With the rapid marketing and demographic changes in the insurance industry, and the need to respond quickly to market demands, business strategies are becoming more complex: Companies are taking a more customer-centric, cross-enterprise view. As organizations evolve out of their traditional product or functional silos to respond to the need for customer-centricity, the insurer's operating model needs to evolve as well. The operating model represents business processes core to the organization, coupled with technology infrastructure. This requires tight integration across the four quadrants of people, process, data and technology.
Here's an example: Let's say that Samantha is a participant in a group retirement plan. From the company's perspective, it has some basic demographic data on her, and understands her relationship with it: She has two products (retirement and life), no financial advisor relationship, and only manages her account through the web. Based on the demographic and relationship data, the company has classified her as low risk of attrition, but also has low interaction, indicating that her interest or awareness of the products and services may be low. She's not currently maximizing her plan contribution rate. However, she has a positive customer lifetime value score indicating that she is the type of customer the company wants more of, and would be a good candidate for cross- and up-sell opportunities. Knowing that Samantha only interacts with the plan provider a couple of times a year, one fundamental question arises: How can it engage with her on her terms and grow her relationship (e.g., customer satisfaction, revenue, loyalty) with the company?
Most insurers would be challenged to answer this question. On the surface, the example is simple from the customer's perspective, but the ability to align the customer vision with business strategy, process integration and analytic objectives is very challenging. This example process crosses over product lines, functional and organizational boundaries. Legacy systems and siloed applications impede the ability to create a seamless customer experience. Many companies don't have a holistic view of the customer or lack the ability to bring disparate systems and functional areas together. They especially lack the ability to embed the predictive analytics or scores within a business process.
[Previously from Alt-Simmons: How insurance companies became self-aware]
Many organizations are taking a three-pronged approach along their customer-centric journey:
• Enterprise architecture. Enterprise architecture planning and design provides a framework for sustainable business processes and technology alignment. A company's enterprise architecture view encompasses long-term integration and standardization requirements. As your company shifts to this customer-centric perspective, think about what needs to be standardized and repeatable to enable this workflow.
The trade-off is that centralization and standardization required for automation can reduce flexibility at the local departmental, functional or product level. The challenge is to identify the right levels of business process integration and standardization; finding the right amount of local versus enterprise-level control. This is why the concept of the core is so important - identifying what can be reused and repeated versus what needs to be customized. Most organizational infrastructure is geared toward local customization. The process of rationalizing infrastructure can be time-consuming and expensive. However, there can be a significant payoff in increased customer satisfaction, simplification, reduced costs and improved business agility.
• Business operating model. An organization's operating model provides a baseline for integrating and standardizing business processes in order to bring goods and services to a customer. Taking a customer-centric view aligns business units around a common goal, creating a shared understanding of customer needs. Within the confines of the operating model, organizations determine the level of integration appropriate for their business.
As the company perspective evolves to outward in, taking a persona-based approach provides a good starting point for defining the value stream. The persona, a hypothetical customer, may represent a particular customer segment within your business. Through understanding the customers' needs from their perspective, you can begin to outline strategies for supporting that customer's value stream.
• IT engagement model. The engagement model provides governance to ensure that business and IT projects meet business objectives, linking project goals with implementation decisions. In organizations with a strong execution foundation, IT is a business enabler, and not perceived as a roadblock.
Analytics, in the form of predictive algorithms, segments or propensity scores, etc., may be integrated within the business processes. The need for analytic teams to integrate within this ecosystem is critical. Within our example, predictive models and scores drive the decision process across the workflow. The enterprise architecture includes infrastructure to support analytic development and deployment cycles, along with the foundational data structures necessary support the information supply chain. IT takes on operational support for the analytic and data infrastructure, freeing analysts up to focus on innovation work.
Taking a customer-centric, enterprise view doesn't have to happen all at once. The foundation can be built one project at a time. The first step is to identify your customer value streams: What do my customers want/need and how I can I best meet those needs? At this stage, don't get too tied up in details. Once you've established that vision, begin to think about how your organization needs to respond. Which functional areas or product lines are involved? What systems have to come together? What data is needed? As we lay out the customer-centric workflows, where are the critical decision points? Can we address the decisions with standard business rules, or is there an opportunity to embed advanced analytics in the process?
With the vision laid out, the undertaking might look massive. However, the strategy can be executed on a project by project basis, with each project aligned to the overall business vision and architectural design. This ensures that the vision doesn't become too abstract, the technology foundation evolves over time, and the implementation costs and risks are distributed across projects.
About the author: Rachel Alt-Simmons is the Senior Industry Consultant for Insurance at Cary, NC,-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.