Theory To Practice

Not-So-Mad Men

Does bad performance lead to risky behavior?

Summer 2010 by Michael E. Raynor

It is difficult to enter the business section of any bookstore without being told that managers are people too, so they are subject to all the same cognitive failings as everyone else. Biases for authority, bandwagons, and confirmation are just the A, B, and C of a long list of psychological foibles that plague us. Read too much of this literature and you’ll end up wondering how any of us managed not to eat rat poison for breakfast—never mind make a complex decision in the ambiguous context of a corporation.

There’s a certain satisfying coherence to this view of the world. After all, managers don’t stop being human when they get to the office (whatever Dilbert might have to say to the contrary). Consequently, human irrationalities are necessarily managerial irrationalities that will likely show up in irrational corporate-level behaviors. Managers—men and women alike—are, to borrow from the title of the hit TV drama, mad, just like the rest of us.

The genesis of this sort of applied psychology—often known as “behavioral economics”—can arguably be traced to a seminal study by MIT management professor Ed Bowman. In the first of two landmark articles appearing in MIT Sloan Management Review in 1980, Bowman observed that firms with higher return on equity had lower volatility in ROE. In other words, higher returns were correlated with lower risk.

Most of us see this immediately as a puzzle worthy of our attention. After all, with our finance hat on, it seems obvious that risk and return should positively correlate. The argument for such a correspondence goes something like this: When evaluating an investment opportunity, the investor (at least implicitly, but often explicitly) projects a range of possible outcomes for the investment. Investments with extremely positive and extremely negative possibilities are said to be high-risk; those that investors expect to have a narrower range are said to carry less risk. Weighting each possible outcome by its associated estimated probability yields an expected value for that investment. Risk-neutral investors are indifferent among investments with the same expected values. But most investors are risk-averse and will typically pay less for an investment with higher risk, all else being equal. The relationship between the discount to the expected value and the risk associated with the outcomes can be thought of as the “risk premium” that investors command for accepting a given level of risk.

Bowman, however, found that firms with the highest volatility in ROE actually had the lowest average ROE, and vice versa. In other words, risk and return were negatively correlated. This finding quickly became known as the Bowman Paradox.

Drawing on the now-famous work of psychologists Daniel Kahneman and Amos Tversky, Bowman suggested that “prospect theory” is at work. Technically, this manifests itself as risk aversion in the face of possible gains and risk-seeking when faced with possible losses. Bowman hypothesized that firms that are doing well will systematically avoid risky investments even with high expected values (since a poor outcome would spoil a strong track record), while poorly performing firms would systematically seek out risky investments in the hope of reversing their misfortunes (since a good outcome could get them out of the hole). He tested this possibility by examining annual reports, looking for indications that companies had become risk-seeking in response to poor past results. The more poorly performing firms, Bowman found, seemed to make more frequent and aggressive claims about changes to their behavior.

At one level, this is comforting. A company that is performing poorly should change its behavior. And if the claim were merely that managers of strongly performing and poorly performing firms see the same opportunities as having similar risk profiles but choose differently because of their circumstances, we could still preserve a semblance of rational, deliberate decision-making. Companies doing well have relatively more to lose with higher-risk behavior, while those doing poorly might have relatively more to gain. These asymmetries in payoffs are a rational basis for different attitudes toward risk.

But this isn’t where the field has gone. Rather, the claim is that managers perceive the risks differently because of their circumstances and as a consequence of those perceptions choose differently. In other words, decisions aren’t rational and objective after all. And this is something that needs fixing.

Many have suggested that we need to devote significant effort to mitigating the impact of biases through careful attention to how they affect us. From decision-making processes to control mechanisms, there has been a great deal of hand-wringing (and perhaps hand-waving) over how best to compensate for managers’ “predictable irrationality” (borrowing from the title of Dan Ariely’s popular book on the topic).

Now, some of these efforts might actually be helpful, and who can be against improvement? But the issue is not whether managers can improve their decision-making by identifying and counteracting decision-making biases—for they certainly can—but, rather, how much time and attention they should devote to this alleged problem.

This takes us back to Bowman’s initial findings. His research remains one of the few large-scale empirical investigations linking corporate-level decision-making biases with corporate-level performance outcomes. And so, although the decision-making biases that led to risk-seeking behavior are well established, much of the support for prospect theory as an explanation of managerial irrationality—and the subsequent enthusiasm for control measures to combat this bias—rests ultimately on Bowman’s nearly 35-year-old analysis. Perhaps there is merit in revisiting his method and his findings.

One way to qualify Bowman’s work is to strip away those factors that affect firm performance—and hence variability in performance—that don’t reflect managerial choices. For example, companies of different ages might exhibit different variability in performance over their lifespans simply as a result of random fluctuations: Looking at a five-year window means comparing, say, years eleven to sixteen of a firm that ultimately survived for forty years with the only five years of another’s existence. And the mix of such companies might reasonably be expected to vary by industry (e.g., high-tech, which has a relatively high rate of entry and exit compared to commodity chemicals) and time period (say, recessionary versus expansionary economies). If these factors—and not managerial decision-making—are driving the Bowman Paradox, then much of the emphasis on correcting biases in decision-making might well be misplaced.

Using a more extensive database of corporate performance than Bowman had available to him and more sophisticated regression techniques than were available then, we can control for industry, industry concentration, year, company size, market share, age, and leverage. As it turns out, the Bowman Paradox remains an accurate characterization of firm-level behavior when dealing with “raw” performance data. But when we look only at that portion of corporate performance affected most directly by managerial choices, the story changes significantly: The paradoxical negative relationship between risk and return is transformed into an equally strong positive—and utterly rational—relationship. In other words, it appears that managers do not systematically pursue risky behavior in response to bad performance. Instead, factors such as industry structure and company life-cycle considerations drive seemingly irrational outcomes.

Those engaged in the current debate on how best to avoid future economic and financial meltdowns would do well to consider this finding. It is almost certainly the case that we need both structural reform and improvements in company-level decision-making in order to avoid excessive risk-taking in the future. In fixing the current system, however, it’s important to identify the dominant sources of risk we want to control and allocate our efforts accordingly. For our problems may well lie not so much with mad men as with—to take a cue from a movie made in the 1960s rather than a TV show set in the ’60s—a mad, mad, mad, mad world.

MICHAEL E. RAYNOR MICHAEL E. RAYNOR is with Deloitte Consulting LLP. In addition to applying theory, he occasionally tries to create some; BusinessWeek named his most recent book, The Strategy Paradox, one of the top 10 books of 2007. He can be reached via www.michaelraynor.com.