Paul Magnone: Good Decisions Require Data AND Instinct

Hey everyone, welcome back to Make It Happen Mondays, where we talk about sales, business, entrepreneurship, personal growth, mental health, and everything in between with guests who I truly respect and I think make a positive impact on the world around us. Today's conversation is with Paul Magnoni. Now, Paul is a Columbia Business School professor, the head of global alliances at Google, and co-author of the book, Decisions Over Decimals, Striking the Balance Between Intuition and Information, which is really what got my attention about Paul. Now, if you've listened to my podcast or watched any of my content, you've heard me talk a lot about the science versus the art of sales and how there needs to be a balance.

In this conversation, Paul and I talk about your gut instinct, which is the art, versus the data, which is the science, and how to make decisions more effectively. Because most people struggle to make decisions, and the reason for that is because decisions represent change in the status quo, and we as human beings are not wired for change. Throughout our conversation, we talk about some very specific tactics and approaches he uses to help people and teams make better decisions, and some of them include starting by agreeing on the problem first and foremost, and then applying some precision questioning techniques that he gets into, his iWIC knowledge matrix, which is based on the question, what is it that I wish I knew, which I thought was a really cool question to ask, his time risk trust matrix, and much more.

I hope you enjoy the conversation as much as I did, and find something that will help you make better decisions in your life and business moving forward. Let's make it happen. What's happening, make it happen, family? Big shout out to our partners today, Gong, Vidyard, and Chili Piper. Gong's data is more than valuable. It's cornerstone in any organization looking to collect the data that's going to tell them where they can improve and where they need to spend their time making changes. Vidyard makes it easy for people to use videos anywhere. No matter whether you're sending videos in email or on social media, posting them somewhere, or sending them in a DM, Vidyard has got you covered. Our friends at Chili Piper are so much fun to be around.

They make it easy for people to get on your calendar, and every sales rep has got to have this function locked in. It's one of the most important things we can do as a seller. How can I get you on my calendar easily? Chili Piper can make that happen for you. Be sure that you're checking out all these great tools, and now let's pass it over to John to find out who's joining him today. See you soon, everybody. All right, Paul, welcome to the podcast, my friend. How are you doing today? Doing okay. Thanks for having me, John. Yeah, thanks for coming in. I've been looking forward to this conversation after taking a little peek at your book and reading some of your background and also some of the cool things that you're working on here.

But for everybody else's enjoyment here, why don't you give the 30-second overview of where you're coming from, and we'll set the stage for this conversation today. Because I think the audience is going to be really intrigued about decision-making and the process around it and data intelligence and all these other things. But let's tell a story of how you got here. Sure. So how I, well, I guess there's two stories, how we got here and the core of the book. How we got here is I'd written a prior book with one of the co-authors of this book. And through the process after that book coming out, that one's called Drinking from the Fire Hose, we got connected to Oded Netzer, who is, at the time, was a professor at Columbia.

And we started to guest lecture. He is now the vice dean of research at Columbia Business School. And we have been teaching with him for seven years around decision-making. So we're, in addition to our day jobs at Google and Amex, respectively, myself and Chris, we've been teaching this material. And we finally said, you know, we should write this stuff down. And so we did. And I think it's pretty well-received. And what is this stuff? Well, it's about decision-making. What's fascinating is most people, well, it's kind of bipolar, right? Some people are pretty anxious about decision-making, and other people think they're fabulous decision-makers. And yet, if you say, how do you make a decision, it's usually a rock, paper, scissor, kind of chaotic word salad that comes through.

And we believe that there is structure to it. And the structure is a balance of a good, healthy dose of understanding the data, but also listen to your intuition and your inner voice, because a decision is also about human judgment. And so bringing those together is what we talk about. And I think that's what interests me about your background with this is, you know, I think you went to school to be an electrical engineer, and then, you know, you have an engineering, kind of an engineering background. And I talk a lot about the balance of art and science, right? About how science lays the foundation for the art form to be that much more effective. And so I think you have a need, I mean, you were at IBM for what, 20 years?

