Experiments at Work

What's the best way to boost sales or handle competing resellers? By lab-testing business ideas, Kay-Yut Chen gets rid of some of the guesswork

Outside Kay-Yut Chen's economics laboratory at Hewlett-Packard in Palo Alto, Calif., the November air is unseasonably warm, even for California, and splashes of yellow and green leaves shimmer against the clear blue sky. But inside, in a windowless, fluorescent-lit room, the 12 visitors participating in today's experiment sit patiently at their randomly assigned computers. When I point to the incongruity, Chen doesn't miss a beat: "That shows one thing--the assumption that people like money is correct."

This simple assumption goes to work for Chen whenever the HP principal scientist runs an experiment. The participants--mainly "starving students" from nearby Stanford University--will earn $25 to $75 or more, depending on how well they play today's game. The experiment simulates interactions between sales agents and sales managers. At each period of play, the computer tells sales agents the current market conditions, and based on that information the agents must decide how much effort they will put into making the sale. Although effort incurs costs that take away from the total payout, effort also increases the likelihood of sales success. The agents' total payout is simply the sum of the fixed payment and variable payment for successful sales minus the cost of effort. Managers, in turn, determine the fixed and variable payments they will offer--knowing their own payout will be total sales minus payouts to agents.

Chen explains these rules but says nothing about strategy. He doesn't need to: through a little computer-mediated back-and-forth with their managers, most agents wise up to the fact that this game rewards sales but offers no incentive to tell managers anything. Similar compensation schemes in the real world explain why salespeople tend to sandbag their forecasts, making it hard for their companies to plan ahead.

Chen thinks he has solved the sandbagging problem: have each salesperson choose a personal balance of fixed and variable compensation. For example, the salesperson can choose a high commission percentage with no fixed salary or, at the other extreme, a modest fixed salary and no commission--or some combination in between. Each choice implicitly reveals how much the salesperson plans to sell, much as an insurance subscriber's choice of deductible and premium reveals how sick she is. Based on a truth-telling mechanism from game theory, this design works on paper. But as an experimental economist, Chen will keep testing it empirically, comparing the emerging design with other available models, such as the one he is testing today.

Chen has successfully used that approach to help HP managers design good contracts with retailers and resellers, and he is starting to tackle other thorny problems for his employer: figuring out how to protect HP's bottom line against international currency fluctuations and discovering ways for brick-and-mortar retailers and HP's online store to coexist happily.

Kay-Yut Chen's experiments showed that a proposed incentive program would backfire. So HP, his employer, scrapped the idea.

The science of experimental economics has boomed with the rise of personal computers--especially after one of its founding fathers, Vernon L. Smith of George Mason University, won the Nobel Prize in economics in 2002 (sharing the honor with Princeton University psychologist Daniel Kahneman). But the field has not caught on in what seems its most logical application: making business decisions within a company. When Chen started his lab in 1994, it became the first economics laboratory inside a corporation, and to this day no other firm maintains a lab like his. "He's basically 'Mr. Experimental Economics in Business,'" says Teck H. Ho, chair of the marketing group at the Haas School of Business at the University of California, Berkeley.

Some blame the absence of such labs on the shortsightedness of corporate America. Charles R. Plott, the experimental economist at the California Institute of Technology who pioneered the field, puts it this way: "A lot of us in academia have done business applications, but for someone to take a new science inside a big business that is just rife with competition for funds--and be able to create a science facility that can handle the basic research and the pressures of day to day--that's a monumental task Chen has succeeded in."

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