BiggerPockets Business Podcast 99: Finding Profitable Opportunities Using “Deliberate Data” with Dr. John Johnson

BiggerPockets Business Podcast 99: Finding Profitable Opportunities Using “Deliberate Data” with Dr. John Johnson

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Data can be a confusing topic for most people, but what about when it has to do with your business? How is your business using data? Are you even using data at all? Dr. John Johnson, expert witness, professor, and founder of Edgeworth Economics and Edgeworth Analytics argues for businesses using data to grow.

Dr. Johnson understands why so many people fall victim to studies and findings that may not be entirely accurate. He talks through confirmation bias and how we, as consumers, can find the red flags when listening to interpretations of data. We are urged to take time to think before we accept statistics and data as fact.

He also dives into how he started his own firms, Edgeworth Economics and Edgeworth Analytics, and how he himself uses data to track his firm’s growth, recruiting, and revenue. Often, his firm is hired to find why a product or group of products is or isn’t selling, which strategies make the most profitable sense, and how a business can change to ensure more sales. Aside from that, Dr. Johnson also acts as an expert witness in corporate lawsuits, sifting through the data to find out what is really true, and what has been inflated.

There’s no mistaking that data is important for modern businesses, but what’s more important is how you use and interpret this data to come up with accurate conclusions. His book, Everydata: The Misinformation Hidden in the Little Data You Consume Every Day goes into the data all around us, and how we can sift through it to find truth.

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Read the Transcript Here

J:
Welcome to The BiggerPockets Business Podcast, show number 99.

John:
What is the narrow question I’m trying to answer where the data can be informative? If you don’t frame the question first and you just start looking at the data willy-nilly, you’re not going to get an answer. But practical reality is, I think data analytics and data analysis, especially for small businesses where time is going to be a concern, should be deliberate.

Announcer:
Welcome to a real-world MBA from the school of hard knocks, where entrepreneurs reveal what it really takes to make it. Whether you’re already in business or you’re on your way there. this show is for you, this is BiggerPockets Business.

J:
How’s it going everybody, I am J Scott, your cohost for The BiggerPockets Business Podcast. And we are on our last double digit show, show number 99. I can’t believe I have done this intro 99 times, and 99 times I have introduced my lovely cohost, Mrs. Carol Scott. And I’m doing it again. How’re you doing today, Mrs. Carol Scott?

Carol:
99 BiggerPockets Business Podcasts on the wall, that’s what I’m sitting here thinking about. Isn’t that so funny? Well, I’m going to tell you what I’m blown away about the number 99 right now. I’ll tell you what, I used to be able to rent a car for $99 for the entire week. No, no longer, my friends. I’m telling you what, I think people are just so completely over what has gone down in the past 12 months, and everyone is like, “Forget it, I am going out. I am traveling. I am living my life.” Have you seen travel prices lately? Oh my goodness. Rental car prices are through the roof, hotels, through the roof.
I took my mom back to the airport yesterday, so many people, it is crazy town. That said, I’m pretty excited to start traveling too, I’ve got to be honest. Good stuff coming up, as always.

J:
Absolutely. And yeah, lots of stuff going on. And there’s no segue from that discussion into today’s topic.

Carol:
I was trying so hard. I had something and then it just completely unraveled. It was right here. It was right here.

J:
Well, luckily, we don’t need a good segue into today’s topic because today’s topic stands alone. It’s a great topic. And we have a great guest. Our guest today, his name is Dr. John Johnson, and he is a PhD economist. He is the founder and the CEO of two world-class companies, Edgeworth Economics and Edgeworth Analytics. He’s the author of a really cool book called Everydata: The Misinformation Hidden in the Little Data You Consume Every Day. He’s taught at Georgetown University. He’s been quoted pretty much everywhere. And he’s here today to talk to us about data.
I know it sounds like a really boring subject, doesn’t it? And normally, would be a boring subject, but it’s not boring with Dr. Johnson. Here’s the thing, he turns this actually into an exciting and interesting conversation. We talk about everything from how we can be better consumers of data, how we can see through bad data, how our cognitive biases and confirmation biases can impact our interpretation of data. And most importantly, we talk about how we can use data in our businesses to make our businesses more successful, to help grow our businesses, to help focus our businesses on the things that are going to make us money.
We even talk about his business journey, because he’s built two companies and he knows about building a service-based company where he is the product. He has a company where he is an expert witness and he has a bunch of expert witnesses around him, and people hire his company because of him. And we talked about the things that we can do as experts to grow a company and to scale a company where normally we would be the product, but we want to make our company bigger than just us. It’s a great conversation. This whole episode was just absolutely amazing.
If you want more information about John Johnson about Edgeworth Economics, Edgeworth Analytics, or the stuff we talk about in this episode, check out our show notes at biggerpockets.com/bizshow99. Again, that’s biggerpockets.com/bizshow99. Without any further ado, let’s welcome John Johnson to the show.

Carol:
Dr. John Johnson, welcome to The BiggerPockets Business Podcast. We are so looking forward to learning more about data and how we interpret and use that data in our businesses. And I believe you are an entrepreneur as well, so cannot wait to hear some of your entrepreneurial story. So thank you for being here today.

John:
Oh, great. To be here, I’m really excited. Hopefully, I have something interesting to say, and I do love to talk about data, so I think we’ll find some good things to talk about, I’m sure.

