Decision Vision Episode 74: How Can I Improve My Business Decision Making Skills? – An Interview with Tyler Ludlow, Decision Skills Institute
Decision making skills are vital for any successful business owner. In this edition of “Decision Vision,” decision scientist Tyler Ludlow joins host Mike Blake to discuss the process for making good decisions and much more. “Decision Vision” is presented by Brady Ware & Company.
Decision Skills Institute
The Institute helps people that might otherwise might be overwhelmed by complexity, stress, or worry, to overcome them and take action. We took 50 years of cutting-edge research, applied for decades at the world’s most successful companies, and created a framework that empowers individuals to consistently make better decisions, leading to better results, faster. We are the Robin Hoods of Decision Science!
Tyler Ludlow, Founder and Chief Decision Scientist, Decision Skills Institute
As a decision scientist, Tyler Ludlow helps people everywhere turn decision burdens into opportunities for growth.
He began his Decision Science career at Unilever, part of the team that won the 2008 DAS Practice Award for embedding DA into organizational decision making. Two years later Chevron won the same award prior to receiving the first Raiffa-Howard Award for Organizational Decision Quality in 2014. Meanwhile, Tyler joined Lilly in 2012 and was a part of the team that received the Raiffa-Howard Award in 2016.
At Lilly he facilitated large, complex, and strategic decisions, such as a $750M clinical trial investment and corporate change initiatives that structurally changed the business. Tyler has trained over a thousand business leaders and managers in basic and advanced decision science applications, always with a practice-oriented, how-can-I-actually-use-this-stuff mindset. He is now the owner at Decision Science Advisory, a company focused on establishing and strengthening decision expertise groups in the pharmaceutical industry.
After a decade of helping senior leaders and organizations make large, complex, and strategic decisions, he turned his focus to individual and personal contexts. He established and led Lilly’s efforts to support and enable better decision making between patients and their healthcare providers, including creating the Shared Decision Making Summit, an event that brings together stakeholders from across healthcare (patients, caregivers, advocates, providers, researchers, pharma companies, regulators, etc) to identify practical ways to collectively change and improve healthcare decision making. He founded the Decision Skills Institute to make cutting-edge decision science accessible to everyone. It’s mission is to make the world more deciderate by impacting 10 million decisions in 10 years.
At home, he with his wife try to apply decision science in one of the most difficult contexts – in parenting their ten children.
Michael Blake, Brady Ware & Company
Michael Blake is Host of the “Decision Vision” podcast series and a Director of Brady Ware & Company. Mike specializes in the valuation of intellectual property-driven firms, such as software firms, aerospace firms and professional services firms, most frequently in the capacity as a transaction advisor, helping clients obtain great outcomes from complex transaction opportunities. He is also a specialist in the appraisal of intellectual properties as stand-alone assets, such as software, trade secrets, and patents.
Mike has been a full-time business appraiser for 13 years with public accounting firms, boutique business appraisal firms, and an owner of his own firm. Prior to that, he spent 8 years in venture capital and investment banking, including transactions in the U.S., Israel, Russia, Ukraine, and Belarus.
Brady Ware & Company
Brady Ware & Company is a regional full-service accounting and advisory firm which helps businesses and entrepreneurs make visions a reality. Brady Ware services clients nationally from its offices in Alpharetta, GA; Columbus and Dayton, OH; and Richmond, IN. The firm is growth minded, committed to the regions in which they operate, and most importantly, they make significant investments in their people and service offerings to meet the changing financial needs of those they are privileged to serve. The firm is dedicated to providing results that make a difference for its clients.
Decision Vision Podcast Series
“Decision Vision” is a podcast covering topics and issues facing small business owners and connecting them with solutions from leading experts. This series is presented by Brady Ware & Company. If you are a decision maker for a small business, we’d love to hear from you. Contact us at email@example.com and make sure to listen to every Thursday to the “Decision Vision” podcast.
Visit Brady Ware & Company on social media:
Intro: [00:00:01] Welcome to Decision Vision, a podcast series focusing on critical business decisions. Brought to you by Brady Ware & Company. Brady Ware is a regional full-service accounting and advisory firm that helps businesses and entrepreneurs make visions a reality.
Mike Blake: [00:00:21] And welcome to Decision Vision, a podcast giving you, the listener, clear vision to make great decisions. In each episode, we discuss the process of decision making on a different topic from the business owner’s or executive’s perspective. We aren’t necessarily telling you what to do, but we can put you in a position to make an informed decision on your own and understand when you might need help along the way.
Mike Blake: [00:00:41] My name is Mike Blake and I’m your host for today’s program. I’m a director at Brady Ware & Company, a full-service accounting firm based in Dayton, Ohio, with offices in Dayton, Columbus, Ohio, Richmond, Indiana, and Alpharetta, Georgia. Brady Ware is sponsoring this podcast, which is being recorded in Atlanta for social distancing protocols. If you like this podcast, please subscribe on your favorite podcast aggregator. And please consider leaving a review of the podcast as well.
