There are many management fads that come and go: Poka-Yoke, Quality Circles, Taylor Principles, Management by Walking Around…I am sure you have your favorite.
One simple one that has stuck in our minds is “Management By Exception”.
What does this have to do with BI? Let me explain:
Imagine that you just rolled out a corporate data warehouse with 500+ metrics stored in it. How do you know which 10 of these to look at on any given day? Should you look at the “strategic” ones first and then drill-down to the rest (Balanced Scorecard)? Or should you look at the ones which are trending out of bounds?
Most managers we speak to prefer the latter approach: tell me where the “fire” is. Management By Exception.
But here’s the rub: by its very nature, you do not know a-priori where the “fire” will be on any given day. So if your BI strategy is to use a row-oriented database for your corporate DWH, augmented by spot summary tables to make it perform, you may find yourself boxed in. On any given day, you may find that one of the areas on “fire” has a metric for which your IT team didn’t pre-compute an aggregate. And *just* when you need to do rapid-fire BI, it fails you – until your IT department can turn around and build a new summary table for that particular metric x dimension combination.
Avoid this you can. Use an analytic platform that scales at query performance preserving atomic grain. In this Black Swan era of increasing volatility, BI patterns are becoming increasingly unpredictable.
Think about it. Do you disagree? Email us at blog_at_metricmine_dot_com