Reading the buzz on the Jim Davis’s presentation at SAS Global Executive Forum, what it made me realize is that if as an industry we can’t agree on what Business Intelligence is or Business Analytics, how are we supposed to make sense of it in implementation?
You have analytics players, enterprise application vendors, business process consultants, and analysts all trying to sell the ‘hype’ of a better way to analyze your business and makes decisions. SAS wants to sell their analytic solution that really pioneered data mining in businesses. Oracle and IBM wants to push dashboard solutions that links to business processes and their enterprise applications. Gartner that tries to tie together people, process, and technology but is really is focused on what technology to buy. Then, you have consultants that are trying to help you implement the technology even as they document your processes. The problem is that it’s all boiling down to the one with the best tool wins.
Enter in the ‘Business’ and now you have a problem. All they want to know is how they can meet their business objectives. IT is trying to sell the solution and make them understand the technology, and the business glazes over and can’t figure out what to focus on. I’ve sat in these discussions where IT tells me, “You tell us what to do, we’ll do it. Don’t worry about the solution.” It is open ended. This leads to IT unable to work towards tangible goals and results. The business walks away frustrated, projects run from months into years, and original budgets are thrown out the window. I liken these projects to Boston’s Big Dig.
Neil Raden provided a perfect way to get through the fluff and hype that surrounds analytics and business intelligence. See article From BI to Business Analytics, It’s All Fluff
“I don’t like the term business analytics; it doesn’t tell me anything. Frankly, I think business intelligence as a term is downright laughable, too. What does that mean? Is integrating data intelligence? Is generating reports intelligence? Maybe its informing, but isn’t intelligence something you HAVE not something you do? Does doing what we call BI lead to intelligence, or just some information? A long time ago we called this decision support, and that gets my vote.”
So here’s my take on what steps to take when and how to venture into BI and analytic solutions.
Steps:
- What decisions need to be made?
- At what point in our business and business processes are these decisions made?
- What information is needed at these points?
- How should our applications and data provide this information – triggers or visualization?
See the steps? It starts with the business decion and ends in the technology. So, when you begin to review vendors and solutions, make sure you have steps 1,2,3 in mind before you determine how to solve step 4.
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Filed under: Decision Cycle, business intelligence, performance management , Analytics, business analytics, business intelligence, Business process, Data mining, decision support, performance management
From SmartDataCollective:
by Terri Rylander on March 31 2009, 12:20
It really doesn’t matter what you call it – business intelligence, business analytics, decision support, or something else. What matters is that it provides business value. Accurate and appropriate information needs to make it into the process decision points, whether that’s a human or technology. I agree in general with your basic steps above but might add that you need to know what happens next in the process and how that information might be used further down the stream – so maybe it’s step 3.5. Really, the most important thing is keeping your eye on the end goal and purpose for using information, and making sure that gets met. Great post Michelle – thanks for moving the spotlight off the naming argument and onto the real objective!