Mike Blake: [00:01:09] So today’s topic is a little bit of a meta topic. And by meta, what I mean is that, this podcast is called Decision Vision. And for the most part, the topics have involved exploring the process of making a decision on a particular topic. We’ve gotten more granular and topical from time to time because events warranted it, or I just thought it was interesting, or, quite frankly, because the conversation needed to be more tactical, particularly during the onset of the coronavirus pandemic. But today we’re going to kind of go out in a different direction and explore the process of making good decisions.
Mike Blake: [00:01:58] And I think we’re going to do a series of these over time that explore different facets of making a good decision generally. And how to develop a good decision-making skill set. And I was kind of inspired by this, of all things a MasterClass video. And if you spend any time on YouTube, for some reason, your MasterClass will throw up a commercial on YouTube. And by the way, those things are fantastic. I watch the commercials – just the commercials. They are so good.
Mike Blake: [00:02:36] But anyway, they had this thing by Garry Kasparov, who is a world chess champion and a dominant player for a very long time. And he has a MasterClass on chess playing. And I used to play chess competitively. I don’t anymore. I’m too old and I do other things now. But one of the things that he said about the value of the game of chess, I thought it was so insightful. And for all the games I played and all that I’ve studied about the game, I never really understood this. It’s that the game of chess makes you a better decision maker. Because the game of chess is about making decisions. It is a process of making decisions and thinking ahead. And not just thinking ahead, but also having to decide, you know, “Do I move this piece here? This piece there? Do I capture this piece? Don’t I not capture this piece?” And every move is a decision. And I thought, “Wow. That’s really neat and profound.” I didn’t waste all that time in college and high school playing chess.
Mike Blake: [00:03:42] And so, a few weeks ago, I ran into this fellow – rather he was introduced to me by Brian Falony, who’s our marketing director here at Brady Ware. And he’s a specialist on making decisions. And a specialist on making a decision in one particular facet that I find excruciatingly interesting. And I know that’s a strange turn of phrase. But it really is that. And that is, the use of data in making decisions. And, you know, data is all now. It really has been for about ten years or so. Everybody is listening to this podcast or at least 98 percent of you, I’m sure, have heard the term big data. Most of you probably has a pretty good idea as to what it means, has a handle on it.
Mike Blake: [00:04:42] But what do you do with that? Right? And is big data for me? I happen to be a numbers geek. I do numbers for a living. So, I have some training in data analytics. But a lot of people don’t. And data analytics was really not taught in business school any meaningful way until about 10, 15 years ago, with the exception of some very specialized programs, for example, at Georgia Tech.
Mike Blake: [00:05:10] And on top of that – and this will probably be another topic that I’d do at some point – but for those who know me or listen to the podcast, you know, I do a lot of work with startups. And I can’t tell you how many times somebody pitches me a deal and they say, “Our business model is data. And we’re going to sell that data to folks that want to use that data.” But then you sort of get into it, “Well, how do you do that?” Or, “What’s the data worth?” Or, “What’s the business that even sell data?” And very quickly that conversation goes from smooth sailing to running a ground in about 19 icebergs and a rocky shore. Because data is so – oddly enough, data for something that is designed to be very specific. Once you really sort of get down to brass tacks, you try to convert the — into useful, actionable business strategy. It’s not all that easy to do.
Mike Blake: [00:06:10] And so, helping us with that is my new friend, Tyler Ludlow, who is Founder and Chief Decision Scientist of Decision Skills Institute. After earning a Degree in Applied Mathematics and an MBA, Tyler studied Decision Science at Stanford University. He then mastered its application at Global 500 companies leading decisions for $750 million investment, a global product launch, and more. Tyler has worked with top universities such as Stanford, Yale, and Dartmouth, as well as 18 of the top 20 pharmaceutical companies.
Mike Blake: [00:06:45] After a decade in those contexts, Tyler decided to pull a Robin Hood at decision science and founded the Decisions Skills Institute to bring it to people everywhere. He helps people like you turn your decision burdens into opportunities for growth. Tyler’s best decisions were marrying his wife and having their ten children. That’s not a typo. I may have to go into that as well. Talk about a recidivist. Together they enjoy the outdoors. I’ll bet you do this. No space for anybody. Hiking, backpacking, rafting, ice climbing, etc. Tyler, thanks so much for coming on the program and welcome.
Tyler Ludlow: [00:07:21] Hey, thank you. I’m glad to be here.
Mike Blake: [00:07:24] Ten children?
Tyler Ludlow: [00:07:27] Yes. And actually, I had to recently update that description. A couple months ago, it used to be nine but we have a little two-month-old.
Mike Blake: [00:07:34] Well, congratulations. Are you guys like The Partridge Family and you just drive around in an old school bus or what?
Tyler Ludlow: [00:07:42] We haven’t owned a regular vehicle in a long time, that’s for sure. Yeah. No. But we love it. We love it. They’re great kids. They’re awesome. It’s a lot of fun. It’s a party.
