Transforming Product Development Through Data-Driven Decision Making

February 17, 2025

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Devan Robertson

Sr. Product Manager

In the fast-paced world of financial technology, delivering value to clients isn’t just about writing code—it’s about making informed decisions that directly impact the bottom line. Over the past two years, our journey to become a truly data-driven organization has transformed how we develop and enhance our products, enabling us to better serve our customers and, by extension, theirs.


The Power of Business Intelligence in Action

Traditional software development often relies on intuition and customer feedback to guide product decisions. While these inputs remain valuable, incorporating comprehensive data analytics into our decision-making process provides an unprecedented level of clarity and precision in understanding both system performance and client impact. 

Our investment in advanced data capabilities—including business event streaming, robust data warehouses, and sophisticated visualization tools—has created a powerful feedback loop that connects system performance directly to client success metrics. This infrastructure allows us to monitor, measure, and analyze every aspect of our software’s performance in real-time, ensuring we maintain the highest levels of service while identifying opportunities to innovate further. 

From Metrics to Meaningful Improvements

The impact of this data-driven approach extends far beyond basic performance monitoring. By analyzing patterns in action processing, decisioning, and other performance metrics, we can now: 

  • Quantify the impact of potential feature enhancements before development begins 
  • Identify bottlenecks and optimization opportunities that might otherwise go unnoticed 
  • Measure the real-world effectiveness of system improvements after deployment 
  • Predict and prevent potential issues before they affect our clients 

This wealth of information has revolutionized our product development prioritization process. Rather than relying solely on qualitative feedback, we can now make decisions based on concrete data that shows precisely where improvements will deliver the most value. 

Turning Data into Client Success 

Perhaps the most significant benefit of our data-driven approach is how it helps us align our development efforts with our clients’ success metrics. Features we develop, and enhancements we implement are backed by data that demonstrate their value-add. 

For instance, our analytics platform helped us quantify the impact of new decision automation features that were included in a recent release. While these features were requested by many of our clients, the impact varied by client, based on how each client had configured previous features and their volume of specific types of claims.  This insight prompted us to adjust our delivery approach and allow some features to be configurable so that clients could enable them when the impact was understood and the implementation would be least disruptive. 

Looking Ahead: The Future of Data-Driven Development 

As we continue to evolve our data capabilities, we’re discovering new ways to leverage this information to benefit our clients. From predictive analytics that help to streamline processes to machine learning algorithms that identify opportunities for automation, we’re constantly exploring new ways to use data to enhance our product offering. 

Our commitment to data-driven decision-making isn’t just about improving our software—it’s about ensuring that every change we make delivers measurable value to our clients and their customers. By maintaining this focus on quantifiable results, we can continue to evolve our products in ways that matter most to the financial institutions we serve. 

In an industry where efficiency and accuracy are paramount, our approach ensures that we’re not just meeting expectations—we’re continuously raising the bar for what financial institutions can expect from their solutions partner. This is how we transform data into value, one iteration at a time. 

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