In my past several IIS innovation research articles, I challenged insurers to think big, really big, about how they might innovate with purpose to change the world—and, in doing so, drive tremendous growth. In this article, I address the flipside of that challenge: how to hone too many potentially good ideas into a manageable yet holistic set of innovation investments.

Executives often tell me that their problem is not having too few big ideas, but having too many. Great ideas are purportedly coming at them from every direction. They come from the front lines where the organization interacts with customers and contends with competitors; from technology and marketing wizards keeping a sharp eye on disruptive market trends; from senior executives and board members grappling with issues at the organization’s strategic horizon; and sometimes even from conversations with outside advisers like me.

Peter Drucker offered some of the best advice on how to handle so many potentially great (and possibly awful) ideas:

“Don’t subscribe to romantic theories of innovation that depend on ‘flashes of genius.’ Innovation begins with the analysis of opportunities. The search has to be organized and must be done on a regular, systematic basis.”

In the spirit of Drucker’s advice, here’s a four-step plan insurers can use to initiate a systematic process to uncover, screen, and scale the best ideas using an innovation portfolio approach.

Stimulate and Inventory Opportunities

Start by casting a wide net in the context of your company’s environment, purpose, strategy and capabilities. For example, hold scenario-planning sessions with senior executives and board members to explore continuous and disruptive opportunities and challenges that arise out of key strategic questions. Organize learning workshops to educate and gain insight from the wider organization about potential future scenarios. Engage teams at multiple levels to articulate both desirable and dangerous future histories for the organization. Sponsor innovation contests to uncover both continuous and disruptive ideas.

Continuous innovations offer incremental or faster, better and cheaper-type optimizations, such as shedding costs, reducing cycle times and generating incremental revenue. With sufficient license, numerous continuous innovation ideas can flow out of such discussions. Make sure you capture them.

Disruptive innovations rise to the level of game-changing and world-changing potential. It’s important to create space for these really big ideas. For example, stimulate potential organizational responses to thought questions like these:

• What are the most pressing protection gaps in the communities your company currently serves?
• How might those gaps evolve over the next several decades, especially for those who are the most underserved?
• What evolving technological capabilities might help narrow those gaps, especially as they continue to progress following the Laws of Zero?
• How might you apply these leading edge tools to better expose, model and mitigate meaningful slices of corresponding risks?
• What early lessons from innovators and early adopters around the world might be adapted to your community’s evolving challenges?
• What extreme competitive threats (that is, doomsday scenarios) might new entrants wielding these disruptive solutions pose to your business?

Categorize Opportunities Based on Investment Type and Impact

Next, categorize the opportunities according to investment type and a potential competitive impact. This will allow you to array all the ideas in the 3x3 matrix formed by the two categories, as illustrated in Figure 1.

Figure 1: Categorize Ideas Along Two Key Dimensions

Each idea can be categorized as one of three distinct types of investments:

• Stay in business (SIB) investments
• Return on investment (ROI) opportunities
• Option-creating investments (OCIs)

Categorization enables more suitable metrics and better comparative analysis. It also allows for strategic allocation of investment resources across categories based on organizational need.

SIB investments are for basic infrastructure or nondiscretionary requirements. They are common across companies. For example, large investors and regulators are promulgating a range of industry-standard Environmental, Social and Governance (ESG)-related reporting and compliance requirements that most companies will have to follow. The rise in cybersecurity challenges requires significant infrastructure enhancements. COVID-19 has driven significant investments to reconfigure built environments and enable remote work, where possible. SIB investments should be assessed on how adequately they meet regulatory or technical requirements while minimizing risk and cost.

ROI opportunities are company-specific offerings that are pursued for near-term financial returns. Most continuous innovation ideas fall within this category. Standard measures, such as net present value (NPV), return on equity (ROE) or other well-understood metrics are applicable for evaluating ROI opportunities.

OCIs are the earliest stage of innovation initiatives. Companies typically pursue them to explore business opportunities that might yield large returns in the future. They resemble financial options—from which the name is derived—in that they exhibit high risk and offer tremendously high potential returns but do not commit the organization to exercising the option. OCIs do not yield financial returns directly. Instead, they reduce uncertainties and build capabilities and learnings that could be translated into future ROI opportunities, if appropriate. All discontinuous innovation ideas should start as OCIs.