Mike Blake: [00:07:54] I mean, do all ten still live at home? I mean, some must be out of the house by now.
Tyler Ludlow: [00:07:59] Our oldest is 21 and he has an interesting life that kid. His senior year of high school, he did a computer full-time programming bootcamp, three=month program thing. So, he’s had a full=time professional career job as a developer at Geico for two years now. And is looking to buy his first house shortly. So, he’ll be moving out. And then our 19-year-old will be moving out shortly. But we go down every two years or so down to – well, down to our newest. So, we still have a full house at the moment.
Mike Blake: [00:08:39] Well, that’s neat. And you now hold the official Decision Vision podcast record for most children. The previous record holder was Tom Brooks, who came on, I think, somewhere in the thirties for this show. And he has eight. And I thought that record was a stand, frankly, for a lot longer than it did. So, congratulations. I know that this acknowledgement makes the whole thing worthwhile, I’m sure.
Tyler Ludlow: [00:09:05] Absolutely. Absolutely.
Mike Blake: [00:09:08] Wow. Okay. Well, that could be a separate podcast. But I did promise our audience we would talk about big data decisions, so we will transfer back to that. So, Tyler, let’s start off. What makes for a good decision? How do you know if a decision that you made is a good decision?
Tyler Ludlow: [00:09:33] That’s a great question. You know, actually, that exact question many times when I speak at an event or do a workshop, I will start with that question prompt. And use a Q&A response and then I can record everyone’s ideas. And what I find when most people answer that question, the most common theme is that I got what I wanted. They got good results. It’s something about the outcomes.
Tyler Ludlow: [00:10:02] I think it’s interesting in the corporate settings where a lot of decisions are made by committee or by group. The number two thing that I see come up is, everyone agrees on it. Everyone’s on board or something like that, which I think most of us could envision we can make a good decision. And sometimes the best decision, everyone doesn’t agree with. And as well as you can make a good decision and have bad results and have a bad outcome.
Tyler Ludlow: [00:10:33] I can also talk about kids and what not. I mean, I can’t remember the number of times where I didn’t study for a test. Which I think normally will be considered a bad decision. And still ended up getting a good or decent grade on. so that’s a good outcome. So, the key to me in answering this question is, first, being able to decouple or detangle decisions and their results or their outcomes. And to realize that we’re talking about what makes a good decision. It’s, we want to focus in on making good decisions regardless of the outcomes. Recognizing that better outcomes happen more frequently when we make good decisions.
Mike Blake: [00:11:18] And I want to spend a little bit of time on that point, because you can, in fact, have a good outcome from a bad decision, can’t you?
Tyler Ludlow: [00:11:30] Oh, yeah, yeah.
Mike Blake: [00:11:30] Right. Well, let’s-
Tyler Ludlow: [00:11:30] People notice all the time.
Mike Blake: [00:11:33] Well, they do. But take an extreme example. Let say that, a person decided that for whatever reason, they would start using drugs. And in the course of using drugs, they met another user that led to a fantastic professional opportunity. And it made them very wealthy. It made them very successful. And maybe that even led to a scenario in which they went into rehab and got off the drugs. But you’d never tell somebody to go start using drugs because that’s the path to success.
Tyler Ludlow: [00:12:12] Right. Right.
Mike Blake: [00:12:12] And I think one of the things that makes the – one of the things that makes a decision good versus bad is separating kind of process from luck. When you make a decision, the goal, I think, is to control as much of the outcome as possible. Because you control how much you just sort of stacked the deck in your favor as opposed to whether or not there is actually a good outcome.
Tyler Ludlow: [00:12:42] Yeah. There’s a lot about – I love the way you kind of separate out process. There’s the process that you use to make the decision. And then there’s sort of the moment that you decide. And then there’s all the other implementations, so to speak, putting it into action that happens down the road. And we can do all sorts of things to influence the outcome or mitigate certain risks or whatnot that help better results to show it more frequently. Usually we can’t guarantee it. That’s what makes life so interesting and exciting and fun. I mean, that’s what makes it all that variety. It also is what brings us all the stress and the worry so much about these things in the future.
Tyler Ludlow: [00:13:21] But, yeah, we do what we can at the moment that we make the decision. Then, we do our best, again, to stick to it, implement, adjust all those things afterwards. But it’s not the actual outcome itself that should be our measuring stick for whether we made a good choice or not.
Mike Blake: [00:13:37] Now, could the definition be modified, maybe if you have a process that’s leading to lots of good outcomes? Maybe that’s a way to kind of think about it, is if you have a good decision process, over time you should have better outcomes than the person that has the poorer decision process. And then that gets into basic statistical analysis that, over time as your sample size gets greater, your expected outcomes should start to match your actual outcomes from your sample size.
Tyler Ludlow: [00:14:15] Yes. Absolutely. On the nose. I tend to use the phrasing of better outcomes more frequently. You’re never guaranteed on one to be better off. But you’re right, as you make more overtime, you should be better off. Yes, absolutely.
