The Trellance Data Blog

Three Factors for Success with Credit Union Data Analytics

Posted by Mitch Nelson on Aug 28, 2019 12:52:00 PM


The credit union industry looks very different now than it did twenty years ago. Just think about what credit unions will look like twenty years from now. Where does the journey for the next twenty years start? Twenty years ago, it would have been hard to imagine remote deposit capture, peer-to-peer payments, or even mobile banking. It is equally hard to imagine what banking will look like twenty years from now. 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, or identify attriting members—and that’s just the tip of the iceberg. It all comes down to the basic idea that knowledge is power. And data provides that  knowledge. As credit unions continue to consolidate and disappear, those that are strongest come out ahead and leveraging data is a competitive advantage. Here are some basic success factors.

The Right People

How many people your data analytics program needs depends on the resources available to your credit union. Typically, larger credit unions can commit more personnel. The most important person is someone from the management team – every project needs an internal champion. They own the process and serve 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.

The Right Process

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

  1. Strategic planning: This 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: This stage is about assembly. Assemble your team. Assemble your infrastructure. Make sure you have all the hardware, software, and key players in place. Make sure that you have 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.

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. 

Putting It All Together

More analytics options exist now than ever before. Although many credit unions haven’t yet fully adopted analytics, the barriers to entry are becoming increasing 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.

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Topics: Data Integration, Data Analytics