De-Siloing Data for P&C Insurers

Big data stands to transform the insurance industry in unprecedented ways, providing insights into customer behavior and risk that are unmatched in the history of the industry. Yet property and casualty insurers have significant hurdles to overcome before they can leverage big data and its associated analytical tools to its fullest extent. P&C insurers struggle to use the data they gather because many organizations are still siloed, meaning that information is stored in separate databases that don’t communicate between offices, buildings or departments. About 80% of the average P&C company’s data is dark data, or data that is difficult or impossible to find when needed, MarkLogic’s  Derek Laufenberg  writes. How can insurance companies bring their dark data into the light? Here are some pathways to integration: Evaluate Your Assets There is a great amount of untapped potential in the company data that decision makers are unable to access. The best way to begin leveraging this data is to inventory data sources, TechRepublic writer Mary Shacklett explains. When a P&C insurer’s data sources are accounted for, it's easier to plan a process for effectively integrating those sources and improving access to them. After discovering the company’s existing data sources, consider how this data is currently used and shared. Do staff use cloud-based spreadsheets to share and compare data? Do they rely on email and regularly scheduled meetings? “The centuries-old insurance industry seems to still be heavily drowning in paperwork and redundant manual procedures,”  Kevin Doubleday writes in Insurance Thought Leadership. Evaluating data storage, accessing and sharing procedures help illuminate the most effective places to start the integration process. See also: Cognitive Computing: Taming Big Data   Put the Company in the Customer’s Shoes Data management strategies influence customer satisfaction, loyalty and willingness to recommend a company more than most executives think, Corrie Mieszczak at Evergage says. Mieszczak recommends approaching de-siloing with the goal of developing “a 360-degree view of each customer.” As property and casualty insurance becomes more customer-focused and retention-sensitive, the need to understand customers becomes more urgent. To learn what customers want, P&C insurers need to track the right data and leverage it to meet that customer’s needs when they occur, John Mayo adds at PropertyCasualty360. Once data sources are accounted for — and leaders understand how they’re currently used and shared — its easier to understand how those sources relate to the customer experience. “Corporate silos are customer experience killers because customers don’t care about how your company is organized,” Forbes’ Dan Gingiss says. Instead, pinpointing the end of the customer experience enables P&C insurers to spot places where integration will be most effective. By integrating data and employing tools like artificial intelligence and machine learning, forward-thinking insurance companies are creating a competitive advantage for themselves, says Dario Debarbieri at IBM Watson. Debarbieri suggests that the customer experience can be optimized through seamless collaboration across marketing, commerce and supply chain channels. Insurance companies that incorporate the customer’s perspective into their approach to de-siloing improve their chances of becoming future-ready. As outlined in an MIT Sloan Management Review study co-written by Peter Weill and Stephanie L. Woerner, “Future-ready enterprises are able to innovate to engage and satisfy customers while at the same time reducing costs.” These organizations give customers a good experience while at the same time treating their data as an accessible strategic asset. Determine What De-Siloing Can Do for You Risk is one of the top concerns for P&C insurers facing integration. If the data set is hacked, for example, InfoSum and DataSift founder Nick Halstead says that connecting all of the organization’s data into a single pool potentially puts more information at risk. Yet merging silos can also play a key role in improving overall enterprise risk management, Risk Management Monitor’s Thomas Abelmann adds. By integrating data and planning across the organization, P&C insurers become more effective at creating, implementing and evaluating competitive strategies — and staying ahead of risks. “In the past 30 years, we’ve made enormous strides in creating technological tools that help de-silo data and information so they can be better shared and used across organizations,” Bluescape CTO Demian Entrekin says. “But silos still exist in most complex organizations, particularly when it comes to nonlinear areas like strategy.” Better integration can also help insurance companies fight fraud, according to Ethics and Insurance blog founder Duncan Minty. Analytical software, including programs that use artificial intelligence (AI), can improve fraud detection, but only if the algorithms are trained on a sufficient data set — a set that can be much more difficult to obtain when data is siloed. Finally, de-siloing can improve efficiency and productivity, two essential steps for an insurance industry struggling with a concurrent drop in auto insurance premiums and a rise in catastrophic property claims. “When your company’s data lives in separate, non-communicating systems, you’re hampering your company’s ability to get the most out of that information,” says April Rassa, marketing and growth director at Progressly. “You’re also creating extra work for employees, because when it comes time to actually put the data to use, the only way to share knowledge with other departments is via manual, inefficient methods such as spreadsheets, email or chat.” Joe McKendrick at Informatica says that de-siloing offers the opportunity to solve one of the largest problems facing insurance companies and other industries today: a surfeit of data with very little insight. Integration, McKendrick adds, helps organizations understand customers, competitors and risks. See also: Insurtech’s Act 2: About to Start   Don’t Cut Corners Many insurtech companies and other organizations offer myriad shortcuts for integrating data, but many of these shortcuts don’t provide the commitment or stability needed for long-term success. “The popular cloud-based analytics services — IBM’s Watson, Salesforce’s Einstein, et al — offer easy-to-use and economical options for bringing analytics functionality in house, but this isn’t a very good idea,” says Scott Robinson, Lucina Health director of business intelligence. Instead, Robinson advocates for an approach that treats analytics as a new way to look at the insurance business — both its internal processes and its treatment of customers. By encouraging departments and teams to bake in the use of analytics, and by offering a comprehensive software platform that allows each group to focus on its area of expertise, insurers stand to create more lasting, effective change. Yet P&C insurers must take care not to let a goal of comprehensive, stable change turn into a quest for unattainable perfection, Datameer’s John Morrell says. “Creating the perfect data architecture and data delivery processes is, in practical terms, unachievable.” Instead, P&C carriers can focus on taking the process one step at a time, enabling more access to data by beginning with the departments, offices or teams who can best improve customer service with better access. By evaluating the availability of data sets — and their role in the customer experience — P&C insurance companies are better-positioned to choose the solutions that benefit their operations most. “Digital transformation requires breaking down the classic silos of front, middle and back offices to transform each into a unified, seamless customer experience,” says business transformation and automation leader Vartul Mittal. To succeed at this task, P&C insurers must do more than simply create an app or improve their website. They’ll need to focus on “contextual data and a middle office that can move from explaining the past to predicting the future” by leveraging machine learning, sophisticated algorithms and access to big data.