Mike Blake: [00:14:28] So, you’re approaching decision making from a data perspective, which I love. I wish people that did what I do for a living would approach things from a more rigorous data perspective as well. But again, that’s another podcast. You know, everything is about big data and artificial intelligence now. And we sort of have this healthy sprinkling of block chain as well somewhere in there. Why aren’t we just turning everything over to robots, some websites, at this point to make our decisions?
Tyler Ludlow: [00:15:05] That’s a good question, because we probably should be turning more – we’re learning that we can be turning more and more over. So, why do we not just turn it all over? I think there’s a few reasons. One, for example, just last week, I attended a virtual conference. And it was on decision making. And at that conference, there was a session on the merging or the integration of data science and decision science.
Tyler Ludlow: [00:15:34] And one of the presenters was this gentleman who was a data scientist. And he had sort of a framework, a model, slides, some pictures, graphics that he was showing. And it was really intriguing because he showed how, from a data science perspective, one of the features that big data provides is identifying problems or opportunities. I mean, it’s seeing the patterns that we, as humans, don’t. Our brains can’t handle all that.
Tyler Ludlow: [00:16:07] And those are, I think, potential opportunities. Because I think the key – we talked about decision making process in general. I think the place that most of us go wrong is that most folks will see decision making as, “I go collect some data. I analyze it. And make a decision.” And where that cynically can go wrong is that you get the right answer to the wrong problem. That you’re not really tackling. That you’re not framing. Taking some time to sort of frame that decision. You know, what is this? What’s my main objective? What’s most important to me? Just kind of early insight and all that kind of stuff.
Tyler Ludlow: [00:16:43] And I think that is one of the opportunities to blend data – what you call it data science or big data or whatever. But data with decision making is, one, identifying the opportunities. Sometimes we don’t see those. I think big machine learning AI can bring up opportunities. So, I think that’s one way that it can help in that mix to make classic definition of being able to decide.
Tyler Ludlow: [00:17:11] Even the root of the word to decide comes from decision. You can hear it in sort of the root of the word scissors. I think they both come from the same root in Greek or Latin. And so, it’s about cutting off all options except one that then you move forward with. And that’s what a decision is. To select that best alternative, the measuring stick is what we care about. It’s the value criteria that are important to us. And AI can’t tell us that. We have to get clear on what we want. And that’s part of – I mean, AI can do it. Machinery can do a lot to learn how to find that in the data and get better at spotting a cat in the picture or other more important things. But to be clear about what’s important in the beginning and what we’re driving after, let alone to take these opportunities and then say, “Yes. This is one that we want to move after and frame that decision.” I think that’s where the humans are needed.
Mike Blake: [00:18:16] Now, I think there’s a misconception that all of a sudden data matters as if nobody used any data before to rely on making important decisions. Right?
Tyler Ludlow: [00:18:27] Right.
Mike Blake: [00:18:27] And so, it’s a misconception to say that data hasn’t been around or hasn’t been driving decisions for a long time. But what’s different now? What has changed where data is now sort of a top of mind, very much kind of vote set, if you will, a decision tool that’s available.
Tyler Ludlow: [00:18:54] Well, I think it’s just the last word that you used, availability. Something being available. I think that’s one of the biggest keys. I mean, you could layer onto that computing power, right? The ability to be able to do something with it, to make sense of it, especially to be able to make sense of it in a timely fashion. Often we don’t control the time bounds of the decisions in which we need to – that we need to make. I can think, you know, we’ve done a lot over the years with stochastic simulation or Monte Carlo simulation, being able to use a computer to do that. The theory and the thought of how that would be valuable existed before the computing power. And even in the early days, it could be done on big behemoth processors.
Tyler Ludlow: [00:19:37] But to be able to put that at people’s fingertips, I mean, I’ve worked on projects where it was, you know, all of that rocket science, so to speak, gets embedded under the hood. And the decision makers, they’re not even going to an expert anymore to work with it. It’s just happening at their fingertips. They’re getting almost instantaneous looks at distributions of potential future outcomes and then being able to make their decision about whether to go forward or not
Tyler Ludlow: [00:20:01] So, I think the availability of the data, like as you asked your question, I was thinking how a company that I used to work at, a pharma company. Every drug that we had, every molecule that we had for every potential disease that it might be efficacious in, we would do an assessment of the likelihood of it being able to clear each of its clinical study hurdles on its way to potentially being approved. And so, it’s an assessment about the future.
Tyler Ludlow: [00:20:33] And historical data in the past might be informative, but there’s a lot of subjective information about current science, regulatory stuff, and all sorts of things that we’re looking towards the future. One reason why we relied so much on subjective assessment in that process is because there wasn’t available data to be able to aggregate. That’s happening. That’s changing in more and more places where you get the data available. And then you have the computational power to make sense of it in a timeframe that’s useful for the decision maker. I think those are some of the big keys.
