The Trellance Data Blog

5 Traits of a Data-Driven Credit Union

Posted by Peter Keers, PMP on Feb 11, 2015 2:45:00 PM


Big Data/Analytics is increasingly on the strategic radar for credit unions. Much of the focus, however, is on software tools alone. This is only a part of the picture. The underpinning of a successful Big Data/Analytics effort is creating a culture that supports a data-driven credit union.

What is a data-driven credit union? In his forthcoming book, Creating a Data-Driven Organization, author Carl Anderson lists three characteristics of an organization that is NOT data driven:

  • Reports past or present facts without much context
  • Fails to explain why something has or has not occurred
  • Does not recommend what action to take in light of the information

Anderson defines a data-driven organization as having, “… the right processes and the right culture in place to augment or drive critical business decisions with [the right] analyses and so have a direct impact on the business.”

He lists some traits credit unions must develop to become data-driven:

  1. Collect the Right Data

This means not only collecting relevant data. It also means the quality of the data (“cleanliness”) is supremely important.

  1. Data is Accessible and Queryable

Data must be available and in a form that allows users to ask questions that yield meaningful results. The data “plumbing” is all important. If the “pipes” are not properly installed, the expected fountain of information is reduced to a trickle of undrinkable water.

  1. Make the Right Tools Available

An enterprise-grade Big Data/Analytics program needs to have enterprise-grade tools. Users at all levels must have the right hardware, software, and training to make the program work effectively.

  1. The Right Personnel

This trait applies to two categories of people. The first category is the data specailists. These are professionals who are trained and experienced  in acquiring, preparing, and analyzing data. The second group is all the other people in the business who use data to do their jobs. This group needs two important inputs: communcation and training. In the  Big Data/Analytics world there is no such thing as “build it and they will come”.  Users must be taught and motivated to be data-driven.

  1. Action Orientation

A definite hallmark of a data-driven culture is a bias toward turning insights gained from analysis into action. The entire Big Data/Analytics effort is wasted unless the results of analyses result in action that helps the organization reach its goals.

Credit unions seeking to be data-driven need to understand why having these traits are essential. Fulfillment of these criteria becomes the foundation of a program that delivers solid business value.

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