. So I'll sometimes ask a leader, what's your ideal outcome? And when you ask somebody what their ideal outcome is, they start to dream in their head. Or a lot of people do, probably not everyone. And they'll say, well, you know, we'll dominate the marketplace or, you know, whatever. That's a creative process. It's imagining. And then logically in the process, you bring in the engineering so you get the imagineers. Like at Disney, you say, well, how can we do that? The problem with putting the how can we do it before the what are we trying to do? Is that it kills the creativity and it confines organizations to do things that they already have capacity to do, not to build up their capability to do something that no one has done. One of my favorite quotes is the Schopenhauer quote. You probably know it. Talent hits a target no one else can hit. Genius hits a target no one else can see. So if you want to become peerless as an organization and use your data to help you get there, you got a dream.

That's a very cool quote from Schopenhauer.

I love Schopenhauer. I know he was a big downer, but that was a good one.

Nice. I think one of the big problems when you start thinking about, well, okay, I need to make a decision. I've got this data is when the data is counter to your intuition about what should happen.

So don't you hate that? Yeah, we all hate that.

Have you got any advice for what to do in this situation?

So if you're alone, if you're by yourself and the data is telling you that you shouldn't do something that you want to do, now's the time to lean back and ask yourself, I need to think about my thinking right now. That's metacognition. Metacognition just means thinking about thinking. How am I thinking about this? Is it really a life and death matter? Is it really just going to get my goat that I can't do the thing that my intuition wants me to do? And of course, this is in high stakes situations. Again, back to the ice cream. You're choosing your ice cream flavor. What's the worst will Happen you won't like it and you'll go get a different flavor. Big deal. You know, it's a $5 decision. And then you can ask yourself, what are the. What is affecting me right now? Who is impacting me? Managers and leaders and indeed all of us have people in our environment that are pulling for one thing or another or trying to influence us or they have an agenda. If you have a big team, you got a bunch of agendas operating. And if all you do is just say what's affecting me right now? And how am I responding to that? See, I'm trying not to use the word feeling here. How am I responding to that? Just to increase, increase your awareness of the effects. And then finally, what do I normally do? Do I normally go with my gut? I just published an article in Fast Company about when you shouldn't go with your gut. And you hear leaders say, well, my gut's really good. That's because they haven't collected the data and done a retrospective on their important decisions. Right. So they think they're imagining that they're really good at this gut level stuff. So you're testing a hypothesis there. So I'll give you an example of the emotion. I had a client when I was, I used to be a stockbroker long time ago, before I went to grad school. And in fact, being a stockbroker was what led me to study psychology because I couldn't figure out why all these smart people were making such terrible decisions with their money. You know, I was like, and certainly I would never do that. Well, I learned that it wasn't stupid people, it was humans. Had a woman who was in her mid-60s, she had very little money in retirement, but she did have an account with us. She emptied the account one day, took a check, took all her money out and gave it to her son in law to open a retail store. No risk there. No amount of conversation with her, no amount of data and facts about the historically risky thing she was about to do would convince her. And as you can tell, that's been decades ago. I can't stop thinking about that woman occasionally and what happened to her. Because your listeners will know that the data tells us a brand new retail store opened by someone with no retail experience is probably going to fail, I'm sure.

Yeah, pretty low success rate there. And it just seemed like we sort of come back to the idea of biases again. So if you don't evaluate how well your sort of previous decisions have performed, you're going to determine how Good. Your gut actually is. And you're to going, going to be biased into believing that you're, you're better at decision making than you think you are.

But also you will miss learning what you're really good at. You know, so doing a retrospective and just creating some data categories for yourself and writing this down on a legal pad or wherever you're putting it on your phone, whatever you're going to do allows you to have a full data set. Might not be complete. That's probably okay. But you'll see where you tend to make mistakes. But you'll also see where you're really good. And that's the exciting part about collecting your own data on your own behavior. It's like, wow, I was creative back then. I was insightful. I saw something before other people saw it.

Having data that shows that I'm amazing. That seems like a women's situation. I like that.

That's the thing, Right.

All right, so I'd like to talk about one more problem related to.

Sure.

Data driven decision making. And this is something that's become especially important with the sort of the rise of AI in the last year is when AI says this and the decision maker just blindly accepts the result. Can you talk about when you need to be skeptical about results or auto generated decisions?

