MBA Masterclass I Love Cash Flow: Building Intellectual Proof of Concept

Lisa Koengeter: All right, we are going to get started. Thank you all again for joining us... this evening, this morning, for those of you who are joining us from Asia. My name is Lisa Koengeter and I am the director of Admissions for the Executive MBA Program. It's my pleasure to welcome you on behalf of our full-time, our evening, our weekend, and our executive MBA programs to this MBA Masterclass Series on "I Love Cash Flow: Building Intellectual Proof of Concept" with Professor Scott Meadow. So in this Masterclass series, we feature our world-renowned faculty giving you a glimpse inside of the classroom and our very distinct approach to business education. It's what we call the Chicago Approach. And today you are gonna experience that live, and there's two key features of that approach I want to call your attention to. One is our data-driven, our evidence-based teaching, which will give you tools to be able to ask better questions, to think more strategically, and to solve really big problems. You'll have a sample of that evidence-based, data-driven approach tonight as you hear from Professor Meadow. The second component of the Chicago Booth experience that I want to call your attention to is our very collaborative community. Here at Booth, you'll join a supportive network of students, faculty, staff, alumni, who will all be your champion each and every step of the way through your journey as an MBA student. Professor Meadows' participation in tonight's event I think is a great example of that collaborative spirit here at Booth. His generosity to help not only students in the classroom, alumni, but also all of you this evening who are joining us as prospective students. So in true Booth style of this collaborative environment, we encourage questions. We encourage you to use the Q&A box and send us your questions throughout the class this evening. We will save a few minutes at the end of the presentation to answer your questions live. All right, with that, let's meet your professor for this Masterclass: Scott Meadow. Professor Meadow is a Clinical Professor of Entrepreneurship at Chicago Booth. And he is also a partner at the Edgewater Funds and Maroon Partners. Over the course of his career, Scott has approved hundreds of equity financings and he's personally led more than 60 investments -- including two dozen healthcare services companies, over a dozen consumer services and retail companies, as well as many biotech companies. In December of 2011, Scott's activities were recognized by the State of Illinois when he received the Richard J. Daley medal. Each year, this medal is awarded to one single individual who has been an advocate of venture capital and private equity in the state. In addition to all of these accomplishments, Scott is a dynamic teacher in the classroom. He's taught over 10,000 students at Chicago Booth in entrepreneurial finance, private equity, commercializing innovation, introduction to venture capital and our new venture challenge program. He was awarded the Phoenix Prize for Excellence in Teaching four times: the first person to do so. Professor Meadow earned his AB Magna Cum Laude from Harvard College and his MBA from Harvard Business School. And with that, please join me in welcoming professor Scott Meadow. Scott, I turned the mic over to you.