J:
Oh, I’m positive. In fact, when I read originally that your area of expertise was distilling complex data down into simple and straight forward explanations, I knew I wanted to have you on the show. I am a data guy myself, not like you. You are a PhD from MIT, I am not, but I do have an engineering and a math degree, and so I’ve always been a big fan of data. So I’m really excited about this discussion. You run a company, and I want to hear a little bit about your company. Technically, your company is focused on economics consulting, and that term, economics, means a lot of different things in a lot of different contexts. Can you take us back a little bit and just tell us a little bit about your background, your story, what that means you being an economist and also a statistician and what specifically it is that you and your business do?

John:
Yeah. I had actually thought, dutifully, after I got my PhD, that I was going to be the most popular professor on the University of Illinois campus for the rest of my life. And I found that being a professor and an academic was incredibly lonely. I was very social, I wanted to work on practical real world problems. So my background is a PhD in economics, actually, I have a dual specialization in micro economics, how do firms work? But then also in what’s called econometrics, which is kind of the marriage of statistics and economics. And so over the course of my 20-year career, since I graduated from graduate school, even more technological advances with data, the size of the data sets, the types of data sets. And so it’s a perfect world for me and that I love applying and dealing with real world problems.
Economic consulting broadly is, we do a lot of different things, but generally, by economic consulting firm, Edgeworth Economics, we often do expert testimony where we are brought into situations where companies are suing each other or there’s other large litigation, and there’s a really big problem and data is a pretty central part of it. For example, I did a case very early in my career involving chocolate candy bars, and I had data on every single chocolate candy bar sold in the US for 10 years, and had to analyze what had happened to pricing and model all this data. I had a tour of the chocolate facilities and see how that worked.
And so basically, I kind of parachute, in writing, business into industries and advise them, or offer my opinions on how they work from an outsider perspective, being very true to the data. So that’s the economics business. And then we have the sister company, the analytics business, which is more about more advisory work, where we’re trying to advise companies how to make better use of their data, as opposed to looking at the data they already have and saying, “Okay, this is what it means to us.”

J:
That’s awesome. And I love that. And I want to dig into how we as business owners, entrepreneurs can use data to make our businesses and ourselves more successful. But I’d love, before we jump in there, because I’ve heard you in a couple of other podcasts and I’ve started reading your book, and you have a lot of amazing, more general ideas and thoughts on how to distill data down into simple forms that’s larger than just how to do that in a business setting. And I think this is a pretty timely discussion. Anybody that’s been paying attention for the last two elections, anybody that’s been paying attention over the last year with COVID knows that there’s a lot of talk about data and statistics.
And in a lot of ways, not everybody agrees with the conclusions that they claim that the data and statistics they put forward-

John:
Nice political correctness there. That was beautifully glossed over.

J:
Yes. And it’s both sides. I don’t take sides politically. But I would love to talk a little bit about some tips that you might have for us as just people, not necessarily business owners, but just as people when we are listening to data, when we’re listening to the interpretation of data more specifically, how can we do a better job of taking what we’re listening to, taking what we’re reading, taking what we’re hearing, and determining what’s real and what’s not real, and whether the conclusions that are being reached were actually by the data that we’re hearing.

John:
Yeah. I did write this book called Everydata, it’s a few years old now, at the background of the 2016 election. And the reason why I remember that is because when I did my media tour, the only thing anybody wanted to talk about was polling, and I’m like, “But there’s a lot more to the world than polling data.” But as a teacher at heart, and as someone who in my practical job has to explain data to whether it’s a judge, the jury, whether it’s a business person, or even helping my son with his AP statistics homework, which is actually one of my proudest moments, the ability to explain simply or get people to think about data in an interactive way.
Most people think when you talk about data numbers, math, they’re like, “Oh, I’m terrified of that. Oh, I don’t understand math. I don’t understand numbers. How could I possibly interpret or think about data in my everyday life?” And a lot of the messaging that I try to say is, “Look, I’m not asking to turn you into a professional statistician, but if you think that you can’t develop intuition for certain red flags, certain things to think about when you see data, when you consume data, you’re wrong.” There’s a level of awareness that comes when you read things in the newspaper.
So, one of the things I always talk about is the stories, my favorite examples is, you read in the newspaper a story that says, “Starbucks raises house values.” And basically the idea that, look, it turns out that if you look at the value of houses where there are Starbucks, they are much higher home values. Now, does that really mean that the placement of the Starbucks itself is what raises the home values? Well, where do you think Starbucks strategically places their stores? In higher value homes. You don’t need any particular statistical expertise to read that news story and say, “Hmm, something’s not right about that.”
So that’s the classic… I think a lot of people hear the phrase, correlation is not causation, but in the news and in the types of things you consume on TV, there’s lots of headlines, there’s lots of flashy things. And most of the time when you see data relationships being put forward, even the ability to stop, to think about, what is the source of the data? Do the people who are giving you the data have an agenda of any type? Just so you know. Is it an objective broker or not? And again, people take positions and use data, but then also asking some simple questions. And again, you don’t have to be, at the end of the day, a statistician to do that.
Another example from the book and that I’ve talked about before involves claims like four out of five, four out of five dentists prefer some brand of gum. And then you’ll just read the fine print, and it’s, “Four out of five dentists amongst those dentists who prefer a brand of gum prefer this gum.” So there are these kinds of things that, as you just start to look at them, there’s these different kinds of things. Another great example, averages. People love to talk about the average temperature, or the average GDP. And there’s a place for averaging, but sometimes that masks incredible variation under the surface.
So as you go about your daily life with data, as you’re confronted with data, as you see data, just the idea of pausing, stopping, thinking, “Is there something else here that I would want to know?” That simple discipline can really go far. Now, again, not saying that means you’re going to become a statistician and doing key statistics in the back room or something like that. But the point is, I think you can actually understand to be a little bit more thoughtful, and it’s pretty accessible in that sense.