21 years at IBM, right out of engineering school. And my first client was AT&T and Bell Labs. And we, you learn pretty quick to be humbled by technical giants who, you know, the Bell Labs folks wanted to work with the IBM Labs folks. And yet you had to explain to them that this is how you construct a deal. Right? So I was, I felt very fortunate that at the time, I never thought of myself as a salesperson. As you pointed out, I went to engineering school. I'm a double E by training, electrical engineer by training, but managed to find my way to IBM right after school and went through IBM sales training. So for this, for your audience here, IBM sales training back in the day, to this day, still nothing better.

Yeah. And I've seen, you know, challenger selling and all these different techniques and so forth. And great. They're all wonderful. Sometimes they're just vocabulary changes, but you know, yeah, but ultimately terrific. And so there are three of us, as I mentioned before, and you have two that are engineers by training and one's a data scientist. And we wind up talking about intuition and which almost sounds bizarre, except what we're pointing out is bring that alongside the numbers. Don't ignore the numbers because we adore the numbers too. And I think that's, that's always been, you know, my challenge in a lot of ways, personally, I've always said that if you, if you ask like, what have I been blessed with personally?

A lot of it has to do with the fact that I don't overanalyze, right? I, intuition wise, I can come up and look at a situation with very few data points and usually make a very educated decision. And I don't belabor it. I don't overanalyze it and miss the opportunity. I'll take a swing and I might screw up, but for the most part, I'm usually all right. And on the flip side, cause I, my dad's a, he was an electrical engineer as well. I have the science side of me that I collect a lot of data. I know how to collect data. Like you read about, like I got spreadsheets for days, but then I kind of look at it and I'm like, ah, I don't know what to do with this crap. You know what I mean? Like I, and because data can lie in a lot of ways if it's not really collected the right way and all this other stuff.

So I would love to, you know, set the stage here to, to find that middle ground with you and, and a lot of the structure that you talk about in this book and some of the approaches that you use is that middle ground of balancing the two, right? Of not being a total gut because total gut's going to get you in a lot of trouble. And it has gotten me in a lot of trouble or so overanalyzed that you actually are paralyzed to make a decision. So, so how do you balance those two, the art and the science of decision-making and talk to us through some of the frameworks that you use to help people guide people through this? Sure. Um, terrific question. And so let's first take a quick step back and say, what is a decision?

And a decision really represents change. Right. And humans are not wired for change. Nope. And most are risk averse and they largely feel there's no roadmap. So they revert and retreat to what's comfortable for them. So the engineers in the audience will go to the numbers and the high flyers in the audience will go to gut instinct. And that's the problem right there, right? Because you actually are operating from a position of discomfort. So to eliminate the discomfort, you have to start off with a pretty simple framework. Now let's, let me give you an example of where that's normal. An operating room, right? You don't know what's, you're the doctor, the nurse, the staff there. You don't know what's coming through the door, but you are prepared.

You have a framework and a punch list to go through. You can go through other examples of fire departments, the military, even a football team. How does the quarterback, we're in the middle of football season as we're taping this today. The quarterback goes up to the offensive line and calls an audible with three seconds to go. Because the quarterback has a feel for what's going on and the team is prepared. When he calls an audible, they all move in motion in the right way because they're prepared and they have a framework. And you get into a boardroom or any standard business deal and there is no framework. So that's what we're talking about here. Establish a framework and really look at what some of the normal issues are.

And the first thing is, did you even frame the problem? And are you all in agreement on what the problem is that needs to be solved? So we start there and then we go through a kind of a three-phase approach talking about precision questioning, contextual analysis, and then synthesis of the information, which people are actually pretty terrible at synthesis. And they could be much better quite easily if they focus on it. And so those are frameworks that we can talk about in the next few minutes. But it is that kind of willing approach to make a conscious decision and not be swayed by momentum. That's the difference. Well, and I think that's a great point as far as not being swayed by momentum because, you know, a lot of like if we take it to sales reps, you know, like just because something worked, you know, randomly in a, you know, with your approach, whatever it was, whether email or call or, you know, negotiation tactic or whatever.

Whatever it is, doesn't exactly prove that that's the right thing to do. But because that is what worked for me in the past, I'm going to keep doing it. Even though, even if it only worked a couple of times, which I found very, very prevalent in our industry quite a bit. Right. Well, and frankly, a sales leader could come into a meeting and say, listen, you know, we've got to grow the business 50%. Okay. You just got anchored. Right. And everyone's like, oh, okay. Well, what are the steps we need to do to grow 50%? And you've got half the room who's thinking, we can't grow 50%. You've got maybe a few brave souls in the room who are saying, why are we going for just 50? Right. Right. As opposed to saying, listen, the business needs to grow.

