Beyond BI to EDM (again)

There is some great "premium" content on ebizQ for those signed up as Gold Club members (its free, just sign up here) including this one - Forrester: It's Time to Reinvent Your BI Strategy
. In this report Boris Evelson gives some good guidance on BI strategy in general but I can't help feeling there is more to it. For instance:

Forrester defines BI as a set of processes and technologies that transform raw, meaningless data into useful and actionable information.

Just because you have actionable information, does not mean you are done. You must take action also and, increasingly, this means that people who don't understand BI (front line staff, store clerks etc) or systems (website, IVR system, order processing system) must take these actions. The problem with a traditional BI approach, even a revamped one like that suggested by Boris, leaves you one step short of your goal. The person who knows first, or knows best, won't beat someone unless they can also act, and act correctly, first also.

There's lots of good stuff about BI in the report and then Boris says this:

Enterprises can't just focus on being efficient anymore. Squeezing more efficiency from operational applications such as ERP, CRM, or SCM, no longer helps enterprises to stay competitive. BI applications are needed for business processes and business operations to become more effective. For example, workflow and rules can be used to efficiently process a customer credit application, but BI analytics can effectively segment a customer population and target credit offers to specific customer segments for a better response and improved cross-sell and upsell ratios.

Now I am really going to have to disagree with him! Not, you understand, about the need to move to effectiveness rather than just efficiency. He's absolutely right about that. No, I have to disagree with him about BI being a solution to this kind of challenge.

BI, rightly or wrongly, has become inextricable from the functionality of BI vendors and that means they are focused on analysis and reporting tools. The rules and workflow in the customer credit application cannot be improved just by using BI - you need to think of the credit decision separate from the processing and you need to embed not just rules but also predictive analytics into the decision. You might well have rules derived from data mining, the extreme end of the BI analytics spectrum, but even here you are going to have to have thought about the problem as one of improving the rules for a specific transaction and not as one of analyzing the customer base to understand it. This is the difference between analytics in BI (more sophisticated analysis) and the analytics in enterprise decision management (making more, and predictive, information available for a specific instance in a specific transaction so as to improve a specific decision).

Boris goes on to say that

"BPM might make processing a customer credit application less expensive, but analytics can use sophisticated customer segmentation to increase cross-sell and upsell ratios in real time during a customer interaction -- when it counts"

And he is partially right. BPM certainly won't do this but I don't think most BI implementations will either. BI might help you find out what kind of things worked in the past or to identify agents who do a good job but this is just the beginning. To make this process more effective you also need to make the decisions explicit, automate them using rules and use analytics to derive those rules and to enhance them by adding predictions into the context of the single transaction.

Go beyond BI, even revamped BI, and use EDM to make your processes more effective.