These days, everyone wants to be able to "compete on analytics," as more stories come to the fore about struggling organizations that leveraged their customer or business data to make new and profitable discoveries, thereby saving bundles of money.
However, too many executives get caught up in the hype and excitement and end up laying out too much money for expensive BI solutions that they may not have even needed.
In a new article published at DM Review, Rick Sherman, founder of Athena IT Solutions, cautions that many companies and executives grab at a BI solution, then sit back and expect a deluge of news insights into new and existing business opportunities. It's time to clear away some of these misconceptions, Sherman says.
The four most prevalent flawed assumptions about BI include the following:
1) Assuming this is all revolutionary stuff. Business intelligence has been around since the 1990s, Sherman points out, adding that "BI tool technology hasn't changed much in the last several years, but the way it is marketed certainly has. Initially, these tools were marketed for organizations building data warehouses (DWs).... Since Y2K, however, ERP teams and the ERP vendors have shifted their attention from getting the data into applications to getting useful business values out of that data. With new interest from the ERP vendors who started partnering with the BI vendors, they realized they could market their tools to be used for that task."
2) Assuming that everyone needs real-time data. "Most business processes don't need real-time data. In fact, real-time data would cause problems or create noise, e.g., inconsistent data results, that would have to be filtered out.... you build performance management and BI solutions to satisfy a business need. Real-time BI often is suggested because it can be done technically, not because of a business need."
3) Assuming that you have made the data warehouse obsolete. "t's often asserted that 60 to 70 percent of a DW effort involves data integration. And that's just the beginning, because data integration becomes an ever-expanding issue as more data sources, both internally and externally, are added as you enable more data for the business users. DW is essential to most enterprises to enable data consistency, ensure data integrity and quality, and store historical data for trending and analytics."
4) Assuming that operational BI should be separate from "legacy" BI. Business users need information to do their jobs, so their BI tool should get that data regardless of where it is or what form it's in.
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