This post is a comment to Ronald Damhof’s latest blog in which he argues the need for a stronger theoretical foundation in the field. By now, you should know that’s also one of my hobby horses. Let me illustrate the need for this kind of rigourness by two examples.
First, we all know the success stories of successful BI-implementations, especially those that were put on the stand by Davenport’s book “Competing on analytics”. Harrah’s, a casino and hotel chain is one of those examples; the CEO wrote the foreword of Davenport’s book. However, Harrah’s is also used as an example of a successful implementation of IT Portfolio Management (MIT Sloan Management Review, spring 2004, Vol.45, no.3) with corresponding net effects on Harrah’s performance. I won’t deny a priori the positive effects of both a portfolio management approach and the extensive use of analytics. But available publications gives us to little insight into the real net-effects and the causal relationships (instead of positive correlations).
This leads me to the second example. Even in scientific research we often read about the same succesful companies (sorry, no reference here). Amazon, Google, Dell you name them are always in the spotlights. In the ’80’s it was Sabre, American Hospital Supply (AHS) and Otis Elevator to name some earlier examples.
Why is that, I ask myself…
intriguing post…Arnott said it in his article (JIT- 2005 – 20), the field of Decision Support needs more case studies.
I would like to add to this that we – as a communituy- need case studies showing not only the good, but also the bad and the ugly…
Made a reference on my blog to this post….
Especially the bad and the ugly. However: referencing succes stories is also often a hard job. Most succesfull implementations have had as well success as hard times. The hard times tend to be remembered longer…
The successes everybody talks about are often succeses claimed by marketing-specialized companies. Which leads to the following question: Wasn’t marketing one of the first real business implementations of BI, so where are our marketing stories?