Carol:
Excellent.

J:
Yeah. And I liked the fact that you just used the example of the correlation isn’t causation, doesn’t necessarily imply causation. I think that’s a common refrain and the common argument that we use, but there are a lot of logical fallacies out there, and that’s just one of them. There’s confirmation bias, and we’ve seen a ton of confirmation bias over the past several years and cherry picking of data and all kinds of other cognitive biases. And so these are things that we can say to ourselves, and I like to think I’m a pretty logical analytical person, I like to think that I’m pretty objective, but I recognize that I have cognitive biases.
I probably do plenty of confirmation bias all the time, even though I think I don’t and I try not to. Is there some way we can check our own biases? Are there things that we can be doing to try and determine where we fall on that scale of, are we gullible or can we trust our instincts?

John:
Well, look, I think just to be fair, I’m a professional statistician, I look at numbers all day, and there’s still times when I see something on an infomercial, I’m like, “Wow, can that really do that? That’s great. I’m going to lose 10 pounds if I go on the avocado diet. That Teflon pan, I can bake it at 350 degrees. That’s amazing.” There’s lots of things like that where we’re all prone to just as humans. And so I think part of it is that vigilance, you can’t let your guard down, but also just usually when a claim seems too good to be true, it usually is.
And so I think as a starting point, what I tried to say to people that I say this to, is just practically, but also in the business world, same thing is, if you’re trying to make a serious decision, and if that’s you’re trying to spend a certain amount of money, you’re sending your child to a certain school, you’re making a certain big job decision where you’re actually relying on some data, then really step back and think about what’s the source of the data. There’s lots of noise in everyday life and there’s certain things that we can’t all engage in every single number if we just read the newspaper or see everything on the internet or Twitter.
So you’ve got to pick and choose, because I think people have limited bandwidth. But as a practical matter for me, I try to discipline myself by starting at, “All right. Well, let’s think about the major decisions, the major things. What’s the data mean for that?” If I’m going to have some action that I’m going to take up based on something, I want to make sure that I’ve really investigated it. That’s a good starting point because as I said, you could try to verify every number you ever see, but I don’t know how you’ll get anything else done in your life, so you’ve got to balance the consumption part of this.

Carol:
I love this. I’m especially loving this, I feel like I’m learning so much already, John, just because J is absolutely, hands down, without a shadow of a doubt, the data guy in this whole partnership we’ve got going on over here. So I’m not typically one that’s going to be like really figuring out how to take the data and how to interpret it and figure out what is what and where all the pieces fit in together. So I’m loving that you’re already providing these little actionable tips throughout here. So I want to learn more about the book that you mentioned earlier. You talked about how it’s empowering people to be better consumers of data.
And I have a feeling that might be geared towards someone just like me. So can you tell us more about your book? Tell us who it’s for.

John:
The name of the book is called Everydata: The Misinformation Hidden in the Little Data You Consume Every day. And the point was to really collect as many practical real-world examples as possible of these basic data concepts. And so each chapter is about a concept, whether it’s averaging or cherry picking or some other statistical idea, forecasting, and then we just take practical examples, whether it’s from the newspaper, from popular media and we, as my coauthor, Mike Gluck, who, another interesting story is, he was actually a high school friend of mine who’s a professional writer and we teamed up, and I learned a lot of writing from him and he learned a lot of statistics for me.
But the point is, it is accessible. And the whole idea was that you can pick up that book, you can look at a chapter at a time, you can see a theme. There’s a great story about baby food and cherry picking of data about baby food for example. There’s a lot of interesting information about the space shuttle Challenger explosion and how the decision to set up the space shuttle in 1986, although under incredible time constraints, was based on looking at a very small data set and looking at it the wrong way. And if you’d looked at it a different way, you would have actually seen, the engineers would have seen that there was a very high probability of that space shuttle blowing up at those temperatures.
So there’s lots of information there, but the point is, it’s a very practical guide to thinking about data. There’s really no math, there’s no equations, I don’t think there’s any equations, but it’s a lot more about, how do you take the information around you and make sense of it.

Carol:
Excellent. J, I just have to say one thing, I’m fascinated that you’re able to take a topic like this and really turn it into actionable things for everyday people. So far, in the few minutes that we’ve been recording, you’ve talked about touring chocolate factories and internalizing or figuring out data around chocolate bars. You’re talking about baby food, you’re talking about the Space Shuttle Challenger. So you’re taking a topic that to me, and I suspect a lot of other entrepreneurs and other people like me, can be very daunting, very just, “What the heck do I do with it?” And distill it down into just everyday experiences so that we can make it more meaningful in our everyday life.
So I think that’s awesome that you and your buddy from high school teamed up to write it. Very cool.

John:
Thank you. I’m very proud of it. And it is fun. It’s a fun thing to do because, again, I am a teacher at heart, I didn’t go try to be an academic because I didn’t like teaching. I love the students. And in fact, one of my business partners was one of my best undergraduate students. So 20 years later, I’m in business with someone who I taught, but the teaching part is the common theme of what actually motivates me and all the parts of my job, is I love to teach and mentor people about these things that oftentimes people are like, “Oh, data? Ugh.” And I’m like, “No, no, no, you don’t understand. This is some good stuff here.”

Carol:
Yeah, you’re making it cool.

