If ROIC Is So Great, Then Why Doesn’t Everyone Use It?
That’s the question we get when we argue that return on invested capital ( ROIC ) does a better job of explaining changes in shareholder value than any other metric . Why do investors, executives, and the financial media focus on reported earnings and other metrics such as EBITDA that ignore the balance sheet? Why aren’t executives around the world adopting ROIC in order to boost returns? Anyone asking those questions should read the 1996 CFO Magazine article ” Metric Wars .” Back in the mid-90’s, ROIC-based models such as Economic Value Added (NYSE: EVA ) and Cash Flow Return On Investment (CFROI) were all the rage, with corporate giants such as Coca-Cola (NYSE: KO ), AT&T (NYSE: T ), and Procter & Gamble (NYSE: PG ) linking them to executive compensation and highlighting them in communications with shareholders. Fierce competition ensued, as a variety of consultants developed and marketed their own shareholder value models, all, at their core, based around the idea that companies need to earn a return on capital above their cost of capital. That revolution was short-lived. Coca-Cola and AT&T stopped regularly highlighting EVA in filings after 1998. Some of the consulting companies mentioned in the CFO piece no longer exist, such as Finegan & Gressle, while others like The Boston Consulting Group no longer highlight the same metrics. It would be easy to assume that ROIC-based models had their chance in the marketplace and failed because they weren’t good enough, but that would be wrong. The story of the “Metric Wars” shows that it was the marketing strategy, not the underlying model, which was flawed. The Consultant’s Concoction The lack of resources and technology available at the time required the proponents of these metrics to do many hours of manual work to provide the metrics for the client and its comp group. As a result, the firms wanted to differentiate their models or build barriers to entry around them so that competitors could not piggyback on their original work. Transparency was not in the consultants’ best interests. If everyone could see the inner workings of their formulas, clients wouldn’t have any incentive to pay big money for their model over a competitor’s. As a result, the various firms guarded their models and would attack a competitor’s formula as a “consultant’s concoction.” This was an understandable development, as the recurring revenue stream from a consulting client can be very valuable. Unfortunately, it also led to lot of significant problems for the ultimate end-users of that data. Excess Complexity: consultants needed to make the work seem really difficult so clients would not replicate and competitors could not decipher it. Lack Of Transparency: since each company’s formula was its bread and butter, they kept the details of how they were calculated hidden. It was hard for those on the outside to understand or trust the process. No Comparability: with no single standardized formula, it was impossible for companies or investors to benchmark results to their peers. Short Shelf Life: the analyses were only as fresh as the last engagement, and since the “proprietary” formulas could change from year to year, clients might not always have the most up-to-date analysis. Little Differentiation: While all the different consultant’s formulas had their own tweaks, they were based around the same basic idea. With so little fundamental differentiation, the various consultants spent a great deal of time and effort tearing each other down and nitpicking competing formulas, ultimately spreading more confusion. Add this to the tech bubble attitude of the late 90’s, when stock valuations became more about stories and potential rather than any fundamental research, and the work these consultants were doing fell by the wayside. Today, only Stern Stewart and Credit Suisse (which bought CFROI or HOLT in 2001) remain as survivors from the Metric Wars. Neither has had a ton of success monetizing their formulas since then, in part because they remain committed to their “concoctions” for consulting business, and also because they rely on inconsistent and limited data feeds that lack analysis of the financial footnotes or management disclosure and analysis. A Different Strategy What New Constructs does today is not so different from what Stern Stewart, The Boston Consulting Group, and others did 20 years ago. We’re working off the same conceptual framework and implementing many similar calculations. What’s changed is the level of rigor we put into building technology to gather high-quality data and build best-in-market models with scale. Our point of differentiation is the scale and speed with which we can build the models and provide analytics. Our highly educated and trained analysts leverage our proprietary technology to deeply analyze 10-Ks and 10-Qs in a matter of seconds on average. While we make thousands of adjustments in our models to close accounting loopholes and portray the true economics of the underlying business, every adjustment is not only 100% transparent but also overrideable by clients. Anyone can go to the Education tab of our website and get detailed explanations of the metrics we use, how we calculate them, and the various adjustments we make to accounting data. Our data is comparable across different companies, so anyone can easily use our screeners to compare profitability and valuation. During the Metrics Wars, the technology simply didn’t exist to create such a large database and deliver that much information without charging a prohibitively large fee to clients. Because of these limitations, those companies failed even though their underlying framework was sound. In the intervening years, the burgeoning financial punditry has helped propagate the myth that the market only cares about reported earnings. The rise of the E*Trade baby and amateur investors only furthered the focus on simplistic data points that could be easily calculated and consumed. More sophisticated fundamental research became harder and harder to find. Today, there is a noticeable gap for the many investors out there that want high-quality fundamental research. Most of the available research out there doesn’t attempt to assess the true drivers of value. Wall Street analysts lack the independence to deliver truly objective research, and what little truly high-quality research exists tends to be too expensive for the average investor to access. Our goal is to remove the noise that clouds the connection between corporate performance and valuation by providing an analytical framework that is intuitive yet rigorous. For over 95% of the world’s market cap, we provide apples-to-apples corporate performance and valuation metrics. We are ready to join the Metric Wars. Disclosure: David Trainer and Sam McBride receive no compensation to write about any specific stock, sector, style, or theme. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.