Scott: Thank you, Lisa, thanks so much. And if anything happens to me in the next hour and I should keel over dead or something, make sure Lisa is speaking at my funeral. That was such a beautiful introduction. Thank you, Lisa. OK, well, let's get started. And we've got this fun, this fun kind of cartoon to look at. And we have here really Sisyphus. And Sisyphus, for those of you that don't know, got in an argument with Zeus back in the time of Greek mythology. And he was basically doomed to push that rock that he's carrying up a hill only to have it roll down. And that curse was for the end of time. And so our Sisyphus here is, as you can see, staring at this rock, and what does the rock represent? The rock represents his customers, his employees, his competitors, his suppliers, all there -- his lawyers, his investment bankers: all the people that he, as an entrepreneur, has to think about as he's leading this adventure into a disruptive concept. Now you see this over here, this banana peel. That's supposed to be funny. But let me just tell you that as an instructor in the entrepreneurial world, a person that's got that many things on his mind has 100 percent probability of slipping and falling on that banana peel. So the issue is not so much that you slip and fall on the banana peel -- 'cause there's 100 percent probability that's gonna happen -- the real issue is, you know, have you done enough so that you can get yourself up and keep pushing forward? So that's what we're gonna talk about a little bit over the next hour. So we're gonna talk about the entrepreneur and the investor, and issues impairing that partnership. And so some of those things are, there's a lack of efficiency in deploying capital to private equity projects. Sometimes, people put too much in, sometimes they don't put enough in -- and it tends to create problems. There's sort of limited joint development of the projects underlying profit formula. So an entrepreneur will show up with the profit formula; the investor doesn't know where that came from. There's no systematic methodology for forecasting fixed and variable cost structure of the enterprise. And think about it: If you're starting something up, the riskiest time in the venture's life is at the beginning. And if you can substitute variable cost for fixed, that's gonna give you a much better chance of succeeding. There's difficulty in predicting meaningful milestones for the project. So we would like to put money in, but put that money in against milestones and move the economic formula forward. And then there's a general lack of transparency in the company's forecast. So the investor oftentimes doesn't know where those numbers come from. And then finally, there's limited analytical support for the long-term trajectory of the business. So what do I mean by this one? So I think everybody's probably heard of the concept of hockey-stick projections, right? And that was considered to be, you know, kind of ... It's kind of joke. If you say somebody has hockey-stick projections, that means that they're not really realistic projections. But think about it this way: If you're starting a company that's disruptive to its base concept, wouldn't you expect hockey-stick projections? So the issue is not so much the hockey-stick projections, but what kind of analytical modules have you developed, and what kind of systematic support do you have for those projections? And that's very, very important. So if you've thought about these six things as variances occur, there's no foundation for editing the business concept unless you put that foundation in place. And that's what we're gonna talk about a bit. So just in the way of background. Venture capital, private equity investors only invest in novel sectors that they understand. So what does that mean? So here's some technology, healthcare, financial institutions, industrial, aerospace, infrastructure, et cetera, are all sector-specific niches in the entrepreneurial market that people in the venture business as investors tend to focus on. So for an investment in a new sector or disruptive concept to be palatable to a private equity investor, that private equity investor has to be confident that the idea is novel, that the entrepreneur has the centrality to execute -- which means strategic sector-specific knowledge -- and some kind of operational access to the people that are gonna make the project successful. And most importantly, that the entrepreneur has the capacity to communicate the concept: i.e., smoothing out information assymmetries that exist and that are inherent in such an early-stage investment. So effective entrepreneurs reduce information asymmetry so that they can attract the kind of investor that can make them successful. And how can they tell if that investor can make them successful? If the investor can help them recruit executives; provide access to potential and investors and acquirers; provide introductions to the right customers; coach senior managers; provide industry expertise and strategic perspective; and help editing the business model based on new information. But investors can only add value to the project if they understand the economics and the profit formula and trust the centrality of the entrepreneur. So entrepreneurs must effectively communicate the economics of the business, the profit formula and capital gain opportunity to potential investors. So this is something that probably everybody has seen before. This is a set of forecasts for a new business, OK? Now let's say Lisa and I are partners and we're getting ready to fly out to the West Coast and meet with Kleiner Perkins about our new project, OK? And Lisa thought we ought to show Kleiner Perkins five-year projections that grow from roughly $2 million to roughly $50 million. But I on the other hand thought we ought to show them something that grew from $10 million to $100 million. And we went back and forth, and back and forth on this for quite a while -- and we ultimately settled on these numbers. We go out to 3000 Sand Hill Road, or maybe 4000 Sand Hill Road, and we sit in front of four associates at Kleiner Perkins with our business concept. And we think we're gonna get a lot of questions about numbers but instead, they ask us three questions. Question number one is, you know: Is your project something that you two have experience in, in the past? And we say, yes, that's the case. And then they start to think to themselves, "Geez, have we invested in this sector in the past? Do we have a group of potential executives that could either help Scott and Lisa or potentially join their board and make them better?" And lastly, will Scott and Lisa play ball with our modus operandi in terms of how we want to manage a project? So assuming that we had a pretty good meeting, the team at Kleiner Perkins is gonna go back and they're gonna talk to a partner. And if the partner feels that they can potentially help us and help us in the right way based on the kind of sector-specific expertise that they have -- and the experience that they have in the sector that we're in -- they're likely to come back and ask us for a second meeting. Now when Lisa and I fly out for our second meeting, OK, they're gonna give us a set of projections that are very different than the ones you see before. In fact, they're gonna take out a giant meat cleaver and they're gonna cut through our projections and slice 20 percent off the top. And you know what? There's not a word we can say about it. Because they're not -- they just don't trust our ability to come up with referenceable, credible projections. So what we're gonna talk about a little bit is how we can come up with referenceable projections that hopefully help us, as entrepreneurs, hold on to as much of the company as we possibly can. So part of that process has to do with something that I call analogs, OK? And an analog is a company or group of companies derived from secondary market research and confirmed by personal interviews that mirror the economics, operating characteristics, investment requirements, and customer profile of our new projects. Among other things, analog should allow us to model and communicate project economics for our concept, or target a company, using components that reflect the economics of similar businesses. They help us forecast revenue and its key drivers, things like unit volume and average sales growth or sales price. They help us understand the growth at the unit level and from addition, and the addition of units. They help us predict the cost structure and hypothesize about investment requirements. So selecting analogs requires a little bit of creativity. We aim to find referenceable data about the economic drivers