Recently, we hosted our sixth annual Insurity Valen Analytics Summit in the mountains of Colorado. I wanted to share with you some of the insightful and illuminating nuggets that came out of this intimate gathering with our clients and partners, and my colleagues and I will be doing so in a series of posts over the next few weeks.
But first, it’s important to consider where we started over five years ago at our first summit in 2015. Back then, the prospect of advanced data and analytics truly driving value, and how exactly that would happen, was a bit like the Wild West—ad hoc and maverick-minded approaches as insurers were going-it-alone on the data frontier. Since then, insurers have progressed and actively recognize the need for advanced analytics solutions—and the need to partner along with building solutions in-house. In fact, it’s one of the trends we cover in our 2020 Outlook Report. But back in 2015, clients were asking the executive why question. Why advanced analytics and why now? It was the right question and bringing us all together at our first summit helped us define some key business challenges.
- We discovered our first why by going back to 2008 and looking at the challenges around driving profit due to lowered investment yields. We needed to find a way to generate better profitability in underwriting.
- Which lead us to our second why—improving profitability—which requires better, more informed underwriting decisions. But, we saw a problem. While every industry faces an aging workforce, it’s more acute in insurance. About 30% more. So, at the very moment insurers need to rely on their best people to produce better results, the best people began to retire.
- That brings up our third why—an aging talent workforce, which requires companies to future-proof their organizations. Leveraging data analytics to enable consistent decision-making for experienced and new talent quickly rose to the top as an answer to the challenge.
Naturally, once our whys were established, we asked and started to answer the executive how dilemma: How do you design analytics to meet these critical business challenges? How do you expand analytics throughout the organization? How do you lead the change management required to get your people adopting analytics into the decision-making process? Over the last two or three years, we’ve seen many of our clients successfully implement solutions that answer these hows.
Which brings us to the present, and to our clients asking us to orchestrate a different kind of conversation. We’re all agreed that data analytics is the backbone of the future and, now more than ever, our industry is bombarded with what feels like millions of options. But, while choice is powerful, it can also be paralyzing.
Today, we’re at a pivotal moment where technology, talent, and innovation are intersecting. And it begs the question: now what?
Here’s what we know:
- The table stakes are well understood. Basic analytics, including point solutions for predictive analytics, are not enough. Insurers must become more sophisticated and analytically-driven organizations.
- There’s still a lot of noise. I anticipate many of you have been told that if you are not racing toward insurtechs, you are becoming obsolete. Perhaps many of you have been told that self-driving cars and workforce automation are going to wipe out auto and workers’ compensation premiums. And, you’ve also probably heard that if you are not using AI, you will not survive. Bright and shiny is not always best. Insurers must also stay focused on pragmatic solutions that drive immediate ROI.
- There’s a generational shift. Millennials are changing the rules of engagement, both as clients and employees. Organizations must adapt to these changes to remain profitable and relevant.
That’s a lot to take in, especially when most of us are still dealing with employees at differing levels of technology and analytics adoption. Widespread cultural change is still a work in progress, and we have a point of view about how to address this moment in building the future. A point of view you may or may not share, and it’s this: stick with the fundamentals. Start with the outcome in mind, and ask yourself:
- What is the business problem I am solving? Or, what is the opportunity I am chasing?
- What tools, data, or analytics will deliver reliable and measurable results to achieve my desired outcomes?
- Am I trying to boil the ocean, or is it better to start with low-hanging fruit and grab early wins so I can build from a place of success?
Answering what seems to be small questions like these requires big thinking and innovative ideas.
If you are asking these questions and trying to truly differentiate yourself in a fiercely competitive market, you can best meet that challenge with a very specific and integrated set of capabilities and tools that serve as building blocks. As a culmination of bringing together thought leaders, technologies, companies, teams, and relevant resources, we at Insurity now have a unique set of data analytics capabilities that are poised to inform a new era of intelligence and insight. Insurity’s data and analytics solutions are a holistic and open approach to helping insurers leverage data analytics. We’ve come a long way with data, analytics, and technology in insurance, and we’re thrilled to continue to lead the charge here at Insurity—by always starting with why.
In the coming weeks, my colleagues and I will be sharing what we discussed over our two-day conference including:
- How to effectively implement predictive analytics to modernize your underwriting process in order to achieve better pricing, profits, and competitive advantage.
- Key concerns and questions from your peers about integrating third-party data, consolidation and accessibility of information and systems, and enhanced analytics capabilities.
Tune in next week as we explore the power of predictive analytics at the point of underwriting, and how we’re helping insurers realize real results with this important capability.