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Data Success starts with Data Education


Gartner's 100 data analytics predictions for 2025, offered up this roadmap for data-driven transformation. It does NOT start with hiring or purchasing a tool.

Let me repeat that, data success does NOT begin with purchasing any resource at all. It DOES start with understanding the value of data and selling that value inside the organization, then envisioning the value to progress to a current state assessment and then education.

Data is one of the most robust assets any enterprise can have, and credit unions are in a fortunate position to have a plethora of it. For a credit union to succeed with data, it must acknowledge its organizational data knowledge gaps. It is difficult to move forward when no one is speaking the same language. Understanding the core competency in data knowledge will only strengthen a credit union's success in launching a data effort.

To harness and leverage their data to improve their member's lives, they need to have the following:

  • Straightforward, data vision and strategy

  • Member-centric use case

  • Data maturity (with rock star data governance)

  • A data-centric culture

  • Road map for workplace adoption.

Here are five questions to help determine the current state of your data knowledge.

1. Is the enterprise data vision relevant?

Take a moment to review the organization's data vision. What was the business problem identified that data will solve? Does it seem relevant? How should it be adjusted or just completely scraped?

2. What friction do our members/customers experience doing business with us?

Your members/customers are engaging with your organization in ways they may not have in the past. The iterative changes your organization can make to reduce friction will prove beneficial both short and long term.

3. What is the current state of our data culture?

Taking a moment to identify the good, the bad, and the ugly of your "new normal" will help bring clarity to positive aspects of your organization's culture and what to continue to encourage, foster and feed.

4. What is the current state of our organizational data maturity?

Take a moment to review the current state of your organizations' data maturity. What is the current state of your organizations' data? Do you have a formal data governance program? If data maturity feels like a low priority, please take a moment to adjust your thinking. Data maturity is the foundation, the blueprint, the architectural renderings to your dream data home. Most home building experts will never head to an open piece of land and dig and hope to create a home. Why would you do that with your data?

5. What does your workplace adoption road map look like?

What are the time horizons? Does it include strategy, culture, data maturity, and member-centric use case development workflows?

Education can come from various sources, including books, articles, webinars, and online classes. Ensure the education is credit union industry-specific and offers application of the knowledge.


For true data success, take the time to build up a data knowledge capability. It will pay back in dividends.

 

Summer School: Discount

We've got an August session of the virtual, actionable, data education 7-class series available for an INSANE 75% off

the standard price.

Perfect time to send more than one team member AND check the "launched data journey in 2022" box DONE!

Learn More



 

Looking for a little on-site, in-person data education?

You know you need a better data strategy to compete, but what’s the next step in your data journey?

CU Sol has assembled a great crew of talented CU data thought leaders to help you:

Demystify data so that you can de-construct your obstacles, differentiate your credit union to improve your members' lives!

Don't miss out on your Date with Data

August 15 & 16 at the iconic

America's Museum, Manchester, NH

Learn More


 



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:






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