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James Taylor
James Taylor's Decision Management
James is one the leading experts in enterprise decision management, a published author and a principal of Smart (enough) Systems LLC. His blog discusses the use of decision management technologies like predictive analytics and business rules to deliver agility, improve business processes and bring intelligent automation to SOA.

« Sharing intelligence with your systems | Main | Decision management is critical to event driven architecture »

July 16, 2007
What lies between "gut feel" and magic when it comes to decision-making?

Timo Elliott over at the BI Questions blog had some great cartoons on this topic - this one about "gut-feel" and this one about what executives want from BI. These are both genuinely funny but they also point out a serious issue - that gut-feel may be overrated but that it will not necessarily be replaced with better decision-making just because more data is available.

It seems to me that there are two aspects to this problem - the problem of executives (who want the magic button for strategic decisions) and the problem of workers (who want a somewhat magical button for day-to-day stuff). Starting with the second one, you can (and should) focus on the challenge of automating decisions not just supporting them. After all, front-line workers have less time and less experience with data analysis and so are easier to overwhelm with data. They are also, perhaps, not the people you want making "gut-feel" decisions about your customers.

Clearly this does not work for the strategic decisions, however, as they are not repeatable enough to lend themselves to automation. Often these decisions are about decision strategy - how aggressive should I be about pricing decisions, about retention, about risk. If you think about each of the operational decisions (micro decisions) and automate them then one of the side effects is the ability to run simulations of how a change in strategy might impact these decisions. This is, of course, not something you could do if those decisions were being taken manually. This allows you to consider the macro as well as the micro decisions in a systematic way.

While this kind of decision simulation has not got to the point of being able to say "Let's say you want to save millions of dollars - you just push this button here", it is at the point where you can say "which of these three approaches should generate the best return, given the real-world constraints on my business" and then have an easy way to pick the rules that seem to work best and push them into production without pain.

I blogged about another Joe McKendrick post that seems relevant here - Sharing intelligence with your systems - and you might like this article on shifting your CPM into action. Meanwhile Cyril had a nice post on this too Decision Automation in BI: Design Guidelines for Business Analytics and Rules 

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Posted by jtaylor in Business Activity Monitoring • Business Intelligence • Business Rules • Decision Technologies • Predictive Analytics |Digg This|Add to del.icio.us

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