Analytics: Unlocking Value in BI Initiatives
- 15 April, 2009 09:42
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Over the past few years, one of the hottest growth areas in IT has been in the business intelligence (BI) space. Companies have finally realised there is value in their data and have launched major BI initiatives in their organisations. But most companies are making a colossal mistake in how they are approaching this challenge because they fail to realise 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:
- 1. Data Warehouse (DW)--companies need a place for data to reside and rules on how the data should be structured.
- 2. Business Intelligence--companies need a way to slice and dice the data and generate reports.
- 3. Analytics--companies need to extract the data, analyze trends, uncover opportunities, find new customer segments, and so forth.
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 organisations.
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.
This is because analytics is done by people and these people can look outside of the current data limitations in an organisation and can even look outside the company walls for answers. This is what separates data and reports from information and answers. This is providing "business intelligence."
When analytics is added to this structure, the entire offering becomes powerful. Analytics enables companies to move beyond reporting and into a higher decision-making and questioning mode. Analytics opens the door for things that will have maximum impact on the business: marketing campaign effectiveness, pricing, channel segmentation, customer treatment, supply chain optimization, risk mitigation, sales effectiveness, and so forth.
The only way to accomplish this, is to embrace the concept of analytics being a key component of any business intelligence plan. Business intelligence without analytics is just reporting.
So, instead of companies just talking about their DW and BI strategies, they must now accept analytics as a core component of business intelligence. This change in mindset will solve the dilemma of Data ≠ Information:
Current Mindset: DW + BI = Data
Future Mindset: DW + (BI + Analytics) = Information
Analytics will be the next big value-add offering for IT organisations. The businesses which embrace it, will grow. The IT organisations that own it and drive it will thrive. It is that simple.
Scott Staples is the president and Co-CEO of IT Services at [[xref:http://www.mindtree.com/|MindTree|MindTree
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