Next, make a high-level assessment of the idea’s future potential competitive impact.

Consider Wayne Gretsky’s adage about skating to where the puck is going, rather than to where it is. This dimension measures differentiation against what competitors will likely have deployed by the time an idea is launched. Once successfully completed, would the innovation have an advantage, be at parity or be at a disadvantage against the competition?

This method addresses two key screening mistakes. The first is evaluating an innovation idea against the organization’s current internal capabilities or product offerings, rather than the alternatives that customers will have in the market. The second mistake is evaluating the idea against current competitive offerings, rather than recognizing that competitors won’t stand still, either.

See also: When Incumbents Downplay Disruption...

Screen the Opportunities

Arraying opportunities in this analysis framework allows for simple heuristics to eliminate seemingly good ideas that fall outside of acceptable boundaries. For example, companies should not pursue opportunities that, once completed, are already at a disadvantage against the competition—no matter how much they improve upon current internal capabilities. There’s no reason to pursue OCIs that, no matter how advanced they are, would deliver only competitive parity, as new parity offerings would be unlikely to dislodge existing offerings or deliver outsized returns. Figure 2 illustrates how the analysis might look at the end of this stage.

Figure 2: Initial Screening

For the remaining opportunities, develop an initial sizing of investment levels and potential benefits according to each investment category. This allows for another level of screening, as shown in Figure 3.

Figure 3: Additional Screening Based on High-Level Sizing

For example, eliminate ROI opportunities that do not meet standard corporate hurdle rates. Eliminate OCI opportunities that do not exhibit extraordinary option value or require relatively significant upfront investments. Eliminate SIB ideas that do not adequately minimize cost and risk—be very skeptical of SIB opportunities justified by predicted ROI or OCI benefits.

Rebalance the Innovation Portfolio

No new set of innovation initiatives, no matter how potentially great, can be considered in isolation from continuing innovation programs. The final step of the screening process is to evaluate both existing and potential initiatives in the context of the overall innovation portfolio, and to rebalance that portfolio as appropriate.

The right prioritization and allocation across the portfolio depends on a company’s investment capabilities, competitive circumstances and strategic aspirations. For example, as shown in Figure 4, a market leader could gear its portfolio toward aggressive growth by enhancing its infrastructure, investing heavily in near-term profitable opportunities and developing a small number of disruptive options for furthering its competitive advantage.

Figure 4: A Market Leader’s Balanced Portfolio

In my experience, the right number of disruptive options is on the low end of the magic seven, plus or minus two. That’s because the limiting factor is senior executive attention, not investment dollars. Market leaders have a lot of money to invest, but no project with truly disruptive innovation can succeed without significant senior executive attention. At the same time, astute companies will not place “all their eggs in one basket” by having only one or two future-looking disruptive options. Instead, they hedge their bets by having multiple bets in place.

Other illustrative portfolio profiles are shown in Figure 5. Commodity businesses tend to minimize SIB investments and OCIs. Companies that are retooling might emphasize infrastructure and near-term investments and only minimally invest in future options. Underperforming companies tend to invest in programs that barely achieve competitive parity or worse and do little to prepare for the future in any of the three investment categories.

Figure 5: Other Illustrative Portfolio Profiles

***

At the end of this four-step process, companies should have a prioritized and staged investment plan that represents a coordinated enterprise innovation strategy and follows a think-big, start–small, learn-fast innovation roadmap.

Achieving an adequate understanding of the entire landscape of possibilities facilitates and encourages thinking big. Management of the innovation portfolio provides clear criteria for evaluating other big ideas as they come up. It also demands the discipline of starting small and learning fast in the pursuit of disruptive innovations that will shape the company’s future history.

I’m a golf nut. The Tournament Players Championship, the PGA Tour’s flagship event, was held recently in northern Florida. The weather was sunny and warm to start, but then a front blew through, carrying a day’s worth of rain and leaving behind it forty degree temperatures with cold north winds. During the rain delay, Shane Lowry of Ireland, one of golf’s global stars, was asked by a television interviewer how he was spending the downtime. Lowry, scrolling on his phone, said, “I’m on Amazon buying a stocking cap for tomorrow’s round, as I didn’t bring one.” 

