The 4 Factors of Data Analytics Success in a Credit Union

The credit union industry looks very different now than it did twenty years ago. At that time, it would have been hard to imagine remote deposit capture, peer-to-peer payments, or even mobile banking.

What will the next twenty years look like, and where does that journey start? Just as we couldn’t have predicted the credit union landscape of today, the future is equally hard to imagine. However, one thing is certain: the trend of digital transformation will continue. For many credit unions, data analytics will play a big role in that.

Credit unions don’t necessarily need data analytics programs. However, credit unions that leverage their data remain better-positioned to provide individualized member experiences, remain in compliance, uncover new sales opportunities and identify members in danger of leaving—and that’s just the tip of the iceberg. It all comes down to the idea that knowledge is power – and data provides that knowledge. As credit unions continue to consolidate and disappear, those that leverage data to retain a competitive advantage will thrive. Below are some basic success factors for credit unions utilizing data analytics.

1. Choose the Right People

The success of your data analytics program depends on the resources available to your credit union. Typically, larger credit unions can commit more personnel and resources. The most important person is someone from the management team – after all, every project needs an internal champion. The data analytics manager owns the process and serves as a driving force, keeping everything moving and on track.

Supporting the manager are the technical staff. These are the IT professionals, data developers, architects, subject matter experts and report developers who work with the data. A good analytics team also requires input from business users. These are the team members who identify the credit union’s needs. Generally, the credit union’s data analytics solutions are created for (and with input from) the business users.

2. Build a Strong Process

There are four basic steps in any successful credit union data analytics journey. Here is what they look like:

  1. Strategic planning: The first stage is all about ideas. What issues does the credit union want to address? What does the analytics team need, and who do they need it from?
  2. Analytics platform implementation: The next step revolves around assembly. Assemble your team. Assemble your infrastructure. Make sure you have all the hardware, software and key players in place – and don’t forget access to the data you need.
  3. Analytics adoption and penetration: This stage is about continuing momentum. Analytics adoption means that once you’ve assembled your platform, your team integrates it into their activities. Analytics penetration is about getting actionable data to your business users. Essentially, this step is about follow-through—analytics is a process, not a goal! You should actually use your analytics capabilities once you have them.
  4. Control measures and management: Finally, you’ll want to know that your analytics are doing what they’re supposed to. This stage is about metrics: can you measure the impact? Can you calculate ROI? Does your solution work?
 

No credit union analytics program will succeed without these four basic processes in place. Without a plan and a solid foundation, you’re not likely to get results.

3. Use the Right Tools

The last factor for a successful credit union analytics program is the right tools. It doesn’t matter if you’re set up on premise or off—you’ll need capable hardware and supporting systems. Similarly, you’ll also rely heavily on software. How do you store your data? How do you move, transfer, and integrate that data? Finally, how do you report that data? You’ll need robust tools to maintain your data’s safety, quality, accessibility, and motility—otherwise, you’ll have a real tough time putting together graphical representations of that data.

4. Put it all Together

More analytics options exist now than ever before. While many credit unions previously didn’t fully adopt analytics, these days the barriers to entry are more manageable and affordable. If you’re not sure where to start, check out this article about how to start your credit union’s analytics journey. You can also look for consultants or vendors who can help—many have years of experience helping credit unions with their programs. From implementing data warehousing to providing analytics and reporting applications, support is there for you.

Interested in learning more strategies for success in leveraging data analytics at your credit union? Join us for the upcoming 2021 Trellance Credit Union Spring Summit.

See Event Details for the Trellance Credit Union Spring Summit

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