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Is Data Education the Key to CU Survival

Originally published 5.25 in the CU Times

Data is generated by every credit union transaction that occurs, and adequate analyzation of that data can lead to numerous positive outcomes for credit unions, including the ability to gain new insights into member behavior and enhance the member experience, increases in product usage and income, and the chance to identify new lending opportunities. While credit union leaders recognize the importance of a strong data analytics strategy, many have a ways to go when it comes to developing and implementing one, and those that delay their work in this area by too long could suffer dire consequences.

That was the point driven home by Anne Legg, founder of the San Diego, Calif.-based THRIVE Strategic Services, and Alan Bergstrom, vice president of marketing and business development for back-office services CUSO Aux, who recently teamed up to create a new data education program, in a recent CU Times interview. All new users of the Lakewood, Colo.-based CUSO’s data analytics solution Cuery are given the option of enrolling in the program. Named the CU Elevation, the data education and coaching program lasts one year and is led by Legg, who teaches data analytics for the Southwest CUNA School of Management and has helped over 600 credit union leaders with their data analytics strategies.

According to an Aux survey of 30 credit union leaders conducted in February and March 2022, 97% believe data analytics is just as if not more important than it was before the pandemic – which forced many credit unions to put their data analytics strategy plans on pause. However, most agreed they are not where they hoped to be in their strategies at this point in time, and of those that named specific impediments to implementing a strategy, most stated that it was “another system they’d need to learn and incorporate” or “not in the budget yet.” Survey respondents were from credit unions ranging in asset size from $50 million to $4 billion and spanning U.S. locations from Montana to Maine.

For this CU Times Q&A, Legg and Bergstrom discussed their naturally-fitting partnership, what a data-driven culture might look like for a credit union and why it’s imperative for credit unions to make data analytics strategy implementation a priority.

CU Times: How did the partnership between the two of you evolve?

Legg: I had known Alan in other capacities, and [when what is now Aux was being created], I was working on building out data capability [for credit unions]. So we were working, as I like to say, in this data success continuum in our own swim lanes, and it was a natural conversation of, what does this look like since we have the same mission of trying to get credit unions to be successful with their data? It was like old friends talking about what we do, and then pretty soon we were doing it.

Bergstrom: A while ago, we had contracted with Anne to help us create some content around strategic issues involving the use of credit union member data. She has tremendous insight into what it takes to become a data-centric organization – the culture piece, the data governance piece, all of those things that aren’t technical in nature. So we built Cuery, which is a software tool to allow credit unions to more effectively access their data and integrate their data, but we don’t do any of the strategy or culture training or anything like that. As we were onboarding our first [Cuery] client, [the $319 billion, Cheyenne, Wyo.-based WyHy Federal Credit Union], we recognized that we can get all this technical stuff, but how are we going to get people inside the organization to understand the full potential that this technology can provide? How can they make decisions around it? How can they draw insights from the data? That isn’t our area of specialty, but that’s what Anne brings to the table.

Legg: With WyHy, it was about a year ago and there was this neat intersection where I’m out there fulfilling credit unions’ entry into data with the data education piece, and one of my clients was WyHy. And it so clearly came to me and I said, ‘Hey, Alan, I’m looking at what’s going on here, and this feels like a perfect intersection.’ And that’s when he said, ‘You know what, knowing what we know about our experience, it does feel like a perfect intersection.’

Bergstrom: Anne has taken her program, the 7-Class Data Education Series, into a number of state leagues, where it’s offered as part of a formal education and training program. WyHy had signed up for Cuery first, and they belong to the Mountain West Credit Union Association, where Anne was teaching her course. As Anne formalized that with that particular league, we said we’d be willing to sponsor some of the students to take her course. So we’ve done that twice now, I think we’re probably helped out about a dozen students at that association be exposed to her seven-part class.

CU Times: What does the data education program for Cuery clients entail?

