Communications equipment maker Harris offers one example. The company has augmented its internal search capabilities with more traditional analytics, says Janice Lindsay, director of supply chain management. When engineers do a search for parts based on criteria such as power consumption or interface, an Endeca Technologies search engine looks at the raw results, then looks up quantitative information such as defect rates, available discounts, reliability ratings, and how much longer the part is expected to be manufactured. It then uses those factors to recommend which parts engineers should use. The results returned are filtered and ranked based on as many as 200 criteria, using information from ERP, manufacturing, product design, and other internal systems as well as from supplier systems and industry databases.
Through the use of dynamic summarization — a technique that does not require data cubes to be defined up front for the analysis tool to traverse — the Endeca Information Access Platform can analyze any data source for patterns, says Endeca’s Matt Eichner, vice president of strategic development.
Davis cites Factiva as another example of the unstructured analysis that might be brought to bear. The service searches Web sites and blogs to find mentions of companies, then analyzes the text to determine if the reference is favorable or not, ultimately producing a reputation index. Marrying this capability to traditional BI “is an interesting idea,” says Ovum colleague Charlesworth, “but it’s very early.” Davis estimates it to be about fives years out.
In the meantime, IT has plenty to do rationalizing its BI environment and meeting increased demand, and bringing BI into more operational aspects of the business. Remember one fundamental truth through it all, says Wachovia’s Thorpe: “You need to be business-driven, not IT-driven. Otherwise, you get a tool that no one uses.”