I think assertions need to be interrogated. So an assertion is just a statement of fact. So for example, I'll tell you that I play around on ChatGPT and did you know that I'm a professor at the University of Colorado? I'm not, I am not a professor anywhere. I spent one year in academe and then I spun out and went and became a consultant. But I think assertions are need to be validated, whether it's from an AI generating thing or. And sources, you know, fact checking. I had a client. Oh gosh, this was a company that built and launched satellites. These were smart people, literal rocket scientists. They hired a guy to be their head of Latin America and did not validate his credentials. He said he had a master's degree in chemistry. He did not. He said he was fluent in Portuguese. He was not. I mean they did basic. Just a basic mistake. And this happens. This happens a lot. So I always ask people, how do you know that an assertion? You'll hear a lot of assertions in speeches when people stand up and say, well, the lizard brain. That is a very old theory. It's called the triune theory of brain development. Long been surpassed by better theories. But people heard it back there. They Thought it sounded good. Like, oh, I know about neuroscience, actually. I can pronounce lizard brain and I say it on stage and, you know, and then people start wondering, ooh, do I have this primitive part of my brain that's going to take control and make me act crazy? No. No, you don't.

I hopefully, like, your brain stem's still active while you're speaking on stage, but. But, yeah, yeah.

Your brain is never not engaged. If your brain is not engaged, you're dead. Right. But it sometimes gets. Our behavior can be more. We can let our emotion be in the driver's seat, particularly if we're mad, if we're super happy, or. Here's the good one, falling in love. Now, you probably want to disengage your rational side slightly, you know, in that scenario. So the brain is always with us, and our emotions are always with us. We do have really good research, and I'll throw out a name. Lisa Barrett Ellman. Barrett Barrett Ellman. David Eagleman write about this in their books and they give the sources for how we know this. It's a fascinating study.

Yes, absolutely fascinating area. And many, many pop songs and books and movies on the subject of going crazy while falling in love.

Oh, my gosh. Yes. We never get tired of that theme. Right.

All right, so one of the things you talk about in your book is the idea that you need to be courageous at work. Now, so is this the same thing as being self confident or is it something else?

It's something else, actually. And we know this from research that Jim Dettter has done at the University of Virginia. See, I'm citing my sources now you've cued me of that. That self confidence doesn't mean that you're always self confident, that you don't always say what you think. In fact, if you always say what you think, if you are always contributing, you're probably not sufficiently attending to your environment. So every good attribute like self confidence or courage needs a good brain at work to evaluate the situation that we're in. To be self confident in a scenario where that's not going to get you what you want is not smart. Courage is very similar. So it turns out that people are more courageous in organizations that value diversity of thought, that don't expect people to be courageous when it's a big thing, if they've punished them for being courageous on small matters. If you make it impossible for people to tell you, oh, we have a mistake in our code, if the manager goes, whack, whack, whack, don't bring me problems, bring me solutions. Right? You've heard that over and over. If people can't bring you what's wrong and get your assistance to make it right, don't expect them to tell you that the guy sitting in the cubicle next to them is embezzling. They won't do it. But it's not about so much about the person. It's about the environment that they're in. And people that are really good at this are courageous when it has benefits, but they're also wise enough to know when they're going to get smacked.

Okay, so it sounds like maybe the office culture is an important thing here. So can you talk about how a leader might go about trying to develop a culture where you can raise issues about things and how you can get problems addressed?

That's a really important aspect of leadership. And one of the pieces of advice that I give leaders all the time is to learn in public. And by that I mean, you know, you're out and about, you're standing in, you know, cube city, and people have gathered around and you're just having an informal conversation, and you think of a question you want to ask, and you ask the question. And then when the person who knows more than you do answers your question, listen, don't talk, nod your head, be engaged. What are you doing? Why am I saying this? You're broadcasting to everyone. The undercurrent, the unspoken is learning is important. Everyone needs to be a learner, including, including me, the CEO, the svp, whoever I happen to be. The other way leaders can do it is when someone does raise an issue that you listen thoughtfully to what the issue is and you make a determination about what you need to do, but you walk them through your rationale. So you're teaching people it's okay to bring me an issue that you think is a problem, even if I decide that we don't need to do much about it, or maybe we do need to some. But you make it a conversation, not an interrogation, and not a situation where they bring you something, say, oh, you know, I think this pencil is, and you give them a thumbs up or a thumbs down. The hardest thing to do as a leader, when you have a lot to do, is to suspend judgment in favor of curiosity, at least briefly. I'm talking 40 seconds. I'm not talking about. You don't have to listen to somebody for an hour. You really don't. You can listen a little bit, and then if they're trying to boil the ocean, you can direct them without judging them or scolding them.

