While the business intelligence space has matured greatly in the last decade, it has been and remains an area where insurers need to work with a variety of platforms and tools to build out their capabilities. This requires a mix of technical skillsets, business expertise, and vendor relationships. While few efforts at an insurer are more complex or time consuming as a core system replacement, a major BI initiative will eventually touch all aspects of an organization. I will be presenting more on this topic in a webinar on December 1, 2015.
Today there are more vendors that provide a full business intelligence suite which includes the data layer, the industry-specific data models, the presentation and visualization tools, and the pre-built insurance reports and dashboards. But these suites still need to be tailored to and integrated into the rest of the insurer’s environment. Some policy administration system vendors are either pre-integrating with or releasing their own business intelligence suites. This does simplify the deployment but adds another variable to the “suite vs best-of-breed” decision, and until these options have more production exposure most insurers are still opting for best-of-breed.
For now, most of these approaches don’t provide some of the ancillary but very important data and analytics areas such as predictive modeling tools and the models themselves, the use of aggregated third-party data sources, or the emerging area of big data. And no matter what approach an insurer takes, it is a near-universal condition that there will be siloes of historical data that need to be considered with or migrated into the new BI solution, and that will take time and effort.
So despite plethora of vendor options and the general acknowledgement across the industry that good business intelligence is key to ongoing success, why aren’t more insurers further along in their data strategy?
1. Most insurers struggle with multiple legacy systems and siloes of disparate data, and they are still at the first steps of bringing that data together.
2. The data that does exist in the organization is of variable quality or completeness. New systems don’t immediately solve that problem without a broader plan in place.
3. Insurers and core systems have traditionally looked at data from a policy view, complicating the effort to move to new models that tend to take a 365 degree customer view.
4. Many insurers still have no formal data governance in place and lack organizational agreement on data definitions.
A good vendor partner can help put the framework and some tools in place to solve the above four roadblocks, but it requires more than just technology. It requires process and cultural change, which can’t be driven solely by IT.
Many insurers are still looking for a data champion to help push a strategy across the organization and get buy-in from other business leaders. As organizations mature, this data champion role is often formalized as a Chief Data Officer (CDO), and that person typically has a strong data background. But for insurers who are still looking to get a data strategy off the ground, it’s most important to find a leader who is respected in the organization and who is passionate about the value that good business intelligence can bring, even if they have little data experience themselves.