And what do we think is possible with the resources at hand? And if we were to add resources, where can we take this thing? That should be the way that conversation goes, as opposed to, hey, I just need to hit a number because, I don't know, I picked a number. Well, and that's similar. Like, that's what they're, it's so lazy that I noticed a lot of sales leaders specifically, they'll talk about, oh, 3X pipeline. Well, we need 3X pipeline. Well, why do you need 3X pipeline? Well, because that's basically the industry standard, right? Or a three-month ramp for new hires. It's like, does it really take 3 months? Or does it really take 6 to 9 months to get somebody fully ramped and do their job, right?

Sure. But they use these lazy metrics that are out there in a general sense. And is that because of the, been there, done, like, hey, I'm trying to mirror what other people have been doing successfully. And so I just mirror that and I'm lazy to look at the numbers myself. Do you think that's the reason that a lot of us fall into the lazy? Yeah, I think people, I think you're exactly right. People go to norms. One of my favorite quotes is, for every complex problem, there is an answer that is simple, clear, and wrong. There you go. Right? Because, well, 3X. Okay, so 3X pipeline, that's kind of normal. Sometimes you hear 5X. But a 3X pipeline, that says nothing about what the close rate on a deal is.

That says nothing about what the profitability on a deal is. And that says nothing about the duration it takes to actually close a deal. So, you know, that's a happy metric. That's a, you know. That was the actual justification I got from a sales leader recently. He said, well, we've moved from a 3X pipeline to a 5X pipeline. And I said, okay, why? He goes, because deals are taking longer to close. And I was like, okay. I mean, I get the general consensus here of why you need more stuff in your pipeline if things are taking longer to close. I go, but have you looked at why those deals are taking longer to close? What types of deals are taking longer to close? Are there revenue and all these different things?

He didn't really have a lot of answers. He was just a very lazy. That's the thing. So, at that point, I would have the conversation going into one of the techniques of the book, right? One of the conversations is, well, what's the essential question? And people talk about first principles. And then they say, well, we need to know what the first principle is. What's that essential thing? And then they don't know how to get to it. So, use this simple question. I wish I knew. And if you just ask a group of people, what is it that you wish you knew about the close rate for the business? You hire smart people. Let them open up and use their brains. Describe what it is that is surprising them that they're noticing.

And the key word in there is wish because it gives permission for people to say what they really think as opposed to the anchoring example that I used before. And so, as you go through that, what is it I wish I knew? Well, I wish I knew why it takes long to close. I wish I knew if the close is dependent on, you know, people or process or a technology gap. I wish I knew, right? And it can go from there. So, you ask an open-ended question. And from there, you kind of gather the feedback across the organization, not just the leaders. I mean, everybody who touches customers should weigh in on that perspective. And then you funnel that back together. And after you spend even just a few hours doing that over the course of a couple of days, you might come out with, oh, well, the reason I can't sell this product to millennials is because I didn't define millennial tightly enough.

And it's, you know, maybe it has something to do with the pandemic and coming out of the pandemic. Maybe it has something to do with, you know, Gen X buyers are buying differently. And, hey, you can take that 3X pipeline up to 20X and that doesn't address those other issues. So, you need to have that open-ended conversation. And as you go through that IWIC, we call it IWIC, I wish I knew. As you go through that IWIC exercise and you zero in on, oh, these are the key questions that we really need answered, then you go get the data. Then go wallow in the spreadsheets. Absolutely. We love that. So, spend time interrogating the right data. So, you mentioned this, you know, everyone who touches a customer, like the anchoring of, hey, we need to grow 50% versus the collaboration of, you know, how do we get there type of scenario.

Where is that balance of leadership and employees when it comes to this, right? Because there's a certain point where, you know, executive or the market says, you know, from a VCs or whoever say, you guys have to grow 50% this year. So, now the senior, senior executive C-level leadership says, okay, well, that means we got to grow 50% through net new and we got to increase this by this. And then it trickles down to the directors and the managers of basically how do we have to get there. So, in healthy organizations, because we know there's plenty of unhealthy organizations. But how does this work from a, because what you're talking about is a lot of bottom up ability to understand, you know, the right questions to ask and how to get to where we want to go as opposed to putting an anchor down.

