Data is an asset– and it continues to grow at an exponential pace. When companies properly apply data and analytics, they stand to gain substantial strategic and competitive advantages. In order to do this, companies must understand that analytics as a discipline does not work in a vacuum. To glean actionable insights that drive decisions, improve processes, and find opportunities, both data and business intelligence must be gathered, synthesized, and interpreted. This necessitates a collaborative, integrated, complementary culture where data and analytics are the “norm” throughout the entire organization: the basis for decision-making, problem-solving, and process-driving. Companies are witnessing the explosive growth of data all around us – from the content we stream to our health records to our wearable devices. Firms should be employing a top-down culture change that enables their organizations to ingest and make use of data in a meaningful way.
Gone are the days of siloed number-crunchers sitting behind a computer: a successful organization understands the value of analysts who are technically savvy storytellers. A skilled analyst is proactive in scenario-modeling because they are fully integrated into the business. They understand where pitfalls or opportunities may lie and use data and information to bring informed questions and ideas forward. A skilled analyst understands the value behind model assumptions, including the probability that each input occurs. A skilled analyst can “look around the corner” to ask questions of their customers and business partners: what might we be overlooking? What if we changed this scenario? Why have we always done “X” this way? A skilled analyst pulls everything together – from their business knowledge, to the strategic vision of the firm, to the patterns in the data – to make insightful, actionable recommendations.
In insurance, analytics can and should be integrated throughout the organization: product, sales, marketing, and underwriting. From a top line perspective, sales may segment data that offers insights into our financial advisors and customers’ demographics, product preferences, selling, and buying habits. From a risk perspective, underwriting and claims data may indicate potential anti-selection, potential gaps in underwriting standards, or opportunities for improved mortality or morbidity results. Analytics allows us to identify those aspects of the underwriting process that may be duplicative or not necessarily be providing protective value. From a customer experience standpoint this results in a more streamlined, user-friendly application process. Data may additionally allow us to better prioritize problem-solving and opportunities and home in on what’s important. For example: where are the largest potential risk drivers? How might we reach a vital-yet-underserved market? Conversely, data may show when limited resources may be diverted elsewhere when opportunities are deemed lesser in size or impact.
The data revolution is upon us. While our ancestors surged ahead in productivity and output by way of machining and factories, today’s transformation centers on the availability and usability of information.