of the project. So what we're looking for are companies with similar revenue models and comparable payment terms in the same line of business; with similar cost structures that pursue the same customers; that follow the same business and economic cycles; that require a similar level of initial investment; require the same type of human capital; and have similar working capital characteristics; and require operational access to similar resources that are out there. So if you're scratching your head and saying, "Geez, what is an analog?" I think most of us have heard of the company Staples that sells office products. Well, I was fortunate to be involved in the startup of that. And if we were thinking about what are the appropriate economic variables that go into the Staples profit formula, we would look at an analog like Home Depot or something like that. So Home Depot would be an analog for Staples. If we look at the economic variables associated with making Home Depot successful, similar, those economic variables will be helpful in helping us understand Staples. So that's what an analog is all about. So in coming up with the appropriate analogs, we have to do some marketing research. And the first kind of marketing research that I'm gonna talk to you about is something that you're all familiar about -- and that's secondary marketing research. So if you Google something, that would be an example of pursuing secondary marketing research. Secondary marketing research is something that was written by somebody else about a topic that we are interested in. And we access that to learn from a secondary source information that will make us knowledgeable, a little more knowledgeable about the business. So this is an example of secondary marketing research, OK? So this is a -- an equity research report developed by J.P. Morgan. So this is secondary marketing research because it's a report written by this group of people about a company called Bad Bath & Beyond. But I'm gonna use this as an example of conducting something that I'm gonna call personal research, which helps you fall back on -- which asks you to fall back on your own personal social capital. So imagine that we are starting, that Lisa and I, the business that we wanna talk about is a high-end bath and towel company. So we're selling very expensive bath and towels in a 5,000-square foot store. And so we thought it would be a good idea to get, to not only read this report -- which is accessing secondary marketing research -- but also call up the people that wrote this report and conduct personal research to help us understand more about the business. So we place 100 emails to Christopher Horvers, CFA. And he does not answer. You know why? Because he's Christopher Horvers, CFA. Then we call him 20 or 30 times. And he doesn't pay any attention. You know why? Because he's Christopher Horvers, CFA. Well, if he's Christopher Horvers, CFA, that means he's not Christopher Horvers, partner; Christopher Horvers, managing director; Christopher Horvers, vice president; So Christopher Horvers is hanging on to the bottom rung of the ladder, trying to climb up that ladder. So he's not going to take the time to talk to Lisa and I about our idea because his base business is writing equity research for institutional sales people at J.P. Morgan who sell stock to big companies like Ford Motor Company, CalPERS, CalSTRS, and people of that sort. So he's not gonna take any time talking to us. But that's OK 'cause we look down here and we see Garrett Castellani. Now Garrett Castellani went to Duke, which is a school in the Southern United States, it's a pretty fine institution. He played lacrosse. He was in a national fraternity. He then went to Booth, got his MBA, and now is working at J.P. Morgan. And so we reach out to Garrett and we ask him if he'd be willing to talk to us about Bed Bath & Beyond. And the thing about Garrett is that nobody talks to Garrett, OK? So Garrett, you know, on Saturday nights he'll go to a cocktail party. He'll hand out his business card. It'll say Garrett Castellani, you know, Associate, J.P. Morgan. And he can thump his chest and say that he's an investment banker. But then, on Monday morning, he's gonna return to the office: into a four-by-four office with no windows and with just enough space under the door so people can shove pizza and Red Bull to keep him going 120 hours a week, you know, cranking out information. A matter of fact: Many of you probably understand that it's Garrett Castellani who wrote 70 or maybe 80 percent of this report and everybody else was proofreading. So if we can reach out and get Garrett to talk to us, then he's probably gonna provide us with a lot of very important information. And so if we go back and we look on LinkedIn or Facebook or some other social media vehicle, there's probably going to be seven degrees of separation between ourselves and Garrett. And if we pick up the phone and in a very nice and very calm way, say, "Garrett, hello, my name's Scott Meadow. I heard wonderful things about you as a lacrosse player. We were in the same fraternity. I went to Colgate, you went to Duke. I wonder if you would have a few minutes to answer some of our questions about a bath and towel concept that we're trying to start, that Lisa and I trying to start." And guess what? Garrett is happy to do so because nobody talks to Garrett. So Lisa and I ask our first question; 15 minutes later, he answers our question. We ask our second question; 15 minutes after that, he answers that question. We asked our third question; 15 minutes after that, he answers that. And we're tempted to go to a fourth question, but we don't wanna push our luck. So he answers all those questions. We ask Garrett, "Is it all right if we call you back if we have any more questions?" He says, "Absolutely, no problem. Call me back any time." Think about it. From his standpoint, by talking to us he feels a little better about himself. And he walks out the door of J.P. Morgan at 12:15 in the morning as opposed to 11:30 at night, just because he spent a few minutes talking to us. So once we've been able to find a series of people like Garrett, then we put together sort of a list of people that we're going to interview. And let's take somebody like Alex Tang. We set this up in such a manner so that we have -- we have background here so that we could talk about, you know -- kind of grease the wheels a little bit to ask him the really tough questions. And then we have over here, the kinds of topics that we hope to address with Alex and with all the other people that we've been able to reach out to. So personal research should address key aspects that we think are linchpin variables in terms of making our concept successful. So how do we go about that? Well, first of all, there are quantitative factors that we need to understand. So some of those had to do with the operations of the business; the income statement; the balance sheet; the cash flow; growth; and things of that sort. So these, what we've listed, are factors that we need -- that we need to be informed about, and that we think are important in terms of understanding our new concept. And then we list the rationale for why we think those particular issues are important. For example, advertising and marketing expense. We need to understand the amount spent to produce given revenue in this particular project. So we want to highlight the factors that we need to be informed about and then look for analogs, which I've listed on the right hand side of the sheet. These quantitative analogs will inform us about the factors that we have across the top. So this information, these factors, we've flipped and we've put on the horizontal and we've used analog companies -- like the ones that I've listed here -- to inform us about these factors. Now ... hey Lisa, can you read that particular number for me right there? I'm joking, Lisa. You don't have to do anything. The point is that you're probably wondering, "Scott, why are you showing us such messy slides?" Because I'm going to talk to you distinctively about the red boxes. Because those are the areas, those are the things that I think are the most important. That being said: Since we're partners and we're joint and several -- which is a legal term that means, that if I do 10 bad deals and you do 10 good deals, and my bad deals cancel out your good deals, then you don't make any money. OK? So therefore, you are going to be inclined to look at the information that, that my team and I have been looking at and see if there's something there that you catch that will help make the project successful. So I'm talking about the red boxes but I'm leaving the rest of this available because your