Data You Can Use

From pizza trackers, same-day deliveries, and instant messaging; to five-minute insurance quotes, drone or satellite-based inspections, and mobile apps, it’s clear that growing customer expectations continue to drive industries like insurance to explore new ways of doing business.

Many insurance carriers are pursuing potential enhancements offered by insurtechs that promise to reduce cycle times and provide broader resource access, 24/7 communication channels, self-service options, and almost instantaneous decision making.

Within claims departments, processes that report losses, evaluate insurance coverage, estimate damages, and deliver payments were traditionally measured in days, weeks, or months. Now, new processes and innovations enable some claims to be detected instantly by sensors and reported automatically to carriers through automation. Some carriers are even exploring completion processes that enable the entire claims-process cycle, including payments, to be completed within minutes.

While each carrier’s mix of available products, technologies, or development resources differ—and the complexity or necessity of tasks vary—new data-driven solutions offer the insurance industry a long list of options to supplement legacy solutions in support of emerging customer expectations. As carriers evaluate new solutions, it is increasingly clear that securing accurate and timely data remains a critical component for many successful insurtech implementations such as artificial intelligence, machine learning, predictive models, and straight-through processing.

Here are a few fundamentals that can help ensure the success of future data-driven insurtech solutions.

1. Begin with the end in mind. While it is easy to be distracted by the new shiny object, engage in a meaningful discussion with your leadership team that clearly articulates the objective of any new data-driven initiative. What specific problem are you trying to solve? How does the initiative align with the strategic direction of your organization? What would success look like?

2. Know who wears the crown. It is rare that any team wins without a leader. Identify the leader of each new initiative before development begins to ensure his active participation to the extent that he is knowledgeable, recognized as a subject-matter expert, informed with the knowledge to make sound decisions, and equipped to both champion and manage the initiative from the project phase through business-as-usual and long-term success.

3. “If you fail to plan, you are planning to fail.” Benjamin Franklin’s famous quote continues to resonate with today’s new initiatives. As we try to divide often-scarce resources appropriately, there is immense value in employing project-management disciplines. Some examples include: detailing a project charter with goals, scope, timeline, and budget; creating a business case; and scheduling regular team meetings to discuss status reports on your progress toward achieving defined milestones.

4. All of us are smarter than one of us. Ensure all stakeholders are involved early and often so they can share input or challenges during the exploration and development of new data-driven initiatives. Business units—such as legal, compliance, information security, information technology, and procurement—should be considered for potential impact and feedback. There is also value in reaching out to your industry peers, vendor business partners, or customer groups for their perspectives on the solutions being considered.

5. Data integrity is key. Develop processes that feed secure, reliable, complete, and accurate data throughout your systems. Great data and a good process are better than good data and a great process.

6. But data by itself is insufficient. Data builds a great foundation, but rarely provides a standalone solution. Seek solutions that allow your organization to turn data into information, information into insights, and insights into decisions.

7. Data security is critical. Protecting company and customer data can be as complicated as any new initiative you explore. The importance of appropriate due diligence and contract terms when introducing new data-driven solutions cannot be overstated. Work with your information security teams to categorize your data sources into buckets and build sound processes for each category, such as: internal sources; third-party data sources (vendor), public, private, personally identified information (PII), sensitive, and restricted.

8. All data is not created equal. Avoid relying on a single data source and consider the benefits of creating a mix of data from a variety of sources. To avoid creating clutter from a “data dump,” critically evaluate the key data points necessary to inform decisions instead of being distracted by “nice to have” data that will not add value to each initiative.

9. Balance available solution perspectives. Dare to cast a wide research net that includes solutions offered by your incumbent vendors; other traditional, “industry staple” vendors; and new insurtechs that may offer new approaches, innovations, accelerated implementations, new or different pricing options, or that may be seeking a development partner.

10. Implementation is not the finish line. After putting new technology or processes into production, consider this the starting line on a race to meet customers’ new expectations. The journey continues as you measure, monitor, evaluate, and adjust your processes as needed. Ensure your data trends are reported and successes are celebrated.

With significant industry investments in new technology, the future promises to be exciting for those who dare to explore innovation, turn data into decisions, and consider options presented by insurtechs.