J:
One of the things that I see a mistake I see people make with data, and I don’t know if it’s so much on the people that are providing the data and driving what they believe the conclusions are of the people receiving the data. I’ve mentioned this on the show before, one of my favorite quotes of all time was an Albert Einstein quote that everything should be made as simple as possible, but no simpler. And I think that it’s a great thing to remember when we’re talking about data, because I often find that there’s often this appeal to common sense with data. It’s like, “Well, you can look at the data, but just use your common sense. If your intuition says, ‘Hey, this makes sense,’ it probably makes sense.”
But then there are plenty of studies out there, anybody that’s read a few of the books on this topic, including yours, Daniel Kahneman has a great book, Freakonomics is a great book. We know that a lot of times, common sense, our brains didn’t evolve to take complex statistical situations and basically distill them down into what we believe is common sense. Our brains evolved to basically steer clear of predators that want to eat us. And so, how do we think about this keeping things simple and relying on our intuition and relying on our common sense, but at the same time, knowing that we can’t necessarily trust our common sense, especially with complex topics like data and statistics.

John:
Yeah. That’s a great question. And I think there’s a few ways to separated out expertise comes in a lot of different ways. And although I’m a data person I don’t know everything about every business that I study, every topic I study, and I actually often have to rely on people that have other expertise to help inform what am I going to be looking for in the data. Now, that doesn’t mean that I want my results to be biased by what I’m told, but it does mean that when I approach a data problem, I’m also thinking about the framework of, how does this business work? What are people telling me they think the issues are? And again, not because necessarily the data’s going to confirm that or not, but I need to know at least what the context is to actually get to the data in a meaningful way.
I think taking the Einstein quote, which I also love the point is I think put a little bit more finely is, it’s not about I as an expert statistician or economist need to find the solution to a given problem, and simplicity means I haven’t made it so complicated for the sake of being complicated. Economists loves theoretical models and they love very, “Let me show you my coolest new statistical technique, and I’m going to run this really neat estimator that you’ve never heard of, but wow, it’s really cool.” But maybe something else would have been good enough. It would have been just perfectly fine. And so I think what I apply that in my professional life, I think about it as a professional, understanding the differences between where simplicity actually can be applied and where you have to go the extra mile, and that means I don’t try to play outside of my space.
And so if I’m working with a company where they know their particular industry, I want to learn as much as I can first, so then when I go to the data, I can say, “Okay, well I see this in the data, but that doesn’t really square with what you’re telling me why is that?” That’s the way to, I think, get around that. But it’s got to come from a place of information. And again, I can bring data skills to the table and I can bring rigor and logic, but it’s a collaborative effort, especially when we advise like small businesses. We’re trying to help solve a problem. So that’s the way I approach it, is just understanding. But all of the nuance, and in some respects, the reasons why people go to schools for year and years to learn this stuff is because it’s about those nuanced things, that extra step that makes it hard.
It’s a lot different standard if I’m reading the newspaper, I can see, “Okay, something doesn’t seem right.” But if I’m helping a company make a multi-million-dollar decision, that’s probably going to have to be a little different standard for what we’re doing.

Carol:
Excellent. So you’re talking about these different businesses companies in different industries, you’re helping them solve problems, you’re helping them make good decisions. So let’s go there, let’s explore that more. You’re consulting them on using data better overall. So what types of businesses do you help? And what things do you do to help businesses with their data?

John:
Right. So again, so I already talked a little bit about the litigation side of our practice, which are generally companies that are in a litigated dispute. And that often though involves learn every detail of their business so we can look at their detailed pricing data and really understand. But beyond that, the other types of consulting we do often involve companies that have a specific issue. So let me give you an example, we recently consulted with a retail store that had basically attached to a museum where they had a lot of inventory that they kept in the store, lots of products. And that was part of the design was that, “Wow, we have such offerings.”
But they were concerned about carrying all this inventory, did it make sense? And so we were able to analyze their data from their cash registers and actually look at it for them and help them identify amongst all the products they were selling, what were the highest profitability, what were like the no profitability, so they could make intelligent decisions with their data about, “Oh, this is moving off the shelf, this isn’t. Okay, well, maybe if we want to shrink our inventory and not carry as much, here’s the set of products we need to keep. Here’s the products we don’t.” It’s such a very simple, but real world example where we were able to help people with that.
During COVID, we’ve actually had a lot of interesting… It’s been interesting because obviously, a year ago, and we’re all coming up on the one year or so anniversary of this all going into lockdown, we had a number of companies or organizations approach us about helping them with their COVID testing numbers, and could we compile data in a way that would show COVID tests? And so one of the organizations we worked for was an association of laboratories that asked us to help them to have come up with dashboards where we could actually illustrate for their members how quickly tests are being processed, what the volume of tests were, things like that.
That was taking data, not very complicated data, but making it visual. How do you collect it? And then how do you actually make a demonstrative, a picture, a web interface, that allows people to look at it? So that’s two, just examples, but it’s pretty varied. And it’s also all sizes and shapes. We do things for small, small companies. One of the things we’ve tried to do is we want to make our expertise accessible. So yes, we work for some very, very large well-known companies, but we also have really tried to develop a way to advise smaller companies and smaller businesses as well.