economic self-interest is such that it's highly likely that you'll take a good look at what I've got here, and hopefully find something that Lisa and I missed, and point it out to us in the future. So once we've come up with the appropriate analogs, the next step is to develop what is known as a unit model. Now there's lots of conversation about unit models and a lot of flapping about it. But a unit model emerges from the analogs. And a unit model seeks to explain the profit formula based on a rational economic segmentation of the business: like a single location and an account for something like a enterprise software investment; a tribe, a region, a specific new drug. So analogs provide information on the individual unit. They help us build up the economics of a concept that has never existed before. And so we construct a unit model to evaluate the profit formula of the business in microcosm. So another way of saying that is we construct a unit model to evaluate the profit formula, using the least amount of capital possible. And the reason is, is because the most expensive money that we're going to acquire to fund this project happens at the beginning. And so therefore, what we're trying to do is prove that this works using the least amount of money. Easier to get funded from the venture capital community and probably easier for us to execute. So in constructing a unit model, we use analogs as the building blocks of revenue cost, working capital and unit level investment, as well as direct costs like normalized SG&A and CAPEX. So let's go through some simple, simple terms that I think everybody's familiar with. Revenues minus cost of good sold, minus operating expenses, equals something that I call "unit level profit contribution." And then if we take unit level profit contribution, I'm suggesting we subtract out something called "normalized SG&A" -- which equals earnings before interest, taxes, depreciation and amortization. So what is normalized SG&A? So what we're trying to prove with this unit model is that the unit we're trying to evaluate, the profit formula. And in evaluating the profit formula, we have to look at the unit model under normal sort of circumstances. And so let's say it may cost us a million or a million and a half dollars of overhead to get our business started. But if we are opening a single unit and we allocated all that money to the single unit, it would come out with a negative profit formula and we would probably never invest in the company again. So instead, we look for an analog that represents what the SG&A of the company is likely to be when it is more mature. So, we might, if we were looking at setting up something like Staples, we might go back and look at Home Depot and see that they're spending normalized SG&A of 2.5 percent. We may borrow that 2.5 percent from Home Depot and apply it so that what we're getting is a true measure of an evaluation of the profit formula. So: EBITDA minus depreciation and amortization -- and all the other things that we generally see as part of the P&L and cashflow statement -- take us down to unit level cashflow. Which brings us down to the bottom of the page. And the bottom of the page is a mechanism for evaluating the unit model. And this is a unit model, OK? And we basically take it out for 10 years. There's no terminal value or value that we would sell the business for, OK? And this is the investment that we're going to make in the unit model at time zero. And we're discounting these cash flows back against this unit level cashflow. And that gives us a 10-year internal rate of return of 38 percent. And you probably say, "OK, well, Scott, what's so special about 38 percent?" Or what's so special about 30 percent? Well, when I first got to Booth about 20 years ago, I took all the projects that I had written up. And I think it was about 60. And I was able to get another 50 from friends of mine in the industry, and colleagues of mine, or teaching assistants of mine; looked at each one of those companies; and put them each in a unit model form. And what we found is that a business that had a, an internal rate of return at the unit level of 30 percent had a 80 percent chance of being successful. And a business that had a 10-year unit model IRR of 25 percent had a 40 percent chance of being successful. So that made 30 percent very important to us and we always seek to look for concepts that can generate at least 30 percent. But the question I've gotta ask everybody is, what grade would you give the student that put this particular analysis together? I mean, it's a pretty fancy little piece of analysis. It looks like a nice job of Excel spreadsheeting here. Well, I would give this student a D-minus. OK? Why a D-minus? Because just like when Lisa and I walked into Kleiner Perkins' office, there is no references as to where any of these numbers come from, came from. So therefore, we can expect that nobody is gonna take them seriously as a result of us not providing background as to where these number came from. So a better example of what things should look like are what we have here. And what you see in every row for this particular unit model, we have individual footnotes that talk about where each one of these numbers came from and what our assumptions are associated with that. So we clearly state the assumptions and sources. We include references to complex calculations that might have come up, and we give the reader a basis to make adjustments in case one of our colleagues looks at this and says, "You know what? I don't think -- I don't think that it's reasonable for service revenue in this year to be at this number. I wonder where he got that from. Oh, I see. Well... It's still wrong -- but at least I know where it came from. I can sit down with Scott. We can together come up with a number that we think is more appropriate and make an adjustment." Remember we live in an Excel world. And what we are looking for is a set of numbers that is transparent, that everybody understands, and that everybody has contributed to -- so that everybody's singing from the same hymnal. So this is a unit model that I would give an A to. So: How do we determine whether or not a unit model is a good business model or not? Well, let me suggest two very important features. One is how much cash is required to invest in the unit model with zero being fantastic -- right? -- and $3.5 million being a lot of money to put into the unit model, OK? So how much we put into the unit model is important. The other dimension is how long does it take for the unit model to be cash-flow positive? OK? Well, the best is zero. It's cash-flow positive right away. Not so good is six years. So what you see in the red box in the upper right-hand corner is a pretty good model: a model that gets to cash-flow positive in about a year and is in probably the $200,000 or $300,000 investment dimension. So at this point, let's take a second and talk about the four different types of unit models. So the first one is a physical location or a store. So what would be an example of that? Well, a retail store, a lab facility, a production plant, a geriatric community, a hospital, et cetera. OK? And as we're trying to understand that, if I gave you a set of numbers, talking about the total initial investment at the unit level, OK? And you see these dots here and all this information over here? Pretend that there's nothing there and all you have is the numbers. And let's say that this is a sporting goods store that has never existed before. And the initial inventory is $2.3 million. And you look at that and you say, "That's interesting." And then your eye goes down the page and you say, "Geez, accounts payable." So Scott's saying to me that the trade, since this is a sporting goods store -- Wilson's Sporting Goods, Nike, et cetera -- those kind of vendors are willing to finance half the inventory. Wow. And this is a concept that has never existed. I don't believe that that's gonna happen. That doesn't make any sense to me. And you fold it up, and you put it away, and you go work on something else. But now pretend that everything on the right is visible -- and you can look at analogs like Best Buy, Oshman's et cetera -- and you can see that the number and the accounts payable that I talked about, we actually observed in analogs that we were able to use to research the investment associated with this particular company. So I think everybody's pretty familiar with what a facility-based model would look like. An individual McDonald's. An individual Staples. A healthcare facility like Sunrise Assisted Living. And we end up getting a 10-year IRR here that's pretty, pretty attractive. So that's a facility-based unit model. A