Data Analytics

To understand recent failures in projections (notably in election polls), let's revisit four technologies that did not live up to the hype.

The question on new technology usually is: Why should we adopt it? A better question may be: What happens if you don't?

Insurers used to have to measure precisely, collect only samples and know exactly what they were looking for. No longer.

Having multiple databases can harm the data’s integrity and result in redundant work or even reduce consumer satisfaction.

The consumer experience is a funnel, and personalization can be applied to each touch-point in the funnel.

When it comes to your IT and data strategies, are they #same or are they #goals? You need to be careful.

The way insurers manage data and leverage analytics capabilities is improving slowly, but steady progress is being made.

Putting models into production is the fun part -- but requires not only testing but also a plan for monitoring and updating as time goes on.