Data Modernization in Insurance Part I: Creating a Data and Analytics Strategy

In today's rapidly evolving insurance industry, data is the lifeblood that fuels business growth.

Insurers must harness the power of data and analytics to inform decision-making, drive innovation, and maximize competitiveness. Embarking on the journey toward data modernization is therefore essential to staying ahead – or just keeping up – and a well-defined data and analytics strategy is a critical first step.

Building the Foundation: Strategic Alignment

The strength of any data and analytics strategy is founded on alignment with the overarching business strategy. Without such alignment, it can be challenging to secure funding and assemble the right resources to drive data modernization. Insurance companies must clearly demonstrate how prioritizing and investing data and analytics capabilities translates into tangible benefits for the organization and serves several key purposes:

• Drives profitability: The insurance industry is inherently data-centric, and optimizing data’s potential to achieve business goals can provide a competitive edge. By ensuring a clear path to desired outcomes, insurers can identify areas that require investment, thereby engendering confidence in the decision-making process. Furthermore, emerging trends can be identified early, enabling the company to stay ahead of the curve.
• Maximizes efficiencies: Often, insurance companies focus too much on accessing data and building data infrastructure and not enough on developing insights. Shifting to a results-oriented focus on actionable insights can dramatically improve efficiency by identifying resource-intensive processes, removing bottlenecks, and embracing a source-of-truth philosophy to ensure data accuracy.
• Manages costs: The adoption of cloud infrastructure can help reduce run times, improve technology management and consistency, and lead to substantial cost savings. Real-time cost monitoring provides transparency and allows for dynamic adjustments to resource allocation, enabling cost-efficient utilization.
• Increases innovation: By leveraging cutting-edge data and analytics techniques, insurers can develop new processes, enhance their capabilities, and utilize novel data assets. Innovation should not be pursued for innovation’s sake, but always directed toward the organization’s business strategy and long-term goals.

For additional insights on this topic, view Derek Kueker's recorded webinar, "Data Modernization: Realizing Future-State Analytics & Efficiency": 

Moving Forward: Next-Generation Data and Analytics

After establishing organizational alignment around strategy and securing corresponding investments into platforms, processes, and people, insurers are equipped to modernize their data and analytics programs. This modernization includes three primary elements:

• Shorter analytics platform lifecycles: The modern data environment demands a shift in expectations regarding platform lifecycles. Instead of expecting systems to last for decades, organizations should plan and invest for three to five years to allow for agility and quick adaptation to emerging technologies. This requires developing clear definitions around the purpose and interaction points of these platforms, as well as actively driving business requirements for enhancements.
• Third-party data integration: The integration of third-party data is becoming increasingly critical.  It is essential to create an environment for managing external datasets and connecting them with internal ecosystems. This includes addressing legal considerations and ensuring that data acquisition strategies benefit multiple functions within the organization.
• End-to-end business process integration: Above all, a data and analytics program needs to work, so ensuring interoperability between systems is vital. This involves driving platform uniformity, addressing delays in data flow, enhancing security, and clarifying data ownership models across the entire data lifecycle.