geographic-based unit model is a little different. So let's say that Lisa and I were starting a business that, well the business that we're starting is the Dove Bar business. And I think everybody's familiar with a Dove Bar, right? It's that delicious ice cream treat. It's got about 6 percent butterfat and, you know, this much delicious chocolate around the outside. You take one bite and you go into diabetic shock, OK? Everybody know what I'm talking about? OK. So let's pretend that Lisa and I -- the company actually started in a small town between Chicago and Milwaukee. And let's say that Lisa and I go up to Milwaukee, and we go in to see the frozen confection buyer at 7-Eleven. And we're trying to make our case about how fantastic our Dove Bar is. And, you know, the buyer, whose name is Jane Wilson -- Jane just, you know, she didn't really get it. So Lisa rips open one of the Dove Bars, sticks it Jane's mouth: Jane takes a bite. She's sold. OK? And she asks us to wait in the waiting room. And so Lisa and I go out in the waiting room. She calls some of her colleagues -- the frozen confection buyer at 7-Eleven that's out in the Phoenix area, in the Atlanta area, et cetera -- and she calls us back in and she says, "Listen, Lisa and Scott, we are so excited about your Dove Bar that we wanna put it in every 7-Eleven in the United States." Right? And Lisa and I are so excited that we're already picking out what color metallic paint we're gonna get on our new BMWs after we sell our stock in this fantastic investment. But before we walk out the door, we sort of think to ourselves, "Geez, if we are just supplying 7-Eleven, then fundamentally we become a house brand for 7-Eleven and 7-Eleven controls us in every possible way." So Lisa and I go back in and we say, "Jane, listen, what we would like you to do: We're just a small company, OK? And what we would like you to consider is just letting us supply 7-Eleven stores in the Milwaukee area. Now we know that that's a big hassle logistically for you. But if you allow us to test our product in your stores in the Milwaukee area, we will give you an exclusive in the convenience store vertical for 18 months." Well, Jane likes that and she says yes. Lisa and I we've got something good going. So we go over to Kroger and we have the same conversation with Kroger, OK? Lisa has to shove the ice cream bar in the mouth of the person that we're talking about. And we tell Kroger, "Listen, if you let us just service the Kroger stores in the Milwaukee area, we will give you an exclusive for the grocery chain vertical for 18 months." When we're done there, we go to Walgreens. Same conversation, just Milwaukee, 18 months exclusive. And then lastly, we go to Costco and same thing. Just Milwaukee, 18 months and exclusive. Now think about what we've got in Milwaukee. We are doing business with four national distribution channels, OK? And in addition to that, when we're trying to sell a product like the Dove Bar, we have to advertise that product on TV or people aren't gonna know what we're talking about. We can't do banner ads effectively on the Dove Bar. But that's OK because we can buy advertising on a regional basis -- which means that we can hit Jane in the head with as many advertisements in Milwaukee about the Dove Bar as Coca-Cola can hit Jane in the head with. So what do we have in Milwaukee? We have a geographic regional unit model. In essence, we have a national business in microcosm because what you can see is complete proof of concept in the Milwaukee market. So that's what, that's what a geographic unit model looks like. Least amount of money going in to prove the model. Now all of these models are a little different. So if I was a venture capitalist and I was to walk in to a partner meeting with everybody that I'm talking to, and I was to say to you, "We need a million and a half dollars to finance Dove Bar and $500,000 is going for advertising," you're not gonna be very impressed with that -- but because I haven't told you how we're gonna spend the money on the advertising. So therefore, we're gonna use an analog like this, which is the marketing program for a consumer services concept. And what I'm going to show to you is how much money is being spent and how we intend to spend it by media. And on top of that, we're going to monitor the concept on a weekly basis, which should allow us to fine tune this as we go forward. So it's very important that we provide data at every step of the way for an emerging concept. Let's talk a little bit about a technology-based concept. And a technology-based concept is, is structured around the amount of money that it takes to develop the technology and introduce it to the market divided by the number of accounts we're likely to get with our first version of the technology. So let me, let me just see if I can show you an example here. So here we are building up the cost of generating -- and this, by the way, is a real project. Venture capitalists spent $35 million on this particular project. And this is their homework, OK? So let's take a look. So the first thing they did -- and the product that they invested in is enterprise software -- so they built this up. This is, as you can see, the estimated lines of code, lines of code per programmer, et cetera, et cetera. Which gives way to the number of programmers they're going to need, et cetera. And that comes out to about $483,000, and about $100,000 of hardware. And you could see, we have references over here where every single number came from. And if you were thinking, "Geez, if I'm going to adhere to his method, am I going to have to make 40 or 50 phone calls?" Well, if you're a sector-specific expert, you'll probably be able to get the work done with three or four phone calls. But the people that were putting this forward assumed that our $583,000 R&D investment is divided by 50 accounts. OK? Now this is enterprise software. So when we say enterprise, we're talking about, you know, Ford Motor Company, or United Healthcare, or something like that. So what's the likelihood -- OK? -- what's the likelihood that a company like Ford Motor Company or United Healthcare, that there's gonna be 50 of those that are going to buy enterprise software from a company that's never existed before? You see my problem? That's a problem. So we come over here. But if the initial investment of 583 is allocated over 50 units, then at the unit level, we're only investing $12,000 and we get a tremendous outcome. A 66 percent, 10-year internal rate of return. Now I'm sure everybody that's tuned in knows pretty clearly that there's no way we're going to be able to sell 50 enterprise customers in our first year. In fact, it would be amazing if we could sell three of them. But just to be polite, let's say one of my partners sticks their hand up and says, "You know, Scott, just for the fun of it, run these numbers, but just put in 10 units instead of 50 units." And when we do that, looking at dividing the 583 by 10 units, it drags the 10-year IRR down to 15 percent. Now, the unfortunate thing that I've gotta tell you is this is as far as my venture capital colleagues went and then lost all $35 million of their investment. When in fact, had they just thought about things in a little bit more rational basis, this would've been a turn down from the beginning. So the last unit model that I'm going to talk about is something called a specialized asset. And this is predominantly used for biotech. Now since we're moving up towards the hour, this is a very interesting model, and it also goes out for 10 years, But it's a little different because we have to get through a process that's for a biotech company that is overseen by the FDA. And that's why you see pre-clinical, phase one, phase two, phase three. And then over here, you see an infusion schedule of money that is put in without equity by large pharma companies, hoping to get something that I call episodic drugs launched, financed by venture capitalists. And then over here, we see that ultimately, this business makes nothing, makes no money throughout its life. You see all those negative numbers? But right here in year five, somebody comes in and buys the business, and that's the positive, that's the positive cash flow that gives us a very attractive unit model. Now, what you need to understand is that a specialized asset unit model that's coming up with a new kind of antibiotic called Cethromycin is really interesting thing to talk about. But you can't hear the end of the story until you take my class, Commercializing Innovation, which I hope you will when you come to Chicago Booth. Thank you all for sitting through my discussion. And I think we have time for some questions.

