S3 | E17: Putting Data Strategy Into Action: From Whiteboard to Real-World Impact

Organizations across the US financial sector are investing more time and energy into creating a data strategy, but many still struggle to move from planning to execution. In this episode of the Risk Intel Podcast, Jeff Fink returns for Part 4 of our Data Strategy series, sharing tactical guidance on how to operationalize a data strategy and deliver real business value. Listen to the whole episode below or if you missed Part 1-3, use these links to catch up.

• Part 1: How to Start a Data Strategy From Nothing: Make the Mind Shift From Stuck To Start
• Part 2: Defining A Data Strategy: What a Data Strategy is - and Isn’t
• Part 3: The Data Strategy Divide:  Why Reports Aren’t Enough

Whether you're a chief data officer at a regional bank or an operations leader at a credit union or community bank, this episode offers a practical roadmap for putting your strategy into motion.

Why Do Data Strategies Often Gets Stuck?

As Jeff explains, many data strategies live and die on the whiteboard. Institutions spend significant time defining goals, but never fully execute because they don’t know where to start, or they over-engineer the process before showing any tangible results.

The solution? Jeff says to start small. Deliver fast. Iterate intelligently.

Practical Steps to Execute Your Data Strategy

Jeff recommends following these four steps to transform your data strategy into actionable outcomes:

Step One: Start With a Business Goal, using Existing, Accessible Data

Anchor your efforts to a clear business priority, such as improving customer retention, increasing operational efficiency, or achieving regulatory compliance. Data initiatives that lack a business-driven objective often fail to gain traction. Think in terms of a minimum viable product (MVP). A simple dashboard on loan pipeline trends or customer churn can be a powerful first deliverable that builds internal momentum and proves value.

“Pick something where the data already exists and is accessible, something you can actually get your hands on.” - Jeff Fink

Choosing an impactful business goal is imperative for company-wide buy in, but it’s just as important to ensure you choose a goal where data is accessible. Whether it lives in your core banking system, CRM, or spreadsheets, Jeff says to avoid overcomplicating the early stages with data you can’t easily retrieve or validate.

Step Two: Assemble a Lightweight, Nimble Team

Build a small cross-functional team led by an internal data champion, someone who understands the data and the business. Jeff suggests someone like a business analyst or operations manager to help get started. Supplement with external advisors or partners to bring structure and accelerate results.

Assigning ownership, while still keeping the team small, enables them to hit the ground running. Smaller teams also allow for better accountability and quicker decision making. With the right people making an agile team,  the execution of the first part of the data strategy or “pilot solution” will be a quick win for any team.

Step Three: Deliver Tangible Insights Using Real Data

Pilot solutions must use real operational data (not test or sample data), to truly resonate with business stakeholders. Jeff warns against making this too complicated with a diverse set of tools and investments. For the pilot – something like Excel or Power BI can provide sufficient data insight. Since it’s so early on, there will be some level of manual transformation needed to deliver a valuable presentation of the data. It's important to show what the end result will look like and deliver a small, but meaningful success early on in order to retain excitement and commitment.

One of the most important steps in the stage of the data strategy execution is documenting everything. In order for this to be scalable, and to impact more and more business goals, it’s important to know what worked, what didn’t, and why. Jeff suggested documenting the whole process, including the feedback received from stakeholders.

Step Four: Create a Scalable Roadmap

Once you've delivered value, it’s time to think about scale. Collaborate with IT to design a production-ready architecture, implement appropriate governance, and identify needed roles such as data analysts and engineers. Consider long-term needs like cloud storage, data quality, and user adoption. This stage should include data validation, mapping to additional data elements needed, along with partnering with other teams to ensure architecture, governance, and people are aligned.

Ed and Jeff spoke about a technique their team implemented called a “pre-mortem”. This approach gathers the team to talk through the impediments, challenges, and potential obstacles before you go down this path. The goal is to increase the likelihood of success by thinking ahead of what could go wrong and coming up with solutions before these obstacles become problems, then enacting a scalable plan.  

Still Stuck? Here’s Jeff Fink’s Advice

If you're still unsure how to start executing your data strategy, Jeff’s recommendation is straightforward:

“Think big, but start small - and know you’re going to iterate from there. Avoid the Big Bang approach.”

Even modest wins build credibility, attract internal champions, and lay the groundwork for scaling your data program with confidence.

Want To Catch Up on the Full Data Strategy Series?

This episode builds on a robust foundation laid in Parts 1–3, where Jeff Fink covers topics like:

• Part 1: How to Start a Data Strategy From Nothing: Make the Mind Shift From Stuck To Start
• Part 2: Defining A Data Strategy: What a Data Strategy is - and Isn’t
• Part 3: The Data Strategy Divide:  Why Reports Aren’t Enough

Whether you’re just beginning your data journey or looking to refine your enterprise strategy, this series offers expert insights to guide your next move.

Looking for help bringing your data strategy to life? Contact SRA Watchtower today to see how our solutions and expertise in data management can execute on your strategy and goals.

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