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The Three Dimensions of Intelligent Business Processes

(Posted by guest Blogger, Gib Bassett)

Today I read a September 21 Gartner Research note by Gareth Herschel titled, “The Role of Analytics in Adding Value to Business Processes.”  As someone expert in analytics more so than Business Process Management (BPM) and Business Rules Management (BRM), Gareth raises some important points to remember when discussing the role of analytics in business processes.

This topic is all the rage right now, but few have raised the points Gareth does.  Consider his viewpoint that there are three ways analytics add value to business processes, and the implications of each.  The degree of difficulty escalates with each level, culminating in the third dimension where decision makers rely more on data derived facts than gut instincts to affect process performance.

  1. Easy - Analytics to remove either high cost or low value steps in a process.  Lower cost product replacement over higher cost repair, and fast tracking low risk claims, are examples.
  2. Less Easy - Analytics added to a process.  Using customer service call history as an input into cross or upsell offers is an example.
  3. Hard - Analytics to support the improvement of a step or steps within a process.  A retail bank analyzing its marketing offers to determine how results would vary based on different communication scenarios is an example.

Number 3 is considered hardest because it requires admition by a process “owner” that performance data may support a more effective process than personal experience or domain expertise.  That’s interesting in light of many Business Intelligence (BI) vendors focusing on providing just these types of analysis, yet they almost universally lack a closed loop back to the operational systems or applications in question.  So there’s an inherent latency involved that agile-minded organizations will find unappealing – and yet Gareth notes the agile-minded are key supporters of the easiest of the three dimensions.  I see dichotomy here in that the more difficult (and potentially most valuable) approach happens to support the least agility (but it could).

An Enterprise Decision Management (EDM) approach avoids this scenario by serving as the glue between traditional BI and BPM software; rules, policies and analytics can all be managed separately from their execution environments and be as “real time” as required when rendered as SOA-compliant Decision Services.  I would also note that an EDM approach to decision management facilitates the coming together of the application developer and BI-sides of an IT organization.  This can especially be helpful in light of this closing note by Gareth:

"Determining the appropriate combination of analytical techniques, and the different aspects of the process they can support, will become a critical domain skill for business process managers and developers across every organization. In every case, the analysis that is used should become part of the tracking and measurement process to ensure that the analysis and the decisions taken as a result of the analysis are correct."

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