Lisa: Professor Meadows, this was amazing. Thank you for the time. We have a number of questions that have come in. If you have time to take a few live, I would love to pose a few questions and I'm gonna have my colleague Zach help me as well. So Professor Meadows, the first question I have for you: "What are common missteps or oversights in constructing unit models? Which of these can literally more costly than the others?"

Scott: Well, I think the most, the most critical item is segmentation. And what I mean by that was the technology venture that we were looking at. If we go through the process of coming up with the amount that it costs not only to develop the product, but also to market it -- because you've gotta remember that technology companies don't fail because of the technology; they fail because of the marketing. So once we've accumulated all those costs in the denominator, then misjudging how many customers we are likely to get and what the sales cycle is likely to be for a new and emerging company, that can destroy a business. Particularly in the very important technology sector that we're all pursuing in various ways today.

Lisa: All right another one for you, from Gillan: "How does the need for valid unit models change with funding rounds? Should the models change across funding rounds: say, between Series A versus D, where concept objectives have changed and the business model has proved to be more believable with each round? Thoughts on that?

Scott: So that's a thoughtful question, Gillan. I hope you're an admitted student. No, I think the important thing about this is, we are going to be constantly refining this unit model. Right? Every week, every month, constantly refining it. And when we fund a venture like this, we're hoping that the money that goes into the company in the first round of investing is really enough money to take us through the proof-of-concept stage. And so during that period of time, we basically have been able to learn a lot more about the analogs that we've used, and whether or not they're appropriate or not appropriate. And then, how this is likely to look in the future as it moves to a stage in its development that's more mature. So the unit model is absolutely essential, whether you're doing making a venture capital investment or you're spending a billion dollars to do a leveraged buyout. Because the unit model applied in the leveraged buyout is equally important because if the unit model is not running effectively, you'll go bankrupt and lose all your money in that leveraged buyout. So you're constantly refining, constantly updating, and getting a better and better understanding of the true economics of the business the longer you live with it.

