BPM: Theory to Practice

Tim Huenemann

The intersection of big data and BPM

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Data and process are often at odds in mindshare and management philosophy. Have you noticed that some managers tend to be data people, while others are process people? Sentiments such as "we would do better if we had better information about our customers" are often detached from thoughts of "we would do better if we had more efficient and effective processes." But obviously, data and process are interrelated and management should be about both.

As your organization considers big data technologies or generally an increased use of large-scale analytics, there is an opportunity--and a need--to make sure your business processes (and BPM approach) are not ignored. Following are some areas where big data intersects with BPM and where the process management in your organization should be considered hand-in-hand with the new analytics.

More Insight
Generally, more analysis should lead to more actionable insight. Sometimes this insight can be used to improve business processes, or, on a larger scale, lead you to perform wholesale business process redesign.This doesn't necessarily mean there would be a change in the goals and approach of your BPM initiatives. But as managers get more and more data to play with, they will have more and more ideas, and the desire for process change may increase. It can be hard to predict what exactly will transpire--but in general, you should prepare for increased change.

Process Improvement
Specifically, some processes can explicitly benefit from the results of Big Data analysis. What used to be a gut-feel decision or a crudely automated decision can now be supported with large-scale analysis. In this case, it's good for managers or your BPM practitioners to get out in front of the change and analyze the impact that the use of big data will have on existing operations.

I suggest performing a "process impact analysis" of the new big data capabilities to see where they can and will be used and what processes will need to be updated. Don't deploy a bunch of new analytical capability into a functional area without anticipating and managing the process changes that will go with it.

Processes for Big Data
Sometimes a big data initiative creates a completely new set of permanent processes and roles to segment, analyze and summarize the data and package up the conclusions and insights. Just as with other expansions of capability or function in your organization, you need to design and implement processes according to your management approach.

Definition and Metrics
A common problem with big data initiatives is starting with lots of data without a plan for what to use it for and then vaguely wondering what can be done with all of it. The better approach is to identify statistics that are both predictive and persistent and then analyze the data to improve performance based on the evidence. Process work in your organization may have already identified key metrics (related to customer, internal, or supplier processes), and these can be used as input into a Big Data implementation.

Nothing in an organization should be done in a silo--including big data. Be sure to include process management in your big data efforts.

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This blog offers a true “practitioner’s perspective,” with issues and commentary based on real-world experience across many industries.

Tim Huenemann

Tim Huenemann is the senior principal for business architecture and process management at Trexin Consulting. He has more than 20 years of experience in process management and business-focused IT. In his consulting work, he helps organizations execute business strategy by implementing effective process management and IT solutions. He regularly translates BPM theory into practice, and practice, and more practice. Contact Tim at tim.huenemann[at]trexin.com.

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