How To Embed Analytical Minds Across An Organization

Wings Financial Credit Union ($4.7B, Apple Valley, MN) reformed its business intelligence and analytics team two years ago with the goal of nurturing BI and analytics skills across the organization.

To ensure it was focusing efforts in the right areas, the North Star State cooperative looked to the practices of a credit union known for its engagement between BI and analytics team and other departments. That’s how Wings conceived of the idea that became its Internal Practitioner program.

Today, Wings trains employees to build data queries and prepare visualizations for their own departments. The credit union currently has four employees participating in the program, which takes six to 12 months to complete.

Here, Mike Lindberg, manager of strategic analytics and member insights at Wings, talks about the program’s design, what employees take away, how it impacts the credit union’s mission, and more.

What’s the idea behind the Internal Practitioner program? How does it work?

Mike Lindberg: Originally, we thought we were going to train these folks to become our next data analysts, that this program would essentially act as an onboarding in case someone left or we wanted to expand. We had a curriculum focused on data architecture best practices, holistic data governance, and information on data science, but that was too much.

Now, we base the program on the capacity of the business unit to loan us that person. We target six to 12 months or six to 10 hours per week. Otherwise, we take requests for reports, analytics, or data science for employees who go through this program to complete. We gauge how long each project will take, and that’s how long the work loan is.

How is the work different now?

ML: The sweet spot is in the data visualization and interpretation side of things, so we focus on using Tableau and querying a SQL database. Learning these skills is enough to handle most of the requests that come in.

Our ultimate goal is to provide high-level data governance and train them on where to look for the data they need and how to query it. We use Tableau for our data visualizations, so they need to learn that system. Then, there’s a work list of different projects their business unit leader has submitted, so they get to work on those.

What business units have employees in the program? How did you select these units?

ML: We chose business units based on the volume of requests coming in and their willingness to try the program.

We picked consumer loans and IT when we first started more than a year ago. We’ve since expanded into mortgage lending and payments systems. These are business units that have significant impact on organizational revenue and member experience but don’t have incentive-based pay. Ideally, we’d target retail delivery and others like that in the branch network, but we would have to account for their missed sales in some capacity.

How did you choose the employees you did?

ML: Business unit managers choose practitioners who have a desire to learn. In most cases, these are younger folks who had some interest in analytics or in doing something beyond what they’re currently doing. The program affords an opportunity for employees to enrich their employment and learn a new skill.

Do you use a grading system to measure how proficient they are?

ML: We’re working on that right now. With the help of the manager or vice president the practitioner reports to, we set a performance goal that’s mapped to the program and grade them based on items delivered.

We’re working on measuring proficiency with the tool and things like that, but their ability to deliver something that is both acceptable and functional for the business unit is really the statement of their knowledge of the software.

How does Wings benefit from this program? How does the employee?

ML: From an organizational standpoint, our practitioners are helping us align the analytics with the business. They help enrich the business unit’s usage of data.

For the individual, this allows high-performing employees to step into something a little more strategic, less operational. And, it will help them in their career. These folks have really taken an interest in BI and analytics and have communicated some desire to move into this space in the long-term.

We still have a center of expertise with our BI and analytics team, but we’re able to distribute knowledge all through the business units.

How long have you had the program?

ML: The two practitioners who started the program have been in it for longer than 12 months. We found that once the business unit adopted the analytics, the work didn’t dry up. So, if we initially had a list of 20 things, and we delivered those, we now have a list of 40. More questions are being asked of the practitioners and it’s helping the decision-makers in the business units make better decisions.

The second two are six months in.

What sort of feedback have you received from the practitioners themselves?

ML: They’re excited by their work. If nothing less, our BI and analytics team is run like a consulting unit, though I consider it more of a servant to the organization. We serve our organization; those who work well on our team are those who are able to serve.

It’s a mentality shift that comes with working for a credit union. The service we provide within the organization is rewarding because the net effect is for the entire membership to benefit.

Can you talk more about the service aspect?

ML: As a credit union, we are focused on our membership. But the truth is we get to serve our members. Instead of taking from the customer and giving to the shareholder, we work to provide value to our member-owners. Our analytics team, and certainly our practitioner program, are looking to reinforce that by serving our business unit leaders to make better decisions that benefit our entire membership.

What lessons have you learned since starting this program?

ML: We started out thinking too much. We built it thinking we needed essentially to train our replacements. We’ve found the sweet spot that aligns these practitioners in a way that they can be the resident experts within their business unit and still rely on insights from our BI and analytics team. It provides us with a hybrid analytics model. We still have a center of expertise with our BI and analytics team, but we are able to distribute knowledge all through the business units.

This interview has been edited and condensed.