Lisa: Excellent. And a question here from Roland: "How do you find an analog if the company is a totally new concept, maybe like a SpaceX?"

Scott: Well, because we're not, we're not looking for an analog for the whole company. OK? That's very important. Since I was just giving a short talk, I did use a company to illustrate what an analog means. And so I used, I used Home Depot as an analog for Staples. But that's what not what we're going to to do if we're working together on stuff like this. We're gonna break the unit model down into really four pieces: Revenue, cost, working capital and investment. And then the factors that go into revenue -- that go from revenue to total revenue, from cost to total cost -- those are each going to be individual analogs. So the way we can effectively research the concept is to basically go in and get a good understanding of those individual factors, and find analogs for those factors. We can't, we obviously can't find an analog like the Home Depot analog for a concept that's never existed before. But the individual components that make up the microeconomics of the concept have existed in one form or another in the past. I don't know enough about the company that you referenced to use it as an example in our short amount of time. So I hope you forgive me for answering the question that way.

Lisa: That was perfect. Thank you. Aperva would like to know: "Can you have more than one type of model?"

Scott: Great question, Aperva. I hope to see you in Commercializing Innovation also. Can you have more than one kind of unit model? Well, let's take something -- let's take something relatively easy, like Burrito Beach. Burrito Beach is a fast-casual restaurant chain that locates in office buildings, and you can just run down and grab yourself a taco and go up to your desk. So the food on a one-to-10 scale with Chipotle being a 10 is like an 8 1/2 but the convenience is an 11. So now I did that big explanation, Lisa and I forgot -- now I remember the question.

Lisa: More than one type of model.

Scott: More than one type of model, OK. So in that particular example, we would have to understand the unit level economics at the individual restaurant level. So that's one unit model that we would need to understand. But we're not gonna open up one Burrito Beach. We are going to saturate a geography with Burrito Beaches. So in that case, we would have to understand the unit economics at the individual restaurant level and the economics at the geographic level because that's how we're rolling the concept out. And then in addition, we're probably going to have to develop software that helps the customer interface as well as helps us prepare the food for the customer as well. So in that one example of some, you know, of a fast-food restaurant chain, we're gonna use three different kinds of models to understand it.

Lisa: Excellent, thank you. Catherine has a question: "When is it viable to transition from using analogs to create supportable forecasts, into using actual data from the company itself? If a company differs significantly from its analogs, how do you determine if this is a red flag or a potential differentiator?"

