Data Vision vs. Data Strategy: Why Credit Unions Need Both

Data transformation is arguably the most complex undertaking facing incumbents in financial services today. Credit unions in pursuit of data analytics maturity confront a huge spectrum of challenges. From cultural readiness and talent acquisition to data governance and processing power, there are several complicated prerequisites on the journey to analytics success.

Of course, the anxiety around anything complex doesn’t necessarily stem from the number of challenges; it often comes from not knowing where to start. And, where to start has everything to do with where you’re going. That is why locating a credit union’s North Star – the guiding light that will inform its data analytics strategy – is so crucial.

Data Analytics Needs a Why and a How

Before cracking the “how” of data analytics, credit unions must have a good handle on the “why.” For most credit union leaders, the onus for change is their members. It’s likely, then, the North Star, or the “why,” of the data analytics strategy falls under an umbrella of getting better at helping members achieve financial wellness. The digital era has brought with it an expansive set of possibilities for doing exactly that.

Products, services, channels and experiences credit unions once dreamed of delivering are now within reach thanks to rapidly advancing technologies. The catch, however, is that every digital solution relies on data – good, clean, accessible data.

Reaching data maturity means getting to a place where a credit union can consistently rely on that good, clean, accessible data. Getting there is not easy, but understanding the “why” of the effort keeps leaders motivated as they progress along the implementation journey.

It’s important to recognize a credit union’s North Star is not the same thing as a data transformation strategy. Whereas the North Star illuminates the path to data maturity, the strategy is the path.

There’s No Single Path to Data Maturity

Like a rigorous climb in the natural world, reaching the summit of data transformation can take many different routes. Just as rock climbers sometimes move vertically, sometimes horizontally and sometimes at an angle, credit unions each have different approaches to reaching data maturity.

To be sure, the divergent paths credit unions take add to the complexity the industry is facing as it confronts data transformation. A singular strategy to implementation – one that works for all – simply doesn’t exist. However, there are guideposts credit union climbers can rely on as they formulate their own path to the summit.

It’s crucial one of these guideposts – the development of a data strategy – is addressed first. The strategy serves as a credit union’s data analytics blueprint, implementation roadmap and budget and will impact every subsequent guidepost the credit union pursues.

A Lack of Strategy Is the Largest Barrier to Data Transformation

Those who have studied the credit union approach to data transformation consistently cite the same set of barriers – things like insufficient data science talent, outdated technologies and inadequate integration of data with legacy systems. In our experience, however, the lack of a definitive strategy is the single largest barrier to data transformation. It’s a truth that spans all sizes and types of organizations. Credit unions that do not determine the “how” that aligns with their “why” have a hard time staying focused – not to mention energized – as they move through the journey.

Establishing a definitive data strategy requires credit unions to put in time, effort and intentionality across three dimensions:

• Understanding the current state: What does the credit union have today in terms of the people, processes and technology? What are the resulting capabilities? How is data flowing in and out of the cooperative at this very moment?
• Visualizing the future state: Where does the credit union want to go? What are the business problems data analytics will help solve? Which of the possible use cases will yield the greatest impact?
• Designing the roadmap: Which steps does the credit union need to take and in what order? How do the priority initiatives line up with budget, time and talent resources? What are the quick wins that will drive motivation and keep teams moving forward?

A Functional Roadmap Is Extensive, yet Manageable

Although it comes third in the process of building a data strategy, developing a unique roadmap for a credit union’s way forward is arguably one of the most important steps. The roadmap must be extensive, detailing precisely how the credit union will build an enterprise-wide data analytics program with cross-functional components. At the same time, it is only the first of what are likely to be many iterative roadmaps over the course of a credit union’s transformation. No credit union, or any other organization for that matter, has the crystal-ball foresight to build a roadmap that functions in perpetuity. Agile organizations make it a habit to review plans frequently and adapt as necessary. The initial roadmap’s job is to get a credit union on the right path and prescribe incremental successes that ultimately inform the development of future roadmaps.

Incremental, Methodical Transformation Is Best

All-encompassing transformation of the credit union business model isn’t feasible all at once. Instead, growth-minded cooperatives are choosing incremental maturity in areas that truly impact the member experience today – areas like data analytics. With endless possibilities for deepening member relationships, improving business decisions and minimizing losses, data analytics brings a credit union’s North Star ambitions to life.

Yet, to be meaningful, data transformation must also be methodical. By applying a strategy-first approach and implementing it slowly and intentionally, credit unions achieve the transformation they need and the heightened experience members want.

Credit unions interested in more information are invited to download “The Strategy-First Approach to Data Analytics: Six guideposts for credit unions on the journey to data transformation.”

Shazia Manus is Chief Strategy & Business Development Officer for AdvantEdge Analytics, a CUNA Mutual Group company. She can be reached at shazia.manus@cunamutual.com.