J:
I love that. And it’s funny, when we started this discussion or when I started doing a little bit of research about you, obviously your brain goes to, “Okay, he’s a big data guy. He does consulting. He’s probably helping these big companies, these billion-dollar companies figure out how to improve their margins by a 0.2% or move the needle just very slightly looking at large data sets.” But the examples you just gave are things that impact small businesses. There are things that impact potentially any business, just looking at inventory and deciding or determining what inventory is most likely moving the needle on business sales and so it allows a business owner to determine where they should be putting their time and their effort and their marketing potentially, or inventory, or if they’re in brick and mortar, where they should be putting their shelf space, stuff like that.
That’s stuff that applies to all of us as business owners. And the second example you gave of visualizing data, that’s something that all of us could do a better job at, and it allows us to keep our employees and our customers and our vendors apprised of what’s going on in our business when we can take the data and we can actually put it in forms that are easier to visualize. So can you give us some suggestions, for somebody that’s just starting a business, let’s say, or somebody that has a small business that’s growing their business, what areas of our business should we be focused on when it comes to data?
We don’t want to get down in the weeds and spend all the time that we should be spending actually growing our business thinking about esoteric pieces of data, but I’m sure there’s some areas where we should really be thinking when we jump into our business, what are a couple of those areas of what can we be doing better?

John:
I think the key to sound data analysis is just in the ordinary course of even starting a company, running a company, there is a lot of data produced, even a small business. Think about your financial data that immediately comes to mind, think about your invoicing data, think about just keeping track of your payroll. There’s three data sets, no matter how large or small your company is, you probably have those. Look, I think it depends on the life cycle of the business. When I think back to starting my business, the first six months were like, let’s make sure we bring money in the door so we can eat tomorrow. All right, great.
And then as you start to grow, and my company had a really rapid growth spurt, we were like, how do we keep up with this? How do we start to look at what is the right data set for tracking profitability? Where is all this growth coming from? Recruiting then started to become a really big issue for us internally, keeping track of where the best places to recruit our candidates for our work with. So those are three examples from my own experience, but the point is for each of those, I think a key to using the data effectively is, what is the narrow question I’m trying to answer where the data can be informative?
If you don’t frame the question first and you just start looking at the data willy-nilly, you’re not going to get an answer. You might see something, and some of us might just, “Oh wow, that’s interesting. I saw that in my Excel spreadsheet.” But practical reality is I think data analytics and data analysis, especially for small businesses where time is going to be a concern should be deliberate. What is the question I need to answer? And again, as the business owner, you should know that. And so that’s one part of it. Then the second part is with the data I have accessible, data doesn’t come ready to use. And that’s a big, scary thing for people.
It’s like, “Huh, you mean my customer names are wrong or you mean I got to clean up all this data? Maybe I can’t just run this in Excel, I have to do something more sophisticated.” That could be a great frustration, but if you frame the question appropriately, I think that helps you a little bit better with, okay, well, what are the data sets? And then what can I actually answer that’s going to give me something actionable for my business? So to me the idea of being deliberate with data when you’re a small business and understanding maybe the answer isn’t perfect, but an answer informed by hopefully useful data is better than one that’s informed purely by instinct with no data at all.
Yes, I like to do rigorous, very careful work, and I’m not saying there’s no value in that, but most small businesses need answers. And so that’s where you have to go first is, “All right. Well, let’s think pretty targeted about where can there be value added to the data from the data you have.”

J:
Awesome. I love it. I want to transition a little bit because on this show, we talk to two types of people. We talk to experts, people that are very knowledgeable about some area of business and they help teach and communicate expertise to our community. And then we talk to entrepreneurs, people who tell us about the businesses that they’ve started and grown. You’ve done both. You’re clearly an expert on the data side of things, you’re clearly an expert on interpreting data and economics, but you’ve also started at least two businesses. I know we’ve talked about two of your businesses. We’ve talked about Edgeworth Economics and Edgeworth Analytics.
I’d love to hear more about your journey, not just as an expert, but as an entrepreneur. So what led you to saying, you had mentioned earlier you thought you were just going to be a professor for a long time. I imagine there are probably plenty of jobs out there that you could take, you could work for the government or any number of organizations as an economist, but you decided to go the entrepreneur path. So talk to us a little bit about what led you down the path as an entrepreneur and why you decided to start your own firm.

John:
I think it requires a little bit of craziness. Honestly, when I look back, we’ve been in business 11 years, we started in 2009, which you might remember was the Great Recession. And I’d been a professor for two years, and we did move to DC, my wife and I, and our nine-month-old daughter at the time. And we moved here because I took a job at a consulting firm, and I’m like, “Well, if it doesn’t work out, there are lots of jobs in government, we won’t have to move again.” So I worked at an economic consulting firm where I actually learned a lot of practical skills, but what happened over time was I got frustrated.
And I got frustrated because I kept getting told, “Be patient, wait your turn. If you just wait a few years, like 10 years, people will retire and then you can step up and have the kinds of opportunities you would like.” And if there’s one word somebody would never want to use to describe me, it would be being patient. And so I decided somewhat crazy, it’s a little complicated, but essentially, I decided to go out on my own. And we made some early mistakes, but ultimately, one of my best undergraduate students, I called him, he was at Honeywell in Illinois, and asked him if he would move here to be our HR director.
My first research assistant, who I had worked with at my former firm and then went off to get his MBA, I said, “Would you like to do this with me?” And a colleague of mine from Los Angeles, another PhD, the three of us, I said, “Would you like to do this? Let’s try it.” And we did. And so we started and we hustled really hard in the beginning. And it’s interesting because over the lifecycle of the firm, I wanted the place to always be someplace… I wanted to be proud by name it was associated with. But the name Edwards is actually named after an economist whose main theory was about the Edgeworth Box, where you find the gains from trade and make everybody better off without making anybody else worse off.
And so that’s been the corporate philosophy from the beginning, a place that’s empowering young experts to thrive, to grow, to create opportunities for themselves in an environment that we really work hard to make it a special place in terms of how we treat our employees. Just everything about the place in some respects, one of the neatest parts about creating a firm is you create it in your own reflection. And so the values that you bring to the table are important. So whether it’s the rigor we bring to the work or the value we place on our employees, that’s the story. Quickly fast forward, 10 years, I had been thinking that we do so much litigation consulting work.
I wanted to do more of this analytics work as well. I thought it was a nice compliment to what we do on the litigation side. Talked to one of my former employees who had worked at Edgeworth and left to go do something else and said, “Well, what do you think about if we try to bring these analytics skills to small businesses? What if we create a program called the Data Blueprints where a small business can retain us, all of us, hire us to have office hours with a smart person to talk to you through your problem, just spend a half hour. And if you have an issue, we’ll talk to you and see if we can help you outline it?”
And so he came and of course, what happened is COVID happened as we were about to launch significantly that business. So I’ve had the luck of two businesses I’ve tried to create or have created a bit in the middle of major, bad economic times. So Analytics is in its infancy and we’re doing a lot of different things, but it’s a fascinating set of stories. And I think every entrepreneur has interesting stories, but that’s basically mine.