Mike Blake: [00:21:09] You know the Monte Carlo tools are now so powerful. And I found out with my clients to be so eye opening. I’m fortunate, I kind of made a commitment to learn that kind of modeling a long time ago. And in addition to having it sort of generate referrals for my competitors who aren’t really very comfortable doing that. When you are able to show a client not a static outcome, like a forecast, for example, or three or four forecasts based on best case scenario, worst case, middle case, scenario. That stuff drives me crazy. But instead, with Monte Carlo, you’re able to show people a full range of potential outcomes. And literally show an image that paints a picture of the distribution to show kind of the relative trade=off between likelihood of outcome and extreme amount of outcome, basically.
Mike Blake: [00:22:12] And at first my client thought it was witchcraft. But once I sort of explained to them that, “No. It’s not witchcraft. But it is different.” There’s just so much there. And I don’t think Monte Carlo simulation and the tools that enable it, they don’t get enough credit in terms of how much that can and is starting to revolutionize decision making.
Tyler Ludlow: [00:22:36] Yeah. Yeah. Dead on. And as you were talking, I was just thinking, “This is just timely.” Just last night three of my boys were playing Risk together, 19-year-old, my 14-year-old, and my nine year old. And a week or so – it may have been during this conference that I mentioned that was attending. You know, we were looking all this at remodeling stuff. And I had this idea that I should teach my kids just the concepts of Monte Carlo simulation. And I thought, it’s been a little while since we played a game of Risk. I’ll teach them to use it in Risk. And I’ll show, “Hey, you can look at these different strategies. Should I attack one country to the other? There’s a best case. There’s the worst case. There’s an average.” But it’s really the distribution of potential outcomes that you want to make your strategy based off of.
Tyler Ludlow: [00:23:23] And so, it just so happened they started their own game last night. And so, they’re partway through when I walked in. And I said, “Hey, guys. I’m going to interrupt your game a little bit. I’m going to teach you this thing called Monte Carlo simulation.” We homeschool our kids so they’re okay with a little bit of mom and dad interrupting life to do some teaching. So, we did that. And we talked, like, 15, 20 minutes. I just gave them the concepts. I showed them the loop sheets engine. That was a very light Monte Carlo engine. And they all got it. In fact, my nine-year-old was the most excited about it because he usually gets pounced on by his older brothers when he plays. But he was like, “I can have this little magic crystal ball type spreadsheet that can give me an idea of how successful I might be. That’s really cool, dad.
Tyler Ludlow: [00:24:11] So, it went better than I thought it would. But it made me think kind of like your last comments, you know, as we keep moving forward and people become more fluent in these sorts of techniques and data and in the use of it, even if they’re not a data scientist, just the usage of it, I think it will dramatically inform and increase the quality of our decision making.
Mike Blake: [00:24:35] So, what is it that makes data big? How did data go from being data to big data?
Tyler Ludlow: [00:24:42] Good question. Well, certainly back to maybe a little bit of this availability piece and the ubiquitousness of that availability. A lot of it having to do with databases becoming more proliferated in all different areas of our business. Things being more trackable so that they leave behind a database trail. And then the ability to share that data between systems. I mean, even just the analysis that we’re talking about doing, even if that analysis was possible processor-wise, and the data existed to do it with, you still have to then get the data into the system that’s going to do the analysis.
Tyler Ludlow: [00:25:27] And whether that’s an engine like Excel or add-ons into it or it’s a bespoke piece of software, the interoperability – so the availability, the ubiquitousness of that, and the interoperability of that, sharing of that data – to get it to the points where it’s gets closer to that point in time where the decision is being made or being looked into. To me, those are some of the key things that had it go from data to big data.
Tyler Ludlow: [00:25:58] I think one of the big challenges is how do you make big sense from big data? Now, we’re swimming in it. We’re swimming in this stuff. And how do you then use that in a timely fashion to actually make sense of it where it’s not a block box. Where you understand the story that’s being told. And you could communicate to somebody else this is why we’re doing it this way. As opposed to just, “Hey, this machine told me I don’t know that type things.
Mike Blake: [00:26:27] Can every business benefit from using data to drive decisions or maybe using it more than they already do?
Tyler Ludlow: [00:26:39] So, I think the answer is yes. But that’s kind of the answer that most people would expect. But then I think the cynics are rightly so in thinking, “Really? Like, everyone? All of us? Even some of these small entrepreneurs, small business folks?” Which, I think, that sort of pushback is good. So, I think the answer is yes in the right way.
Tyler Ludlow: [00:27:04] One of the biggest challenges, I think, we have in smaller organizations down to our personal lives – I think that’s the smallest organization, me and my individual life. One of the biggest challenges, I think, we have is learning how to press the pause button and reflect a little bit before we make a decision. And not just be in the flow of everything else that’s going on. And creating an opportunity like almost creating that fork in the road. And then saying, “Hey, I’m going to do something about it.” Sometimes in the moment when we’re going down the river, we don’t have the ability to necessarily make – take much time and make a decision about which fork in the river we’re going to go down just because of how fast the current is.
