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I spend a lot of my time thinking about collaboration and analytics in the insurance space. So I was quick to read through the article "Next-Gen Analytics Drive Efficiency."
I wasn't surprised that the article did not mention collaboration. In my narrow view of the technology world, collaboration and analytics work together -- you can't have one without the other. I've previously defined collaboration as the ability to work together between an insurance carrier, agency/broker, and the customer.
One of my big takeaways from the article was the desperate need for both collaboration and analytics at the agency level. The article mentions five factors driving analytics at the agency level but I wanted to evaluate these factors for collaboration as well.
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1. Competition. Sure, analytics can help with competition. But collaboration seems just as important, if not more so. Analytics can lead to better profit margins. Collaboration can lead to more clients.
2. Consolidation. As more brokers and agencies merge, the absolute need for collaboration will grow. If you go from 5 offices to 50 offices, how will your offices talk?
3. Focus on Maintaining or Improving Margins. Analytics can certainly drive better profit margins by improving on the decision making process. But collaboration is the low hanging fruit. If you can get your broker team working together, they can work faster and better. Period.
4. Drive for efficiency. Again, collaboration is the low hanging fruit! In fact, analytics won't help if an agency is not willing to change the behavior and workflow. I would suggest creating collaboration is a good first workflow test to determine how quickly your company can adopt future changes.
5. Rising Client Expectations. This factor screams for collaboration. Again, I love analytics, but they won't matter if you don't change your workflow to deliver a better client experience. Collaboration is king.
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As I've been evaluating the insurance space, it's become clear that the industry is focused on financial analytics. For example, how can analytics support the actuarial work already going on. There is also a push to use analytics to improve Customer Relationship Management systems. For example, how can analytics pick up on opportunities with customers?If Customer X asks for Policy Y, how can we know when to reach out next? And what policy is most likely needed?
We are working at the edge of another space -- what I call risk management analytics. It's a hybrid of both knowledge management, contract analysis and sentiment analytics.
If you are interested in why insurance carriers, brokers, and agents are interested in risk management analytics, download our ebook "What is the ROI on Collaborative Contract Review?"