Of all the options for stocking caps--tour reps doling out free gear, a massive pro shop at the course, several stores nearby--the winner was Amazon. Lowry, 34 years old, is a Millennial. I’m 58, a Boomer II, and would’ve gone the same route. Raise your hand if you would’ve at least started the hunt on your phone.   

The easier a thing is to use, goes the technology adage, the harder it was to build. “The Everything Store,” as Amazon is known, makes it look so easy we’re prone to take it for granted. But their portfolio of human, physical and especially technology assets is unrivaled. Taken together, the stuff just works, and stocking caps arrive before tomorrow’s frigid tee time. 

Two questions relevant to our work in insurance.

Question #1: When is the last time you talked to a human at Amazon? 

I’ve been a Prime member since 2010, and, aside from thanking delivery drivers whenever I see them, the answer here is never. And I’m a very satisfied customer.  

From the sale of their first book, Amazon designed their business to be as friction-less as possible, defined as people-less, i.e., zero human contact. “If an Amazon customer needs to speak with a person at Amazon,” said founder Jeff Bezos. “We view that as a fail.” 

Contact centers are a hot spot with our insurance customers, as resource costs are rising and manpower availability is shrinking. Smart automation is a winning strategy. Smart elimination of inbound contacts works even better.  

There are two components to contact elimination. The first is process-oriented, around defect reduction and execution. The majority of inbound customer contacts happen when something is wrong. What is your rate of negative customer contacts by event per unit sold? You should know this number, and it should always be trending down.

Disciplined process management can feel like bureaucracy to the inexperienced. But effective process is not bureaucracy; bureaucracy is senseless processing (as I described in an earlier article). 

The second component of contact elimination is informational. Click on Amazon looking for stocking caps, and everything you need is right there in front of you--an array of relevant choices, detailed product information, “customer reviews,” “answered questions” and delivery dates. (The one thing not there is an 800-number.)   

See also: What if Amazon Entered Insurance?

When Amazon introduced “customer reviews” in 1995, many people thought they’d lost their marbles, and book publishers threatened to pull product, believing negative reviews would hurt book sales. Amazon’s philosophy, then as now, is that the company doesn’t make money when it sells things; it makes money when it helps customers make purchasing decisions. So “customer reviews” won out, and more--not fewer--books were sold.  

What do your customers really want from you, and how does your digital presence deliver against those desires? Are your channels providing the information customers truly want and need? The answers have little to do with technology.     

Which brings us to question #2: What’s the name of Amazon’s CIO? 

The answer is, they don’t have one. Neither do Alphabet (Google), Meta, Apple, Netflix or any other digital-native firm you can name. Technology is implemented directly in business units. Though digital natives typically have the functional equivalent of a CTO, the role exists to coordinate platform and tool choices, orchestrating and enabling business success.  

The point is, IT isn’t a department. It’s a way of life. The business owns the customers, and so it owns the technology interacting with those customers. A corporate technology structure operating at one remove from customers is a distance too far. 

A recent study from PEGA reveals 68% of corporate technology executives want to move from “command and control” to more of an enabling, facilitating function. The same study reveals 48% of non-technology executives don’t trust corporate IT. 

Assuming a typical 80/20 technology budget split, we’re seeing more customers allocate the 80% for “lights-on” to corporate IT and the other 20%, the strategic portion, to the business. In this structure, corporate IT operates as a support function, like finance. Think: rapid evolution driven by the business, not the T-word driven by corporate IT.

Until recently, this kind of arrangement was unrealistic in terms of implementation. But new AI and smart orchestration technologies enable fantastic end-to-end customer experiences with legacy as-is, data where-at. 

The “institutional no” regarding new product- and customer-facing initiatives becomes an institutional yes.

If my kids want to figure out whether a band has made it into the mainstream, they ask whether I've heard of it. (Precious few pass the test.) Likewise, I know that an esoteric technology has hit it big when a national, non-technical publication writes a major feature about it -- and "no-code" technology just got its moment in the sun at the New York Times. 