So, what's that balance between leadership dictating, we have to do this, and you guys have to figure out how we do this, versus we have to grow, let's figure out what we can do to grow as a group here. So, I have no problem, and the process that we're describing does not exclude a top-down mandate from leadership, right? But leadership themselves, did they go through that exercise and say, I wish I knew how I can move this product with a millennial cohort of customers as we're coming out of pandemic mode and the great resignation is happening. So, it's healthy to get the views from across the organization. But even if the leaders, you talk about your top staff, if you're honest with yourselves and you have the open conversation, you may say, well, yeah, millennials sounds great, but what I really want is Henry millennials.

Do you know Henry? So, Henry millennials, high earning, not rich yet. Okay, nice. So, it's actually, you can look it up out there. I was going to say Google. You can Google it. So, there's about 20 million in the workforce. There's about 20 million Henry millennials versus 70 million overall millennials. Oh, okay. What are the characteristics of a Henry millennial? They do a lot of digital browsing. They really value customer service because they want white glove service. And they have expectations about delivery and different expectations about delivery now, especially, you know, still wrapping up the pandemic. Okay, well, I'm going to go after that cluster differently than I'm going to go after a general cluster.

And if the top of the business says that, then they might say, well, how does customer support address that? How does, you know, all the other disciplines within the organization address that? So, this is not, we're not suggesting that everything needs to be ground up. It could be the top tier of the organization that's doing this. The fact is people aren't having the thoughtful conversation. What's up, everybody? I know you're enjoying this conversation. John does a great job with genuine curiosity on these episodes, and our guests consistently bring the heat. We want to take a moment here and let you know that you've got an opportunity, an opportunity to become better than you were yesterday.

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That URL, one more time, is joinjbsales.com. Let's get back to the show with JB and our guests for this week. So how does this align and is that you talk about precision questioning and there's also, you know, you talk about in negotiations, asking powerful questions. Is this all in the same vein? And could you kind of unpack a little bit about the precision questioning and in a negotiations format? Because we're always in a negotiations, whether it's internal, external, how to ask better questions there. So, you know, it's interesting what you learn in your youth or what you relearn when you have kids that you can relabel as precision questioning. The fact is, there's not a lot of tolerance for half questions, like if you have kids, right?

Well, why is that? Well, you give an answer. It's not a complete answer. But why? But why? You start digging a little deeper and a little deeper until you get to the most atomic level of, oh, I'm really looking, you know, getting back to that Henry. I'm really looking for this very specific group. And you only do that by getting more specific, kind of one question, one answer, filtering further down and further down. That's very different than, or narrowing further down, I should say. That's very different than divergent questions, right? So, you may say, if a leader says, listen, we're going to go after this segment, divergent questions. So, an example, why are we talking about this now? If it's a go and a no-go, why this moment?

What are your assumptions about that cohort that you think we want to sell to? How do we know it to be true that we have brand permission to go sell into that group, right? What could be done and what should be done? So, that's kind of an action question of how do we get to them? Hey, maybe we don't have a marketing campaign to even get to them. You know, you can get into cause and effect kind of questions. So, there's a whole host of divergent questions that start to put some shape into a generic, hey, I want to go after millennials, or I want to go after, maybe I want to go after retirees. Okay, define retiree. Why do we want to go after that, right? I want to go after high-growth B2B, right?

I want to go after a high-growth industry and become a supplier to them of my products. Great. Why? Why do we think we have permission to do that? Do we have access to them? Why are we talking about this now in November? Is this the right time to launch, right? So, these are kind of straightforward questions, but people go back to the boss came in and said, we're going to go do this, and they start solving the problem. Because they think, well, the problem's been thought out. This is, you know, the old joke of, I'm going to go and get the requirements. You start coding. I'll be right back and tell you what we're actually building. Yeah. Well, so how do you deal with that as a young employee, for instance, right?

