CAMBRIDGE, Mass., March 4, 2009 — The recent economic crisis has led to the downfall of many businesses, but it can't be blamed for all of the failures. Research by MIT Sloan School of Management Visiting Scholar M. Shayne Gary found that the “boom and bust” dynamics experienced by many businesses are caused by decision errors and biases that can be avoided.
Gary's research found that boom and bust dynamics are common in just about every industry ranging from consumer electronics and telecommunications to toys and real estate. The common management behavior triggering such booms and busts is aggressive capacity expansion in the boom period when demand exceeds supply. However, this frequently leads to the bust when firms can't decrease the amount of goods produced in time to respond to lessening demand as the market saturates.
The combination of poor forecasting and the time delays involved in decreasing supply is so difficult to manage that firms rarely learn from these experiences. Many go bankrupt while others survive the bust only to enter the same cycle a few years later, said Gary.
Past examples of companies afflicted by boom and bust dynamics include Atari in home video games, EMI in medical devices, Swatch in fashion watches, and Lucent Technologies in telecommunications equipment. These businesses experienced booming growth, but then in a very short period of time suffered dramatic collapses and in some cases financial bust.
While the boom and bust cycle has existed for hundreds of years, Gary and his coauthors maintain in “Boom and Bust Behavior: On the Persistence of Strategic Decision Biases,” that it can be avoided. “We think there are pretty persistent decision biases at work here and we suggest some interventions that could alleviate these decision biases,” said Gary. “For example, if people build a more accurate mental model of the deep structure that causes the boom and bust cycle then we can mitigate the decision making deficiencies.”
Similar to how doctors diagnose routine cases using knowledge organized in schemata of different illness categories to diagnose and treat patients, “a schemata of product lifecycle diffusion could easily guide managers to consider information about the potential number of customers in a total market, the industry growth rate, competitors' aggregate capacity investments, and the average useful lifetime of the product,” wrote the authors. “[O]ur claim is that using any naïve logistic product lifecycle schemata instead of grossly deficient mental models might reduce errors even by an order of magnitude. Yet the disciplined use of schemata composed of high level causal models is not a 'natural' part of decision making in business.”
Another strategy for avoiding the boom and bust cycle is ensuring that managers adopt an outside view by paying attention to similar cases of diffusion and capacity building to detect inflection or turning points. “By doing this, the manager will realize that if the company expands capacity then everyone else will expand capacity as well and that will lead to overcapacity and a dramatic decline in profits,” said Gary.
The authors write, “These two strategies would probably offer remarkable performance improvements. What is surprising is that they are not part of the standard 'tool box' of managers and management training. As a result, problems such as boom and bust persist and are repeated, many times over.”
Gary added, “When the economy shrinks as much as it has over the last 18 months, it will negatively impact many organizations, but not every business with a bust is a victim of the macroeconomy. Many bring it on themselves by overbuilding capacity and saturating the market so there is absolutely nowhere to go but down.”
The paper was coauthored by Gary, Giovanni Dosi of the Laboratory of Economics and Management (LEM) at Scuola Superiore Sant'Anna, and Dan Lovall of the University of Western Australia.