Analytics: Unlocking Value in Business Intelligence (BI) Initiatives
Most companies are making a colossal mistake in how they are approaching the business intelligence challenge because they fail to realize data does not equal information.
Tue, April 14, 2009
CIO — Over the past few years, one of the hottest growth areas in IT has been in the business intelligence (BI) space. Companies have finally realized there is value in their data and have launched major BI initiatives in their organizations. But most companies are making a colossal mistake in how they are approaching this challenge because they fail to realize data does not equal information.
This is an important concept and bears repeating: Data ≠ Information.
To turn data into information, companies need a three-step process:
- Data Warehouse (DW)—companies need a place for data to reside and rules on how the data should be structured.
- Business Intelligence—companies need a way to slice and dice the data and generate reports.
- Analytics—companies need to extract the data, analyze trends, uncover opportunities, find new customer segments, and so forth.
Most companies fail to add the third step to their DW and BI initiatives and hence fall short on converting data into information. Why is this happening?
It really comes down to an issue with nomenclature. The term, "business intelligence" is the culprit here. Software companies like SAP (Business Objects), IBM (Cognos), Oracle, Microsoft and others in this space have put themselves in a great position by promoting the term, "business intelligence" to describe this sector. They are basically telling companies that if they buy their software, they will automatically have the tools-capability to gather intelligence to run their businesses. Plus, since these tools are providing "intelligence", they come with premium pricing.
This has become one of the most effective software industry marketing campaigns in the past decade. There is no question these software companies have very good tools for things like reporting, data mining, creating dashboards, etc., but calling this "business intelligence" has misled IT organizations.
Why? All of these tools, and the strategy and structure behind them, are geared toward providing data to business users and not creating information for them. This is because the tools are really just pipes with a business user using the pipe to get data out of the data warehouse. In the simplest of terms, a data warehouse is a box and BI tools are pipes coming in and out of the box—basic plumbing.
While it is paramount to have a solid DW and BI infrastructure in place, real "business intelligence" can only occur when analytics is also added into the mix. The DW and BI infrastructure allow business users to query against existing data, but it is only analytics that enable business users to go beyond the current boundaries of that data.