Legg: So we’re really building up a capability as they’re using a tool [Cuery]. There are four phases, and the first one is onboarding. As you’re bringing on the Aux solution, we’re looking at what knowledge and enterprise gaps you have in this framework of capability. And then the next three phases, which are application, guide and level up, are all coaching components. Application is building proficiency – the credit union is saying, I know what I need to do, now how do we get that to be strengthened? Guide is building that traction and beginning to say, OK, now I see change, let’s make more change. And finally the level up piece is working toward that mastery.

Obviously in data, you’re never done, and that’s the whole point. It becomes this gorgeous, ubiquitous air that we all breathe, and for us to get to this ubiquity, you have to have this capability, comfort and confidence in what you’re doing.

CU Times: Who from a credit union is involved in data analytics?

Legg: It really goes down to who is going to be responsible for data success. That’s going to partially be your technical pieces, but also, who are your robust end users of data right now? Obviously you’ve got the CFO, but in addition to that, you have marketing, branches, cards and lending. You’ve got a lot of different data users who are going to be taking that data, bringing it through the organization and getting insights to level up and do new cool, amazing things for members.

CU Times: How would different roles within a credit union – say a CFO versus a marketing professional – approach data analysis differently?

Legg: Many times, we want credit unions to be looking at those ‘enterprise frictions.’ So they all may be working on something that they all have a part in. It might be, hey, let’s look at that overall lending journey, when the member comes in and what happens as they go through and get their product fulfilled. And then there’s that ownership part. Once they have that loan, what else happens to it? So when we think about the friction journey, the CFO is in there from a pricing, possibly a decisioning, possibly a risk management perspective, and marketing is in there from, what’s my target, what’s the channel and how do I manage pull-through? And now I’m looking at this dashboard that tells me that journey, and I can now see, wow, our pricing has a lot to do with our target. Out target has a lot to do with the channel. The channel has a lot to do with how we pulled through. These are all things that we’ve been working beautifully in our own silos, but now I can see that relationship.

CU Times: What does “creating a data-driven culture” mean and what should it look like at a credit union?

Legg: So we start at the point of inquiry. An inquiry isn’t limited to any discipline within a credit union, and it’s really what blossoms a data culture. We have these end users of data, and we’re coming at it from, what is their business problem? So maybe it’s a lending member problem, or marketing insight, and now you have this capability that is only limited by what your inquiry is. You infuse that data into the credit union’s DNA, and if I had to say what a desired end state is, it’s ubiquity. It’s everywhere, you’re breathing it every day and you’re using it automatically to make decisions.

CU Times: How do you address the roadblocks standing in the way of credit unions implementing a data analytics strategy?

Legg: Two big obstacles are time and talent, and what’s great about this relationship [with Aux] is that we’re approaching those head on and saying, let’s truly identify what you have. What is your ability? Do you have half a person who can do this? This isn’t something you have to buy into – you’re going to build it up the way your credit union can.

There are two things we do – first, we want to understand what you’re working on right now, because the credit union probably has a use case where we can kill two birds with one stone. Let’s understand what you’ve got and get in there. Second, the reason why this goes on for so long [one year] is because we understand you have other jobs. It’s digestible, and the way they’re understanding data is incremental.

CU Times: What might the long-term impacts be to the industry as a whole if credit unions were to neglect data analytics?

Legg: At the end of the day, we’re talking about relevance, not just from a holistic perspective, but in what the value is that you give to a member. We’re mission-based financial institutions, and with that, there are two really important nuggets. One is financial health, and the other is mission impact, and now we’re able to prove what those two things look like and define them, and be able to go back to the member and say, this is the value. Not necessarily that they just have an easier mortgage and they’re saving money, but that their life is better because they have a really good financial partner.

Bergstrom: I would say from an industry perspective, in addition to remaining relevant, is remaining competitive. If you’re not utilizing data, you’re going to fall further and further behind in terms of making smart decisions, performing better and delivering value to your member. When those negative things happen, credit unions are no longer able to survive, let alone thrive. We end up with fewer and fewer credit unions and I think that’s a bad thing for us overall. The worst case for the credit union movement would be that we have more than a handful of very large credit unions, and then the differentiation between credit unions and banks tends to go away.


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