Practical analysis for investment professionals
05 December 2013

Book Review: Best-Practice EVA: The Definitive Guide to Measuring and Maximizing Shareholder Value

Best-Practice EVA: The Definitive Guide to Measuring and Maximizing Shareholder Value. G. Bennett Stewart III.


In 1991, G. Bennett Stewart III, a founding partner of Stern Stewart & Company, changed the way we evaluate corporate performance. His book The Quest for Value (Harper Business Publishing, 1991) brought the concept of economic value added (EVA) into the mainstream. EVA improved analysts’ and investors’ ability to determine whether management was enhancing value for a firm’s owners.

Although EVA has been one of the most powerful metrics for evaluating performance over the last two decades, certain shortcomings of the methodology became apparent to Stewart. Now, having left Stern Stewart in 2006 to start EVA Dimensions LLC, Stewart has returned with an update to the EVA methodology in Best-Practice EVA: The Definitive Guide to Measuring and Maximizing Shareholder Value.

Stewart’s rejection of accounting-based metrics in favor of EVA derives from the recognition that accounting rules are at odds with economic reality and make valid comparisons across companies or business units virtually impossible. As he explains, “A fundamental reason accounting is so flawed as a management and shareholder valuation tool is that accounting statements cater to lenders rather than owners. EVA serves to remedy this problem.”

For analysts outside the corporation, EVA can be thought of simply as a tool for determining how well a company is performing. Stewart shows in extensive detail, however, that EVA can also play a role in corporate decision making: Companies that use EVA in setting performance-based compensation motivate line managers to make investment decisions that add the greatest value to the firm.

Evaluating managers through EVA steers them toward net present value (NPV) as a basis for determining which projects to undertake. Internal rate of return (IRR), a widely used criterion, can lead managers to reject projects that entail large capital expenditures. EVA encourages managers to approve such projects so long as the returns exceed the cost of capital.

Before jumping into his newly derived EVA metrics, Stewart provides a detailed overview of the original EVA methodology for those unfamiliar with the topic. Throughout the book, Stewart not only includes simple examples to allow the reader to gain an understanding of the core concepts but also intertwines them with case studies of actual companies that have applied the EVA methodology to their financial decision making. Numerous companies, including Coca-Cola and AutoZone, have used EVA to drive their success.

Even as EVA became one of the leading methodologies for both performance evaluation and the allocation of capital, Stewart recognized that EVA had certain limitations. Like other absolute measures, EVA could not be used to compare performance over time, across different lines of business, or against peers that differed in size. In addition, financial managers found the traditional EVA methodology difficult to implement. To deal with these limitations, Stewart’s firm developed three new EVA ratio metrics that can completely replace such commonly used ratios as return on net assets, return on investment, return on equity, and IRR.

Stewart begins with EVA margin, which is the ratio of the change in EVA to prior sales. Even though EVA margin is not the measure to maximize, he argues that it is an extremely important driver of the second ratio, EVA momentum. EVA margin, Stewart asserts, should replace the widely used DuPont equation.

From EVA margin, Stewart moves on to EVA momentum, the measure that firms should seek to maximize. EVA momentum, he writes, “is the only corporate ratio indicator where bigger is always better, because it gets bigger when EVA gets bigger, which means that a firm’s NPV and MVA (market value added) and shareholder return are getting bigger, too.”

The last of the three ratios is market-implied EVA momentum (MIM). MIM reverse-engineers stock prices to estimate the EVA growth rates that investors are projecting. Stewart argues that this approach is more reliable than using consensus earnings per share, which is a survey of sell-side analysts. By using the actual price of the stock, MIM incorporates the opinions of all investors. Stewart points out three advantages of using MIM. First, the higher the MIM, the greater the confidence the market has in management’s forward plan. Second, MIM provides a benchmark against which to compare EVA momentum. Companies that consistently underperform the market’s expected EVA growth rate are likely to see investors mark down the price of the stock. Finally, chief financial officers can use the MIM of their competitors to establish minimum performance goals for their forward plans.

Although most of the book is devoted to operationalizing EVA, Stewart has not forgotten analysts who would like to use the methodology for stock selection. In Chapter 11 (“EVA and the Buy Side”), he introduces a new metric, PRVit (pronounced “prove it”), or performance-risk-valuation investment technology. His colleague (now his wife) Ling Yang helped turn this metric into a workable product. PRVit, the ratio of true value to trading value, gives analysts a measure that can help determine whether a stock is a buy, sell, or hold. Using AutoZone and Tiffany & Co. as examples, Stewart demonstrates the effectiveness of PRVit as a tool for investment analysts.

The final chapter discusses how a firm can become a best-practice EVA company. Stewart uses this opportunity to pitch the services and software of his own company. Notwithstanding this bit of commercialism, Best-Practice EVA provides financial managers with a thorough understanding of the advantages of the new EVA ratios over traditional measures. These tools can incentivize managers to use capital more efficiently in creating shareholder value. Executives who are looking for metrics that line managers can use to fuel growth, as well as financial analysts seeking tools to enhance the investment decision-making process, will find Best-Practice EVA an invaluable addition to their evaluation arsenals.

More book reviews are available on the CFA Institute website or in the Financial Analysts Journal.


Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.

About the Author(s)
Ronald L. Moy, CFA

Ronald L. Moy, CFA, is associate professor of finance at Tobin College of Business, St. John's University, Staten Island, New York.

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