The job of IT departments can be concisely described as having two parts: managing data and advising business people about how the data could be used.
In many cases the use of new data sources can provide a huge boost to business profitability and success.
Examples abound in both the transactional and analytic arenas. On the transactional side, some of the biggest opportunities lie in the tracking of products and other physical objects via radio frequency identification (RFID) or, in some cases, more active mobile devices. Indeed, if you're in an industry such as retail, distribution or transportation, that's probably a top-of-mind issue for you and a major part of your company's medium-range capital budgeting. Also, companies in more and more industries are developing miniature commodity-trading desks and bringing in investment transaction data to support them.
Less obvious, yet potentially even more important, are the possible sources of new analytic data. There's data that's already available for you to collect, data that you can buy and entirely new data that you would have to create. There's conventionally structured data, unconventionally structured data and data that's barely structured at all. The possibilities are varied enough that if you don't take the time to think them through, you may well miss a company-changing opportunity.
Search-engine logs tell you of customers' questions and interests in their own words. General Web-visitor logs give you similar insight. You may have a lot of customer satisfaction and product-quality data sitting around to be text-mined from warranty claims, call centre reports and the like. And if a solution could be found to the privacy issues, even more information could be gleaned by voice-mining actual telephone conversations. In other cases, you can obtain valuable data from third parties such as credit reporting companies.
But the really mind-blowing possibilities arise when enterprises deliberately set out to create and capture data for the primary purpose of using it analytically through loyalty cards, location-based analytics, extra customer feedback and price/offer testing.
These examples are concentrated in CRM and product quality for a good reason -- those are the main areas of business where statistical analysis flourishes.
As the scope of predictive analytics expands, the opportunities for profitable data-creation strategies will do so as well.
Curt Monash is a consultant