According to Gartner’s 2015 Magic Quadrant for Business Intelligence and Analytics Platforms (2/23/15), a key aspect of being a leader in the field of analytics is enabling business staff to perform interactive data analysis without requiring them to have IT or data science skills.  This is one of the reasons that for the 3rd year in a row, Gartner has positioned Tableau in the leader quadrant:

Gartner Magic Quad BI 15

In the past Business Intelligence and analytics initiatives were sponsored by IT with two primary goals:

  1. Provide a single version of the truth in one repository to eliminate inconsistent reporting results and complaints that the “database is not accurate”
  2. Reduce the crushing burden of creating and maintaining multiple reports that really just provide different ways of understanding the same data

While these two IT-related goals are still valid today, increasingly BI and analytics initiatives are being driven by the business staff who want to be able to make better decisions, faster, without waiting for IT. We see this every day in our work with associations – the staff want to be able to have a “conversation” with the data and ask new and better questions, interactively, on the fly, without waiting for IT to create reports. This new breed of business analyst in the association world does not typically have degrees in statistics or data science, but they do have business questions and they know that using data to make decisions will increase the likelihood that their decisions will be good ones.  IT wants to enable the business staff to perform this analysis without impediment, so everyone really wants the same thing.

We all place high value on making complicated things as simple and easy to do as possible.  Consistently making good business decisions is complicated enough – most of us don’t also want to have to learn complicated software in order to do it.  In our experience, enabling association staff to perform data discovery with Tableau has the delightful secondary benefit of inspiring them to begin asking new and ever better questions of the data, which in turn can advance the association’s mission.

But the tool is not the solution.  The next important thing to conquer on the data continuum will be the less appealing but absolutely essential functions around data governance.  Data governance is required in order to maintain the “single version of the truth” and ensure that everyone within the association is using the same definitions for key terms, like “member”, “customer”, “attendee”, and “donor”.  We call this creating a “common language dictionary” and believe me, it’s not all that “common”!

Leadership in association analytics requires IT and the business staff to work together to engage in data discovery and analytics initiatives that result in “democratizing data” for the business staff without sacrificing the data governance responsible for providing accurate, valid and secure data.