During a recent industry briefing call, the Chief Analytics Officer of a life insurance carrier asked me an interesting question: “Should I try to get funding support for our new analytics initiative on the basis that it’s cool and sexy?”
When I prompted her about what’s sexy and cool about her proposal, she replied, “Well, machine learning is sexy, because especially in our industry, it’s the new hot thing. And it’s cool because I think we can improve how we make underwriting decisions on new policies.”
Then, I followed up with an important clarifying question, ”Do you have the technology support to implement that model, if you did indeed find a better underwriting mousetrap?” She had to admit she didn’t yet know how or whether she could implement such a new model in their production systems, which is maintained by the technology organization. She also didn’t know the best way to work with the underwriters to adopt the pricing policy changes that her upgraded model would support.
Why cool isn’t enough
Here’s why I have found cool doesn’t win the day: In many financial services firms, few executives want to be a guinea pig for an investment that is novel in their industry, especially in fiscally and operationally conservative environments like the life insurance industry. Cool simply isn’t enough.
It’s not sufficient to build a predictive model that’s merely more accurate or precise than the current decisioning approach. Unless that model is used to change the way that material decisions are made, it’s often an academic exercise.
Precise and accurate models can indeed produce business value, but only if they are implemented—and not just by the technology team. You also need to follow through with the business users, to ensure they understand what you’re asking them to adapt and use as a new decisioning mechanism.
The resource allocation conundrum
Executives’ key role is to allocate resources towards some opportunities, and away from others—which means some initiatives win, and others lose. In financial services companies, many of those decisions are made based on IRR and ROI criteria. Because of the many possible investments to be made, the initiatives that win are often those that offer the most compelling return on investment.
This is no small task. After all, decisions to allocate resources are risky ventures: you might back a great idea that never pans out; you might pass on an investment that someone else turns into a winner; you might under-invest in an option that could have been a game-changer. People’s jobs depend on whether you are right or wrong on those investment decisions. Hence, there is a lot of power, risk, and consequence bundled into resource allocation.
Investment decisions are really about taking a stand, and being held accountable in a risky situation—like Paul Newman in “Cool Hand Luke,” or Uma Thurman as the Bride in “Kill Bill.” Decisions are sexy!
How analytics investments win out
It’s not surprising, then, that decision-makers want analytic guidance to make the best decisions, so that the organization maximizes their opportunity to produce wins. Fortunately, analytics investments are one of the few areas that helps you better allocate those resources and understand how to continually improve those decisions. In other words, when implemented correctly, a good analytics program will improve executives’ ability to make these crucial decisions—which makes their return directly measurable.
Analytics investments often win when leaders are convinced that they will be able to make more granular decisions based on evidence-driven outcomes. In the end, that’s how analytics are valuable: If your analytics initiative will help guide more effective decisions, and those decisions affect the allocation of resources every day by hundreds of people in your organization, and the organization will produce wins for your customers because of it… that’s not just cool, that’s sexy.
Therefore, my response to our insurance CAO was this: “In my experience, no, you should not use cool and sexy to sell your proposal. You should sell it on value and execution.”
When you execute successfully, and deliver value, that’s how you prove that decisions are sexy.