You know, because part of that, and let's go with the football. You brought it up, right? Here's the conundrum that I'm sitting here in Boston as a New England Patriots fan, all right? You got Bill Belichick, who has been there, done that for however many damn years he's done it, and he's got six rings to prove his success, okay? You got Mac Jones, who comes into the league as a rookie, right? First-year rookie, top 13 in the draft. After his first year, they start rearranging the offensive. You know, they bring in a new offensive coordinator. They change the offense completely, and he starts asking questions. Why? Why are we doing this? It doesn't make sense. You know, this is not how. I was on one track.

Now we're doing it differently, and I don't understand it. Part of me says, shut your pie hole. You're a second-year rookie here, and you got somebody like Bill Belichick telling you what to do. Don't question his, quote-unquote, authority. The other part of me says he's talented enough to – he should be involved in the conversation and should be kind of curious about why. But where's that balance kind of – when you earn the right to ask why, and if it's inherent that you always have the right to ask why, how do you do it with somebody who is not as experienced as the person who's telling you how to do it? Yeah, that's a great question, and I think you nailed it up front when you said talent.

So this presumes that you've hired what you perceive to be the right talent. And if you've hired talent and you're not going to listen to them or put them to work the right way, then shame on you because you're wasting company resources. But there is very much a respectful way on both sides of that conversation. And if the coach or the business leader says, listen, this is what I asked you for. This is what you got to give me. This is what I want this meeting to be about, or this is what I want to see on the field, or, you know, what have you, right? There's still a way to say, here's the synthesis of what you asked for. Let me give it to you right up front. I've got all the backing details, and I also want to point out to you something that's surprised me about this.

It may be an outlier, but because I'm a thoughtful employee, because you hired me for that, I think we should take five minutes to talk about this, right? Now, I'm not a Patriots fan. Not many are, so don't worry. But I'd imagine there's a moment in the locker room or in the weeklies where the conversation happens. Hey, I've noticed that when we're in this configuration, because of the way our talent is or whatever, we may be able to exploit the following, which maybe you see or you don't see on tape when you're not on the field. And that's why I think, and this gets back to the conversation about data, right? So example on my end, you know, as a young VP of sales for my first startup, our CFO was the smartest kid.

I mean, I grew up with him in high school. He's literally one of the smartest people I've ever come across. And it was funny. He's not a sales guy in any way, shape, or form, right? And he would tell me every year, we have to grow 50%. And the first year when we were doing, I don't know, a half a million dollars of revenue, the next year, 50% growth was pretty easy, right? But after the fifth or sixth year, I'm like, Jesus, Calvin, you know, I can't do this. Like, what other resources are you going to give me? And he'd be like, because we were self-funded, like, go do it. I'm like, Calvin, there's only so much harder I can work here. So what I spent an entire year doing was this was literally analyzing every piece and tracking every piece of data I could, whether it was like where the leads were coming from, how long the meetings, what second meeting and all this other stuff.

So at the end of the year, I had this beautiful spreadsheet and it was a calculator, effectively, that said, okay, when he told me I got to grow 50% this year, I'd put it in. I'd be like, okay, Calvin, that means we need two more inside sales reps. We need another 50,000 in spend on marketing and we need this. And he'd be like, well, we don't have the money to do that. And then I'd show him the data and I'd say, Calvin, well, then I don't, I can't hit your numbers if we can't have those resources. And it became a very logical, he stopped arguing with me because what I was doing was I was arguing off of emotion early on. I was a very like feeling oriented. I can't do this. And he was a pure logic person saying, I don't believe you do it right until I could learn how to speak his language of data.

He wouldn't listen to me, but then he started to listen to me and I actually didn't have to rely on the data as much. So again, going back to the balance of decision making, you know, how much of it is on the person who is being told what to do to be able to analyze and track some data and intelligence to be able to produce kind of like, yeah, but like I did it your way. And this is what happens versus if I did it this way, this is what happens. Right. Well, it's on both sides, right? It's the, it, it's incumbent upon the person doing the work to speak up and say what they think. And it's incumbent upon the leader to make the time for that conversation. And if you find that that's not happening, maybe that's not the organization you want to be in long term.

