It’s challenging for insurers to differentiate themselves through products and services, but data and analytics can enable them to break free from commoditization with better and faster decisions. This potential is reflected in increasing levels of investment in data and analytics across the industry; these investments now exceed 0.7% of direct written premium (DWP), on average. Recent Aite-Novarica Group studies indicate that over half of all insurers are replacing or conducting major enhancements to their data environments and associated capabilities.
According to an Aite-Novarica Group survey of insurer CIOs, the average property/casualty insurer is spending 4.4% of DWP on IT. Of that, 17% is spent on data, resulting in average spending of 0.68% of DWP. (For more information, see the Aite-Novarica Group report Property/Casualty Insurer IT Budgets and Projects 2023.) The term “data” typically includes data warehouses, business intelligence (BI), predictive analytics, third-party data and practices such as master data management.
Where Insurers Are Investing
Insurer business units are prioritizing further expansion of BI and analytics over all other capabilities in 2023, reflecting the fact that carrier capabilities tend to lag in this area. Many insurers face data access challenges, resulting in significant effort expended for sourcing and merging data to produce reports. Data quality issues also affect insurers’ ability to receive the full benefit from analytics efforts.
When asked to self-assess on various system capabilities, insurer CIOs indicated that the biggest gaps are in data and digital (which has a significant reliance on data). For larger property/casualty insurers, customer relationship management (CRM) is emerging as an area of concern; more than half of insurers rated their capabilities for CRM as “poor” or worse, up from over 40% last year. CRM systems are highly reliant on access to quality data. For midsize property/casualty insurers, customer portals and predictive analytics remain pain points.
To achieve their data objectives, insurers will need to improve their data maturity. Creating and maintaining a trusted source of data and analytics within an insurer requires competency and coordination across multiple disciplines. Insurers with mature data capabilities have access to unique insights and apply them in all aspects of their business to further competitive advantage.
The True Meaning of “Data Maturity”
Aite-Novarica Group has developed the Insurance Data and Analytics Maturity Model (iDAMM) to facilitate an insurer’s journey to high levels of data maturity. The iDAMM provides a framework for insurers to evaluate their data-related capabilities and establish a plan to reach data maturity by assessing their data organization and capabilities across seven dimensions and 21 subdimensions, including leadership and organization, data governance and architecture and technology management.
The model uses three stages of maturity: Traditional, Evolving and Transforming. Insurers are likely to have different levels of maturity across different model elements. Moving into a more mature stage is a function of organizational and technological capability, not duration. Like transformations in other parts of the insurer, data and analytics innovation requires enabling technology, organizational change and executive sponsorship.
Sustaining data mastery requires an insurer to establish and maintain a data culture. Data cultures are those in which data is fully democratized, data literacy is high and tactical and strategic decision making are largely data-driven (but still informed by intuition). Further, all users value data highly and act as corporate data stewards in maintaining high data quality and protection.
See also: Achieving a 'Logical Data Fabric'
Building a Data Culture
Building a data culture is challenging. Insurers that have achieved data mastery will have a culture grounded in data and analytics that can survive leadership changes and shifts in business focus. This means that everyone cares about data quality, as everyone understands innately the value of information and insights. Strategic and tactical decisions are heavily influenced by signals in the data, though intuition developed through industry experience also plays a role.
Insurance industry data masters derive significantly more value from their data than other insurers, putting them at a major competitive advantage. Insurers that wish to achieve and sustain data mastery should assess where they are in their data and analytics journey, define a target state and plan investments and initiatives to bridge the gaps between them. The iDAMM is a useful tool to assess an organization’s current level of maturity and align that with where the organization seeks to grow.
For more information on achieving data maturity, see Aite-Novarica Group’s new report Establishing and Sustaining Data Mastery: Introducing the Insurance Data & Analytics Maturity Model (iDAMM).
