Return On Invested Capital (ROIC): The Paradigm For Linking Corporate Performance To Valuation

Return on invested capital is the single most important metric for linking corporate performance to valuation because it is the best measure of profitability. New Constructs is dedicated as a research firm— we have been since 2002— to providing the best measure of return on invested capital and the best tools for valuing companies to investors in securities across all market caps and eventually all regions of the world. Our agenda today is going to be very simple. We're going to cover 5 items. This presentation is available for you to download from the video at any time, as you can see in the link below. We're going to cover the core principles behind return on invested capital, why more investors don't use ROIC. If it's so great, why doesn't everyone use it? How to calculate it, how to scale those calculations, and I'm gonna provide some additional resources so you can have a better sense of exactly what it is we do and how to apply it. Everything begins with our core beliefs, and that focuses on the purpose of the capital markets is to allocate capital to its most efficient use. And this, I believe, is a key driver to improvements in standards of living around the world. Our investing principles based on this underlying belief is that real cash flows matter and that superior profitability is ultimately rewarded by the market. Now, how do we execute on that? How do we stand up for our beliefs? Well, that means you have to find the best measure of profitability. We believe that to be return on invested capital. And we believe that the relationship between return on invested capital And stock valuation is very intuitive. That's because over the long term, the market assigns the most value per dollar invested in the market to the companies that produce the most cash per invested in the company. Makes sense. You make a lot of money as a company based on the capital that's invested in you. Well, the market's going to give you more valuation relative to the capital that people invest in you. And a bedrock observation is in this regression analysis. You'll see this in a lot of our work. But what we've found is that the correlation between return on invested capital here and enterprise value to invested capital here— both of these are an unlevered measure of profitability, an unlevered measure of valuation. Enterprise value to invested capital is like a more sophisticated price-to-book. But the main number you want to focus on here is this 59%. It says that return on invested capital explains 59% of the changes in enterprise value to invested capital for the S&P 500. In effect, return on invested capital explains 59% of the changes in valuation for the S&P 500. And you'll see throughout our, our research that this correlation holds in larger sample sizes and smaller sample sizes. So if return on invested capital is so great, why doesn't everyone use it? Well, this is a link to a white paper that goes into more detail, but I'm gonna hit the high points for you. The main key things are that too many people are focused on other things, and ROIC is actually too much work. As simple as a concept it is, it's actually a lot of work to execute. But let's first focus on what the investor population looks like here over the last 10+ years. This data comes from a study by a professor at Wharton at University of Pennsylvania, Brian Boucher. It was done as far back as 2004. And I would submit to you that I think these numbers have probably gotten even more skewed toward closet indexers, right? And this is a survey of institutional investors, how they would self-describe. 61% self-described as closet indexers, 31% described basically as describe themselves as traders. Only 8% self-described as what we would call a value investor— dedicated, low turnover, and large stakes, right? Concentrated portfolio, not trading a lot. That's your traditional value investor. And I would submit to you that I've met with most of the people that would self-describe as 8% over the last several years, for the last 10, 12 years, and most of the— even a large portion of those aren't truly as dedicated or as value investor as they would like to lead people to believe. So the takeaway is there's just not many people out there that actually want to truly be investors. Either they're just following what everyone else does as a cloud indexer, or they're traders, right? Very few people really even self-describe on an institutional level as value investors. And I think there's also a big issue with respect to understanding the difference between entertainment and investing. You know, and, you know, Jim Cramer is a super smart guy, awesome guy, awesome entertainer, right? Great entertainer. It's not really investing advice. In fact, if you read the disclaimers on the shows, they'll tell you that. If you read the disclaimers in a lot of places, you'll be surprised by what they say they don't do or that they do do, right? Also understand that some of these folks are your competitors. They've got access to meaningfully better resources, right? And they don't want you to know what the real return on invested capital is. Because it gets in the way of selling more stock, selling more advertisement, or their earning outsized returns. You also need to recognize that companies are not on your side. I've been reading filings and the footnotes since the mid-'90s, and if there's one thing that I can take away from that is that companies care more about obfuscation than they do about transparency. And this is one of my all-time favorite quotes. I'll never forget when I read this. In the book, The Smartest Guys in the Room, talking about the Enron situation. And on the COVID of the company's in-house risk management manual— and just so you know, in terms of background, the risk management division within Enron grew to be many times larger than any other division in the business. And their goal was to do what I'm about to read to you, right? It had nothing— they had more people working on how to get around accounting rules than they did people actually working on the business. So, the manual said, reported earnings follow the rules and principles of accounting. These results do not always create measures