Do Your Big Data Analytics Measure Or Predict?

By Bill Schmazro

Organizations have key business processes that they are constantly trying to re-engineer. These key business processes – loan approvals, college applications, mortgage underwriting, product and component testing, credit applications, medical reviews, employee hiring, environmental testing, requests for proposals, contract bidding, etc. – go through multiple steps, usually involving multiple people with different skill sets, with a business outcome at the end (accept/reject, bid/no bid, pass/fail, retest, reapply, etc.).  And while these processes typically include “analytics” that report on how well the processes worked (process effectiveness), the analytics only provide an “after the fact” view on what happened.

Instead of using analytics to measure how well the process worked, how about using predictive and prescriptive analytics to actually direct the process at the beginning?  Instead of analytics that tell you what happened, how about creating analytics at the front of the process that predict what steps in the process are necessary and in what order?  Sometimes the most effective process is the process that you don’t need to execute, or only have to execute in part.

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