Raising returns on analytics investments in insurance
In an era of narrow margins and slow growth, insurers’ need to invest in analytics has never been greater. A few thoughtful initiatives can accelerate the analytics journey.
Leading insurers are using advanced analytics to tap into both existing and new troves of data, in an effort to unlock value across products and business functions. In a recent McKinsey survey, data and analytics leaders at global life and P&C carriers reported that they were investing as much as $80 million per year in data analytics, and nearly all planned to invest more in 2017. At least half of the firms’ CEOs consider data and analytics a top-five priority.
Despite the investments and the management focus, only about one in six survey respondents reported that data and analytics were delivering high impact. The primary reasons stated for these struggles were (exhibit):
A number of carriers, however, are finding ways to bridge this gap between the potential of analytics and the realized value. These initiatives share a common theme: insurers have to get the technology right, but it is equally important to take a strategic view of analytics efforts, and set in place the organizational, performance management, and change management processes to pave the way for true success.
McKinsey’s survey of data and analytics leaders in the industry confirms that insurance executives are well aware of the potential for analytics to deliver value across a range of functions and products. The same research, however, points to the need for a new approach to realizing this potential. Most analytics initiatives fall short for one of three reasons.
Many senior insurance executives view analytics as small lab experiments or as parts of larger innovation initiatives, and fail to provide enough funding. For similar reasons, many analytics teams lack leadership support and clear mandates. Some teams attempt to solve small-scale problems without making substantive contributions to strategic goals or targets. As one insurance analytics leader put it, “It’s tempting to invest in new tools and try to keep up with technology trends. But use cases and analytics efforts need to be rooted in business strategy.”
One insurer found a way to prioritize analytics investments and align them with strategy. After an annual strategy refresh, the CEO asked each business unit to define and prioritize analytics use cases. With these priorities in hand, the senior team created a five-year analytics road map, focusing on investments with a potential for at least 250 percent annual return on investment in steady state. This clear articulation of the value at stake and investment rationales ensured that all analytics work was aligned with the organization’s strategic goals.
To succeed with analytics initiatives, leaders need to attract the right talent, tap into the best data sources, and build accurate models, but few invest enough in driving frontline adoption, change management, or business buy-in. Without establishing new attitudes and behaviors, even potentially revolutionary insights may deliver little or no value.
About 40 percent of survey respondents cited limited frontline adoption as a leading cause of their organizations’ inability to unlock the full potential of analytics. One life carrier CIO said he now sees machine learning and analytics as commodities: “The true value lies in using data-driven insights, changing mind-sets and behaviors, and driving frontline adoption.”
About 20 percent of survey respondents cited poor data quality, data fragmentation, and lack of data access as the primary hindrances to realizing the full potential of analytics. Many insurers spend inordinate amounts of time cleaning internal data or building centralized repositories. Other carriers struggle because their analytics teams are not aware that valuable data is available in other parts of the organization—or because third-party regulations or ownership challenges prevent them from using it.