Carol:
Well, I love that, but I think you’re not giving yourself quite enough credit, and I think you glossed over a real lot of the hard work stuff that is so absolutely fascinating to me. So I would love to explore more about back in those early days. You’re talking about how you called colleagues that you’d worked with previously, you called a couple of friends, experts in different areas like, “Come on, guys, let’s give this a shot.” And you just said, we just went out there and hustled and we just made it happen. Yeah, I know there’s a heck of a lot more that just goes into it than just hustling and making it happen, especially when your business is a service-based firms.
I think there are so many people in this space, we have so many members of our community who are experts in an area and are interested in starting a service-based firm. So can you walk us through, what was some of the dialogue you had with some of those very first clients? What was the value proposition? How did you approach people? Just so many people are fearful, they just fear having to ask people they know for their business. How did you and your crew do it?

John:
What we did is, when I say we hustled, what I mean is we knew we had a better mouse trap, in a context of being an expert witness, it’s a very top heavy field with individuals, if you think of a stereotypical professor type with the gray patches or the leather patches on their jacket, every case we pitched, we were the best prepared going in. We knew every detail before we went in and when we went and we pitched, we were as aggressive as could be about if I’m going to show you how original I can think about your problem before you hired me, imagine what it’s going to be like when you do. We did a lot of thought leadership.
And I always love that sound, that term, because it sounds a little jargony to me, but we wrote papers, we gave talks, we went to every major law firm where we knew people These law firms are our major clients on the litigation side, and we went and presented our thinking on these issues. We were flexible on our fee structure, which was unheard of in our industry in terms of coming up with… Some cases we did with fixed fees, which gave clients certainty in the recession where the way the industry had generally worked before was, I’m the expert from a big name school, you pay me what I demand because you need to.” And so we redid that.
We created a profile of young, hungry experts that really wanted to work hard, and we also acknowledged that unlike some of our competition where the main expert was the whole story, we wanted the second expert to always be highlighted as well, so that we could be developing relationships that were deeper than just one person’s reputation, but multiple reputations along the way. And then you become as opposed to being about John Johnson, the expert, we wanted to make it about an Edgeworth Economics expert is like this. They’re like job, but there’s also a bunch of other people like John here. And so when you turn to us, that’s what our brand means.
Branding is unheard of in the expert witness industry outside of just me, you are the person. And so we tried to turn that on its head as well. So you’re right, a lot of hard work, a lot of scrambling. We have some great stories. We had an issue with a computer where we had an agreement to buy a massive server, something fell apart and we needed a computer to get something done. And it was like 9:30 at night, and we went to office backs because that was where we could go. And my friend and I, my business partner, Matt, we had his car, we’ll go out, we’re like, “Okay, we need the biggest computer you have, we need to buy this tonight.”
And the sales is like, “Oh, well, you’d really like this computer. Here it is.” And he lays it out, “Okay, we’ll take it.” “I’m sorry, I can’t sell it to you.” I’m like, “Wait a second.” I said, “What’s the best computer you have, we want to buy a computer?” Like, “Oh, well it’s this one right here. It’s this gaming computer, it’s got amazing capabilities, but I can’t sell it to you.” I’m like, “Okay, could you bring your manager over.” Manager comes over. I says, “All right, I understand this is the best computer.” “Oh, it’s a great computer gaming.” I’m like, “Okay, we want to buy this computer.” “Well, I can’t sell it to you.”
I’m like, “Okay, what am I? I know I’ve been working a lot of hours, but what’s going on?” He’s like, “Well, I can’t sell it to you for the discount because it’s the floor model, I have to charge you the full price.” I’m like, “I don’t care what you charge me, I want this computer.”

Carol:
Just give the computer.

John:
Now it’s 10 o’clock, the lights in the store are blinking because they’re shutting down, they’re disconnecting the wires to give it to us. We go pay with my credit card, which we were using for everything. And they set off the alarm in the whole store unhooking this computer. And my colleague, Matt and I like, “It doesn’t matter, we’ve paid for it.” We grab the computer, walk out with the alarm going off and shove it in his car and drive off into the night. But we had a need, we had to figure it out, we weren’t going to take no for an answer, and we did.
There are so many of those stories along the way that entrepreneurs have, and we had them, and we still have them, but it’s just the problems become different as you get bigger. So maybe that’s a little bit finer point on the hard work, I guess I did gloss over it in some respects.

