Business Intelligence (BI) - ERP - Dashboards

How Valuable is Business Intelligence to the Enterprise?

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Finding 1
The BI Learning Curve Has Just Begun
Business intelligence use grows considerably as companies gain experience with this technology. Nearly 90 percent of our respondents use BI, and most others will probably start doing so in the next two years. Still, there are relatively few BI veterans out there—companies with more than half a decade of experience using business intelligence to analyze data on customers, competitors, internal processes or financials. BI veterans use BI for more reasons and provide BI tools to staff more than BI novices do. In particular, many more veterans use BI to analyze customer data. Projecting forward, that means BI usage will grow broader—there’ll be more kinds of BI applications—and deeper within organizations in the coming years. Analysts who predict the “democratization” of BI appear correct.

Finding 2
Effectiveness Is a Sometimes Thing
BI brings benefits, but many goals go unmet. In general, IT executives are bullish on BI; nearly three-quarters say it’s doing a good job of contributing to the bottom line and pleasing users. Newcomers to BI will be glad to know the more experience companies have with BI, the happier they are with the results. But drill down to specific goals and benefits, and the track record is spotty. BI is good at analyzing financial data and internal operations. However, it’s not as effective at analyzing marketing campaigns, or cross-selling and upselling to customers. That’s a problem, especially since these are likely to be big growth areas for BI, judging by how companies with extensive BI experience use them.

Finding 3
BI Success Depends on Execution
IT organizations must focus on data management, ease of use and providing real-time information.To achieve their top business goals for BI—improving processes, sales and marketing compliance and so on—CIOs cite three priorities: improving information quality, improving management’s ability to use information, and offering more kinds of information to more people. We asked respondents how they plan to accomplish these goals. No. 1, by a longshot, is improving data management; next, in priority order are improving ease of use, improving generation of real-time information and embedding BI into business processes and workflows. These tactics should be high priorities for any IT organization implementing BI. Unless they’re achieved, companies will be hard-pressed to generate much value from the tools they use to obtain business intelligence.

Finding 4
Garbage In, Bad Intelligence Out
Good data quality and satisfaction with BI information go hand in hand. But unfortunately, many companies report data quality problems reduce the ROI on business intelligence, even after five years’ experience with these systems. CIOs who invest in establishing data quality processes will be rewarded by increased user satisfaction with the information provided by their BI systems. In addition, about half these companies have undertaken a “master data management” initiative. There’s a correlation between master data management and BI’s impact on the bottom line, but it’s not clear if it’s the result of the MDM initiative alone or other efforts to improve data quality as well.

Finding 5
Weak Links in the BI Chain
In addition to data management and quality issues, CIOs must be concerned about strategic vision, integration, usability and weak points in the BI cycle. It’s startling to see that fewer than 40 percent of companies know what they hope to achieve with BI and how they plan to use it. This sets up BI for alignment problems, such as defining BI goals, and clearly affects the contribution BI makes. Lack of integration affects more than one BI user out of three and—no surprise here—it’s especially a problem with companies in which data quality is lacking. Companies are much better at collecting and organizing data than making it usable or putting it to work. No wonder 58 percent of respondents say users don’t know how to analyze or interpret BI data.

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Filed under: Business Intelligence

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