It can seem like a no-win situation. Business execs want more reports to glean insight on how to manage the company. So IT invests in new BI point solutions -- even as it spends more and more time cleansing data and producing reports -- only to be asked for changes again, since the reports IT delivers keep missing the mark.
That vicious cycle has bedeviled many an organization hungry for meaningful data. At the diversified manufacturer Ingersoll Rand, for example, an escalating quantity of resources was feeding a mélange of BI solutions that various business units use. The company had bolted on BI systems to all sorts of systems, from ERP to finance to CRM, "but we were not getting the value out," says Rob Martens, global director of front-office technology.
Boris Evelson, a BI analyst at Forrester Research, has heard such laments repeatedly. "Over the years, traditional BI deployments have encouraged a perception that it's a costly, complex environment," he says. In reaction, many enterprises have focused on dashboards -- simplified graphical displays that bypass full-blown BI systems and provide executives with business metrics in near real time. But the dashboard solution can be a false economy, Evelson says, because under any meaningful dashboard lurks the same hard groundwork to deploy reporting analytics and data integration, which together incur "80 percent of the cost."
Blame for BI's hit-or-miss ROI lies not with the technology itself but with a fundamental disconnect, says IDC analyst Dan Vesset. "To IT, BI means reporting, query tools, multidimensional analysis, OLAP tools, and maybe data mining," he says. "To an end-user, it could mean anything that supports their decisions." By treating BI as a set of technologies, most organizations veer off track, building ever-more-complex systems that fail to meet user needs -- while what's really needed is a better understanding of the underlying data and business requirements.
"Don't start with a data warehouse or analytics engine. Start with understanding the business issue," Forrester's Evelson advises.
Getting a handle on BI is increasingly essential. Forrester, Gartner, and IDC all identify increasing demand for BI in large organizations, as rising competitiveness pushes execs and line-of-business managers to stay on top of key performance indicators. Not only is a poor BI implementation "a Band-Aid on a hemorrhaging wound," says Ingersoll Rand's Martens, it can't meet the growing need to monitor how well processes are working, how customer demand is evolving, how current sales practices are affecting a company's financial health, and so on.
The message, Martens says, is to fix what you have before you try to expand it. "If you don't, you'll have an absolute train wreck on the way," he says.
Focusing on the core
Most corporations with major BI deployments create large data warehouses or collections of data marts whose incoming data must be cleansed to ensure integrity and consistency -- and whose relationships must be clearly defined in data cubes to ensure that analysis tools can run queries embedded in standard reports.
But if you start with that sort of architectural model, you're likely to fail, says Scott Sognefest, a partner in Deloitte Consulting's BI practice. "There's a growing realization that you can't put BI technology on top of a big pile of data. It's expensive and inefficient," he says. "You wouldn't build a factory and then decide what products you want to produce after it's built, but that's what people do in the BI space."
So understand the business case first. Then you can begin the messy work IT organizations have struggled with for years: building and refining a common data model and ensuring the data you need from multiple systems is consistent. "Data quality and data integrity are not going away. There's no easy way to solve them," says Betsy Burton, a Gartner vice president.
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