Scott: Well, if it's different from the intellectual proof of concept that we have on paper, then we are constantly going to revise our intellectual proof of concept that we have on paper. So we have our model on paper. We have the concept being actualized in the economy. And as we see, as we experience the actual history of the business as it unfolds, we're going to continue to change our unit model to reflect reality. Now, at some point, Catherine, we may decide that after being in business for a while, we were really off on a couple of very key, what I call linchpin variables or factors in the unit model. And that in fact, the unit model is generating a rate of return based on our changes of 20 or 25 percent. If that's the case, then we're gonna look at each other, entrepreneur and investor and say, "Listen. I think you did your absolute best on this. I committed $15 million to this particular project. We've invested a million and a half, and it doesn't look as though this is going to work based on the factors that have appeared as we tried to actualize the concept in the marketplace and let's close this project down. And look, I'm not mad at my friend, Zach, because he lost a million and a half dollars of my money. Thank goodness he didn't lose $15 million of my money. So I'm gonna invite Zach in and say, "Zach, you are a great entrepreneur. You're data-driven. We preserved my capital. Why don't you take a seat in my office, come up with something else and I'll fund you on that project as well."

Lisa: Great. I wanna be mindful of your time, professor. So I'll ask one more question from our audience from Dipdy. She would like to know: "What is a good margin of error to consider in these forecasts?"

Scott: Well, there is no margin of error. We're always working within 100 percent outcome. And what I mean by that is we've done enough research such that the numbers that we're putting forward in our projections are numbers that we truly believe in until they're proven wrong -- at which point we will replace what is wrong with what is right and we will continue, continue to go forward. Now that, what I wasn't able to really talk about here is how we're monitoring a project as it gets actualized in the economy. I mean, we're sitting there having a conversation: if Zach is the CEO of the company, and I'm the venture capitalist, I'm gonna be calling Zach every Friday and talking to him about a series of issues that I think are particularly important, and that he thinks are important -- every Friday. I'm never gonna call Zach up and say, "Hey, Zach, you were 20 percent off this week in this particular cost component. Why?" I mean, that's malpractice on my part. I'm supposed to already know the economics of this business. And so I call Zach up and I say, "Zach, it looks like we got a problem with this particular issue. I mean, is this a one-time occurrence or do you think this is likely to be an indicator of what the long-term economic model is likely to look like?" And based on that, we make an adjustment and we, we go forward. If he says, "I think this is what's permanently gonna be like" -- If he says, "This is what I think it's prominently going to look like," then we're likely to change the number, have a new unit model and continue to go forward until it indicates that we either shouldn't, or we should go faster.

Lisa: Outstanding. I'm gonna ask you one more question around a favorite book. Anything that you recommend to the folks that are on the call tonight, considering Booth, wanting to learn more about this topic, what's a favorite book that you would recommend?

Scott: Well since, you know, I'm an entrepreneurial ... I'm an entrepreneurial educator. But I'm also an English major. So let me see if I can put two of them together.

Lisa: Great.

Scott: So try "Moby-Dick" as a book I'm recommending. And everybody scratch -- why Moby Dick? Well, so ... Captain Ahab, who's the protagonist in "Moby-Dick," is an example of an entrepreneur who literally does absolutely everything wrong. So if you read the book and you watch everything Ahab does, you'll have a good idea of all the things that you shouldn't do. What do I mean? Well first of all, he loses all of his investors' money. Second of all, he is an egomaniac and is chasing, chasing after a market that he's never gonna be able to penetrate. And he gets all of his, all of his employees killed. So, you know, all in all you'll have a fantastic read and you'll also see a whole bunch of things that you never wanna do if you're lucky enough to get funded as an entrepreneur.

Lisa: Outstanding. That's fantastic. This has been really thought-provoking based on all of the questions in the chat. I wish we had more time. Join us at Chicago Booth and you can have more time with Professor Meadow. Professor Meadow, just a few things I'm seeing in the chat in terms of thanking you and how fantastic this session was. Rashida said, "Thank you, Professor Meadow for being here tonight. Your initial overview at the onset of this class was a perfect summation and explanation for how the show 'Shark Tank' works." Caitlin, "This was fantastic. Thoroughly enjoyed this. Thank you very much." Gillan who asked one of our questions. He responded to say, he's applying this fall; this was a great session and thank you. So thank you for the time, the insights and your thought leadership. And with that, we are out of time this evening. And thank you to all of you who have joined us. Keep an eye on our Masterclass series, our website. We have a number of faculty who we are featuring throughout the spring quarter. And you can tune in to more sessions like the one you heard today, and you can also review the recordings from past sessions. So with that, Professor Meadow, thank you. Zach, thank you for helping with the Q&A box. And to all of our attendees, stay healthy, be well, and we hope to see you here at Booth. Take care.

Scott: Thanks again. Thank you, everybody.

Lisa: Bye-bye.