Allen Thompson: The Right Way to Transform the Insurance Sector with Data

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.”
Key Takeaways


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