As insurers grapple with how to convert data into customer insight, they often get bogged down in the costs and risks of replacing legacy systems. Instead, they should focus on culture change – as part of a journey to become data-driven organizations – to help their people and processes turn data into meaningful information.
The root of the problem
Insurers’ struggle to employ data analytics is partly the result of their acquisitive nature, notes Gary Richardson, Insurance Analytics Lead, Data Insights Services with KPMG in the UK. “Insurers often grow by acquisition, resulting in a common brand with lots of individual companies and systems,” says Richardson. “Integration of legacy systems is often postponed if executives prioritize preserving portfolio margins and profitability.”
Although incompatible legacy systems make it hard for an insurer to achieve a single organizational view of data, they are a symptom rather than the root problem, observes Daniel Hodgkiss, Head of Customer Analytics, Data Insight Services at KPMG. “The underlying cause is often culture, with many insurers being policy-centric and therefore having systems that are more geared to a specific product, with minimal view of the customer.”
This product orientation creates silos between business lines, notes Hodgkiss. “One underwriter insists that ‘My data is special, it won’t conform to your data and we shouldn’t try.’ So product groups refuse to give up control of their data or capabilities,” says Hodgkiss, adding that rivalries also exist between business lines and IT or between internal functions, such as sales and finance, which each maintain their own views of customer.
The end result: executives realize there is a data problem but they accept the arguments against merging systems due to the astronomic costs or risks of disrupting stable processes, especially when they hear that infrastructure investment won’t immediately generate new revenue.
Tough questions drive change
In companies where status quo systems reign supreme, change often comes only once senior leaders raise tough questions. “When someone on the board challenges a number on a spreadsheet, and it takes six weeks to answer the question, it sinks in that the company can’t keep operating with ‘apples and oranges’ data,” explains Richardson. “This can trigger a culture change where leaders begin questioning data and digging deeper, rather than taking numbers at face value, the boardroom is becoming the data centre.”
Fortunately, it’s now easier to begin the data integration journey, due to technologies that help companies saddled with legacy problems, including data virtualization and visualization tools that bring discordant data together.
Explains Hodgkiss, “Insurers can install data virtualization software that sits on top of different systems, extract key data and create a data analytics repository in short order. This creates a reporting system that can give a company more access to its critical data. Then, you see what data opportunities exist and focus on generating the metrics you want to drive your business.”
Richardson notes that data virtualization software provides a very pragmatic approach for an organization. “With a limited budget, you can set up a small data laboratory that targets key data sets; merge these data together and derive real value, to show your board the potential.”
“Your ultimate goal may be to build a centralized company data function that creates policy, practices and standards,” explains Hodgkiss. “By creating virtual teams, these common practices start to seep into the business units and break down silos. Over time, your product people will gravitate to this group and become more willing to share data because they start to understand the value they will get from joining and merging it.”
But to begin moving from a policy-centric mindset to a customer-centric view, you have to focus on culture change, points out Hodgkiss. “First, you have to get buy-in from senior leaders who recognize the potential. Second, you have to allay the fears of losing control among the people who own and manage the data. This means selling the benefits of why you are doing this to each group, rather than pushing it out.”
Concludes Richardson, “Although the big goal of bringing together legacy systems is a leviathan task, if leaders break it down into smaller steps, accompanied by internal culture change, an insurer can begin the journey to become a data-driven organization, and turn silos of mismatched data into profitable customer insights.”