How to Read the Tea Leaves

By Paul B. Brown  |  Posted 02-06-2006 Print Email
How to Read the Tea Leaves
The Power to Predict: How Real-Time Businesses Anticipate Customer Needs, Create Opportunities, and Beat the Competition
By Vivek Ranadivé
McGraw-Hill, February 2006
224 pages, $29.95

"The information that drives business today can be harnessed to allow a new level of foresight, especially when we are able to analyze that information in real time and detect meaningful patterns." So writes Frederick W. Smith, chairman and CEO of FedEx Corp., in his introduction to this book by Vivek Ranadivé, the founder, chairman and CEO of Tibco Software.

The question, of course, is how do you predict the future? The answer, argues Ranadivé, is simpler than you think. "You don't have to be able to anticipate what will happen next year, or even in the next quarter," Ranadivé writes. "Just keeping a half step ahead can create huge advantages." Some examples:

  • Knowing that a customer who complains twice is likely to cancel his subscription, you have a chance to keep his business the second time he calls.
  • Seeing a correlation "between consumers who purchase one product and those who buy another is an up-sell opportunity."
  • Recognizing the patterns that inevitably lead to a problem on the production line can save you from losing a day's worth of output.
  • How do you gain such insights? Ranadivé doesn't get as granular as most readers would like, but he does offer a broad outline, the gist of which is that IT is at the center of the action.

    The first thing to do is to make sure you are capturing every possible bit of data that you can about your customers. How many and what type of customer contacts are there? What are they ordering? How often? By what means?

    Second, that information must be distributed in real time to everyone who could possibly be affected. And third, there need to be ways for multiple departments to analyze the data to find patterns.

    Finally, once that information is sorted and analyzed, it should be acted on quickly, either to prevent a problem or to capitalize on a potential opportunity. Even though you don't have a foreign sales office, for example, you notice you are getting customer inquiries from overseas.

    "Collecting real-time information from multiple business systems, correlating that information, comparing it to historical data and then acting upon the results is what predictive business is all about," Ranadivé writes.

    There is a back-to-the-future element in all of this. In the days of the corner grocery, the owner—who doubled as the person behind the counter—knew which customer always ordered an extra turkey for Thanksgiving. He or she was terrific at knowing what customers wanted—or would want.

    Ranadivé is really just talking about automating the process of staying extremely close to the customer by using the power of IT. While you may wish he had included a bigger "how-to" component in all of this, Ranadivé has provided another useful way of employing IT to gain a competitive advantage.



     

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