The attention suggests it's time for insurers to take a hard look at the possibilities of no-code -- generating computer programs without the need for programmers -- which could streamline numerous business processes and slash costs.

I think of no-code as sort of the graphical user interface for programming. Back in the 1980s and '90s, we were all lectured about how we needed to become more computer-literate. We were even told that national competitiveness depended on our becoming more computer-literate than other nations. Then the graphical user interface came along, and computers became much easier to use. There are people who delve deeply into the capabilities of their computers and are wildly computer-literate, but the difference between them and the rest of us is far less than it was when those of us among the great unwashed would just stare at the C prompt and wonder what to do next. 

Although coding is far more complicated than just firing up my laptop, the same sort of progression toward simplicity has been going on for decades. Originally, coding was done in assembler -- strings of 1s and 0s that directly controlled the workings of a computer. Then compilers came along, letting programmers write in (still esoteric) languages that were translated into the 1s and 0s that controlled the computer. By the mid-1960s, the most powerful computers could handle operating systems, which made programming even easier. Operating systems migrated to minicomputers and then to personal computers in the 1980s. Object-oriented programming then arrived, meaning that programmers didn't have to write everything themselves for each app -- they could grab a calculator object or a clock object that someone else had written and just incorporate it into the app. Apps are now everywhere.

No-code takes programming to the next level, because it lets even us non-technical types do that sort of grabbing of objects to assemble apps that make computers do what we want them to do -- without having to wait for the IT department to have resources for us and without having to translate our current processes and our desires into some language that they can turn into code.

No-code also allows more fiddling -- and fiddling is crucial. At the moment, once you go through all the effort of producing a program, it's pretty well set in stone. But, with no-code, you're not only more likely to get things right the first time, because you know just how you want to operate, but you can test and reset easily. After all, you're doing this yourself, not via a steering committee of 12 people and a programming staff that may be many time zones away. You can keep fiddling until you get exactly what you need.

We've published a fair amount about no-code over the years -- the topic has intrigued me ever since I wrote about "code generators" for the Wall Street Journal back in the late 1980s -- and I certainly commend our articles to you, among them: Breakthroughs Via Low-Code and No-Code, Things Heating Up in Low-/No-Code and Unlocking the Power of No-Code. 

But I have yet to see in the insurance industry the sorts of easily understandable examples that are in the New York Times article, so I encourage you to read it, too. For instance, the Times writes about a beekeeper who set up a camera outside his hives and trained a no-code AI app to monitor the pictures and warn him if the dreaded Asian murder hornet showed up. An organization that gives small amounts of cash to mothers in Nigeria to encourage them to immunize their children used a no-code system to build an app that lets employees track that data while in the field. A marketer used a no-code system to track which keywords and titles got his clients' blog posts the most visibility in search engines and to predict what would work for future blog posts. He says results improved by a third.

Describing the capabilities of no-code, the Times writes: 

"'I could say something like, ‘Look up all the customer records from the last year,’ and it will go do that for you automatically,' said Charles Lamanna, Microsoft’s corporate vice president of business apps and platforms. He estimates that half of all office work could be automated with AI if there were enough developers to do the work. 'The only way to do this is to empower everybody to be a no-code developer.'

"Eventually the broader public will be able to create A.I.-enabled software in much the same way that teenagers today can create sophisticated video effects that would have required a professional studio a decade or two ago."

Now, none of this will happen especially soon. It's taken us 75 years to get from assembler to where we are today, so it's unrealistic to think we'll all be programmers soon. But, if the technology has caught the attention of an outlet like the New York Times, then I'd say it's worth at least getting acquainted with the technology, and maybe even exploring how it might be deployed in the field, where people are likely to have the sorts of painful but manageable itches that no-code can scratch.

Cheers,

Paul

Rapid technological advances and changing customer behaviors have accelerated change in many industries. COVID-19 has accentuated the pace of disruption. Insurance companies need to be ready to face these new challenges and take advantage of opportunities.

Insurers have always been data-savvy, but they will have to move faster than ever to keep pace with competitors and other industries. Given the higher volume and velocity, insurers must invest further in their capabilities to store and compute their data assets.

