Saturday, September 5, 2009

Operationalizing Business Intelligence


Linking business intelligence with business results gives workers out in the field better tools to drive day-to-day operations and customers better ways to make informed purchases.

At the advent of business intelligence, the idea was to put the right data and analytics in the hands of people who could make actionable changes that improve the way business is done. Somewhere along the line, that simple idea grew muddled.

BI systems grew up to be scattered across enterprises with the wind, complicated and difficult to use by even the business analysts. As enterprises assess how to move forward with their BI efforts, one of the driving forces of these initiatives is to make BI simpler, easier to access by a wide range of workers. In short, organizations want to bring BI back to its philosophical roots.

“One of the promises of BI when I started was empowering decision-makers and knowledge workers. It was to create pervasive BI and leverage BI for everyone,” says Dyke Hensen, chief marketing officer for PivotLink, who calls himself an old BI "oak tree" after 20 years in the space. “The problem is that over the years a lot of these offerings became very complex, very bloated and expensive.”

Hensen cites figures from The Data Warehousing Institute annual survey that showed the median cost just to maintain BI applications alone clocks in at around $235,000 per year. In his company’s case, Hensen says the goal is to reduce the cost of maintenance by offering BI capabilities via a SAAS (software-as-a-service) model to reduce not just the hardware and software costs, but also the number of employees needed to maintain systems.

However, according to Nimitt Desai, business intelligence and data warehousing lead for Deloitte Consulting, many organizations can’t even feasibly begin to leverage SAAS until they begin to consolidate their BI efforts. One major problem enterprises face today is the sheer number of BI applications spread out over an organization. Desai says it is common to see enterprises running well over 100 analytic environments that they must report against.

“When you have hundreds of systems, then SAAS is a myth,” Desai says. “But if you have a smaller amount of sources, I feel there is a big push in that direction.”

This drive to consolidate sources is much more of a possibility today than even two years ago with the push by major ERP vendors to help bring BI out of the cold and under a larger operational umbrella. Acquisitions such as the SAP pickup of Business Objects last year are a sign of where the BI space is headed.

According to Wayne Eckerson, director of research and services for The Data Warehousing Institute, this shift to bring together operational systems and BI just makes sense.

“It is kind of odd that you have to switch contexts, if you're an operational worker, from an operational app in order to open a dashboard or a report to understand what the impact was of what you just did or see the context of an action,” Eckerson says. “There is definitely an opportunity for vendors to take that gap out of the BI office and embed BI right into operational applications.”

Brian Kilcourse, managing partner for RSR Research, agrees that this "operationalization" of BI is one of the most impactful intelligence trends sweeping through enterprises at the moment. He says he’s seen lots of anecdotal evidence of how a shift to better embed BI within operations gives workers out in the field better tools to drive day-to-day operations or customers better ways to make informed purchases.

“We’re seeing a lot of companies injecting actionable information into operational processes in just-in-time fashion,” Kilcourse says.

For example, in one case study Kilcourse analyzed, he witnessed Virgin Megastores offer its store managers a strong way to improve sales. BI systems there were integrated with up-to-the-minute in-store sales so that managers could see how hit titles were selling in comparison to other hits with similar sales. The intelligence match-up compared the first few days of release of one title with other releases that had similar sales starts and gave managers the ability to project outward. It also offered actionable analysis that enabled workers to pair up other overstocked albums with hot sellers in endcaps to move otherwise stationary products.

Even though Virgin closed its retail stores for other reasons entirely, Kilcourse says this application of operational BI is too good to go ignored.

“They were basically doing a kind of a product mashup on the sales floor in more or less real time based on the signals they're getting from sales as they're occurring,” he says. “So they're basically doing shelf resets based on the fact that one title is flying off the shelves and they want the other one to fly with it.”

Kilcourse says that these sorts of initiatives help organizations better adopt a sense-and-respond type of mentality. He also believes that better embedding BI into operations provides very good back-end benefits.

“One of the big values of it is that the operational systems or the processes can then deliver back some information to the business intelligence system that says, ‘This is what happened after you responded.’”

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