Synchrotech Group

Some assume BI to be the magic differentiator between great and average or mediocre companies. Consider this example. A financial institution had an acquisition target of 200,000 new accounts, a number that usually requires mailing offers to 10 million prospects while expecting a 2% return rate, an assumed rate for direct mail based on intuitive experience. Instead, this bank used BI techniques to mail to a “refined” subset of all prospects yielding a response rate of 12 %. Instead of mailing to the 10 million prospects, BI enabled the bank to focus the most efficient prospects and to only send mail to about 2 million, which generated the required new accounts. In addition to reducing cost, the average profitability of an acquired customer was three times higher than usual because data mining had targeted the customers whose needs best matched the bank’s services.

Another scenario

A rapid oil company takes information from 3'800 outlets and has information uploaded each night to servers at its headquarters. The chain’s main office immediately analyzes key operational measures: cars maintained costs, revenues, profits, and trends. By 5:30 A.M., performance data is available to the company’s managers who can check current revenue, average service price, time required to do each job, and other performance measures. Franchisees with multiple locations can see consolidated views, as can the company’s regional managers.