consistent with the underlying economics. Something you hear me talk about a lot. All right? And Rod's saying the same thing. However, corporate management performance is generally measured by accounting income, not underlying economics. Therefore, risk management strategies are dedicated— are directed at accounting rather than economic performance. In other words, we're trying to boost the accounting to make sure our executives get paid more. We see this all the time in our analysis of non-GAAP earnings, which you can check out on our site and find more— tons of articles on as well. The other thing to keep in mind, disclosure trends are not your friend. More data, more noise. Filings have grown to 200+ pages on average. They're increasingly complex and time-consuming, and accounting rules are constantly changing. I can't— look, FASB's got a tough job. I mean, businesses are more complex and more dynamic. Accounting rules have to be more complex and more dynamic in order to reflect that. And I think they're doing a great job at FASB at providing investors more and more disclosures. That means there's more work for investors to do, but guess what? I'd rather have more work to do and be able to figure out what's going on than for us to not have that data and disclosures and have no way of knowing what is going on. So don't blame FASB for making filings longer. They're doing you a favor. They're giving you the information. It's not your fault that you may not have time to do the work. It's not FASB's fault that you may not have time to do the work. And with respect to the SEC, they struggle under the mountain of data. They struggle under the mountain of data. They lack the technology to go through and understand what's going on. And we've been working very hard to help them with that, giving them plenty of examples of where balance sheets don't balance, income statements don't add up, disclosures are missing, things that our technology helps them identify to free them up to focus on higher-level stuff. And not just make sure companies are following basic rules. Here's the trend with respect to disclosures. The average length of filings back in 1998 was well under half of what it is today. And when I started this work in the mid-'90s, a long annual report was 30, 40 pages. Now a long one is 2,000 pages. It's a lot of work to go through these filings, and there's no substitute to going through the filings in order to get return on invested capital right. Every one of the blue underlined items in this presentation takes you to a link that provides more detail. But now let's talk about how to calculate return on invested capital. It's not hard. The formula is simple. The calculation is hard, I guess, in terms of getting the data right, right? So return on invested capital, easy concept, hard to execute. Just NOPAT over invested capital, or net operating profit after tax Divided by invested capital. And note, you can break return on invested capital down into more discrete drivers. The NOPAT margins, which you multiply times invested capital turns, and that equals NOPAT divided by revenue times revenue divided by invested capital. Or income statement performance, operational performance versus capital efficiency. Easy concept. However, Huh. Getting to the data or getting the data right is very difficult. This is a quick list of all the adjustments you need to make in order to get the NOPAT and the invested capital right. Here's a link to all the white papers on these adjustments. And the big takeaway is we're trying to convert the traditional P&L to the economic P&L. And these are kind of the key differences here in red, right, that we— that are between— that are key to understand and understanding the difference between economic P&L and traditional P&L. Based on the adjustments we show on this page. So what are your options? You can calculate return on invested capital on your own, but most folks don't have the time and expertise to dig through the long filings and model these adjustments. You can get it from someone else, and I would say, who? Most of the time, people are left with no alternative to relying on inferior metrics. We have some white papers here on suboptimal metrics. And again, you know, do you ever hear Cramer talk about return on invested capital? Almost never. And we've got a white paper here also on independent research and its importance. Some of the best research in the world comes out of Wall Street, but then so does some of the worst. So it's too expensive to do on your own. You can't really get it from someone else. That's what we're here to help provide, to bridge that gap. And if you don't believe me in terms of the difficulty in getting the data right, Well, here's a couple of studies, independent studies from MarketWatch and Financial Times. This one from last summer reported from a survey of CFOs that 20% admitted that they fudged their earnings by a magnitude of 10% and that sell-side analysts don't detect it. And in our report on why independent research is important, we talk about why sell-side analysts don't detect those kinds of things. It also— the Financial Times did a report on sell-side analysts, how their ratings really don't matter. We go into more detail on that in our report on why independent research is important. But to put it in a nutshell, Wall Street investment ratings are not only skewed, but they're very misleading. And in many ways, it's on purpose. So what's changed? What's the big deal here? Technology has changed the way we can go through filings and build high-quality models. New Constructs brings the marketplace a paradigm shift in the level of analytical rigor that we can bring to a large number of companies. This changes the landscape for the investing business, the consulting business, as well as corporate strategy. How managers can— how executives can manage their business and understand their profitability, and their profitability in terms of one version of the truth. One measure of return on invested capital, one measure of profitability, that being return on invested capital, for all companies in their peer group in the market and for all divisions within their company. New Constructs has brought a paradigm shift. And to give you a sense of how we do this, we've got a unique research