You’re the head of a movie studio and you have to decide whether to greenlight a film project. To make this decision, you must make two interrelated forecasts: the costs of production and potential box-office revenue. Production costs are easy, you think: you know the shooting days, location costs, and likely outlay for computer-generated imagery. Ticket sales are harder to predict, but you know roughly how many screens the film will be on during opening weekend, how hot your stars are, and how much you will spend on advertising.
Do you have enough data to make the correct decision? Probably not. Research shows that film executives overestimate box-office revenue most of the time.
That’s because they often take what Nobel laureate Daniel Kahneman calls the “inside view.” They build a detailed case for what is going to happen based on the specifics of the case at hand rather than looking at analogous cases and other external sources of information. (If they do look at other data, it’s often only after they’ve already formed impressions.) Without those checks and balances, forecasts tend to be overly optimistic.
It happens to all of us: Despite our best intentions, we fall prey to cognitive and organizational biases that get in the way of good decisions. My colleague Dan Lovallo and I have been studying these phenomena for decades and, together with other co-authors, we recently started a series of articles outlining ways to combat some of the top offenders. Take the inside view bias. It’s been proven that large capital-investment projects like motion pictures, in which outcomes arrive months or years after the initial decision to invest is made, often fail to meet targets set up front. One way to make better forecasts is to take the “outside view,” which means statistically assessing your project based on a reference class of similar projects.
Using the correct reference projects can reduce forecast errors by 70%.
The critical step here, of course, is to identify the right reference projects—a process that is part art and part science. There may be five such projects or there may be 500, but there are usually more than executives want to admit; we like to think our ideas are unique and special. Finding a reference class for a film project might seem like a no-brainer: there are lots of movies in the same genre, with similar story lines and stars. But, as Dan related in this recent podcast, when he asked the head of a major studio how many analogous projects he typically used to forecast movie revenue, he answered, “One.” The most he had ever used? Two. Yet research shows that using the correct reference class can reduce estimation errors by 70 percent.
Other unconscious biases abound in our boardrooms. A common one, especially around budget time, is anchoring: the psychological phenomenon in which a number sticks in your mind (namely, last year’s budget) and influences you, even if you think you’re disregarding it. This fact helps to explain why budgets tend to be so similar year after year. We also recently wrote about many leaders’ tendency to devote outsize attention and investment to glamorous “hero” projects when more mundane ventures and investments are often more profitable.
Biases can lead even the best executives astray. As my colleague Chris Bradley wrote recently, these mental shortcuts exist to help us filter information in day-to-day decision-making but they “can distort the outcomes when we are forced to make big, consequential decisions, infrequently, and under high uncertainty—precisely the type that we confront in the strategy room.” Recognizing them is the first step to avoiding the pitfall.
Tim Koller is a leader in our Corporate Finance Practice, based in New York. The seventh edition of his book Valuation: Measuring and Managing the Value of Companies will be released in the spring of 2020.