Tyler Ludlow: [00:27:54] So, in the moment, I think, there’s one answer about when is it appropriate to use big data and when do you just not have the time or the resources to make it makes sense. But the frequency with which it is useful goes up if we learn how to press the pause button. If we learn to sort of pre-think some of our decisions in a more strategic fashion. Rather than being so reactionary when they actually come up. And so I think in times like this, we get have a little bit of time to reflective. It provides more of an opportunity to go out and get your hands on and do something with that big data. And then once you’ve kind of pre-made that strategic decision, it might pop up here there, here there as you’re running down the river, so to speak.
Mike Blake: [00:28:38] You know, I think that last point is really smart. And I know we didn’t bring you on here to talk about the psychology of decision making. And I’m going to make a topic out of that at some point. But that pressing the pause button before you make a decision, I think I found to be so helpful. If there’s one thing that I’ve learned over my career that has made me a better decision maker, is to push pause and realize that most decisions I need to make in business are not snap decisions. Nobody expects me to make a snap decision. And there is something to taking a morning, or an afternoon, or sleeping on something, or even a weekend to make a decision that just leads to much better – just better outcomes.
Tyler Ludlow: [00:29:26] Yeah. I remember I was approached to help develop a training for, like, 3,000 thousand employees at large companies to work at. And the whole point of that training, it wasn’t around how do you make really big strategic decisions. Which was the normal place that my day job was. It was within the organization. It was about how to help employees think about just taking 15 or 20 minutes to stop and just jot down a few notes. Think through or a little bit of reflection before making that next sort of day to day – thoughtful day to day decision. So you’re absolutely right, learning to be able to do that is one of the biggest challenges. Having a great decision process is fantastic. But if you never take the time to actually deploy it, you’re missing out on it’s value.
Mike Blake: [00:30:19] Yeah. I mean, it’s rare in business that you really have to make wady snap decisions like that. We’re not in the military, so we don’t have to start moving troops around, otherwise people die. It’s like, “Okay. Well, this problem is going to be here.” As long as not using it to avoid the problem, right? There’s something to be said for sort of taking your time and perspective and adding some intellectual capital.
Mike Blake: [00:30:46] One of the things I hear about data and I hear people offer a lot of misgivings – I’m somewhat sympathetic to this argument – is that complete data is almost never reality. And can you fall into a trap of striving to collect that last bit of information that you just never actually make a decision? And then what’s that inflection point? Can you talk through what that inflection point kind of looks like or even feels like? Or you just need to say, “Okay. I’ve got enough. I’m never going to get a sure thing.” But in terms of kind of cost benefit, this is as much as I’m going to get. How do you figure that out?
Tyler Ludlow: [00:31:35] So, yeah. Great question. And I think my answer to it all come from, essentially, just building on the previous little discussion point that we had about pressing the pause button. Or the language that we use is to declare a decision. So, when you declare that decision, there’s some time that you take to say, “What’s my overall objective here? What am I trying to achieve? What are the alternatives I have on the table?” One of the biggest mistakes that people make is that they’ll frame up decisions as being, “Do I do this? Yes or no. Should I do X or Y?” Rather than being able to go sort of a step above that and say, “You know what? How do I frame these questions so I can look at a myriad of alternatives?
Tyler Ludlow: [00:32:24] One of the other mistakes that folks make is that there’s sort of some descriptive titles here. People tend to be alternative focused in their decision making rather than value focused. And what that means is, if you’re going to buy a car or something, you show up at the lot and you start looking at the alternatives, the vehicles that are available to you. And you start looking at the differences between them, horsepower, miles per gallon, leathers, whatever, the trim packages, whatever they have.
Tyler Ludlow: [00:32:56] Rather than being clear about what it is that you’re looking for, what’s important to you. Going in and only starting to look at the value focused side of it. And only going in and saying, “Okay. This is what we’re looking for. How do the options compare?” Even to the point where you’re saying, “I only want to look at options that meet these criteria.”
Tyler Ludlow: [00:33:17] So, when it comes to the data, I think the connection there is that – I’ll give an example aside from car buying. One is apropos. We work with all these kids. We’ve got a bunch of teenagers. And we were looking at another vehicle for the kids, primarily, to drive. So, I’m looking at getting a used vehicle. And I’m trying to think, “Well, what is it that we’re looking at?” If I open the Auto Trader app, there’s a couple hundred thousand vehicles. So, I specify and it needs to be under 150,000 miles. It needs to be $7,000 or less. It needs to have four or five criteria. And from that, we ended up with 14 cars that were nearby. And so, that was really easy then to start sifting through.
Tyler Ludlow: [00:33:58] And I’m not distracted by all of the other pieces of information about this vehicle. I’ve been thoughtful and say, for us, it’s the kids driving. So, it’s miles per gallon because we want them to get to good places. We might use it on long tripe, so we’re looking for leather seats for comfort. And I didn’t want it to break. I wanted it to be cheaper, but not start breaking down the next month, so some limit on the number of miles. And everything else beyond that was not all that important.
