The Right Way to Transform the Insurance Sector with Data: Allen Thompson
Allen Thompson, VP Data and Analytics at The Hanover Insurance Group, shares his advice for choosing which digital transformation projects to pursue and getting the right data foundations in place to ensure they succeed
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.”
Laying the Right Data Foundations
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.”
- Dealing with the pressure to transform. Legacy industries find themselves under a great deal of pressure to transform their technology to make the most of emerging tech. But executives must ensure these investments will meet pressing business needs
- There is no data and analytics ‘magic pill’. Each organization’s data and analytics needs will be unique. The best way to develop your strategy is by working with business stakeholders to identify how data can best meet their needs
- Get the foundation right. Internal data governance, third-party data governance and model governance are the pillars that will manage how an organization uses and processes data