Business Standard

When intelligent people make poor decisions

Strategist Team  |  New Delhi 

History is replete with the horrific consequences unleashed as a result of the cognitive mistakes of the smart set.

IN DECEMBER 2008, two seemingly unrelated events occurred. The first was the release of Stephen Greenspan’s book, Annals of Gullibility: Why We Get Duped and How to Avoid It. Greenspan, a professor of psychology, explained why we allow other people to take advantage of us and discussed gullibility in fields including finance, academia, and the law. He ended the book with helpful advice on becoming less gullible.

The second was the exposure of the greatest in history, run by Bernard Madoff, which cost its unsuspecting investors in excess of $60 billion. A is a fraudulent operation in which a manager uses funds from new investors to pay off old investors. Since there is no legitimate investment activity, it collapses when the operator can’t find enough additional investors. Madoff’s scheme unraveled when he couldn’t meet requests for redemptions from the investors stung by the financial meltdown.

The irony is that Greenspan, who is bright and well regarded, lost 30 percent of his retirement savings in Madoff’s The guy who wrote the book on gullibility got taken by one of the greatest scammers of all time. In fairness, Greenspan didn’t know Madoff. He invested in a fund that turned the money over to the scheme. And Greenspan has been gracious in sharing his story and explaining why he was drawn to investment returns that looked, in retrospect, too good to be true.

If you ask people to offer adjectives they associate with good decision makers, words like “intelligent” and “smart” are generally at the top of the list. But history contains plenty of examples of intelligent people who made poor decisions, with horrific consequences, as the result of cognitive mistakes.

Odds of success are poor, but not for me
Corporate mergers and acquisitions (M&A) are a multitrillion dollar global business year in and year out. Corporations spend vast sums identifying, acquiring, and integrating companies in order gain a strategic edge. There is little doubt that companies make deals with the best of intentions. The problem is that most deals don’t create value for the shareholders of the acquiring company (shareholders of the companies that are bought do fine, on average). In fact, researchers estimate that when one company buys another, the acquiring company’s stock goes down roughly two-thirds of the time. Given that most managers have an explicit objective of increasing value-and that their compensation is often tied to the stock price-the vigor of the M&A market appears moderately surprising. The explanation is that while most executives recognize that the overall M&A record is not good, they believe that they can beat the odds.

“A high-quality beachfront property” is how the chief executive officer of Dow Chemical described Rohm and Haas after Dow agreed to acquire the company in July 2008. Dow was undaunted by the bidding war, which had driven the price premium it had to pay to a steep 74 percent. Instead, the CEO declared the deal “a decisive step towards establishing Dow as an earnings-growth company.” The enthusiasm of Dow’s had all the hallmarks of the inside view. When the deal was announced, the stock price of Dow Chemical slumped 4 percent, putting the deal on top of a growing pile of losses suffered through acquisitions.

Basic math explains why most companies don’t add value when they acquire another firm. The change in value for the buyer equals the difference between the increase in cash flow from combining the two companies (synergies) and the amount over the market value that the acquirer pays (premium). Companies want to get more than they pay for. So if synergies exceed the premium, the price of the buyer’s stock will rise. If not, it will fall. In this case, the value of the synergy-based on Dow’s own figures-was less than the premium it paid, justifying a drop in price. Glowing rhetoric aside, the numbers were not good for the shareholders of Dow Chemical.

What’s in it for me?
Incentives matter, as economists have argued quite compellingly. An incentive is any factor, financial or otherwise, that encourages a particular decision or action. In many situations, incentives create a conflict of interest that compromises a person’s ability to properly consider alternatives. So when you evaluate your own decisions or the decisions of others, consider the choices that the incentives encourage.

Dr. Katrina Firlik, a neurosurgeon, shared an example: at conference dealing with spine surgery, a surgeon presented the case of a female patient with a herniated disc in her neck and pain that was caused by a pinched nerve. She had already failed typical conservative treatments such as physical therapy, medication, and waiting it out.

The surgeon asked the audience to vote on a couple of choices for surgery. The first was the newer anterior approach, where the surgeon removes the entire disc, replaces it with a bone plug, aim fuses the discs. The vast majority of the hands shot up. The second choice was the older posterior approach, where the surgeon removes only the portion of the disc that is compressing the nerve. No fusion is required because the procedure leaves most of the disc intact. Only a few audience members raised their hands.

The speaker then asked the audience, which was almost entirely male, “What if this patient is your wife?” The show of hands was reversed for the same two choices. The main reason is that the amount surgeons are paid for the newer and more complicated procedure is typically several times what they’d receive for the older procedure.

The expert squeeze

Accurately projecting holiday sales is a crucial task for retailers. A forecast that is too low leaves shelves bare and profits lost, while too much optimism leads to dusty inventory and pressure on profit margins. So retailers have a great incentive to come up with a precise sales estimate. To do so, most merchants rely on experts—individuals in the organization who gather information, study trends, and make predictions.

The stakes are especially high for consumer electronics firms because they generate so much of their revenue during the gift-giving season and the value of their inventory depreciates rapidly. The pressure is really on the internal experts at consumer electronics giant Best Buy, one of a multitude of retailers that rely on specialists. So you can imagine the reaction when James Surowiecki, author of the best-selling book, The Wisdom of Crowds, strolled into Best Buy’s headquarters and delivered a startling message: a relatively uninformed crowd could predict better than the firm’s best seers.