Tyler Ludlow: [00:34:28] So, I think that the first key to not being overwhelmed with data and decision making and the wrong one and getting too much is being really clear about what’s important to us. What are the criteria that we’re going to use to make the decision? And those are the only things I needed to go and gather data about or the unknowns that affect that data. I might go, can do some market research to forecast my revenue, which is going to impact my profit. And that’s what I’m basing my decision on or something.
Tyler Ludlow: [00:35:00] So, I think one is gaining clarity of those value criteria ahead of time. So, people that market stuff, like back to the car buying example, the sales guy on the lot is going to want to tell me up and down about these cars. I really only care about the information that matters to me helping to distinguish between my preferred alternative. I don’t really need all the other information. I just need my stuff. So, I think the biggest key is to be clear about our value criteria ahead of time, so that we don’t get distracted with all of the possible data that’s out there. We zero in on what’s really important to us.
Tyler Ludlow: [00:35:40] And then we get clear about saying, “Hey, is the cost of going out and getting that extra data, is that worth the additional insight that it might provide?” And the answer is not always yes. We tend to sometimes take comfort in saying, “Oh, I’ll just go get more data and more data and more data.” Even if it is data that informs my value criteria. It might not be worth it in the time or the cost that it takes to get it relative to the benefit of the additional insight that it might provide.
Mike Blake: [00:36:09] So, on the flip side of this question, I want to ask, is there value to even having a relatively small amount of data? Let’s say that you’re – I don’t know – a food truck. And you may have a very limited amount of data. Perhaps no more than simply your receipts in your inventory. And maybe you have a little bit more. But can good decisions be made on a small amount of data? Or maybe better put, on a fairly incomplete data set.
Tyler Ludlow: [00:36:46] Yes. Yes, they can. And as you’ve kind of alluded to, sometimes that’s all you have. There are some times that that’s all you could reasonably get your hands on or might be affordable to get your hands on, so to speak. And I think this is where coming back to, again, sort of framing up that decision. One of the next pieces of that is saying, “Well, what are the key unknowns that could really drive my outcome scenarios to be really good or really bad?” Like, we talked about this Monte Carlo simulations that range with its potential outcomes. So, what are the factors that really are key to that?
Tyler Ludlow: [00:37:25] So, I’ll give you an example. Years ago, I used to work for a company that did a lot of home, personal care, and food products. And so, some of those would be manufactured in big warehouses. So, we might have a huge product launch. I mean, we’re working on a product launch of a new laundry crystal. So, it was something. It wasn’t sort of a laundry powder nor was it the liquid. It was these crystal things. They were new. They were looking onto this. And it required a new manufacturing line. So, that huge capital expenditure was in the hundreds of millions of dollars. And as you looked at the overall revenue for the project, that was impactful. But it actually had a very – because that was very controlled, we knew a lot about it, it had a very small range of uncertainty around it. Whereas, the range of uncertainty around our market share was much more uncertain.
Tyler Ludlow: [00:38:17] And so, for us to go out and get that data was even a small bit would be super helpful. Whereas, the data on the CAPEX side didn’t provide sort of the benefit or as much benefit. So, having a clear idea of what are the key factors that could really swing my outcomes in one direction or the other. Again, that’s important to know beforehand. And then if you have one of those key factors that you have, even just a little insight on, a little data can go a long way. I mean, if you know nothing about something happening or not, you essentially have a 50-50 chance. But if you just get a little data that helps you to know, hey, it’s more 60-40 than 50-50. The relative value of that uncertainty, you’ve just shrunk that uncertainty by 20 percent. So, that relative value of that little piece of information can be super valuable.
Mike Blake: [00:39:18] So, one of the things I’m sure our listeners are concerned about and I’ve asked before is, “Look, this sounds great. But I don’t have Tyler’s massive education and data analytics. I don’t even have Blake’s sort of back of the envelope iPhone calculator level of data analytics.” Do you need to be a statistician or have one on your staff sort of full time in order to use big data?
Tyler Ludlow: [00:39:49] No. No – I mean, yes. This goes back to the question of should every company use it, right? If you can pick and deploy, there will be times where you want to invest more heavily in it. And times, where you invest less, I believe. And this goes back a little bit to being able to press the pause button and insert, maybe, some strategic decisions. When the time is right, you might buy into it a little bit more than not. But the basic process of being able to be recognizing how to plug data in, how it can create value, give you insight, in particular about unknowns into the future, that sort of process and principle can always be applied.
Tyler Ludlow: [00:40:30] One of the things that we teach in our workshops is how to use something that we call decision archetypes, which is a way to say there’s these simple patterns that show up over and over again in decision making that hinge on these uncertainties. And if you can just start to get a read on the ballpark, sometimes all you really need to know to make the decision is which side of the fence you’re on. You don’t necessarily know how far away from the fence you are to an exact team. At times, it’s nice to know that exact distance from the fence. But as long as I know which side of the fence I’m sitting on, then I know how to decide and how to move forward.
