Information for Competitive Advantage—Three Central Issues

        Michael J. Mazzeo is an Associate Professor in the Department of Management and Strategy, and a Faculty Associate at Northwestern University's Institute for Policy Research. He serves on the editorial board of the Review of Industrial Organization.

        In the business world, given the size of organizations and their global reach, it has become almost impossible for managers to know everything that is going on within their organization. Yet having the right information is critical for everything from strategic decision-making to operational excellence. In businesses of all sizes, firms can use effective policies for obtaining the best possible information from both inside and outside of the organization as a basis for sustainable competitive advantage.

        To illustrate the use of information for competitive advantage I will focus on three issues:

        • Recognizing and minimizing information bias
        • Using information for accountability and incentive
        • Empowering key people to gather information

         Dealing with Information Bias

        Suppose you are the CEO of a company with a dozen divisions. It is senior management’s responsibility to decide which divisions should receive investment dollars and house the growth projects for the firm.

        The division heads who have the information that the CEO needs have their own incentives. These individuals have a vested interest in theirs being the division in which the company’s hot project is housed because it is not only good for the firm, it is good for their own careers and the careers of their team members. This may generate an incentive to put more spin on information about the division’s results or capabilities than a neutral party would report. In other words, there is no such thing as pure information. Information is always biased in some way depending on the incentives of the person delivering it.

        Internal information can come from a variety of sources. A division head will certainly provide an answer about whether or not a target will be met. But consider the value of adding more information obtained from other internal sources. For example, a warehouse manager may be in charge of ordering boxes for the product. Even though the sales forecast from the division head is for 10 million units, the warehouse manager may have ordered only 8 million boxes. That is important additional information.

        Companies are starting to do some exciting things about information bias. For example, companies are beginning to experiment with prediction markets in an effort to alleviate information bias. The best known example of these may be the Presidential election markets in which individuals can place bets on a candidate based on information they get from any number of sources. Just as financial markets process information to arrive at an appropriate value of a firm, if there is a thick market that aggregates information about candidates, that aggregation of information should lead to an accurate prediction of the winner.

        Some organizations have applied the idea of prediction markets to seek, for example, the probability that the firm will reach a particular target in terms of customers. If there is a prediction market in which individuals in the organization who have information can in some way provide it, the information can be aggregated, resulting in less biased information flowing to the decision makers. This will allow the CEO to make better investment decisions in the long run.

        Information for Accountability

        To operate effectively, managers need to keep their teams accountable and provide incentives for individuals within the team to perform. Again, information is critical in order to appropriately evaluate how organizations are operating and to provide the metrics that can reward the good efforts of people. For example, it is often difficult for organizations to tell based on just a poor outcome whether a person is simply doing a bad job or whether the person is making the right efforts but the strategy did not work out due to uncontrollable factors. To do that requires good information about what was done and what happened as a result. This is important because incentives are based on performance and to judge performance strictly on outcomes may be both unfair to the employee and unproductive for the organization.

        Suppose an organization was delivering very high quality products but market share was low. A CEO might have the hypothesis that this was due to a problem with marketing, not with production. The folks in marketing might say: “Well, it’s just a bad economy. It’s nothing that we’re doing in terms of our decision making and the actions that we’re taking. It’s just bad luck that we haven’t been successful.” If it truly is bad luck, the CEO should stick with the strategy, confident that when the economy improves, the organization will be in a very good position. If the poor result is not because of bad luck but instead because of decisions that were made then strategy should be changed.

        It is a challenge to distinguish bad outcomes that were based on good decisions but bad luck from bad outcomes based on bad decisions. The reverse is also true. It would be wrong to reward good outcomes that were the result of bad decisions and good luck.
        Economists are currently studying how this plays out in the oil industry. Corporate boards that want to make their senior managers accountable for their strategic decisions often provide monetary incentives to leaders based on what happened to the stock price. In the oil industry it turns out that the value of oil company stock tracks very closely to the price of oil, and no individual executive has any control over the price of oil. So the fact that stock price was used to provide incentives was a mismatch. They did well because of something out of their control, but perhaps they could have done even better.

        Companies can be more successful if they can go beyond just looking at the outcomes to use additional information to extract the effect of the decision from the effect of the uncontrollable factors. The goal is to find ways to separate skill and effort from luck and good fortune in the outcomes of management decisions. While there may never be enough data to control for all the uncontrollable factors, with better information about each element of the strategy, we can limit the number of unknowns.

        Information and the Value of “Nonproductive” Work

        Recognizing the importance of information, successful companies make information gathering an important part of the job for key people in their organization.

        We interviewed an engineering company in Pueblo, Colorado that specializes in GPS technology. GPS signals cannot penetrate buildings. But this company figured out how to get the signal from the roof to the inside. As a result, companies that manufacture equipment which uses GPS technology no longer have to go outside for testing.

        I asked the CEO about his success and he told me that he spends most of his time talking to potential customers and listening to their needs. Their sales force is tasked with talking to their customers, not to necessarily sell them on something, but to learn about their businesses. That in turn leads to conversations between the salespeople and the engineers about solutions to problems for which they know there is a market.

        Information gathering through communicating and listening can lead to better decisions about where to invest a firm’s money and effort. It comes from what might look like unproductive employee time. In the case of the Pueblo firm, it is an investment that lets the salespeople spend ten hours a week listening instead of selling.

        Soft information becomes hard information or something quantitative when you aggregate all the conversations that you have into a plan. If six people said yes about something, four people said no, and two people said maybe then you have data.

        Each numerical observation in a data set is a story that somebody tells. I think that for companies, their data are their stories. Successful companies are willing to invest in gathering information through what some might see as unproductive work. This calls for people who are good listeners and experts in information acquisition to be filling those roles.

        A Closing Thought

        Notice that in this discussion I did not use the term “data mining,” the idea that there is a mountain of data out there and the management challenge is to find the insights that lie within. Paying careful attention to acquire information that is needed to arrive at sound decisions and designing strategies to gather it is what will yield a competitive advantage.

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