Missed the earlier posts in this series? Start from the beginning here.

Let’s get right into this: My initial assessment is that the independent-agent channel component of the insurance industry is currently living in phase-two of the “industry technology transformation” model we discussed in part 3 of this series. Other components of the industry may be further along, but I’m pretty confident that’s where the IA channel is.

Let’s first talk about why I think this, and then we’ll dip our toes into how it can inform us as independent agencies. Observing the IA channel, I see three primary indicators that we are, indeed, in the midst of phase-two

1. 1. “Business networks” are maturing, but there is a lack of unifying interoperability standards
   2. The software solution space is massive, but we see it consolidating
   3. Independent agencies are using technology, but we’re still working on it being “cultural”

To the first point: The insurance space is ripe for new standardization – specifically around its data objects and the exchange thereof. What data & metadata is important? How do we ethically use data to generate insights while respecting our clients’ personally identifiable information (PII)? What standard ways should we be storing and tagging data for business intelligence purposes. Who owns which data pieces? How do we share data among the channel players (agencies, carriers, solution vendors)? By what protocols, in what formats and through what interfaces?

The insurance space is no stranger to standardization. I believe conversations tackling the above questions, and more, are currently happening – but only in certain circles. This is a good thing – but we need to be careful. “Defacto standards” which are “defined” by everyone snapping to what the guy with the biggest market-share does are, in my opinion, destined to fail. We need to get the right stakeholders to the table to discuss the above and define open standards, much in the way IEEE does for the “hard” engineering sciences.

Open protocols, democratized data, equal-opportunity for revenue… that’s where we need to be driving. The fact that we’re not here yet isn’t bad, it just helps us determine that we are, indeed, in that second phase of the “industry technology transformation” model from our previous post.

To the second point: The insurtech space is still overcrowded, but we see it beginning to consolidate. This consolidation is sometimes happening through natural selection, with crappy offerings dying (as they should) because they are inferior or due to a lack of demand. It’s also sometimes happening via buyout or merger and acquisition, perhaps a less “natural” type of selection but still a valid way to consolidate the space (for good or ill).

Based on what I’ve seen happen before, we’ll see continued consolidation until we hit the “initial set” of best-in-class products. We’ll know we’re there when we observe a more finite and defined set of solution categories, with one to three product offerings to choose from in each. Think about your PC – you have an email program, a web browser, a productivity suite, etc. There are multiple players in each category, but I bet you can easily name the top-three in each. That’s your “initial set” of best-in-class products. Innovation doesn’t stop at this point – but it does look different than that first distillation from the wild-west phase.

I feel like the insurtech space has not yet fully distilled into its “initial set” of best-in-class products. Another sign, to me, that we are indeed in phase two of the transformation model.

And to our last point, and perhaps the hardest to peg with “hard” data. As I mentioned in the first post in this series, independent agency owners are barraged with technology pitches on the daily. There’s a solid general awareness that technology can improve operations, and there exists good pieces of technology which deliver real ROI. It’s not that IAs are ignorant or opposed to technology (well, for the most part, that is) – but I’m going to posit that technology usage is not yet a “cultural thing.”

OK why do I say that? Through what I’ve observed at our own independent agency and conversations I’ve had with other IA owners – our relationship with technology still feels a little less than something “cultural.” Like I said, this is hard to peg down with data – but I still sense a lack of certainty from IA owners re: what they should be using and what they should expect in return from using it. If we’re using software because we feel we have no other choice or we’re afraid we’ll somehow fall behind, I’d argue we’re in more of a compulsion state vs. a cultural one.

AirPods usage is cultural, EZLynx and IVANS usage is because there’s nothing better yet.

Hope I’m continuing to make sense here… thanks for sticking with me. In the next, and I think last, article I hope to offer some ideas about what independent agencies can do now to best position themselves as the industry moves into the its third phase of technology transformation.

Until then, happy insurancing!