Tyler Ludlow: [00:41:11] And so, sometimes, just like you’re talking just a little bit of data or a little bit of – if you’re going back to your question was about, “Hey, do I need all of the analytical chops?” No. Having a process that allows you to do a little bit quickly could take and just – you know, got to take a little bit of learning. But it’s not overly complex, no.
Mike Blake: [00:41:31] We’re talking with Tyler Ludlow of Decision Skills Institute. And we’re sort of running out of time here. But a couple of questions I want to make sure we get to. One is, if I’m a small company, you know, I have limited resources. What are some tips to, maybe, at least amp up my data access or collecting game? Are there some easy things maybe a lot of companies could be doing that are not in order just to, maybe, capture more data they already have or access data, maybe, they don’t know exists? It doesn’t completely upend their entire cost structure.
Tyler Ludlow: [00:42:11] That’s a good question. I’m going to answer it in a slightly – I hope it isn’t in a field to dodging the question to your listeners. I want to say, first, I think the key is to be thoughtful about the decisions that you currently make. The bigger ones, the ones that you’re already taking some time and thought for. And to take the time to say what bits of data or information, if we knew better, might really impact our ability to make that decision in a more quality manner.
Tyler Ludlow: [00:42:48] This goes back to maybe sort of the alternative focus versus value focus bit. Before you start just collecting data, because that’s the style and the fad, I think having clarity about what data would be most meaningful is probably the first thing. And then you can set some very simple strategies to start with of being able to either collect or get your hands on that specific data at the right time. Especially if you’re a small business, and we think about collecting data off of your own processes, that can be an expensive sort of thing to put in a program, a collection program like that. Let alone in the moment. Sometimes it takes longer to do a process in a way that it’s completely trackable afterwards. So, those are investments that you’re making.
Tyler Ludlow: [00:43:39] You want to make sure you’re not doing those just because of fad. And because, “Hey, I know that if we start collecting this data, it will give us insight about this unknown.” And that can really drive our insight into potential outcomes in the future in which way we might go or things going forward. So, that would be my sort of – it’s a bit dodging the answer, but I would start with the bits of information that would be most useful.
Mike Blake: [00:44:03] I don’t think it dodges the answer. I mean, at the end of the day, kind of restating the answer back to you, I think, the answer is you may have to spend some money. Make an investment to extract the data that you already have. But it doesn’t sound like it’s a binary discussion where you either spend no money on it or you spend millions and millions of dollars on it. You can sort of snipe this and decide what data is the most important. And it could be, for some companies – you tell me if I’m wrong – some companies, just one data point or one data set makes all the difference.
Tyler Ludlow: [00:44:41] Yeah. Yeah.
Mike Blake: [00:44:42] Right? And that’s the leverage part you talked about.
Tyler Ludlow: [00:44:44] Absolutely. Absolutely. And I would say that – maybe building onto this – one of the most common themes that I tried to drive home to people when we do teaching and training and workshops and whatnot is that, we know more typically than we think we know about how things might be in the future. So, often, whether it’s scientists or whoever, I start working with someone to help make a decision, it will be clear that it kind of hinges on this one unknown. I’ll start asking about it and the response is, “Well, we don’t know, it could be anything.” Well, that’s true. What would be the height of the next person to walk through the door? Well, it could be anywhere.
Tyler Ludlow: [00:45:19] But you know what? I know it’s probably less than seven feet tall and more than four feet tall. And I could probably still go in narrower and narrower down there. And we tend to know more than we allow ourselves in first pass to think we know about something. And oftentimes just starting to put some reasonable boundaries on things, we realize we can get it into a space where we can then start deriving some insights about what we do. Rather than just saying, “Well, it could be anything. We don’t know until we bought some market research,” or whatever it might be. So, a lot of times you’ve got some of that insight just in our minds – in our heads because of our expertise and our experience.
Mike Blake: [00:45:56] Tyler, we are running out of time. And I have to let you go and do your many things. But I’m sure there are questions that our listeners have out of this discussion where they like to, maybe, ask you and get some expertise on it. Would you be willing to share your contact information if anybody wants to ask your question?
Tyler Ludlow: [00:46:13] Absolutely. If you want to follow up with me directly, my email is just Tyler@decisionskillsinstitute.com.
Mike Blake: [00:46:24] Well, great. That’s going to wrap it up for today’s program. I like to thank Tyler Ludlow, Decision Skills Institute, so much for joining us and sharing his expertise with us. We’ll be exploring a new topic each week, so please tune into so that when you’re faced with your next decision, you have clear vision when making it. If you enjoy this podcast, please consider leaving a review with your favorite podcast aggregator. It helps people find us, so that we can help them. Once again, this is Mike Blake. Our sponsor is Brady Ware & Company. And this has been the Decision Vision Podcast.