Simplification should go beyond data, says Kirk Hewitt, director of reporting and finance at Valero Energy, an oil refiner. Consolidate your BI tools as well. After a decade of acquisitions, Valero found itself with five BI tools in use. The company had already simplified its data environment through the adoption of a common ERP system, common financial management artifacts (such as chart of accounts and management software), and unified databases such as those for customer or refinery information. “We are really a big believer in master data management and in cleaning data at the source,” Hewitt says.
But having multiple BI tools meant that the analytics themselves differed across departments, leading to different results even from that same data. “You often had two different people asking for information, running reports on two different tools, and getting different answers,” he recalls. So Hewitt convinced management to replace the five tools with one from Information Builders. He justified the effort by demonstrating that the license and maintenance savings alone would pay back the consolidation effort in two years. But the lasting value is deeper, he says: “Instead of exploring differences in people’s numbers, analysts can now spend the time actually analyzing the reports.”
Another common BI mistake is to believe all data must live in a warehouse before it can be analyzed. “Today’s BI tools can point to any data store,” says Martens, who uses Oracle’s BI tools.
At the Hillman Group, a metal-products distributor, CIO Jim Honerkamp reached the same conclusion. In its Information Builders implementation, “We’re not using a data warehouse at all. We’re looking right into the databases supporting the transactional systems,” such as for finance and shipping, he notes.
Data warehouses and other historical data stores have their place, however. “You do need to store the data somewhere,” says Forrester’s Evelson, whether it resides in a data warehouse, a database, or a cache. The key is to determine what you need to use for which type of data.
At Valero, Hewitt’s BI applications tap into the SAP Business Warehouse for transactional data, into SAP R/3 directly for sensitive information such as that used by human resources, into an Oracle data warehouse for financial data, and into various SQL databases for departmental data. “There’s no need to pull data from a source into a data warehouse for cleanup and roll-up, and then run the analysis from that intermediate source,” he says. Not only does that add cost and complexity, the act of transforming all data into an intermediate form for the convenience of the BI tool risks losing the associated metadata and associated relationships.
Pushing BI closer to operations
Both vendors and users have become enamored with so-called operational BI. This typically means analysis “in line” to a business process, such as identifying unusual supplier activity that might require a change in pricing or manufacturing schedules, or noting higher-than-expected sales activity of lower-margin products that may indicate a problem in marketing, sales, or distribution.