Analysis Paralysis: Is your data handicapping your bank?

The challenge facing most community financial institutions is not a lack of data. Institutions send millions of datapoints through expensive networks and applications to process, transmit and maintain daily operations. Simply having an abundance of data available does not automatically correlate actionable, valuable insights. This inundation of data is often the primary or first obstacle that hinders rather than helps bankers make smarter decisions and more optimal choices, leading to analysis paralysis.

But what is Analysis Paralysis? Analysis paralysis is the inability to effectively monetize data or information in a meaningful way that results in action.

As many banks have quickly discovered, the true value is not in simply having an abundance of data, but rather, being able to easily turn this cache of data into actionable insights that drive the institution’s ability to serve its community, streamline operations and gain a competitive advantage.

The first step in combating analysis paralysis is having a single source of truth and a centralized data strategy.

Far too often, different departments within the same organization produce conflicting reports with conflicting results despite relying on the “same” input and data sources. This is problematic for several reasons, but most significantly, it limits a banker’s ability to make critical decisions. Establishing a common data repository, defining the data structure and flow with an agreed-upon lexicon is critical to positioning the bank for future success.

The second step is to increase the trust, reliability, and availability of your data.

We are all familiar with the saying garbage-in, garbage-out. The same can be said about data. Generally, bad data is considered data that is inaccurate, incomplete, non-conforming, duplicative or the result of poor data input. While true, this is not the complete picture. For example, data that is aggregated or siloed in a way that makes it in accessible or unusable is also bad data. Likewise, data that fails to garner any meaning or insight into business practices or is not available in a timely manner is bad data. Data that is not normalized, is not agreed-upon, from an organizational perspective, is one that’s going to create issues. If you are not scrubbing the data that is collected to make sure it is complete, accurate, and most importantly useful, you are wasting valuable company resources.

The last step is to align your data strategy with your business strategy.

Data strategy corresponds with how you will measure and monitor the success of your bank.

Understanding the right data to collect and anticipating the future expectation to not only access, but also aggregate data in a meaningful way is paramount to enduring success in this new “big data” era. For example, if you want to take advantage of artificial intelligence (AI) and predictive capabilities in the future, the success of those initiatives is contingent upon aligning your data strategy with your business strategy.

Good data strategy paired with business strategy translates into strong decision-making. When an organization has access to critical consumer information or insights into market tendencies, it is equipped to make decisions that increase revenue, market share and operational efficiencies. When meaningful data is presented in a timely and easy-to-digest manner, executives can react quickly to changes affecting the organization, rather than waiting until the end of the quarter or the next strategic planning meeting before taking action.

At the end of the day, every institution’s data tells a very unique story.

Do you know what story your data is telling about the bank? What is the data telling you about the future? When banks become paralyzed by the data, they lose the ability to guide their story, becoming much more reactive than proactive and ultimately, miss out on opportunities to propel the bank forward and position the bank for future success. Eliminating the paralysis from the analysis ensures data is driving the strategy, and enables the bank to guide their story in positive direction.

As seen in the January 2025 issue of Great Lakes Banker. Read the full issue here.

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