Okay. I do like the idea of being curious at all times, even if it's just for a short moment, rather than outright rejecting new ideas. And so one of the sort of important ideas in your book, we've mentioned this before, is the idea of synthesizing ideas from different places. And so can you talk me how you go about getting good at synthesis?

So one of my favorite ways to get good at synthesis is to put people in novel situations. So, you know, a lot of organizations do team building events or off sites or whatever when you've got your people in a novel situation. It could even be in the conference room in your own office. You don't have to go to the Four Seasons for Pete's sake. Although, you know, that's not a bad place to go. You get them to consider a novel problem. You say, you know, we're having a problem here in our office. We spend way too much money on people to come in and tend our plants. We have all these indoor plants. We want a nice environment. We're spending too much money. We're not even really sure people appreciate the plants. What are your thoughts? And people look at you like you have, you know, three heads. You say, just go with me, just go with me. And you say, okay, how would you investigate this? How would you collect data on this? And they'll tell you, well, I think we should go talk to some people, right? You can do that in 20 minutes. So you say, great, you three, you two, whatever, go talk to people about the plants. And they go out and they talk to people and they come back and they report out and you say, okay, what do you think we should do? Now you ask them, what does this have to do with our day to day work? What are the parallels? What are the themes? What are the patterns? You all just did data collection, analysis, synthesis. And we reached a conclusion and we did it in an hour. Wow, that's pretty cool. You guys are pretty creative. Or you people, I shouldn't say guys, but you know what I mean. We did that at a resort in California. I was in a masterclass with my longtime mentor and we brought the general manager in to give us a problem that he was struggling with. Actually gave us three. And we were divided into three groups. I was in the group that got a problem with their valet service. So what did we do? We went and we talked to the valets and we found out what the pro. What was causing the problem. And we came back and told the general manager and he Said, how did you know that? And we said, oh, we went and talked to the valets. It's like, it's not, it's not that hard.

It's interesting how much communication is often a solution to almost all your problems. I like that. Speaking to the right people, right, and.

Then really listening to what they tell you. You know, put your preconceptions to the side, at least, at least temporarily.

As excellent advice. And I think it seems like a lot of your leadership stories about trying to unpick some kind of dilemma. So do you have any advice for how to go about doing this?

So the first rule of. Well, let me back up and say that the most common reason why I get involved with an organization or a leader or a board of directors is that they're stuck. They never say that. That is never the description they give me. They give me a contextual situation like, well, we have a new CEO and he or she isn't working out, but they're stuck. So the first rule is to realize that you're stuck. And the way you do that is you notice that you and your colleagues have been circling the same problem over and over and over. Might be dressed up in a different costume, but that's the first rule. And then the second is to look for cause. Now people that work in data are really, really familiar with this idea of root cause analysis. And that is true even when you're dealing with human beings. You want to find out what is the cause, but again, you want to proceed as non judgmentally as you possibly can because sometimes what you hear initially is wrong. So sometimes I'm brought in to help a particular executive who stuck and I hear about them from their boss and then I. And they say, well, what do we do? And I go, well, I need to meet them. And I go and meet with them and it's like, oh, the person that they described and the person I met, you know, these are not the same people. This is a very. And actually I learned this when I used to be a therapist, that in marriage therapy, the first person you speak to describes the other person and then you meet the other person and you go, huh? No. And this happens in business. People come to you and they go, Richie, blah, blah, blah, blah, blah, blah, you know, so to get yourself unstuck, you, you really have to know that you need to dial into a particular problem and get some information about what's going on. On. Did I answer your question? I sort of forgot your question along the way to my answer. Sorry about that.

It was generally about stories, a dilemma. Yeah. So I like the idea that if you are having the same arguments with your colleagues or the same discussions over and over again, that's a good indication that you're stuck and you might need to rethink. How about how you're going to solve your problem?

It's a huge clue not to be ignored. I've never had an executive say to me, I wish I had removed that person later. I wish I'd waited longer. That's a really profound example because, you know, firing people is hard. It's something that most people I work with do not like it at all. They feel bad about it, and sometimes that leads them to procrastinate and they get stuck.

