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10:43 AM
Rachel Alt-Simmons, SAS
Rachel Alt-Simmons, SAS

5 Organizational Considerations for Insurance Analytics Teams

How do insurance organizations that are just beginning their analytics journey build enthusiasm and executive support?

We've all seen the growing trend in analytics jobs within the insurance industry, in particular the emergence of "data scientist" teams. Companies like AIG and others have created new chief scientist positions with CEO-level visibility and are hiring statistical talent to staff these new analytics organizations. But while the organizational structure and support for these emerging powerhouse teams might be new, analytics has been prevalent in the insurance industry for decades, and teams come in all shapes and sizes.

The spotlight on the new data scientist revolution is causing insurers to rethink and reformulate their analytics strategies. They're asking themselves: What should my team look like, what skills does it need, who should it report to, and what other investments do we need to make? Even more importantly for organizations that are just beginning their analytics journey: How do we build enthusiasm and executive support?

There are two prevalent approaches: build or buy. In the buy approach, insurers accelerate their analytics capabilities by hiring entirely new teams or supplementing their personnel with consultants or contractors. This approach is often coupled with large-scale transformational projects, specifically for claims, underwriting, and customer-centric marketing and distribution strategies. The pros of the buy strategy are that it allows the insurer to jump-start analytic capabilities and leverage the automation of insight into operational systems as part of the overall transformational program. The con is that this strategy can be very expensive from both a financial and organizational perspective. A key challenge is the organization's ability to understand, consume and integrate insights on a business level, not a technology level. Additionally, it can be challenging to ramp up resources with little organizational background knowledge and partner them with the business domain experts essential to interpreting the information used in analytics.

Rachel Alt-Simmons
Rachel Alt-Simmons, SAS

For insurers taking a more gradual approach, building capabilities provides an excellent way to develop analytics in-house. Even within building, there's a top-down and a bottom-up approach that organizations can find success with.

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Bottom-Up: One organization started to build out its business intelligence and analytics competency center, but before it could get additional funding to build out the team, it needed to prove the value of analytics first. The team defined a low-risk pilot project and partnered with its call center, which also wanted to show the value of predictive analytic capabilities. The successful pilot provided the team with credibility, and additional funding was provided.

Top-Down: Let's look at two interesting examples with very different approaches. Insurer 1 funded its business intelligence and analytics team as a project. It selected talented business and technology professionals from different areas of the business and assigned them to the team for one year. The funding also included technology and database investments. The executive team assisted the startup group by defining a set of analytics projects to work on. This approach gave the group stage gates to determine the effectiveness of its strategy. Insurer 2 already had an in-house analytics team aligned to the marketing organization. It wanted to take on a broader set of projects across the organization and gained support from the chief marketing officer and chief executive officer to create an enterprise-level team. The group drew out a three-year road map defining its analytics, people, process, data and technology strategy with stage-gate investment points.

Is there a right or wrong way to build analytics capabilities? No. But consider the following organizational design mechanisms, whether you're building or buying your team.

  • Strategy: You might be surprised how many insurers don't have analytics goals that align with business goals. Your strategy is the compass that guides your team. Without a clear strategy, the team won't be able to make effective decisions about its structure or the work that's performed.

  • Structure: Your team's structure represents a mix of organizational components, including reporting hierarchy and internal and external team relationships. In organizations using the buy strategy, structure can be one of the most overlooked areas. Sometimes the hierarchy can create unnatural boundaries and conflicts.

  • Processes: Creating an engagement strategy for the team and helping it develop relationships (and subsequent credibility) in the organization is critical to achieving team goals. For example, how is your group going to interact with IT? What are the dependencies between the groups? How will the team take in and prioritize new projects?

  • Rewards: What are the metrics that your team will use to gauge success? Remember that what gets measured gets done. For one organization, "we began measuring the actions and behaviors that produced the desired outcomes, i.e., financial performance, we were driving towards. This allowed us to have a much stronger, real-time sense of how the business was doing and has dramatically improved [employee] performance."

  • People Practices: Work with your human resources organizations to create job descriptions and career paths that are relevant to the skills and talents of your team members.

Obviously, there are many moving parts in this machine. To change the culture, the best approach for gaining support includes a using a senior-level champion to get the organization fired up and committed, regardless of whether you're moving toward a build or buy approach. Organizational design elements should not be underestimated or overlooked. A continuous feedback loop from end users to management ensures that concerns are addressed, information is freely exchanged, and changes in the approach can be made if needed.

About the Author: Rachel Alt-Simmons is senior industry consultant for Insurance at Cary, N.C.-based SAS. Simmons has driven business intelligence initiatives at Travelers and Hartford Life and has been Research Director for Life & Annuity at research firm TowerGroup.

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