9781118041581

(Nancy Kaufman) #1
Collecting Data 129

In the last 25 years, all areas of business—from production to marketing to
finance—have become increasingly data driven.^1 This is true not only for tra-
ditional “bricks and mortar” firms but especially for e-commerce service firms.
Today, firms ranging from IBM to Google employ thousands of statisticians and
data analysts and pay them more than six-figure salaries. In the e-commerce
world, almost everything can be monitored and measured. The detailed behav-
ior of millions of customers can be tracked online. For instance, Google uses
scores of statistical techniques to improve its search engine, monitor search
behavior, and fine-tune its search rankings of the most popular sites.
Yet, data isn’t synonymous with knowledge. The key is to be able to eco-
nomically analyze enormous databases in order to extract relevant informa-
tion such as the firm’s demand curve. Fortunately, there are numerous,
powerful statistics and forecasting programs; these are spreadsheet based, user-
friendly, and readily available at low cost. This permits a powerful division of
labor. Computers are very good at uncovering patterns from huge amounts of
data, while humans are good at explaining and exploiting those patterns.
What’s the best advice for a college or postgraduate student preparing for
a business career or for life in general? After learning some economics, be sure
to learn enough statistics.

This chapter is organized as follows. We begin by examining sources of infor-
mation that provide data for forecasts. These include consumer interviews and
surveys, controlled market studies, and uncontrolled market data. Next, we
explore regression analysis, a statistical method widely used in demand esti-
mation. Finally, we consider a number of important forecasting methods.

COLLECTING DATA


Consumer Surveys

A direct way to gather information is to ask people. Whether face to face, by
telephone, online, or via direct mail, researchers can ask current and prospec-
tive customers a host of questions: How much of the product do you plan to buy
this year? What if the price increased by 10 percent? Do price rebates influ-
ence your purchase decisions, and, if so, by how much? What features do you
value most? Do you know about the current advertising campaign for the prod-
uct? Do you purchase competing products? If so, what do you like about them?

Data-Driven
Business

(^1) The way in which the statistical analysis of data drives business is discussed by S. Lohr, “For Today’s
Graduate, Just One Word: Statistics,” The New York Times, August 6, 2009, p. A1; and G. Mankiw, “A
Course Load for the Game of Life,” The New York Times, September 5, 2010, p. BU5. For an assess-
ment and survey of computer programs for statistical analysis and forecasting, see J. Swain,
“Software Survey: Statistical Analysis,” ORMS Today(February 2011): 42–47, and J. Yurkiwicz,
“Software Survey: Forecasting,” ORMS Today(June 2010): 36–43.
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