Business intelligence and decision making often not linked, Gartner says |
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By Jeff Kelly, News Editor
28 Apr 2009 | SearchDataManagement.com |
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One need only peruse the business pages to realize that a rash of poor business decisions have been made over the last several years, from banks deciding to invest in risky mortgage-backed securities to the Boston Globe's decision not to invest in Monster.com.
Despite huge investments in business intelligence (BI) software and platforms that have resulted in a more informed workforce, most companies still fail to link BI to "the last mile" of business decision making, according to a recent report from Gartner Inc.
The lack of a connection between BI and the decisions it affects has also led to a lack of transparency at many organizations. That prevents BI from getting the full credit it deserves when it results in good decision making, said Kurt Schlegel, an analyst with the Stamford, Conn.-based research firm and co-author of the report.
"Despite unprecedented information availability, the past decade suffered from several imperfect decisions made in both the public and private sectors," Schlegel wrote. "It is not enough to provide voluminous access to information and expect good decisions to be made as a result."
The BI lifecycle is made up of three stages, Schlegel said. The first involves simply organizing, cleansing and collecting data, followed by the second stage of delivering that data, often in the form of reports, in a consistent way to consumers. The third and perhaps most important stage, he said, is actually applying BI to decision making.
Many organizations have matured through stages one and two but have yet to make the leap to stage three, Schlegel said. "It's a crawl, walk, run kind of thing, but I think most organizations are ready to move to stage three."
In order to make the transition, he said, organizations must develop decision support systems that allow them to use BI-related analysis and reports to experiment with more "what if" scenarios that track how a decision was made, with what data, and by whom.
Schlegel called on the BI mega-vendors – SAP, Oracle, IBM and Microsoft -- to invest more resources in developing decision support systems, though he conceded it could be some time before that actually happens, as profits for such technology are initially likely to be low. "Mega-vendors look at emerging markets and, unfortunately, they're often not important to them," he said.
With a dearth of available "out of the box" decision support products, then, collaborative and social software is, at this point, one of the easiest ways for organizations to connect BI with decision outcomes, Schlegel said. "It's a really simple idea with so many benefits."
Collaborative software, like Microsoft's SharePoint Server, could be used not just to let workers share BI reports, he said, but also to test assumptions and potential decisions with the related data.
"This environment would allow decision makers to remotely collaborate in discussions around assumptions, incorporate relevant BI analysis and other decision inputs, and explore and gain consensus around the pros and cons of alternative courses of action," Schlegel wrote.
Collaborative software can also provide a record of how decisions were made -- information that now is often lost once the process is complete. Such records are likely to become increasingly important, he said, as new government regulations emerge demanding more transparency by businesses. They can also help grow institutional knowledge.
"Connecting and capturing this thread with decisions made and outcomes would give organizations greater transparency into how decisions are made," he said, "so that they can identify trusted decision makers and reuse successful decision patterns that represent best practices across a broad range of highly structured and ad hoc decision processes."
Companies should start the process by taking an inventory of the decisions they make and identifying the ones that are most important to their business, Schlegel said. Determining how many temporary staff to hire during the busy holiday season might be a critical decision for a retailer, for example, or -- for a manufacturer -- whether or not to open a new factory.
"[Companies should also] begin a cultural transformation focused on developing decision optimization as a core competency," Schlegel wrote. "Start with a corporate education effort around decision-making best practices, and provide opportunities for decision simulation to socialize the value of transparent decision making and create a common corporate vocabulary to drive a cultural shift."
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