But at the end of the day, I mean, something that's not in the book, but I learned a long time ago, back in my IBM days, sales is an engine. And you could build a, you know, a methodical engine, you could build a hot rod, but ultimately you should be able to figure out as you did in that example, that if I put this amount of fuel in to the engine that we collectively designed, this is the output that I'm going to get. And then if I want more output, is it more fuel or do I change the carburetor? Do I add more pistons? Do I add, you know, what, what is it that I changed? Because it's a well understood model end to end. So that really matters. The other thing that's kind of worth talking about is how a decision actually comes together.

And we describe a model of time, risk, and trust. And if you look at any decision, you can map it in those three dimensions. So is there no time or is there a lot of time? Is there no time and it's low risk versus high risk? Well, if there's no time and it's low risk, well, you know, have the salad. We don't have a salad. Have a sandwich. Great. It's no big deal. Low, no time, low risk. Can I borrow your person for an hour? Yeah. Oh, how about a day? Yeah. How about two days? Hold on. That looked like it was low risk and not a lot of time. It's a quick decision. But now you're draining the organization in a way I didn't expect. So got to pay attention to that. So low risk, high risk. Right. And so the third dimension then is trust.

So if you're looking and saying this is a low risk, no time decision, you should be able to churn through those quickly. If it is a high risk decision with an enormous amount of time, suddenly you're in analysis paralysis. You're in committee mode. You're parliament. You're the U.S. government. You're in a boardroom. And so boardrooms want to move quickly. And what tends to happen with leaders is they look at that third dimension of trust. Do I trust the data that was presented to me? Do I trust the person that gave me that data? And do I trust the organization that backs up that person? Right. And so, you know, your leader says, I want you to grow another 50% year on year. Okay. Look at those three dimensions and say, is this reasonable?

Can we do this? Let me back it up. Let me put it in context for you. So let's talk about that trust of data, right? Because I completely agree. The problem is I think data, and you talk about this without context, is hard to trust. Because you could take the exact set of data and come to two very different and use it to create two very different conclusions, right? I mean, you see it all the time these days as far as, you know, death rates of this and whatever it is. It's like you see the data and you're like, holy shit. But then you hear some context around that data and you're like, oh, wait a minute. It's not that. It's in this section of this massive audience that that's the problem versus that's the problem.

So let's macro this out a minute here. How do you trust any of the data that's right? You know, is it trust but verify? Is it trust but context? Like, how do you look at data right now and trust that it's an accurate representation of what you're trying to understand? Yeah, absolutely. It's a critical question. Great question. You could torture data into telling you anything. Anything. So data will, you know, tell you that it committed whatever felony you wanted to tell you it committed if you torture it enough. So the way to get past that is what you said, context, right? So think about sales. We sold 12 shovels. It's incredible. We sold 12 shovels this month. You know what? Let's all high five and grab a beverage.

Why? Well, we sold 12 shovels in August. Okay. Let's look at the context. Freak snowstorm, which is not going to happen again. So are you going to change your business model to say, hey, every summer we have to stock shovels? No. Obviously, this is an absurd example. By the way, your competitor down the street sold 20 shovels while you sold 12. Are you still celebrating? Let's say you're a little victory dance because you're actually behind when you thought you were ahead. And so it is that context, taking an absolute view of the number, looking at it in comparison to something else. And then if you can, take a look longitudinally, like over a time horizon that says, is this right or not? Does this feel right or not?

And it's interesting. There's all this, as you said, there's all this data that comes at you. I tend to want to validate on my own what I see. And it's easy to see something on a slide. First thing to look at is, what's the scale of the slide? Does the scale make sense? Are they, is whoever's presenting it masking something, putting too much of a rosy picture on it? What is the context in there? So it still comes down to that context and then pulling that information together. Are there kind of standard questions or things that you think of asking about the data? That, that are somewhat universal in, in making sure the context is there or is it situational based, based on what they're trying to prep?

Well, a couple of, a couple of basic things is what data was collected? What data am I not seeing? Again, can I trust the data that I am seeing? Can I trust the person? And then if you're not great at numbers, which a lot of people say they're not great at numbers, do these numbers that the data represents, do they map to some sort of performance indicator that I would expect, right? And so you start to pressure test it when you even look at comparables, even if you're not doing the, you know, running the spreadsheet to calculate out profitability, you might look and say, yeah, this doesn't seem right to me because there's no way that this amount of product would generate this amount of profitability, or there's no way that this amount of product was sold in that amount of time because I know the business.

