Three Reasons Insurance
Analytics Projects Fail
Are there Advantages to a Proven Methodology?
It’s no secret that implementing Analytics is not for the faint-of-heart. Even more so in the specialized field of Insurance Analytics, where legacy systems, geographic separation of business entities, mergers and acquisitions, regulatory requirements and the specialized needs of brokers add to the complexity of Insurance Analytics initiatives, at each step.
Even when the challenges of Insurance Analytics are correctly identified at the outset, and an implementation strategy is carefully mapped out, it seems that success is not guaranteed. Analytics implementation problems can arise. Even simple Analytics implementation issues can escalate, potentially leading to Analytics project failure.
What is it that causes Insurance Analytics projects to get bogged down? How can we obtain the much-needed support at the executive level? Is Insurance Analytics mainly a technological problem, or is there another, more helpful way in which it can be viewed? How does the methodology you choose affect the outcome?
Download for more information on the three most common causes of failure in Insurance Analytics projects, and how Insurance Analytics implementation problems can be avoided.