(Steps in the Juliusterm, Spandau Citadel, Berlin. Photo credit: Till Krech.)
Few insurers lack some kind of analytical competence, but most are challenged to make the transition from isolated use of the relevant technologies to becoming data-driven enterprises. One of the biggest steps is to consolidate analytics capabilities into a single, enterprise-wide department, and insurers are increasingly under pressure to do so.
Smart shareholders are increasingly holding management accountable for analytics road maps. From a strategic point of view, they have come to appreciate the threat of obsolescence, and the dangers of being “just good enough,” in terms of its effect on brand and the capacity for retaining top talent. From a practical point of view, shareholders see road maps as a vehicle for sustainable progress as opposed to isolated “point” implementations or “build once, sell forever” approaches.
That said, the leadership of many companies is still reluctant to move energetically into the analytics arena for fear of fad-chasing. It’s a reasonable concern, but one that should be overcome. In the first place, all industry is moving to a data-driven paradigm, and far from insurance being an exception, it is a data-driven business par excellence. Insurance has always been about data, the industry was a pioneer in data processing, and the next great evolution of the industry will be largely about data analysis. But more concretely, insurance business leaders simply need to learn to distinguish between “fashionista” splurges designed to dazzle shareholders momentarily, on the one hand, and prudent, sustained application of data and analytics technologies to support decision-making and solve challenging business problems, on the other.
Hype vs. Reality
Many insurers have begun to institutionalize the capacity to distinguish between hype and reality by appointing chief analytics officers. These C-suite partners are charged with identifying necessary developments and business opportunities in data and analytics. They are focused on building an enterprise data and analytics practice characterized by a culture of experimentation and continuous improvement. Taking risks can be destabilizing to the status quo of an organization, so the chief analytics officer provides senior sponsorship and room for failure as an inevitable outcome of R&D.
Too many insurance carrier executives hew too closely to managing their P&L on the margin of expense. That approach fails to properly value existing technology investments and squanders opportunities that may arise with each new release. Giving chief analytics officers responsibility for data and analytics infrastructure and applications – things such as the analytics platform, federated data warehouses, external data feeds, etc. – helps to integrate these capabilities into a go-to-market strategy.
Balancing Ambition and Prudence
Appointing a chief analytics officer won’t suddenly make your company an innovation factory. In the first place, he or she is still dependent on the commitment of the entire leadership team. On all levels in the hierarchy, from the chief analytics officer to the board, leadership rather than management can make the difference between mediocrity and excellence in becoming a data-driven company. But it’s also important to always balance ambition with prudence, and that’s especially the case with newer types of technology-driven business process.
There is such a thing as “good enough” and there are limits to what the market – and internal resources – will bear. The critical point is to recognize that these qualities are ephemeral, and that they should be treated as such within a plan for advancement. One of the best ways to ensure that they are is to institute an enterprise data and analytics capability under the direction of a chief analytics officer.