One proven approach for insurers to unlock insights in historically under-tested areas is to first identify instances of natural variation — cases where testing was not conducted intentionally, but a measurable change occurred in the business. Within the day-to-day operations of an insurance company, there are many footholds of this kind that can serve as “gateways” to experimentation, the first step in enhancing insurance organizations' analytic capabilities.

Continue on for examples of key gateways that insurers can use as starting points to jump-start their analytics programs.

No. 1: State Regulations

State regulations enforced by each state's Department of Insurance mean that a single insurer often needs to run its individual states as somewhat distinct businesses. While this poses complexities, it also means that changes like product line modifications, rate adjustments and altered risk scenarios are implemented differently in a subset of states, providing potential gateways to experimentation.

While industry regulations across state lines may at first seem like an obstacle to testing, the natural variance in different initiatives and programs by the state can create opportunities for data-driven program management. For example, if an insurer introduces a new type of policy in some states, it can compare performance across key metrics to similar states without the introduction to isolate the new product's true impact.

No. 2: Innovation

Insurers are increasingly dedicating significant resources to innovation. Drawing on ideas from the field, policyholders and competitors, teams are continuously working to compile the best new initiatives for their organization, pilot them and refine their go-forward strategy. These new programs are natural gateways to in-market testing.

Telematics is one example of this kind of innovation. Telematics technology allows insurance organizations to develop a clearer view of policyholder behavior, then incorporate this knowledge into risk assessments and pricing. Beyond using these insights to better align premiums with risk to enhance rate fairness, insurers can also assess other key program considerations by measuring the impact of introducing a telematics platform. These considerations include how the technology should be introduced and communicated to additional states, markets and policyholders; which promotions, such as “Safe Driver” discounts, are most impactful in driving usage and encouraging safer behaviors; and how this offering ultimately affects policyholder retention and satisfaction. From there, insurers can tweak their program implementation to reach the policyholders with whom it will be most effective.

Because innovative programs like telematics are often introduced to markets in phases, insurers have the opportunity to save both time and resources by fine-tuning these new programs every step of the way before investing in broader rollout.

No. 3: Opt-in Programs

Another gateway to experimentation is through programs that are over-subscribed — specifically, initiatives where more people want to play a role than there is capital to fund them. Because of the amount of interest in these programs, there may be self-selection bias; that is, the characteristics of agents or policyholders that opt in may impact whether the initiative itself achieves the intended affect.

One example of such an opt-in program could be a new, sales-focused agent training program. Consider a scenario in which an insurer developed such a program, and wanted to determine whether it drove a large enough increase in premiums to justify the cost associated with offering the training program more broadly. Although premiums rose after the program launch, it might be difficult to determine if this positive performance was driven by the training program itself or other factors, such as whether the agents that opted into the program were already high performers. One way to isolate an individual program's incremental impact is to analyze the performance of agents who opted into the program against the performance of a group of agents of similar characteristics who did not participate.

Implementing strategies that might shift behavior — such as trainings and new incentive structures — is not without risk. By identifying “natural experiments,” analyzing existing variation as the first step in developing a broader analytics program, insurers can use measurement of past programs to inform their future rollout decisions.

No. 4: Variation in Sales Force Deployment and Call Center Activity

Natural variation resulting from changes in sales force deployment and call center activity can also serve as a gateway to experimentation.

Consider, for example, an insurer that routed policyholders with a high likelihood to discontinue their coverage to a new specialty call center, in hopes of mitigating attrition. The specialty call center was not large enough to handle all such calls, resulting in two similar groups of “high attrition risk” policyholders: Those that were routed to the specialty call center, and those that were served by standard call center representatives. Measuring the retention rates between the policyholders who were routed to the specialty call center and a carefully matched subset of those who were not, the insurer could quantify the specialty call center's attributable impact on retention.

Similarly, an insurer leveraged past natural variation in their sales team's outreach to agents to determine the incremental impact of this engagement on quote and application rates. This measurement also identified which types of interactions generated the greatest increase in production and which types of agents benefited most from this outreach. Armed with these insights, the insurer could improve its deployment of sales team effort, optimizing resources by prioritizing the most impactful outreach.

These gateways are a critical starting point for insurers to adopt a culture of testing and spur innovation. By capitalizing on these opportunities to unlock valuable, data-driven insights, insurers will be empowered to introduce initiatives on an optimal scale and refine new business strategies for maximum profitability.