How to become an insight driven insurer?
Tactics to get business value from data analytics
Recent research by Deloitte shows that many insurers are not as insight driven as they could and should be. But there are exceptions. What can we learn from Deloitte’s research and the best practices in the industry?
Joep Dekkers - 26 June 2017
We interviewed 68 insurers throughout the EMEA region for our report ’A little less conversation, a lot more action – tactics to get satisfaction from data analytics’. The results from this survey were very similar to what I hear from my own clients in the insurance business: most struggle to articulate the return on investment made in analytics capabilities.
We already helped several clients to start professionalising and prioritising their data analytics approach. The first step in this process is that we advise them to adopt a holistic approach. Because before starting to build a solution, organisations should ask: how should the data-analytics approach address our long-term ambitions? Deploying the right people, embedding an insights process, having the right technology in place and respecting data as an asset are other important steps towards becoming an insight driven insurer.
Center of Analytics
One of our clients, an insurer that operates in EMEA, realized that they wanted a single Center of Analytics in one country that served all other countries. We are helping them to set this up by designing a Target Operating Model in which we define the required competencies, the recommended model for cooperation between the center and the business units, the required infrastructure and logistics, and the KPI’s to monitor performance and report.
We also assist our client’s new ‘Center of Excellence’ in setting up different analytics projects, which will help them to build a roadmap and to find the right people for the job. During this process we focus on so-called purple people: people who know how to connect technology to the daily practice of business.
These people also know how to identify the quick wins: small and easy-to-implement projects that add a lot of value. These quick wins are essential for organisations that start using data analytics, because they help to gain support for more complex and risky projects in the rest of the organisation.
Dynamic pricing is something that interests most of our clients. This makes sense, since a typical dynamic pricing project is very labor intensive: data is collected from multiple locations and analyses are at the least still initialised by humans, but in a lot of cases also still conducted by humans. At one of our clients, a Dutch insurance company, we automatised this process, which made it possible to implement dynamic pricing on their website.
Together with the business experts from the client we developed and tested a model that predicts the type of customer that responds to the product, based on all possible kinds of internal and external data. This results in a price offer specific to each different website visitor. This project fits nicely in the strategy of the insurer, since they want to create a more profitable portfolio and also want to get to know their customers better.
Implementing something like dynamic pricing only takes a few weeks; it does not ask for big investments and big adjustments of the IT infrastructure. Exactly that is why we chose ‘A little less conversation, a lot more action’ as the title of our recently published report. If insurance companies want to get satisfaction from data analytics, they simply have to start using the building blocks we mentioned before and begin a small analytics project.