This gets to the intuition side. It's interesting if you, if you talk to VCs, right? They bet on the person, not the company, right? And top leaders in the fortune, fortune, whatever, fortune 500, fortune 1000, the best leaders, they may or may not say this, but people will point out they have a feel for the business, right? So what number is that represented in? It's not. It is, it is, you know, those leaders are able to balance both sides. They have a feel for the business. They understand the people. They understand, you know, they have a good sense of what makes sense for the business. And they correlate that with the data and they're asking the smart questions. As we like to say, the smartest person in the room is not the person that's got the answer.

It's the person that asks the next insightful question. Right question. Yeah. And I think that's, you know, the, going back to the sports analogy, you know, saber metrics or whatever, right? With, you know, the analogy of, of science and art of, you know, Billy Bean and trying to over science and over engineer the A's to win a world series. And he got really far with the sciencing out of all these pieces and putting them together, but he never got to that ultimate win. Right. Whereas right afterwards, he turned, you know, the, the Red Sox again, all the talent, all the talent that did the saber metrics went to the Red Sox. Right. And then they added, and they added all these dirt dogs, right?

Who are all these weird pieces, but then they got David Ortiz and Manny Ramirez and David Ortiz and Manny Ramirez cannot be explained on a spreadsheet, specifically David Ortiz. Clutch is not something that is in saber metrics. They discount that all the, but there's a, but there's just something about David Ortiz when he steps up to the plate in the bottom of the ninth inning with a three, two count, and they're down by two runs and he's got two people on base that he's going to hit that fucking ball. I don't care what your numbers say. And so there's, and that's what got us to win the world series and all that other stuff. So that it's almost like if it, from your perspective, I'd love to just get a gut check on you on, and I know this is a very broad one, but if you were to cut down the percentage of science art, when it comes to decision-making, understanding that science should be the foundation of it.

What do you think that balance should be? Do you think it should be more science than art or should it be an equal balance or is it dependent on the scenario? I think it's an equal balance. I really do. And, you know, we're going to be friends, so we don't have to argue about baseball, but I could bring up the example of the Yankees, right? And I have relatives who are Red Sox fans who tell me that Jeter is the worst player ever. What? Right? They're idiots then. I'm sorry. I'm not a Yankee fan, but if you're telling me that Jeter is the worst player ever, you're a moron. I asked a simple question. I said, if in the period of time that Jeter played baseball, you could have had him as the Red Sox starting shortstop, and you probably had about 18 different shortstops during that period.

Would you see him? No, he doesn't have range. He doesn't have this. He doesn't have that. I'm like, oh, okay. So you're going by, one, your bias, which, no, that never happens at work, right? So going by your bias and going by some numbers, which you think reinforce your bias. And so you're going to fail as a general manager if you did that. Yeah. Because to your point, how do you find the clutch nature of a Jeter, of a Pappy, of like, you know, these different folks? Yeah. You have to look at both sides. And so it tends to, I think it tends to be very balanced. I don't know that it's going to be 50-50. It's almost like, you know, marriage. Some days it's 60-40. Some days it's 40-60. You're backing each other up, right?

So. Yeah. Yeah. I just, it's funny because I always work on that balance. And I, you know, I try to, you know, articulate to sales reps that, you know, there is a big feel about sales. There's no question about it, about who you're talking to and the flow and all these other stuff. But if you don't have a foundation, if you can't back up your feeling with some type of data that is objective to that feeling, right? You're going to miss more than you're going to hit. Well, and if you're in sales, somewhere along the line, you're going to draw out a relationship map. Right. And the relationship map does not come down to numbers. It comes down to personalities, who supports what, whether they're risk averse or not.

And that's part of the decision process. Right. So your relationship map in sales is part of that intuitive side. You're using your left brain and your right brain. Imagine that. Shocker, right? Good luck trying to get them both to work at the same time. Paul, any other kind of big highlights, either from the book or your research that we should dive into briefly here before we wrap things up? Well, I think two quick things. I can't stress enough. Please synthesize. How many meetings are you in where people just told you everything you already know and didn't draw some conclusion or correlation or bring the information together? So even your youngest talent, your freshest, newest talent, they have an ability to do that.