platform. We're the only firm, or one of the very, very few firms that covers a lot of companies, that owns our own data and publishes research, right? Other people that compete with us, they get data from some Database, and then they write reports, right? Or there are other firms that gather their own data, but then they don't write reports. We're the only people that do both, and we think it makes us better at both. We source data directly from the SEC. We download the filings, focus on the financial statements, but especially the footnotes and the MD&A. We've got a proprietary extraction system that our analysts use to go through these filings more quickly and more intelligently. When I started New Constructs in 2002, It was about creating technology to enhance the process for a highly trained, highly educated analyst to go through filings and find the right things. All the data has very unique and sophisticated data classification and management protocols to give us the best database, the best database for understanding the apples-to-apples true underlying economics of businesses in the world for The companies that we cover. We have a calculation engine that sits on top of that. It's agnostic to the data, really. All the model needs to run is to know that the dataset has an adequate amount of data in it. But we can do any kind of calculation we want. We can calculate free cash flow with acquisitions or without acquisitions. I'm not in the business of selling religion, right? I'm in the business of giving you a better dataset. Now, I'm telling you why I think return on invested capital matters, but I don't think that's religion. I think that's just objective perspective based on empirical evidence. But that said, if you disagree with me, I'll provide you any kind of calculation you want. And the interface or the delivery of the product is web-based. It's a SaaS product. You type in a ticker— I'm sorry, an ID and a password. You get in, you type in a ticker, you get an answer. So the way we really built this, the theory behind it was that We wanted to have a tool that allowed our analysts to easily shine lights in the dark corners of all filings and then have the technology record every step of that parsing process so that the machines could learn how to parse based on what expert analysts have done. Today, having begun this work in 2002, we now have a database of human-validated parsing instructions from 80,000+ filings we've tested and perfected. And because the machines have so many filings against which to test their own performance, for example, we say, machines, learn how to parse the income statement based on the 80,000 income statements we have in our database. It goes and does it. And we say, okay, well, let's see how well you do. Go parse this income statement, and we'll compare how well you do that to how an analyst has done it in the past. So machines can test and teach themselves very quickly, which, as you can imagine, Allowing us to create really, really high levels of automation very quickly. And the main quote to summarize sort of our approach to this is, if an analyst has parsed an item in the same way 80,000 times out of 80,000 filings, then we no longer need an analyst to parse that line item. The machine can do it, right? We take that same philosophy to everything in the filings. And as you can imagine, Having been through 80,000+ filings with experts, we're getting really fast and really smart about how to find data. And we're smarter about how to find data because we build models to use the data. We know what to look for. Most of our competitors haven't looked at an actual annual report in over a decade or more. And I encourage you to challenge them on that front. What does it look like? Well, you know, this is an early version of it, but the key takeaway was that I needed to integrate the parsing the filings with the parsing process and a bucket system, right? You can see what's in blue is what's been parsed in the system. And you can see that we actually parsed the actual original line item, original text, parsed the value, and the system remembers where that's been parsed. And it tracks how the analyst does this. We've got this bucket system into which all the data goes. Right. And I don't even want to show you all the bucket system because to me that's actually kind of proprietary. That's a big part of what we've done is we've got to figure out a way to classify and treat everything within filings in a way that supports an economic understanding, not an accounting understanding. And don't get me wrong, accounting is important and we are experts in accounting, but you got to think of accounting as, as the vocabulary and finance as the language. No one word in a vocabulary can have that much meaning by itself without context. Finance is putting all those words together with meaning. So we apply finance to get meaning, proper meaning, out of accounting. And this is the basic interface that we have used to do that and what the analysts have used. It's the efficiency tool that allowed me to get the super smart analysts to stick around long enough, to parse enough, to Justify the cost of training them. And what does that mean? We're gathering tons of stuff. These are the unusual items we found in the MD&A alone. We're covering around 3,000 companies during this timeframe, so we're finding one material unusual hidden item in an MD&A, in the MD&A per company. And an unusual item means unusual gains and charges. So you got to go through the MD&A. XBRL doesn't even go to the MD&A. We're there, we're finding a lot of stuff. We also find things for the balance sheet where we've looked at write-downs. And we look over this 6-year timeframe, almost 33,000 write-downs. When machines are looking for things, they don't get tired. There's no question that humans experience atrophy in going through filings, mental atrophy. It's hard. I've done it. I've been through as many filings manually as probably anybody in the world except for Warren Buffett. That's why I created technology. And we don't just Gather data. We synthesize the data. And here we were able to predict that Eastman Kodak was going to go bankrupt before anyone else because we noticed they had a pension plan assumption that was the highest return on plan asset assumption, or