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James Taylor's Decision Management

James Taylor

Decision Technology as a platform for BI in business processes

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I saw this article in Computerworld on ROI Key to Melding BI, Business Processes in which the IDC event on Business Intelligence and Business Process was discussed, along with some companies who presented. This drive to bring BI, especially "Operational BI" to bear on business processes, especially those automated with BPMS, is getting a fair amount of traction recently.

If you want to bring BI to bear on business processes, especially those you are automating, you need to be clear what it is you want to do. Now presumably you want to improve the process - let's take that as a given, Do you want to use analysis of how you execute the process to improve the process or do you want to use your store of information about products, customers, suppliers etc to improve it? The first of these is what most BPMS vendors will do for you - they will help you see how you execute the process, what trends might be identified and help you use that information to improve the ongoing execution of the process. A nice feedback loop. But what if you want to use the data you have in your corporate data infrastructure?

Essentially you have two choices at this point - one suitable for manual processes  (or at least manual steps within a process) and one for automated steps. If you are thinking about manual steps then you can use traditional BI delivery vehicles. Thus when someone gets a work item on their work list you can make it easy for them to view and analyze the data that might help them make a good decision or take the right actions. But what if you have automated steps? What if you want to inform an automated step within your business process with analysis of your information? Clearly your software is not going to "look" at a report or "use" Excel. It needs some other way to get insight. This is where executable predictive analytics come in. Predictive analytic models are executable pieces of code or rules that take data in (customer payment history, location data, product pricing history or whatever) and put insight out (which product is most likely to appeal to this customer, how risky is this supplier etc). These models are built with the same kind of algorithms you here about in data mining and sophisticated BI but they are focused on delivering something that can be executed not something that can be viewed.

Now you can just go ahead and embed these kinds of analytics in a BPMS using SOA or some other way to bring pieces of code into the process. However, experience with using these kinds of analytics is that they are almost always combined with rules - rules about how to use the new prediction or when to take note of it and when not to. Rules for instance about not making cross-sell offers during complaints or about when to prioritize an apparently risky supplier because of its speedier turnaround. Because of this the most effective way to bring these kinds of analytics to bear on a business process is to develop a decisioning infrastructure, based on a business rules management approach, use this to build decisioning services that can be embedded in your business processes, and then enhance these decisioning services with the embedded predictive analytics. Not only does this allow you to mix analytics and rules effectively, it also allows you to constantly enhance your decision-making without having to change the business process (something I wrote about here).

I posted on this here and about it here on my other blog and discussed how this approach might deliver on key BI issues here. In addition I wrote some about the differences between BI and EDM (EDM or Enterprise Decision Management being the phrase used to describe rules and analytics together) and on why simply giving more people access to BI does not cut it. 

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Tom Davenport and the business analytics concours from Enterprise Decision Management - a Weblog on April 26, 2007 12:52 PM

Some colleagues recently attended The Business Analytics Concours Research Summit at the Babson Executive Conference Center - Wellesley, MA. I bring this up both because I think it is an interesting program and because Tom Davenport and Jeanne Harris were Read More

James Taylor blogs about decision-management technologies such as predictive analytics and business rules, discussing how they deliver agility, improve business processes and bring intelligent automation to SOA.

James Taylor

James Taylor blogs on decision management for ebizQ, and is an independent consultant on decision management, predictive analytics, business rules, and related topics.

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