Missed the earlier posts in this series? Start from the beginning here.

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

1. 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:

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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.

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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.

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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.

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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!

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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.

Missed the earlier posts in this series? Start from the beginning here.

Before we consult our crystal ball and try to get all Nostradamus, attempting to divine just where the insurance industry may be in its technology transformation, let’s maybe a take a minute to pop our head above the din and take stock of what’s going on. Orienting like this is always a good precursor to prognostication, and when done by a newbie to an industry, someone not beholden to the preconceived notions of a lifer, it can sometimes be additionally informative. Without (much) editorial, then, here’s what I, a complete newbie to the world of insurance, have observed about the industry’s current relationship with technology:

1. • When it comes to the pantheon of insurtech that’s pitched at them, independent agency (IA) owners are overwhelmed.  “Everything’s changing!,” they’re told; “Oh, you’re not using XYZ solution yet?!  I see…”  This FOMO (fear of missing out) creates uncertainty, doubt, nervousness.  What happens when people face uncertainty?  The hesitate, they exercise a slow caution, they watch and wait, and they may even dig in their heels.  These are folks who sell insurance, and that’s what they want to do.  Talk of drones and geofencing and Watson or Einstein don’t get them hyped in the least.  
   • Taking a closer look at that same smorgasbord of products and solutions – it’s clear that insurtech has a way to go yet to reach maturity.  For instance, at ITC in 2019 I counted no less five different start-ups staking their claim to being “the best AI-driven data sources for underwriting.”  Spoiler alert, there’s only one best… and it’s likely it doesn’t even exist yet.  There is much consolidation, acquisition, and series-B shortfall to come in this space… not to mention the continual flow of new entrants.  Can you really blame IA owners for being conservative with their investments?
   • The “must have” tools of today’s independent agencies are woefully lacking.  Sure, you’ll hear IAs rave about certain software they use, but I find that nine times out of ten they’re not talking about a tool that is designed specifically to do insurance.  Instead, they’re talking about existing, proven offerings in the sales, marketing, and customer relationship categories – hardened heavyweights used in other industries for years.  The stuff that’s built to specifically do insurance, however, is still hobbled.  Clunky legacy AMSes with faux “cloud capability,” spaghetti-code back-ends and hyper-specialized, low-ROI features/customization?  Multi-raters that are just MS Access (LOL) front-ends for batched scripting and scraping?  These are stone tools, people, stone tools.  But, we shouldn’t blame the tool providers here – they are simply doing the best they can with what’s available to them.  We’re stuck with this duct tape and superglue until carriers find motivation to better enable the distribution channel.  Which leads us to our next observation…
   • Most carriers appear disinterested in altruistic enabling of the insurtech solution space, particularly for the benefit of the IA distribution channel (vs. their own underwriting departments).  There are likely several reasons for this lack of motivation, so let’s speculate a little: (1) Carriers are unsure how the IA and direct-to-consumer channels will ultimately co-exist and therefore opt to split their bets, (2) carriers lack a clear “what’s in it for us” ROI for better enabling IAs, and (3) there is no clear “one ring to rule them all” standard which carriers can adopt.  

While not exhaustive and by no means in-depth, the above is a broad-brush picture of what “technology in insurance” looks like from the independent agent’s seat. IAs are not idle by nature… they want to act, they want to do. To wrap this up, then, and build a bridge to part 3 in our series, what options to IAs have given the above environment?

I’d say the choice before IAs is fairly binary: (1) Wait for the insurtech space to mature a point where there are clear winners and leaders in a manageable number of business-critical categories, then invest. Or, (2) Seek the best information and guidance possible now, using it to define a technology investment strategy and timeline. This series aims to help those who’ve chosen the 2nd path – those who want to invest but not burn R&D dollars all willy-nilly on every new shiny object.

In the following articles I hope to offer guidance that will help IAs place smart bets. Stay tuned.