And so related to this idea, it seems like a lot of the idea about making good decisions as a leader is about making wise choices. And in data, we've got this idea of the. It's called the Data, Information, Knowledge, Wisdom pyramid, where these sort of four levels that build up from just, oh, I've measured something to I can actually make a wise decision.

Yeah, I love it. It's true. I believe in it. Yeah.

So can you talk me through how you think about wisdom and making wise decisions?

Yes. I think wisdom requires perspective. And so wisdom often comes from having a history and experiences of looking at situations from different angles. This is why moving up the ladder in an organization is really beneficial. It helps us develop as professional human beings. You know, you're on a team and you're doing all this coding or data analysis and you think, you know, my boss doesn't get it. Right. They just don't get it. And sometimes you're right, sometimes they don't get it. Then you become a manager and you're managing other people. You see things from a different perspective and then you move up a little more and a little more. Now, not all very senior leaders are wise, but the ones we tend to admire and love are wise. I think an example of this is Frank Blake, who was the CEO of the Home Depot company, which is three miles that way from where I'm sitting. Years ago, when he was CEO, their data systems were hacked and the customer credit card information was compromised. That's a polite way of saying it was stolen. Right? Now, Frank is an attorney by profession and he's very smart. But he did so many things right after this happened. And these are wise things. Number one, he acted quickly, he didn't try to hide it, and he didn't call a crisis communications company. My apologies to all of them. And say, I need you to craft me a statement. And it comes out and it's like this mealy mouth pr, vanilla pudding stuff. Right? No, he said, we need to tell people that this happened. So he came out and said, we were hacked, it's our mistake, none of our customers will be harmed and we're going to fix it. Now, the next thing that some leaders might do. Let me ask you, Richie, what do you think a lot of CEOs in that situation would do with respect to their head of it?

Well, I think it's probably a reflex action to try and discipline the person. Yeah, the IT person, because they're in charge of the data security.

Right. So there's judgment, rapid punishment, metered out criticism. That person feels a lack of support. Frank Blake did the opposite. He put more resources into it. He said, I have confidence in this person and I think that we need to add resources. So they did that. I mean, that's a really, that's a very thoughtful, wise decision. That is a person who has control of themselves and did not do the autopilot reaction of coming on and going, well, you know, the, the CISO and the blah, blah, you know, they, they let us down. No, he said they're functioning in a context and we are going to take responsibility. He issued a public letter that was printed in the newspaper, a full page as I recall, and no excuses, none whatsoever. And financial journalists praised him for that and said, thank goodness we didn't get any of that mealy mouthed PR speak. That takes wisdom, it takes experience and it takes a lot of self regulation, which I think is part of wisdom. Knowing when to do this or when to do nothing or when to do the other thing. And it's imperfect. It's in, you know, there's no algorithm for wisdom that I'm aware of.

That does sound like a fantastic idea, having an algorithm for wisdom. If only the wisdom.

Yeah, let's get to work on that.

All right, super. So with that, do you have any final advice for data leaders?

I think my advice for data leaders is to remember what I said earlier about this process that human beings tend to do, which is we tend to think that our data is the thing itself. Alfred Korgybski said, a map is not the territory. And I think that's a brilliant statement. You can read about Rome, look at pictures of Rome, you can hear about the great pizza they have in Rome, but it's not the same as going to Rome. So the data can tell a data leader. This is, let's say you're reporting up to the chro. Oh, our employee engagement scores are declining and then the data leader leaves it at that. Wouldn't it be cool if the data person and the chro had a conversation about what other sorts of data might they collect? Because the chro, if they're any good, they're going to go out and try to find out more. They're going to collect qualitative data. Wouldn't it be good if actual data experts helped them with that? I think so. And. And I think it's a fabulously expanded way for people in data to have their perspective and their skills and their knowledge useful more broadly in organizations. Typically, it's this, you know, here's your data, ma', am, and the person says, thank you very much for the data, and then they decide what to do with it. When people who are expert in data collection and management and analysis and insight have a lot to say to people who aren't, that's what I would say. Be brave, share your insights, and don't make the mistake of thinking that the map is the territory.

Wonderful advice. All right, so thank you, Constance, for coming on the show. You enjoyed it?

Oh, you are so fun. It.