In Gartner's 100 data analytics predictions for 2025, they offered up this roadmap for data-driven transformation. It does NOT start with hiring or purchasing a tool. Let me repeat that, it 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.
Where can I fill my data knowledge gaps?
With a stop at the
THRIVE has created the only CPE accredited course that delivers the following:
Establishing an enterprise data vision
Creating member-centered data use case
Understanding/defining data maturity
The essentials of data governance
How to develop data consumption by enterprise talent
Building workplace adoption
Creating effective data road maps
Yep, that is 1 through 5 of Gartner's Roadmap :)
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Data Education White Paper
For a credit union to be successful with data, it has to overcome two pain points:
1. Filling organizational data knowledge gaps.
2. Providing a framework to help launch a credit union's data journey.
This white paper highlights the methodology and results of the offering. Students accomplished the following:
Assessment of current credit union data condition
Drafted a data vision statement
Created a data strategy draft
Identified member friction
Diagramed member experience journey
Leveraged member friction into a data use case
Proved proficiency in data maturity concepts
Created data governance plan draft
Resolved member friction use case using design thinking framework
Proved proficiency of center of excellence concepts
Built an Enterprise Data Road Map
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