Your Credit Union Needs a Data Analyst, Not a Data Gopher

Your Credit Union Needs a Data Analyst, Not a Data Gopher


Have you been considering whether to hire a full-time data analyst for your credit union? Perhaps you are weighing whether data retrieval, analysis and presentation functions can continue to be split among existing staff, or whether one person’s dedicated focus is needed. Would there be enough need for someone to do this full time? Here are some thoughts to consider.

Gophers: Bad for golf courses and as your analyst

Don’t hire someone to merely be a “data gopher”. In other words, someone whose role is relegated to “go for this” or “get me that” tasks. Chances are good that many existing reports and tools could accomplish that already, although you’ll certainly experience a lot of situations where the canned solutions will not be quite enough to answer all your questions. You’ll need someone who can both build on what’s available and innovate.

Data analysts aren’t just for the “big”

Your credit union doesn’t need to be particularly large to benefit from having a data analyst on board. You may have native talent you can develop, and if so, great. Keep in mind, though, that people need time to develop those skills. And others will need time to follow up on the insights and action items the data analyst will suggest. Thus, hiring a dedicated data person may make the most sense.

Picture cells subdividing and proliferating—that kind of exponential growth is what you can expect of your data inquiries. The work will ramp up over time, and both the position and the person will evolve to suit those needs.

Third parties might leave you hanging when you need help now

A surge capacity solution of hiring someone ad hoc for your data needs may have been enough to get by until now. However, it’s hard to argue against the idea that having internal data capabilities would ensure you’d not be dependent on outsiders for things you should be able to do yourself.

It’s a little like having your own car versus depending on a friend or the bus. Being able to go where you want when you want means freedom. It means not being tied to someone else’s schedule or having your plans derailed by breakdowns and other events beyond your control.

In the data context, it means you always have someone who will give you top priority. Whether you are responding to examiners’ requests, to member service issues, or to anything needing an answer now, you know you will appreciate having someone reliable and available to meet those demands.

Other advantages you can expect

If you are still wondering what a data analyst can do for you and your credit union, here are some other advantages:

  • Identify growth and cost savings opportunities sooner
  • Pivot quickly to changing circumstances (e.g. we need this data today for an audit)
  • Catch errors and omissions before they become member service issues or audit findings
  • Leadership can focus on the big picture since data work is delegated to a specialist
  • Custom reports can be crafted to track performance and help people find their work for the day
  • The credit union can design its own targeted marketing campaigns
  • Desirable initiatives that were once too costly or impractical can be pursued now
  • Easily evaluate whether configurations function as intended (e.g. Is anyone being charged this fee?)
  • Use your internal expert to educate other team members on making the best use of the data tools available to them

I’m sold—who should I be looking for?

So, let’s say you are convinced and want to hire someone who will help get you there with data. What then? Which characteristics should you look for in a data analyst? Ideally, you should seek someone who…

  • Cares enough about getting it right that they don’t just take you at your word and ‘give you what you ask for’ on a data request, but instead ask precise questions to hammer out the best result.
  • Knows/learns the geography of where the data is and how it’s stored
  • Is/becomes familiar enough with the data codes to identify outliers and aberrant values and recognizes when results are misleading or don’t jibe with other data available elsewhere
  • Develops and implements best-practices approaches to data and reporting
  • Reaches out to others for assistance when needed
  • Thinks logically
  • Promotes data tools and educates people on using them
  • Does not feel threatened by questions or challenges to the data
  • Has eyes and ears open and alert to learning new things
  • Is not merely an order taker, but can suggest avenues of inquiry and action
  • Lays out and presents the data in a clear, compelling way that doesn’t leave a lot of unanswered questions

Finally, if you are still unsure after reading this, I recommend seeking out a credit union who has taken the data plunge and find out how well it worked for them. I expect you will be encouraged by what you hear.


  • George Hopper

    George Hopper is a Data Analyst at BlueOx Credit Union who has been helping credit unions measure success and their progress toward it for the last ten years.

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