Joint research from Accenture Analytics and MIT shows that high performers use analytics to not only better manage their in-house talent, but also to recruit talent from outside.

While a discussion of analytics might focus on technology and data, we shouldn’t lose sight of the people part of the equation. Organizations that find their sweet spot—that intersection of technology and talent that allows the best of both worlds—will be in a better position to adapt to an increasingly fluid marketplace.

That’s corroborated by a joint study from Accenture Analytics and MIT, which found that high performers leverage analytics to enable an end-to-end, multi-pronged talent sourcing strategy. Let’s take a closer look in this Insurance Insight of the Week.

Talent powers the analytics machine

Click the image below for a large version of the Insurance Insight of the Week.

High performers are better talent managers

Click the image below for a large version of the Insurance Insight of the Week.

High performers fill talent gaps more aggressively

So while both high and low performers report challenges in finding talent, it’s clear that high performers

are better at managing existing talent, and at filling gaps more aggressively. Analytics can help drive better decision-making and enhance workflows to help insurers focus on what really matters: retaining, training and acquiring the right talent.

This is echoed in Accenture Technology Vision for Insurance 2016, which identifies five technology trends that leading insurers need to address. This year’s overarching theme is “people first,” which reinforces the importance of people and culture to effectively leveraging technology. Furthermore, one of the identified trends is “liquid workforce” or the need for insurers to harness technology to enable the right people to do the right things—thereby enabling an adaptable, change-ready, responsive workforce.

For more results from the analytics study, download Winning with Analytics. Many thanks to my colleagues, Brian McCarthy and Lynn LaFiandra, as well as David Simchi-Levi and Jyo Gadewadikar at MIT, for sharing their expertise.

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