Prior to COVID-19, the insurance sector was relatively slow to transform itself with data and analytics technologies. The pandemic has helped to change attitudes towards these investments. But executives will struggle to translate this newfound enthusiasm into business results without a clear strategy.
“Data is like the new toy everybody wants to play with, but they don’t want to read the instructions it comes with,” quips Allen Thompson, VP, Data and Analytics at the Hanover Insurance Group.
In this week’s Business of Data podcast, Thompson outlines how and why many insurance sector data and analytics leaders may benefit from going ‘back to basics’ and ensuring their companies have the right data foundations in place.
“Data is such a huge part of every company,” he says. “Without good data, you can't even get basic information about your business. You can't make good decisions. The foundational stuff is important, because what you don’t take care of upstream becomes expensive downstream.”
Thompson believes there are three elements insurers must have in place to succeed with data and analytics: Internal data governance, third-party data governance and model governance. These pillars will dictate the ways an organization uses data, processes data and deals with other issues, such as data ownership, security and lineage.
Thompson argues that executives may feel the pressure to fast-track digital transformation projects based on pressure from company stakeholders or stories of advances that are being made at other companies. But he cautions against rushing to make technology investments without a clear picture of the value they will bring to the business.
“Companies spend a lot of money on technology, business intelligence, data scientists and information workers and they’re getting frustrated because things aren't happening fast enough,” he says. “I think this happens a lot because we really haven't focused on what problem we’re trying to solve.”
He acknowledges that the start of a transformation can be overwhelming but argues that understanding how data and analytics can support the organization helps to reveal the best path forward. The first step, Thompson says, is to roll-up one’s sleeves and work with company stakeholders to find valuable business cases for analytics.
“I advocate starting with an understanding of how the data strategy supports our company strategy,” Thompson recommends. “That’s how I prioritize what I need to fix. And a lot of times it's the basics – lineage, ownership and data quality. If you get those right, you can pretty much do anything down the road, but you have to roll up your sleeves.”