Our Wired World

For Insurers, Time To Advance The Data Debate

Why Refocusing on Data and Analytics is Critical

by Karen Pauli

Ms. Pauli is a principal with Strategy Meets Action, a strategic advisory firm offering consulting, advisory services, and research ‘to help insurers bridge today’s business strategies, plans, and technology investments to the new world of digital transformation, emerging technologies, and InsurTech.’ Reprinted with permission. Visit here.

Data and analytics is a phrase that is probably in 75% of articles and blogs written today. In fact, data and analytics is used so frequently that it almost appears to be one word – dataandanalytics.

SMA research shows that 92% of insurers have data and analytics initiatives under way in 2017. It is the number 2 initiative, only 3 percentage points behind customer experience, to which it is closely aligned!

The importance of data and analytics to the enterprise is no longer debated. However, there is danger in this. A level of complacency has crept into how insurers are addressing data and analytics requirements. SMA survey results show that, on average, 65% of insurers are investing in reporting and dashboards and scorecards, spanning both personal lines and commercial lines of business. Clearly, it is important to do this because managing day-to-day operations is critical. However, and this is the salient point, investing in these areas is historical – it’s where the money has been going for quite some time.

A need for a ‘customer view’

The flip side of this picture is that 80% of survey responders indicate they have no plans for investing in cognitive computing, and 37% have no plans for investing in data and text mining. Use cases follow the same pattern. In terms of the customer and distribution, insurers have been investing in new business analysis and agent performance for years. Yet, 53% of survey responders say they have no plans for using data and analytics for single view of the customer. Numerous other examples abound, as detailed in our research findings.

A level of complacency has crept into how insurers are addressing data and analytics requirements

The insurance industry is definitely focused on investing in data and analytics, but the research shows that the investment is in the same areas, for the same purposes. Insurers continue to get good at what they are already good at. And it is hard not to do this … the positive results are compounding! But one huge factor is making this direction untenable – the pace of change. Technology, particularly technology coming from InsurTech organizations, is exponentially advancing. Customer expectations and the rapidly evolving nature of risk are figuratively (and somewhat literally) running right along next to these emerging technologies, eager for the value being delivered.

When it comes to emerging data sources such as the IoT, wearables, and drones, there are a handful of insurers that are embracing the data and developing capabilities. Yet, up to 82% of insurers have no plans to leverage these data sources. Those insurers advancing with new data sources are rapidly creating a gap that insurers with no plans will find difficult to bridge. This is another example of where the pace of change will have a big influence.

Moving toward innovation

A great percentage of insurers are poised to change direction and move from the data-and-analytics-investment “comfortable zone” and over into innovation. Significant work has been done from an organization and role perspective in terms of data and analytics teams, particularly at an enterprise level. But the measured steps of the past need to be replaced by a faster pace and focused on new targets that emulate the world that we live in.

SMA’s recently released report, Data and Analytics in Insurance: P&C View Through 2020, provides a deep dive into the state of data and analytics today, as well as plans for the future. The report also features an updated version of SMA’s proprietary Data and Analytics Spectrum which provides a framework for insurers to benchmark their initiatives. It also details the various components of a robust data and analytics strategy. Or is it a dataandanalytics strategy?