Surowiecki’s message resonated with Jeff Severts, an executive then running Best Buy’s gift-card business. Severts wondered whether the idea would really work in a corporate setting, so he gave a few hundred people in the organization some basic background information and asked them to forecast February 2005 gift-card sales. When he tallied the results in March, the average of the nearly two hundred respondents was 99.5 percent accurate. His team’s official forecast was off by five percentage points. The crowd was better, but was it a fluke?

Later that year, Severts set up a central location for employees to submit and update their estimates of sales from Thanksgiving through year-end. More than three hundred employees participated, and Severts kept track of the crowd’s collective guess. When the dust settled in early 2006, he revealed that the official August forecast of the internal experts was 93 percent accurate, while the presumed amateur crowd was off by only one-tenth of 1 percent.

Best Buy subsequently allocated additional resources to its prediction market, called TagTrade. The market has yielded useful insights for managers through the more than two thousand employees who have made tens of thousands of trades on topics ranging from customer satisfaction scores to store openings to movie sales. For instance, in early 2008, TagTrade indicated that sales of a new service package for laptops would be disappointing when compared with the formal forecast. When early results confirmed the prediction, the company pulled the offering and relaunched it in the fall. While far from flawless, the prediction market has been more accurate than the experts a majority of the time and has provided with information it would not have had otherwise.

Wine with your music?
Imagine strolling down the supermarket aisle and coming upon a display of French and German wines, roughly matched for price and quality. You do some quick comparisons, place a German wine in your cart, and continue shopping. After you check out, a researcher approaches and asks why you bought the German wine. You mention the price, the wine’s dryness, and how you anticipate it will go nicely with a meal you are planning. The researcher then asks whether you noticed the German music playing and whether it had any bearing on your decision. Like most, you would acknowledge hearing the music and avow that it had nothing to do with your selection.

This scenario is based on an actual study, and the results reveal the chapter’s first mistake: belief that our decisions are independent of our experiences. In this test, the researchers placed the French and German wines next to each other, along with small national flags. Over two weeks, the scientists alternated playing French accordion music and German Bierkeller pieces and watched the results. When French music played, French wines represented 77 percent of the sales. When German music played, consumers selected German wines 73 percent of the time. The music made a huge difference in shaping purchases. But that’s not what the shoppers thought.

While the customers acknowledged that the music made them think of either France or Germany, 86 percent denied the tunes had any influence on their choice. This experiment is an example of priming, which psychologists formally define as “the incidental activation of knowledge structures by the current situational context.” In other words, what comes in through our senses influences how we make decisions, even when it seems completely irrelevant in a logical sense. Priming is by no means limited to music. Researchers have manipulated behavior through exposure to words, smells, and visual backgrounds.

Boeing’s nightmare
In the last few decades, many business consultants and companies have preached the virtues of outsourcing—the practice of contracting a previously in-house service to an outside company. Outsourcing may allow a firm to reduce its costs and capital intensity, desirable goals in a competitive world. And a number of the organizations that have outsourced, including Apple and Dell, have enjoyed terrific business and financial success. The correlation between outsourcing and fine results seemed clear.

Boeing, the world’s largest airplane manufacturer, has long used outside suppliers. Traditionally, Boeing engineers designed a plane and sent the detailed blueprints to suppliers, a system they called “build-to-print.” This process allowed Boeing to control key design and engineering functions while lowering overall costs. But for its newest plane, the 787 Dreamliner, Boeing opted to have the suppliers both design and build the airplane sections, leaving only the final assembly to its own mechanics. The company hoped to pare two years from its historical go-to-market time and envisioned assembling a 787 in just three days, one-tenth the normal time for a plane that size.

The program was a disaster. Despite being a best-seller with almost nine hundred orders, the plane saw its launch repeatedly delayed as the program slipped well over a year behind schedule. The problem was that the suppliers were unable to deliver fully functional sections of the plane for Boeing’s final assembly. While Boeing designed the production system to integrate twelve hundred components, the first plane came in thirty thousand pieces, costing the company substantial time and money as it had to pull design work back in house.

Boeing’s problems with the 787 are symptomatic of the first decision mistake: embracing a strategy without fully understanding the conditions under which it succeeds or fails. Outsourcing is not universally good. For example, outsourcing does not make sense for products that require the complex integration of disparate subcomponents. The reason is that coordination costs are high, so just getting the product to work is a challenge. Think of IBM in the early days of the personal computer industry. The company made almost all its own components to ensure compatibility. In this stage, vertically integrated businesses do best.

Outsourcing does make sense for industries where subcomponents are modules. In these cases, the performance of the subcomponents is well defined, and the final assembly is straightforward. Today, you can build a personal computer yourself with standardized modules. Once an industry defines the modules, it makes more sense for suppliers to specialize in one component instead of trying to make them all. Assemblers like Dell can then focus on design, marketing, and distribution.

Before the 787, Boeing had controlled the design and engineer-g processes for its planes, ensuring the compatibility of the components and a smooth final assembly. But by ceding design and engineering to suppliers, Boeing’s 787 program became a case study in when to avoid outsourcing. Boeing was drawn to outsourcing as an attribute, without fully recognizing the circumstances under which it would work.

PUBLISHER: Harvard University Press
PRICE: Rs 995 ISBN: 9781422176757

Reprinted by permission of Harvard Business Press. Excerpt from Think Twice: Harnessing the Power of Counterintuition. Copyright 2009 Michael J. Mauboussin. All rights reserved.

First Published: Tue, January 12 2010. 00:33 IST