It’s safe to say that data is important to an organization. People understand that data is valuable, but it’s hard to measure that value because it’s based on how you use it, what insights you gather from it, and how you act on those insights. Data can help you identify growth opportunities, find profitable niches, understand why portfolios perform the way they do, and target high-value prospects—but it’s often challenging to determine exactly what role data plays in each of those activities.
Data KPI Snap Poll Methodology
As organizations embark on data transformations or develop enterprise-wide data strategies, it’s important to understand how your organization currently uses data to determine where gaps exist and how you can get the most business impact. I reached out to 25 data leaders at property/casualty insurers to learn about their data practices and key performance indicators (KPIs). Of those contacted, five responded to share insights about the data assets they currently have in production, how they track asset utilization, how they measure data quality, and what other KPIs they use to measure success.
Production Data Assets
All respondents listed operational reports, dashboards, data warehouses, and data lakes as data assets currently in production. The majority listed self-service business intelligence (BI) and data marts as being data assets in production. Few listed actuarial sandbox and data catalog, and none listed data lakehouse.
Data Utilization KPIs
When I inquired about tracking, most respondents stated that they do implement tracking in various ways. One respondent mentioned that their tracking mechanisms are not yet fully implemented but shared their plans to focus on utilization statistics such as query volume, user numbers, and report view totals. Other respondents identified a number of ways to track data asset utilization and adoption, including the number of registered users accessing repetitive assets, system-based usage reports, what computer resources are used, and the creation of data governance councils.
Measuring Data Quality
There was less measurement of data quality among respondents, but all acknowledged that it was an important element of the overall data strategy and expressed plans to implement metrics in the future. One respondent did list financial data as currently being highly governed and monitored but stated that there was far less monitoring of other data domains. Another respondent stated that their organization’s data quality focus centered on client data, with metrics for accuracy, completeness, and validity.
Determining the Value of Data
Two respondents stated that while having formal KPIs to measure impact is a strategic goal, they had not yet defined or implemented such metrics. One of our respondents noted that program success is measured by its impact on other business KPIs, but they stated that there was still too much fluidity to their metrics. Their goal is to move quickly toward using quantifiable impact or return on investment (ROI) to drive organizational decision-making. Additionally, one respondent also measured business value from specific use cases to determine impact.
Concluding Thoughts
As strategic data usage becomes more embedded in insurers’ daily operations, developing a clear set of KPIs to track business value will become increasingly important. To learn more about our research around data and its impact, read our recent report Establishing and Sustaining Data Mastery: Introducing the Insurance Data & Analytics Maturity Model.
