When done right, IPM can be a true game-changer—driving business agility, innovation, simplification and risk reduction. But the fact is, doing IPM right is not easy. There’s no silver bullet. More than a few carriers have tried and failed.
Why do IPM projects go wrong? In my experience, it’s for one of three reasons, and I present them below. You may want to use the following as a guide of the roadblocks you may encounter, and should seek to avoid, when you begin your own IPM initiative.
Roadblock #1: Legacy hardware and custom software
In the average insurance company data center, there’s a significant amount of disparate legacy hardware and software applications, and not a lot of cloud-native technology. In fact, much of that old technology can date back several decades.
How exactly does that happen? Chalk it up to “application sprawl,” the term given to the patchwork solutions that result when large, legacy monolithic applications are band-aided and appended again and again over the years, instead of replaced with a 21st century-worthy solution. The default mantra becomes "Let’s modify and build a couple more, then a couple more, then a couple more,” and data is eventually siloed in different applications, which requires significant integration down the line.
Another problem: custom software. Insurance is a complex, highly regulated industry, with multiple state-specific rules and regulations and requirements. To manage all those variables, insurers have highly customized their software to differentiate their products, making that software very difficult to modernize or replace.
Now compound both of the above challenges with the technology knowledge gap that all companies are facing today. There are not enough IT experts who understand these custom applications—which makes modernization that much more elusive a goal.
Roadblock #2: Inadequate strategy and roadmap
Another reason for misguided IPM initiatives is the absence of a real strategy. Many companies lack both a roadmap that drives business transformation and an operating model that is oriented around multi-cloud and on-premises applications.
Perhaps a specific scenario calls for an incremental deployment. Or perhaps a summary to-the-cloud approach is appropriate, such as in cases of a divestiture, acquisition or data center exit strategy. But without an overarching strategy in place up front to drive the initiative, how can any modernization effort be expected to succeed?
Then, similarly to roadblock #1, talent is an issue as well—or more specifically, attracting that talent. In today’s labor market, it’s difficult to recruit and hire strong cloud engineers. That’s especially difficult for insurance companies, who must convince talented IT professionals to come and stay in an industry that is notorious for both dated technology and structural corporate and regulatory restrictions.
This paucity of talent is a challenge whatever the size or scale of one’s modernization effort. Even if, for example, you are looking to migrate only a fraction of your workload to the cloud, the effort demands as full an IT staff as a more expansive initiative requires.
Roadblock #3: Leading with technology instead of business
This is by far the most damning of business transformation errors. Many modernization efforts are driven not by business strategy, but by technology teams, with limited or no engagement from the business side. When business leaders and teams are not involved in a modernization initiative, it becomes merely a technology project, shuffling data and applications from on-premises to the cloud.
Yet many insurers make that mistake, attempting a “geography move” or “lift and shift.” They summarily move all on-premises applications to the cloud, without a strategy, and measure success by counting the number of applications they need to or have migrated. (We moved 1,500 applications to the cloud!)
When technology, not business, leads the IPM charge, chronic issues such as siloed data and problematic data quality are often left unaddressed. That is, of course, a recipe for failure. When the effort is simply moving on-premises data to the cloud, on-premises problems aren’t solved; they simply become cloud-based problems. That leads directly to cost issues, both in the short and long run.