Research brings it together
It is the bane of modern business: too many data, not enough information. Computers are every—to extract significance from the blizzard of numbers, facts, and stats. Help is on the way, in the form of a new class of software technology known broadly as data-mining. First developed to help scientists make sense of experimental data, this software has enough smarts to "see" meaningful patterns and relationships—to see patterns that might otherwise take tens of man-years to find. That is a huge leap beyond conventional computer databases, which are powerful but unimaginative. They must be told precisely what to look for. Data-mining tools can sift through immense collections of customer, marketing, production, and financial data, and, using statistical and artificial intelligence techniques, identify what is worth noting and what is not.
The payoffs can be huge, as MCI Communications is learning. Like other phone companies, MCI wants to keep its best customers. One way is to identify early those who might be considering jumping to a rival. If it can do that, the carrier can try to keep the customer with offers of special rates and services, for example.
How to find the customers you want to keep from among the millions? MCI's answer has been to comb marketing data on 140 million households, each evaluated on as many as 10,000 attributes—characteristics such as income, lifestyle, and details about past calling habits. But which set of those attributes is the most important to monitor, and within what range of values? A rapidly declining monthly bill may seem like a dead give-away, but is there a subtler pattern in international calling to be looking for, too? Or in the number of calls made to MCl's customer-service lines?
To find out, MCI regularly fires up its IBM SP/2 supercomputer, its "data warehouse", which identifies the most telling variables to keep an eye on. So far, the SP/2 has compiled a set of 22 detailed—and highly secret—statistical profiles based on repeated crunching of historical facts. None of them could have been developed without data-mining programs, says Lance Boxer, MCI's Chief Information Officer.
Data-mining in itself is a relatively tiny market: sales of such programs will grow to maybe USD 750 million by 2001. But the technology is crucial in getting a big payoff from what information technology executives think will be an immensely important growth area in coming years: data warehousing. There are the enormous collections of data—sometimes trillions of bytes—compiled by mass marketers, retailers, or service companies as they monitor transactions from millions of customers. Data warehouses, running on ultrafast computers with specialized software, are the basis on which companies hope to operate in real time—instantly adjusting product mix, inventory levels, cash reserves, marketing programs, or other factors to changing business conditions.[1]
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