Self-Service Business Intelligence Proves Itself

There's a growing trend in self-service data analytics spreading across the enterprise, loosening the grip of CIOs and data managers and putting the power of analytics into the hands of increasingly-lower rung executives. So what's up with this?

These days it seems we can thank big data for just about everything -- improved customer relationship management, micro-targeted pull marketing, enhanced loyalty programs, highly-customized account provisioning, you name it. While the dramatic increase in data volume has led to all kinds of business benefits, utilizing that data can be -- as the now-classic metaphor defines it -- like trying to drink from a fire hose.

The problem, in many cases, is that data analytics often struggles to keep up. Organizations that have failed to keep pace with their analytics may find themselves coping with growing numbers of dissatisfied data users frustrated with anemic results arriving too late with too little value. Often this is the result of well-intentioned IT departmental heads holding on to centralized data management and analytics in an effort to maintain governance, enterprise data consistency, and best practices. The outcome, however, is that everyone’s grumpy. Data users are unhappy that they can’t get the focused, valuable, timely results they need to do their jobs effectively, while IT is frustrated with inefficient data control and the sneaking suspicion that there’s a better way to handle cross-enterprise data management and analysis. And there is.

Coming to a cubicle near you: self-service business intelligenceEnter a new way to serve up customized data reports that puts users in charge of what they receive and how they receive it: self-service BI. This, in many ways, seems inevitable with the rise of big data. The reality is that most organizations have highly specific data analysis needs within horizontal units such as sales, marketing, finance, HR, and others. With all the juicy data now available, centralized enterprise BI teams are simply unable to deliver the highly-focused goods all these disparate business units want. The answer, of course, is to give the power to the people. By enabling business units to utilize their own analytical tools, richer, more relevant data can be brought to bear more quickly to create more timely, effective, and efficient solutions.

Simply put, self-service BI enables users to customize reports for their own needs, bypassing the predefined data and generic reports that are often the product of centralized enterprise BI teams. There is a downside to all this newly-discovered data power, though. It's the same problem enterprises have stumbled into with bring-your-own-device communications strategies struggling with disparate and perhaps conflicting self-service solutions that don’t play nicely with enterprise-level systems.

Still, self-service BI is just too damned attractive to be ignored. That’s why Gartner researchers have recommended a two-tiered approach -- create a single, centralized team working collaboratively with a collection of decentralized teams across the enterprise (here’s a nice summary of their centralized/decentralized BI research). The result (hopefully) is reaping the best of both worlds – business units get their highly-customized, more valuable and timely data analyses while enterprise IT can keep a watchful eye on data consistency, governance, and best practices.

In an Information Age article about self-service business intelligence, BI software vendor Tableau’s CEO Christian Chabot said, “I think we’ll look back at the analytics industry like we currently look back at typing pools. We live in that age now when it comes to data -- anyone who has a question is reliant on a high priesthood of specialists in the back room.”

Self-service BI is changing all that, and for the better.