Some of you might have seen our CEO, Debbie King, speaking at ASAE Annual in Detroit this week.  If not you missed an inspiring presentation about building data analytics into your strategic plans and investing in a data guided culture.  Debbie was joined by Frank Krause, Chief Operating Officer of the American Geophysical Union (AGU), who offered brilliant insight and practical advice on making sure that association analytics are informative and actionable, not merely interesting.  At one point the evolution from static reports to data visualizations is compared to advances from film to digital photography.  This is a fitting analogy that makes the benefits hard to deny.

Have you ever heard of the term "Modelstorminig"?  It's where data modeling meetings brainstorming and it is the best way we have found to build scalable analytics solutions in an agile fashion.  In the old days, when  analytics professionals started gathering requirements for a business intelligence initiative, it was easy to fall into the trap of just doing what we were told. The association staff wants field X, Y and Z and they are used to A, B and C reports. We give it to them. Everyone is happy. For a minute. Then, they have new questions. Then we repeat the whole process again.  It's time-consuming and frustrating for both the business staff and the IT staff. As they say, "times are changing" and that old model simply doesn't work. Today we seek to answer both the questions the association staff have now and those they will have in the future. We try to answer questions they don’t even know to ask yet. This is what is means to "have a conversation with the data".  So, how do we do that?

In traditional project management, every engagement is defined by the triple constraint:  Budget, Schedule, and Scope.  However, we find that the most valuable and sustainable business intelligence results are achieved using the agile methodology.  By defining the “Scope” iteratively and collaborating closely with your association team, we are able to achieve the highest value from analytics within a given budget and time frame.

The Magic Quadrant

In February 2013, Gartner Inc. released an important report entitled Magic Quadrant for Business Intelligence and Analytics Platforms which details the current state of the business intelligence (BI) market and evaluates the strengths and weaknesses of several of the top vendors. It’s interesting to note that in this report, Gartner emphasized the emergence of data discovery into the “mainstream business intelligence and analytics architecture”, something we have been highlighting at DSK Solutions for years.

Business Intelligence (BI) projects that incorporate key aspects of Agile processes dramatically increase the probability of a successful outcome.