9 JULY 2023 9JULY 2023The solution is to create an analytics ecosystem across the organization with two distinct parts: 1) a nuclear analytics team within the business units;2) a Chief Analytics Officer at the Board level. The nuclear analytics teams ideally would have a reportingline to the Line of Business (LoB) leadership, comprised of business analysts, modelers, as well as dedicated data and systems specialists who serve as the bridge between business and IT. These teams ensure that the triangle of business, IT, and analytics work continuously and in tandem. In a McKinsey report issued in 2021, titled "How data and analytics are redefining excellence in P&C underwriting," Javanmardian et. al. indicate that it is important to "keep the effort anchored in the C-suite.Delegating down can dilute long-term aspirations."A Chief Analytics Officer (CAO) is defined as the executive who turns data into decision. The CAO not only has the mandate of overseeing data strategy (Chief Data Officer's job) and creating business intelligence models (Portfolio Management), but he/she will have the authority to work closely with the CIO to establish the infrastructure required for analytics. Informed by the nuclear analytics teams embedded in each LoB, the CAO serves as a key enabler for business and a guide for IT. Involve the FrontlinesAdoption by underwriters is the foundation for a successful data driven culture.It is important to engage the frontlines and ensure their buy in. A key benefit of embedding the nuclear analytics team within the business is to bring the agenda close to the front By understanding what data is available and then integrating it across an organization to make informed decisions, businesses can thrive in today's evolving and competitive landscapelines. Creating tailored analytics for each LoB will also increases support from the LoB's leadership. Even if we think data quality should never become part of an underwriter's annual performance review, underwriters and operations should know the critical data that they are accountable for. In closing, the immediate benefits of a data-driven business modelbecomeob-vious to any executive in the insurance industry. I would argue that one added advantageof the model and recommen-dations presented here is a refreshed talent pool to fill top jobs. Traditional thinking in the insurance industry often sees an underwriter, claims, or distribu-tion professional as the next CEO. An analytics executive trained to think like an underwriter is the kind of leader that can guide an insurance company in to-day's digital world. The time to invest in that talent pool is now.
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