What Was the Event About?
Leveraging data analytics for your organization involves so much more than running a report.
It is impossible to ignore the critical people, processes, and third parties involved in accessing and analyzing the data necessary to create a robust data analytics ecosystem at your credit union.
Effective predictive insights from data analytics can help your organization improve operational efficiencies, provide tailored products and services to deepen member relationships, and create a superior member experience. Filene Fellow Cheri Speier-Pero kicked off the event with guidance for successfully launching, maintaining, and securing the most benefit from data analytics. Put simply, credit unions should endeavor to build a data analyticsecosystem that will create value.
Data analytics is best approached as a journey, with organizations increasing capacity as they advance through ongoing cycles of iteration, improvement, and diffusion across the organization. Building a foundational data infrastructure early on is a critical component, but many successful organizations begin with strategic opportunities or problems to solve and then work backwards to find the data and capability to address them. Although there can be value from insights developed accidentally, most of your analytics efforts should be marshalled to support strategic objectives. As Sara Dolan described in outlining MSUFCU’s first steps into analytics, they began from: “here are our members and here are the challenges before us.”
...leaders must demonstrate a commitment to analytics and foster a data-driven culture across their organization.
A centralized analytics infrastructure is vital to providing useful data and a single source of truth, but this is only one piece of the ecosystem. The organizational adoption of analytics represents a critical element to delivering value. During his keynote, Viswanath Venkatesh from Virginia Tech identified three key areas where developing readiness was central to facilitating adoption: technology, process, and people. Adopting data-based insights may require a paradigm shift in mindset and operations. For their part, leaders must demonstrate a commitment to analytics and foster a data-driven culture across their organization. All staff need to understand the “why” for analytics adoption and be empowered to contribute.
As many credit union executives noted during the event, technical staff are important, but you also need people with deep knowledge of your organization and business to play a role in advancing the work of analytics. As Amber Cisneros from Orange County’s Credit Union noted, “Data without action solves nothing.” Include stakeholders in building infrastructure and processes to maximize usefulness. Include people who can help identify and root out bias in the data and the analytics. Recognize and capture insights from different use-cases and share lessons learned with other teams to build systems interoperability.
Returning to the ecosystem model, when it comes to data, no credit union can go it alone. Many panelists described how external partnerships allowed their credit union to develop more sophisticated solutions. Forging mutually beneficial partnerships can take time. Begin by identifying critical capability or data gaps that might be filled by a partnership. Before pulling the trigger, however, consider how your needs may evolve in coming years and include that into your assessment—can a potential partner fulfill your current need, but also grow with you as your needs change?
Don’t lose sight of your mission and delivering value to your members.
Finally, don’t lose sight of your mission and delivering value to your members. This may provide the best opportunity for credit unions to leverage data analytics and set themselves apart from other financial services providers. Ryan Zilker of Sound Credit Union described an outreach campaign for members identified to be struggling financially during the pandemic. Their empathetic approach proved effective at both alleviating hardship while increasing engagement. Part of Sound’s success came from a recognition that, as Brandeis Marshall from DataedX noted, “People are more than just a data point.”
What are the Credit Union Implications?
What are your next steps? Regardless of your current level of sophistication or size, nearly all speakers agreed on the following takeaways for credit unions looking to leverage data analytics.
- Get in the game. Data analytics is rapidly becoming table stakes for financial services providers. Don’t get left behind.
- Use analytics to create value. Begin with your strategy first. Explore how data can help address an opportunity or solve a problem. Look for easy wins, then grow your capability, size of projects, and adoption across your organization.
- Create a solid data foundation. It may start from humble beginnings, but your organization needs to develop an effective data management and governance infrastructure, technological capability, and sets of processes to make your data and related insights accurate and useful to the right people in your organization.
- It takes a village (or, an ecosystem!). Keep an eye out for the right partners as you build your internal capabilities and supplement them with external support. Even the largest organizations rely on an ecosystem approach to succeed. With the right partners, even smaller credit unions can quickly begin punching above their weight.
- It’s a journey. Build capacity over time, iterate, learn, and improve along the way.
The Future of Financial Services
For credit unions looking to build and grow their data analytics ecosystems, the road ahead may seem obscure where clear vision is preferred. At the same time, many experts predict that analytics adoption will accelerate in coming years as data sets expand and become more legible, the capacity to bring disparate data sources together improves, and expectations from members become demands. Analytics tools will improve ease of use and basic competencies will be further democratized. The day is not far off where business intelligence (BI) insights become as routine and necessary to operations as cash flow statements.
The writing on the wall has been digitized and analyzed—data analytics will be a critical element of financial services going forward. In terms of keeping up, analytics create insight to improve core business processes, member experience, and the bottom line, but analytics can also serve as a key differentiator. For credit unions looking to advance their mission, data analytics offers the promise of truly unique and human-centered insights that create value for members while demonstrating the credit union difference.
Filene is deeply appreciative for support for the Center for Data Analytics and the Future of Financial Services from Alliant Credit Union, America First Credit Union, Kinecta Federal Credit Union, Michigan State University Federal Credit Union, Together Credit Union, Visa, and Vizo Financial Corporate Credit Union.