the amount of money they expected to return on their assets in their pension plan. If any company, any publicly traded company in the year 2010 allowed them to boost revenues by over 2%, earnings by many, many, many times more than that, even though the pension plan was underfunded by $2.6 billion, or 3 times the market cap. Pretty incredible. We identified some misleading earnings, an expensive valuation when the stock implied that the company's profits were going to grow at 10% compounded annually for over a decade. Easy call. We also found that some regulators love this kind of analysis where we found that write-downs were a leading indicator to Companies getting charged with fraud. In this situation, this company had written down over the prior 3 years, for every dollar of assets on the balance sheet, they had written down $3.46. Here's some examples of proof is in performance. You know, I always like to say proof is in performance, and we haven't been right on everything, right? We've been wrong on Netflix for a while, but we've been really right on a lot of stocks. More right— been right about more than we've been wrong. This comes from a recent review of our Danger Zone picks. You can get the full report For details on that report here. Again, we're able to provide this return on invested capital analysis or this correlation, not just across all sectors with the S&P, but even on financials. That's the beauty of return on invested capital and the way we calculate it. It's an unlevered apples-to-apples number across all companies, even financials. And you see, again, a high correlation, same as the S&P, for diversified financials. And then, you know, drill down on individual company, you can derive some unique insights as to how it's undervalued, what it needs to do to get a more appropriate valuation, etc. Not surprisingly, we're recognized by some of our top clients in the world. Our clients are some of the top firms in the world, and we get recognized by the top media outlets in the world. Case study, Open Letter to Larry Ellison. That case study is on our site. You can access it for free anytime using that link. The thesis, quite simply, and I'm going to hit the high points, is that management can boost the market value of Oracle by aligning the firm's strategy and performance compensation with real cash flows, or what we call return on invested capital. And again, this thesis is predicated on our beliefs that real cash flows matter and And superior profitability is ultimately rewarded by the market. And what we're able to provide using the regression analysis is the implied valuations of the stock based on certain levels of return on invested capital. If they can just maintain a 23% return on invested capital, that means their market cap should go up by $24 billion. We do multiple scenarios with targeted suggestions. As to how the company can improve its ROIC, and we show the implied improvement in market value based on that. The report also includes detailed analysis on how undervalued Oracle is relative to cash flows, how to ensure the market actually credits them for focusing on ROIC, targeted proposals on how management can improve ROIC, and again, how to quantify the size of the prize. In the appendix, I'm here just to give you, you know, some additional resources to understand more about new constructs. We help you find safe stocks. We have a Most Attractive Stocks monthly newsletter with 40 stocks, 20 large-cap, 20 small-cap long ideas. We write up specific long ideas all the time. Here are some samples. And our Education Center provides unparalleled transparency and details behind all of our calculations. A lot of webinars, a lot of methodology documents, really everything you need to understand what it is we do. We're transparent about it because we want you to know how much work we do for you. On the other side of things, we help you find dangerous stocks so you can avoid them. We have also another news— monthly newsletter that has 20 large-cap and 20 small-cap of our most dangerous stocks, stocks to avoid. We also do individual company write-ups called the Danger Zone, where we do a sort of laser-in focus on certain companies and why you should avoid them. We also focus on certain ratios and other things that we think can help our clients get a better understanding of how to be successful long-term investors. And we also got a bunch of forensic accounting data that reflects all the work we do in the footnotes, and we share that with you because again, we want you to know how much work we do for you. We also help you find good mutual funds and ETFs. Quarterly, we do the best and worst sector ETFs and mutual funds. We do the same thing by investing style. We have overall sector ratings, and we have a unique methodology Unique perspective on rating funds. Our fund ratings are based on an aggregation of our ratings for the stocks that the fund holds. In other words, we can only cover the funds that hold the stocks that we cover. So we're giving you a bottoms-up analysis of a fund. We'll give you the return on invested capital of a mutual fund. We'll give you the valuation of the mutual fund. We think this is a much, much better perspective— or I'm sorry, a very complementary perspective. to what you get from traditional mutual fund rating firms where they're just looking at past price performance. There's a lot of free resources on our site as well. Lots of free research, free education, free tutorials. We can give you free insights into how our models work with webinars on the How to Use Our Site section of our blog that show you exactly how to understand and, and See our models, show you how we click through the original filings, how we're directly linked to the income statement, the balance sheet, the footnotes, and how customizable the models are. And we're honest. We'll show you our performance. It's out there for you to see. Take a look and don't take our word for it because we'll show you the performance and you'll see that it's actually pretty good, especially in volatile markets. We're helping people stay safe. Thanks very much for joining me today. If you have any questions, feel free to contact me at my email at the front of the presentation, or you can hit us on Twitter, Facebook, etc. Thanks for watching.