Insurance & Technology, a Budding Romance (Part 3)

Missed the earlier posts in this series? See previous post here.

Trying to peg where the insurance industry is in its technology transformation isn’t easy, for a couple reasons:

  1. The “insurance industry” isn’t a single monolithic organism; we have to account for the fact that different functions within the industry may be moving at different paces and have different goals.
  2. What even is a “technology transformation?” Are there standard models for what such a transformation chronology looks like?

Let’s talk about #1.

The adoption of technology, as well as the return on investment for that adoption, is not uniform across the different entities which make up the insurance ecosystem. If we look at the distribution channel, beginning at the insured and ending at the carrier, I’d posit that, until now, it’s those further “up the stack” in the channel who’ve benefited most from the application of technology – carriers the most so. The biggest carriers are all applying technology to benefit their underwriting, claims, and policy administration departments.

That said, it would be a mistake to look at even the carriers as a homogeneous thing – even with that space there are leaders and laggards. Generally, though, carriers are taking better advantage of technology than those down the distribution channel – the independent agencies and brokers. In fact, it may surprise independent agency owners to learn that the insurance industry overall ranks as “highly digitized” on McKinsey Global Institute’s “digitization index” (and this was back in 2016). The index seeks to rank an industry’s technology-transformedness, measuring things like IT expenditure, penetration, and utilization within the workforce.

Great! We’re “highly digitized” as an industry! We’ve arrived! We’re firing on all cylinders and can sit back and watch the clients and revenue roll in. You’re supposed to be chuckling at the sarcasm here… it’s how I’m making the point that the insurance industry is not at all a uniform thing we can talk about with broad characterization. The insurance industry is complex and comprised of multiple operational pieces. Even within those pieces, technology adoption has not reached ubiquity – and I see independent agencies as the furthest behind.

The rest of this series, then, will focus on technology-in-insurance from the independent agency’s point of view, and we’ll consider the IA channel as a little “industry” unto itself.

Let’s talk about #2.

If we’re going to talk about “technology transformation,” it behooves us to have an idea of what such a happening looks like. There are a few notable models we can use, and all are quite scholarly and complex. To make this more accessible, I have chosen to synthesize a few of these models to create a layman’s condensed version we can use. (For the nerds reading, you can check out the three models I used in the footnotes below.) Here, then, is my own condensed version of any given industry’s technology transformation evolution:

Technology transformation of industry, Dave’s layman version

Stage One, Convert & evaluate

A technology transformation cannot properly be said to have begun until an industry’s primary “instruments of exchange” go digital – transitioning away from paper or other physical formats. It’s this “digitization of widgets” that gets the technology ball rolling. Once primary instruments can be digitally manipulated and exchanged, a host of new technologies is created to do so.

These new technologies evolve rapidly and the product ecosystem balloons with offerings whose necessity and ROI are often unclear. Deployment decisions are made by singular managers/departments to solve point-problems, without coordination, and sometimes in conflict, with other pieces of the business. There isn’t a lot of company-wide strategy or industry-wide planning – it’s every IT manager for herself for whatever gains are to be made.

That said, this phase is immense foundational progress. We built a plane! We can use it to move stuff from point A to point B! But, if we’re gonna go big-time, we’ll need a airports and terminals and air traffic controllers and a host of other stuff…

Summary: Stage one is just about the tech. Stuff goes digital and new technology is unilaterally deployed in silos with hopes of targeted improvements.

Stage Two, Connect & define

In stage one, we got a host of cool new products to help us use our digital assets. In this stage, we start to realize that we can take things to new heights if we could just tie everything together and make it talk. It’s in this phase that the “business networks” are overhauled and optimized to facilitate the exchange and exploitation of the newly digitized widgets from stage one.

All my widgets are now digital and I can seamlessly exchange and use them with new products and systems and entities. Value begins stacking as data is augmented by multiple interconnected ecosystem players. I can change my business model to attain new types of customers (going from B2B only to B2C, for example). I will discover newly available markets I didn’t realize existed.

There are a few hallmarks of an industry in this phase: Firstly, as the mediums of exchange start to adapt to the proliferation of tech, the product space enters a new stage of evolution and maturation. There will still be a traffic-jam of contenders, but the product ecosystem will begin to contract and harden. Losers will begin to die-off and the winners and leaders will being to rise to the fore. Second, standards will be born to define the mechanics of exchange and interoperability for digital assets. (Standards, in fact, have an evolution and life-cycle all of their own, which is interesting but beyond the scope of this writing.) Third, adoption of technology becomes less siloed and more coordinated.

Summary: Stuff is connected together and taught a common language, which unlocks new business models and market opportunities. Adoption and deployment become coordinated within a company and even with outside entities.

Stage Three, Adopt & transform

Technology is now an indispensable part of the industry. All new winning ideas in the industry will come with a presumption of technology usage. If it was the posture of the industry that changed in phase two, it’s the ingrained culture of the industry that changes in this phase. We are still free to question the ROI of any given technology implementation, but gone is the FUD (fear, uncertainty, and doubt) around “technology” as an ideology.

Tech has proven its value to the entire ecosystem of a given industry. The product ecosystem has established and mature players who command large slices of the usage space. There will still be lightning-bolt upstarts and newcomers, but we’re no longer in the wild west and they’ll have to face entrenched incumbents. This phase is not at all immune to upheaval or even upending by new ideas, it’s just not churning as quickly nor violently as in the early stages.

Summary: The ecosystem and interoperability are mature enough that the culture of an industry changes. Tech is now ingrained and ubiquitous, a must-have ingredient for success. There are established incumbents in the product space who command large market segment shares.

OK then, we’ve gone a bit long here… but I think we’ve laid the important groundwork. We’ve acknowledged that the insurance industry is a multi-faceted thing with pieces that are transforming at different paces and for different reasons, and we’ve established a simplified “model” that we can use to gauge the IA channel piece specifically. We’ll leave it to the next installment, then, to discuss where the IA channel is in its transformation, and what that means to us.

Thanks for reading!

Footnote: While it probably doesn’t seem like it, I used three established models of technology transformation when creating the Playskool version used in this post. For those interested, those models were: (1) IT-Enabled Business Transformation, Venkatraman, 1994; (2) The Digital Maturity Model, Forrester, 2017, and (3) IT in Enterprise Transformation, Korhonen, 2015. Full disclosure, I also borrowed Salesforce CEO Keith Block’s tech/model/culture simplification from the 2020 World Economic Forum.

Previously published on

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