Insurers (and distributors) are seeking efficiencies and differentiation strategies. One common approach is to become “data driven” in products, services, and customer service. The siren song of increased market share and profitability emanates just around the analytics bend.
The aspiration is laudable, but carries execution risks. Fortunately, we already have the tools to move forward.
Analytics everywhere …
It is all but impossible to pick up a trade magazine that does not contain an article on an insurer who has made it to the end of the data rainbow by using an analytics compass. Case studies drive the point that the more you measure, the more you earn.
Common reference points are Amazon, Google, and Walmart, And there are examples within the insurance industry – Progressive with it Usage Based Insurance and USAA with its IBM Watson implementation.
Canadian insurers are doing their share. Earlier this year, several of the Insurance-Canada.ca Technology Award (ICTA) winners (including the overall winner – Intact, supported by DMTI Spatial) earned the recognition through successful data analytics implementations.
But Data and Tools are not sufficient …
So we’re on the road to data nirvana?
Perhaps not as fast, or effective, as we would like. What are the issues? Two major categories: A single source of truth and people
Many organizations do not have a centralized source of data or tools. This is usually due to legacy systems’ lack of standardized data.
Compounding the problem, individual departments have taken to developing their own ‘analytic’ solutions, using off the shelf tools or, more commonly, spreadsheets and data sometimes downloaded from other systems or re-keyed from other reports.
A common result is a tense meeting, featuring competing/conflicting power point presentations, based on different data.
The Cure brings a Curse….
With the onslaught of Big Data, this could get worse before it gets better. IDC is projecting that Social, Mobile, Analytics, Cloud spending will account for 30% of IT spend next year. Governance of data and control of tools is a critical success factor.
And this is starting to happen. Organizations are setting up data warehouses and data governance policies. Data audits are becoming common. With consistent monitoring, this will take care of half the problems.
There’s a still a link missing.
The enemy amongst us…
Insurers are creating departments staffed with ‘data scientists’ to expedite the usage of powerful analytics tools. This is good. But these folks typically don’t talk to clients, underwrite risks, and settle claims.
The vast majority of line users don’t have an appreciation for analytics beyond simple reporting. As we move to more complex products that are data driven (e.g., Usage-based insurance), we need to help front line users understand that analytics are powerful tools to make their work more effective and, in many ways, interesting.
As an early mentor of mine once said: “The one element we consistently neglect is training.” Without education for these users, we have a very weak link.
So what to do?
Use of analytics is a hot topic, and most managers recognize that it will play a significant role going forward. However, engaged senior management is required to provide structure, governance, and guidance.
Use of data and analytics is like driving a powerful sports car: If the steering is not well connected (common data and governance), we’ll be off the road in minutes.
And if the driver is not trained, we’ll go really fast, but can’t predict where we will end up.
What do you think?
If this resonates with you, what are you doing in your environment? Do you have a data governance structure? How about training and orientation?