Carol:
That’s okay. And I love these stories of perseverance, and those are the types of things we just forget about. So many of us aren’t really back in the beginning stages of our business anymore, you sometimes forget about those very early struggles, but there are lessons that just go on forever. It’s just that extreme unwielding perseverance to just push through, be resourceful and make stuff happen no matter what.

J:
Yeah. I know it’s funny. Well, not funny, but Carol and I have a good friend who is in the expert witness field also, and his company is probably the largest expert witness company in a very niche area, embedded software. And they’ve done some really high profile cases, and he made a mistake that we’ve talked about it before, and I asked him like, “As a business owner, what could you be doing to scale your business and grow your business? What mistakes have you made? What have you learned?” And one of the things that it sounds like he did that you didn’t do was he put his name on the firm. Basically the firm has his last name in it, and he is now the expert.
And so when he gets a call from a big car company like GM to hire him, they want him, because his name is on the door. You picked a name that many people might think there’s the name of somebody in the company, Edgeworth, but it’s not. And so you don’t have that issue of, “Hey, I want Edgeworth. I want him.” “Well, there is no Edgeworth.” “Oh, okay. So you’ve got a lot of great people.” And so it’s one of those things that maybe you didn’t do it on purpose, and he certainly made that mistake, but just when you’re starting a service organization, a consulting-type company, and you’re the expert, it’s probably a good piece of advice to maybe think about not putting your name on the door. Obviously, there’s some benefits there, but there’s also some drawbacks.

John:
Well, and there’s also, this is a little bit more unique to expert witness work, but even that said, there are still times where we get lots of calls, which are like, “No, we want you.” And so one of the things in my business that I know, or the way I always put it is, we’re at a strategic point in our firm where I’m not that old, but I’ve had a great career so far, I will continue to testify, but I’ve had a wonderful career. And so for me, what’s going to fulfill me for the next part of my career is the legacy of this firm, and that can I leave this behind to the next generation of economists to take the firm and run with it?
But that requires a whole different set of skills and work because developing experts, it’s one thing to develop yourself, it’s another thing to develop other experts. And this is true in any service industry. So if you’ve got a certain expertise and you have a staff, how do you create other people that can provide the services from your firm and maybe provide them better, and keep them happy, and motivate them, and want them to still be a part of it? There’s a lot of challenges to that. And so that’s what I spend a lot of my strategic time on now is, “All right, well, how do I make, not just keep this the best firm it can be, but what is this firm going to look like in 10 years? What can this firm look like when I’m not doing this actively?”
Again, I’m trying to think about that 10, 15 years in advance, but that’s a hard problem, and it’s very pervasive in service industries where you really are about relationships and skill sets. And so I think that’s a fascinating issue. And I will tell you, one of the things we do is we always try to use some data in terms of our recruiting and thinking about how do we find the right type of people. I have a hard time sometimes finding entrepreneurial PhD economists because they’re not trained to think that way. So it’s an interesting different set of challenges, but it is fascinating.

J:
Yeah. Especially on the expert witness side, a lot of your success is going to be tied to the personalities of the people doing the testimony, because if you go in front of a jury, they’re going to be assessing you and your credibility, and your trustworthiness, and your mannerisms, and so a lot of that is important. I want to ask the question because we’ve never had an expert witness or somebody who’s had an expert witness company on the show before, but who knows, maybe there are people out in our community who are listening to this who are thinking, “I have a skill, I know more about software, I know more about hardware, I know more about writing books, I know more about real estate.”
Whatever it is that most people out there, and I could potentially use that knowledge to help either the prosecution or the defense side of cases that relate to that topic. How would you recommend, or what would you recommend to somebody who is thinking, “I have this expertise, I want to use this expertise, potentially investigate whether the expert witness world is a place I can use this expertise.” What would you say is a good first or second or third step for them to investigate whether that’s a viable option for them? And if so, how they go about drumming up some business?

John:
Look, I think it’s a tough business to break into cold. So I think the starting point has to be, is there a demand at all for your expertise? And I mean that demand in a legal setting. Maybe there happens to be, like one of my hobbies is poetry, and maybe there’s something out there for like extra work on poetry, I don’t know, I can’t think of that. So I’ll just leave that as my hobby that I do on the side to keep my mind, think about things besides numbers. So the first thing is there really a demand for what your expertise is? And that’s not a reflection on you as your expertise, but it is like, there are certain things that litigated disputes need and there’s certain things that are just not relevant.
And so that could be as simple as doing searches on some of the lawsuits on key terms, there are databases, there’s a publication called Law360, which publishes all sorts of articles about… So you can just do some actual research to see that. And then if you saw or found that there was testimony, expert work, I’ll bet you to look for who are the people that are doing it in your field and see if you can trace that, because I do think it’s very different what the pathway is for different things. A lot of people come from a bigger firm and then move into it, but there are other free agents out there, but you will need to develop a set of relationships.
And those relationships are probably not going to be ones you readily have because they really are with lawyers that are hiring in that expertise. Expert witnesses get hired by lawyers on behalf of their corporate clients, and so although you will be ultimately working for a corporate client, you’re generally hired by the law firms.

Carol:
That’s so interesting. I love that. That’s such a cool, look into that field.

J:
Somewhere there is a poetry copyright lawsuit going on, and those lawyers are thinking, “I need somebody, I don’t have the right person.” You’re that guy.

John:
I’m going to get deposed in some case that they’re going to have looked up my poetry. It’d be like, “Did you write this poem about spring?” I’m like, “Yeah, I did. That’s me. Sorry.”

