Sunday, March 2, 2008

Welcome to the Analytics Theme

How do you make important decisions? Do you trust your gut - or crunch the numbers? Flip a coin - or build a spreadsheet? Ask your spouse - or ask your SPSS?

Does your company make decisions the same way? Decision-making is becoming a key management competency driven by globalization, complexity, and risk. Should we be making these bigger, harder, riskier decisions the same way we've decided things in the past?

In the Analytics Theme at DIG we're going to discuss how decision-making can be improved by developing performance models and applying different analytical techniques to those models.

These techniques - decision trees, probability and statistics, simulation, regression, and optimization - may be ideas you vaguely remember from your Management Science 101 class, or they may be things you and your company are doing on a daily basis. Either way, we want to talk about them.

Once limited to the "quant jocks" with their cumbersome analytical software packages, these techniques are now widely-available thanks to advances in software tools and increased availability of data. And they're being used in some fascinating ways.

We'll hear some of these stories from our speakers and clinicians, but we're hoping to hear the best ones from you. How are you using the tools? How are you applying the techniques? And how are you improving decision-making through analytics?

To get started on this section of the blog, check out CNN's coverage of the Texas and Ohio primaries this Tuesday. I've been watching the campaigns with interest and have been fascinated with CNN's "Delegate Counting Map." They have the typical color-coded states (or counties, depending on the view) showing the results, but are able to run numerous simulations of future scenarios just by tapping a few icons..."If Obama wins the remaining states 55-45, here's what the delegate-count will look like heading into the Pennsylvania primary..."

An intuitive user interface, lots of good data, and the ability to quickly run simulations - that's a powerful analytical environment. Wouldn't it be great to apply the same ideas to your monthly reporting environment?

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