Why credit unions can’t afford to wait on data analytics—and how to get started
The hardest part of data analytics isn’t the technology—it’s the cultural shift within the organization.
That’s the word from Brewster Knowlton, founder and principal consultant at the Knowlton Group, a business intelligence firm that works with credit unions. Knowlton moderated a panel at the Credit Union Analytics Summit here on how credit unions can begin their “data analytics journey,” and one participant was quick to shoot down any hesitation CUs might have about entering that field.
“To start, you really just start—that sounds simplistic and silly, but I say that all the time now,” advised Clay Yearsley, SVP of data analytics at Texas Trust Credit Union. “You need to commit a resource. Somebody’s got to be in charge of this. It really is too big to be somebody’s part-time job.”
In mid-2015, Yearsley was given the challenge of tackling what he called “this data thing,” and he told attendees that he began by doing a data gap analysis, examining what information and systems Texas Trust had, how it accessed information, whether data was tied to third parties, inventorying data gaps and prioritizing those gaps.
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