J:
Okay. Well, we are getting to that point in the show where we are almost ready to wrap up, but before we do, I want to jump into the signal of the show, we call The Four More. And that’s where we ask you the same four questions we ask all of our guests, and then the more part of The Four More is we’d love for you to tell our listeners where they can find out more about you, where they connect with you, where they can get your book, where they can connect with your business. Sound good?

John:
Perfect.

J:
I’m going to take the first question. John, what was your very first or your very worst, I’ll let you pick, job, and what did you take from it that you’re still using today?

John:
I think my first job may be my worst job, but that’s a little unfair. I worked in the Department of Psychiatry at the University of Rochester Medical Center, and I was the office assistant. And so it’s not that my bosses were great, but my job was to file papers and to run mail up to the front of the hospital. But in doing so, it’s a psychiatric unit, so you’re always a little bit, steer clear of people. So that was really my first job in college, and I learned a lot because I was just very diligent, and I think they really liked me. And I also learned that I didn’t necessarily… I just brought my all to the job and I think it encouraged me to…
I always saw a better way of doing things even in that job. And so one day I was bored, so I color coded all the files because I’m like, “I think this would be better.” And my boss was like, “Wow, that’s great. I never thought of that.” I’m like, “There you go.”

Carol:
There you go, I got you something fabulous. Excellent. Here’s my second question for you. What is the very best piece of advice that you have for small business owners or entrepreneurs that you have not yet mentioned here today?

John:
I just think communication is key at every level as a small business owner, communication to your clients, as you start to build your team, your ability to communicate really clearly, and to always be thinking about your messaging, I think is really, really important.

Carol:
Excellent.

J:
I love that. Question number three, you have an amazing book, I’ll remind everybody it’s called, Everydata: The Misinformation Hidden in the Little Data You Consume Every Day, and it’s in the show notes for anybody that wants to pick up that book. I’m a huge fan of books. So besides your own book, give our listeners a recommendation on a book that you really love, maybe one that not everybody has heard of.

John:
Yeah. I was thinking about, it’s not a business book, but I actually love the book, Life of Pi. I try to be a cerebral thoughtful leader and I like self-reflection, and I love book that just speaks to me about those kinds of issues. And so I try to have an eclectic bookshelf, but I think that’s probably one that maybe if you haven’t checked it out, people should read it and see what it says to them.

J:
That’s so weird. I was literally traveling last week and I turned on the TV in the hotel room and that movie was on, and then I watched it. And so I just saw, I might need to pick up the book.

Carol:
That’s right. You should do. And here is the fourth and fun question, we love to ask our entrepreneurs and experts, what is something along the way, and it doesn’t have to be a material thing, it might be an experience, it might be something else that you have splurged on that was totally and entirely worth it?

John:
Well, I have a few, but the one that I think I should been talking about since we’re in COVID is recently I bought virtual reality goggles, the Oculus 2 goggles. And what I’ve started to do is virtual boxing during lunch in my basement. And it’s incredible, the workout is great. My wife is a little bit freaked out, I think, she’s like, “You’re down there again? What are you doing?” One day she’s like, “Are you going to drop dead? You got to slow down.” It’s just like pounding away and breathing. And so it’s been actually though, since I haven’t really traveled very much at all during COVID, it’s actually been a way to go to some other places remotely and just do something different.
So it’s been really good as we’ve gotten to months nine, 10, 11, 12, it’s actually been good for the morale a little bit to have this toy to play with. And I sneak downstairs and find the latest boxer to take on and go at it.

Carol:
That is so fun, J is greed with envy right now. Look at you.

J:
My birthday’s coming up, wait a second. And I can argue that it’s to keep me in shape.

Carol:
There you go. There you go.

John:
It’s a good workout. There’s a really good workout there. I had been running a lot for the first nine months, now as winter came, I stopped like everybody in the winter, a little less. And so I’m like, “Wow, this is fun. It’s got me moving again.”

Carol:
That’s awesome.

J:
I love it. Well, that was the four part of The Four More, now for the more part of the The Four More, tell our listeners where they can connect with you, where they can find out more about you, your companies, your book, anything else you want to tell us?

John:
We’ve actually have a website, we have Edgeworth Economics is the litigation shop, but Edgeworth Analytics, which I think is the group that your listeners might really want to check out, we set up a page on that for www.edgeworthanalytics.com/biggerpockets. And so what we’ll do is we will give away one of our Data Blueprints to one of your listeners who signs up, and that’s where we’re like, I call them our low key office hours program where we just help somebody answer some questions. And we have a new working paper up there on communicating data, which is cool. It takes some of the things from the book, but relates it very purely there. So that would be where I would check it out.
The book is called Everydata, it is on Amazon, you can get it there. And if you check out either company, you’ll find my face somewhere, I’m sure. I know I’m on there.

J:
Dr. John Johnson, thank you so much for joining us. I love this conversation. I think even Carol, who is the least analytical person I know-

Carol:
It was so much fun to learn from you. Thank you. You made it very engaging and relatable. So thank you for that.

John:
Thanks so much. I had a great time and I do love talking about these things as well. It’s so nice to meet you both.

J:
Thanks so much. We’ll talk to you soon.

John:
Bye.

 

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In This Episode We Cover

  • The expert witness and testimony field 
  • Checking your own bias and making sure your decisions are based on accurate data
  • Understanding the context around the data that is being recorded
  • Tracking growth and recruiting so you know where you’re succeeding
  • Using common sense when looking at different data points
  • And So Much More!

Links from the Show

Books Mentioned in this Show:

Connect with John: