Swiss Army knives are designed to do just about anything–from cutting to sawing to drilling to poking to scraping and on and on. But when something new needs to be done, if the gadget isn't there, you can't modify the knife to add new tools. Like a Swiss Army knife, many companies intend for their insurance policy administration systems to do just about anything. Software vendors and systems designers make their living ensuring nearly every feature an insurer might need is included in their product or can be custom added.

Although this paradigm may provide insurers with power and capability, experience warns us to be mindful of systems that become overly bloated with the 20 percent of things contemplated in the 80:20 rule–while some of the things desired for the 80 percent bucket may not be in the system. This is especially significant when new major business or product capabilities evolve, and it becomes essential for them to become rapidly incorporated in policy management systems–capabilities that are inherently part of the 80 percent of needs, capabilities such as predictive analytics. But like a Swiss Army knife, what do we do if our systems can't be readily modified for new required functionality such as analytics?

A simple trip to a bookstore informs us of the mainstream importance of predictive analytics as we observe a startling number of topical pop-culture books on display. In our industry, much has been written in the insurance literature about predictive analytics and models that help insurance executives better analyze and predict circumstance and outcomes–things such as the potential profitability of new and renewal customers and risks. For some companies, these models have become part of the essential fabric of CRM, underwriting, pricing, and agency/broker management, to name a few. There is no doubt predictive analytics has become a mandatory capability in today's insurance world.