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Data-Driven BPM: Making “Big Data” Actionable

Conversation about “big data” often leads to more questions than answers. Where does big data begin and end? Business Intelligence, data warehousing, reporting, in-memory analytics? All of these?

The two questions that must be answered are these:

Conversation about “big data” often leads to more questions than answers. Where does big data begin and end? Business Intelligence, data warehousing, reporting, in-memory analytics? All of these?

The two questions that must be answered are these:

Business process management (BPM) helps moves companies away from silos; big data, too, is about breaking down silos for a cohesive view of information. This process improvement is what connects all the dots – BPM, big data and cloud primarily – to ultimately transform a business. Forrester’s Clay Richardson calls this “big process,” a way to truly grasp business intelligence enabled by big data.

As a result, companies are considering BPM from a “data first” approach, pulling together myriad data from all kinds of separate sources and putting it together in different ways. This single view gives someone the information they need to drill down on in order to make an informed decision. There are a few ways to pull data together:

Making the data “actionable” is the real challenge. When you’ve seen the trend, the risk, the opportunity or the action that you need to do – what next? Do you do what we’ve always done by emailing or calling someone?

The sweet spot of data and process IS making the data actionable. Seeing the information that helps make a decision on a composite dashboard is just the first step and where too many companies stop. True, there are wonderful emerging big data analytics companies today, and a growing number that add dynamic dashboards to view and interpret the data. Then what? A business must be able to fire off the business process to execute the decision made regarding the data. Hello, BPM.

Examples of such processes include:

This results in a “data first” approach to BPM. While difficult to put it into a neat box (we love our neat boxes, but technology isn’t always neat), a few examples with BPM in action in a big data scenario include:

These represent a wide-ranging set of use cases across a number of different industries, and many others are starting to emerge. There is quite a bit of commentary from industry analysts about big process meeting big data. We all know about top-down, bottom-up, middle-out, rules-driven BPM.

It’s time to add one more – data-driven BPM.