As I’ve been surfing the current wave of chatter in the Business Analytics space, I see that the gulf between IT and the realization of business value is, unfortunately, alive and well.

This morning, for example, I attended a presentation by one of the industry's premier trade organizations on “operationalizing” big data analytics. I was looking forward to hearing how organizations are embedding big data analytics into their operational processes and systems. Instead, the presentation focused on the use of BI to make reports, dashboards, and scorecards available to a broader and deeper audience in order to overcome analytic "silos."

Don't get me wrong – I’m a firm believer that driving information and insight to a broader and deeper audience is an important piece of the puzzle. However, simply delivering insight and information to more people is not enough to realize business value and does not, in my mind, equal operationalizing analytics (from big data or any other source!).

To me, operationalizing analytics must include completing the value chain, which means ensuring that action is taken based on the insight. As IT leaders we must play a role in this critical link between insight and value!

How?

First, we must stop presenting the delivery of information and insight as the end of our initiatives. Rather, we must stress to our stakeholders that delivering information and insight is necessary, but not sufficient, to realize business value. Action based on the insight is the missing link.

Second, we must become part of the solution and help find the missing link. In other words, we must work with our stakeholders to ensure that the right processes, people, and downstream systems (automation is often the best way to ensure appropriate action!) are in place to operationalize the insights.

Some great examples of finding the missing link already exist.  Harrah’s, Amazon, and credit card companies, to name a few, have realized significant value by embedding analytics based action into their operational processes and systems.  Now that, to me, is operationalizing analytics!

I could stand on this soapbox all day, but I’d really like to hear my colleagues’ take on this topic.

Please add a comment and share your definition of, and experience with, operationalizing analytics!

 


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