Raising Returns on Analytics Investments in Insurance by McKinsey

Article Synopsis :

Leading insurers are using advanced analytics to scrub existing and new troves of data in an effort to unlock value across products and business functions. This report, “Raising Returns on Analytics Investments In Insurance,” from McKinsey, suggests data and analytics leaders at global life and P&C carriers are investing as much as $80 million per year in data analytics, with nearly all planning to invest more moving forward. Furthermore, CEOs consider data and analytics a top-five priority.

Only 1 in 6 insurers report positive returns on analytics investments. Patience – and an analytics road map – required 

Despite the investments and management focus, only about one in six survey respondents report that data and analytics are delivering high impact. Primary reasons stated include:

• Lack of alignment with strategic goals
• Poor integration with “business as usual” and limited front-line adoption
• Poor data quality, including fragmented or incomplete data, and accuracy and accessibility issues

Additional barriers include budget constraints, talent gaps and unclear scope:

The report identifies five steps to help life and P&C insurers harness the power of analytics:

1. Create a clear roadmap: Based on use cases that support priorities across the value chain. Each analytics initiative should be ranked objectively based on its potential value to the business. The roadmap should take into account industry trends, competitive factors, new business services and possible enhancements to current products.
2. Build analytics results into performance management: Embed analytics into organizational DNA by making it an enterprise priority and managing to it, incorporating operational meaures, predictive measures, feedback and financial metrics.
3. Define clear governance across the organization: Organizational transformation requires clearly defined governance, roles and responsibilities, and escalation and resolution processes.
4. Launch a change campaign: Like any transformation, a data and analytics transformation requires changing the culture and the daily operating model. People can’t execute what they don’t understand.
5. Develop new ways of working: Data access and computing power have expanded at unprecedented rates in the last two to three years, but old habits—and attitudes—die hard. About 85% of survey respondents said that while data guides decision making, managers often discount it because they doubt its quality and integrity. A more collaborative work environment that includes analytics experts in business discussions can help ‘old school’ managers understand the power of analytics and make better, more data-driven decisions.

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