And most often, they think they don't have permission to do that. So this goes back to ask them, what surprised you? What is the synthesis of what you're seeing? And don't go through a 50-slide deck. The meeting starts. Somebody's presenting you. They want to present you sales numbers. They want to present you market projections or whatever. Close everything and say, just talk to me. What is it that you've done the analysis? And we will go through it in the back half of this meeting. Trust me. You'll look at every slide. But just say in English or whatever your language is, say, what is it that you really have a sense of right now? Bring that forward and say what you think. Let's have a conversation about that.

What is surprising in the data that you just saw? What is the thing that you think, oh, that is perhaps the linchpin. That is something that I can't explain that we should spend some more time on. So that person had to do some synthesis to do that. And then, yeah, back it up with data. Always back it up with the data. But have that open conversation. And the reason I circled back to that is because as individual contributors, you should be brave enough to do that. And if you have a difficult boss, you should be able to find a way to say, look, with respect, I just want to take two minutes to point this out. If you are the boss, you should make space for that, either at the beginning or at the end of meetings or sessions or whatever.

Say, so what else are we not thinking about? What else do you want to point out? And other than that, if you're not doing that, then it's all robotic, which is not healthy. It's not enjoyable either. Yeah. And the other thing from our research, we've asked thousands of business leaders where they see the gaps in decision making. Is it the analysis? Is it the execution? And it's right up front in framing the problem. So, you know, we talked at the beginning of this about, you know, I wish I knew what are the first principles? What is the what is the main problem that I'm solving? If you're starting there with with a thoughtful approach, that's the best thing you can do. And I always remember, this is not a moon launch.

It's sailing. You're going to be able to tack and course correct. So you'll be able to move forward if you if you take that approach. Yeah, we look at everything here, especially after COVID hit. Going back to that agile framework, we, you know, we move to everything here at Sell Better by JV Sales is a it's an experiment, right? So there's no more strategy as far as long term strategies. Let's implement this and let's go. Literally, everything is an experiment. And some experiments are longer. Some of the experiments are shorter, but they all have a hypothesis. They all have metrics that we're using to measure whether they're good or bad. And we fail as fast as we possibly can. So as soon as the data is telling us we fail, we adjust, move on and come up with another hypothesis, another experiment.

And that works. And that's great. And that works, especially if you understand the DNA of your business. Like, what is the essence of what you do? Yeah. Right. I mean, you know, back in the day, again, it was years ago, but back in the day at IBM, well, we could do anything. We could put a man on the moon. We could repave the United States. Yeah, but why? Well, is that the essence of what you are? Right. So stick to your core and your fundamentals. I mean, you could branch off into something. But again, that's an active business choice. Awesome. Well, Paul, and it's Magnoni, right? Did I say that right? That's correct. You nailed it. Magnoni. Let me spell that for people who listen. It's P-A-U-L-M-A-G-N-O-N-E.

You can find them on LinkedIn, but Paul, tell people where they can find out more about the book, more about what you're doing, and where you want to point people. Right. So this fine book right here, Decisions Over Decimals, Striking the Balance Between Intuition and Information, for those of you that are seeing the video here, co-authored with Christopher Frank and Oded Netzer, is available hopefully at your local indie bookstore, because we're big fans of that. But you can find it at distributors everywhere, including the big guys, of course. And you can find out some more information about it at dodthebook.com. So D-O-D for Decisions Over Decimals, dodthebook.com. And should you wish to immerse yourself in this a little bit more, all three of us are faculty, as I said before, at Columbia Business School, Columbia University.

Oded is the Vice Dean of Research, and we teach two courses there, one in the Executive MBA program and one in Exec Ed, which anyone can sign up for. And come visit us and take the course. That course is entitled Leading in a Data-Driven World. Very cool. Well, Paul, I really appreciate the conversation. I appreciate you coming on board here. It was a really interesting conversation. Thanks for the time. I appreciate it. Absolutely. And everybody out there, hopefully you enjoyed the conversation as much as I did. Got a few things that made you think a little bit differently, maybe try a different approach here or there. And as I always say, go out there and make somebody smile today, because no matter how bad your day went or you think it's going, if you make somebody smile today, you know you had a good day and the world needs a lot more of that right now.

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