The inability to translate data strategy into tangible use cases has been called by McKinsey, a consulting firm, one of the leading reasons why data efforts fail.
Let's unpack that a bit.
Data use case & data strategy.
Neither of these are strengths for most credit unions. McKinsey reported finding only 30% of financial institutions surveyed had a data strategy, and a data use case is not common vernacular.
Let's start with defining a data use case. A data use case is the business problem that an organization is using data to solve. For a credit union, this should be specifically defined as the member problem the credit union uses data to solve.
Members have four problems that they want to partner with the credit union to get solved.
1. Transportation problem.
The member needs transportation to accomplish basic needs. This should not be confused with an auto loan. The credit union should consider itself as the conduit to transportation.
2. Shelter problem.
The member needs a place to call home as a basic need. This should not be confused with a mortgage. The credit union is the conduit to shelter.
3. Travel and play problem.
The member desires either travel and/or play. They need a financial partner that will help them achieve these goals within their current financial condition.
4. Rainy day and retirement problem.
The member needs a financial partner that will help them set up short-term and long-term deposits.
A member may find themselves with a combination of these needs. They may have shelter but are looking to downsize. They may want to travel but don't know how to save. A member's financial needs describe the member's current financial journey. That journey is leading them to a financial destination that is the member's true financial north. The member's true financial north traditionally focuses on a variation of financial security. It may be retirement, it may be a first-time home purchase, or it may be a sixth car purchase. Members want to have the funds, when they need them, to make their financial dreams come true, to seek their financial true north. And wherever the financial destination is, there is data behind it.
Data comes from various sources, including but not limited to the core, MCIF, CRM loan origination system, payment system, and more. All this data reveals information about the member's current financial condition and their next financial need. It is up to the credit union to fulfill it.
Here are a few quick questions to identify how your credit union is solving members' problems.
What do we know about our members? Specifically, what can you pull right now to identify members' problems?
How do you position products? Evaluate the messaging, is there Auto loan messaging or Auto?
Evaluate the member problem resolution process. How do you think about the member engagement journey? Does it focus on solving the problem, or is it focused inwardly toward the credit union goals?
Gaining clarity on your member, their problems, and how your organization solves them is tantamount to improving your member's lives using data.
Where can I fill my data knowledge gaps?
With a stop at the
Data Education Center.
We believe that data transformation doesn't have to feel overwhelming or expensive to be impactful. After helping over 600 credit union leaders launch their data journeys, we have identified several consistent knowledge gaps. We have worked hard to fill these gaps with a variety of educational artifacts:
What if I want something more? Does someone offer data education classes with real-world applications?
Yep, that is what we do, of course, and so much more. To learn more, please review our data transformation institute
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