The journey begins with solving for data silos that have been created over decades and that inhibit Insurers. The presence of multiple legacy systems may elongate the transformation, so insurers must use automation to achieve speed to value and reduce costs.

Below are the key business imperatives that a modern-day insurer needs to enable to stay ahead of competitors.

The insurance sector of the future will look very different, and this shift has already started to happen across the value chain. Insurers are increasingly re-shaping their roles and value propositions, transforming from purely insuring risks to being data-driven and value-based.

"Data on Cloud" is the driving force behind much of this change and presents a solution for Insurers.

Opportunities for data-driven insurers

For insurers that are weaponizing data, there are tremendous opportunities. Here are key use cases that can be enabled:

See also: Thinking Big for True Transformation

Key decisions that affect the data cloud strategy

Here is a way to envision those decisions: 

Key Decision: Cloud provider lock-in vs. lockout

Recommendation: 

All public cloud providers are continuously enhancing their capabilities to keep up with customer needs. While most key capabilities are common, each cloud provider brings in a few unique capabilities. That’s why it is prudent for Insurance enterprises not to get locked in to one public cloud provider and be flexible.  

Evaluate available options against each architectural building block and pick the best available across the cloud platforms -- perhaps Snowflake for cloud data platform and Azure Synapse or AWS S3 for your data lake needs, especially around unstructured data.

Key Decision: ETL or ELT?

Recommendation: 

ETL – Extract, Transform and Load is used mostly in traditional architectures. As the ETL engine needs to transform a large amount of data, it usually hosts a complex logic and is expensive to run and maintain.  

ELT – Extract, Load and Transform is more suitable for cloud-based data platforms. It is about scaling and processing data in parallel without any impact on performance. A cloud data warehouse such as Snowflake separates storage from computing and allows both to scale as needed. This is especially cost-effective when you consider the amount of resource required to transform data in legacy systems before loading it.

Key Decision: Expert vs. citizen data scientists or both?

Recommendation: Every enterprise has different needs when it comes to AI/ML capabilities, although most  insurance enterprises are looking to enable citizen data scientists’ capabilities in addition to expert data scientists, to achieve the scale and speed that the organization needs. While enabling key features around model building and operationalizing, such as notebook, "API-ification" of a model, model refresh and release to production, the data platform must also be able to support the compute and storage needs for data science use cases. Snowflake's key feature of isolated loads provides separate computing power for each use case, and Auto scales up or down based on data processing volumes.

Key Decision: Data exchange vs. sharing

Recommendation: One of the key needs for building a true data culture is to enable smooth exchange and sharing of data sets. Datasets that are certified by one team can be used by other teams within the enterprise without spending time on the data prep and cleansing work. This facilitates faster insight generation while increasing accuracy. Third-party data plays a critical role in insurance, so, having a streamlined mechanism to procure, certify and publish third-party data is critical. Many insurers are setting up private a data marketplace to facilitate sharing, smooth integration with third-party data and centralized cost monitoring. Although most public cloud providers come with their own marketplace, Snowflake is a step ahead in this capability because of industry-specific data sets  and seamless integration with Insurance core systems using APIs.

Key Decision: Visualization with self-service and AI augmentation

Recommendation: Business intelligence (BI), visualization and analysis ultimately decide how successful your data initiatives are. Technologies such as augmented analytics combine machine learning and AI to assist data preparation, insight generation and explanation to augment how people explore and analyze data in analytics and BI platforms. Adding the power of natural language processing with data for faster and accurate diagnostic, predictive and prescriptive algorithms, we can empower business users to interact with data more effectively.

Key Decision: Optimized cloud

Recommendation: Success of data on a cloud platform does not only depend on building it right but also on how well it is optimized to run post-implementation for cost, performance and security. It is important to have the right governance in place to avoid sticker shock. Most cloud platforms provide some ways of monitoring, but having a solution customized to your organization is critical.

See also: 20 Insurance Issues to Watch in 2022

Why "Data on Cloud"?

Insurers need to think long-term while choosing a data platform, so it is recommended that they choose cloud-agnostic capabilities that are scalable, secure and at the same time very cost-effective. Generally, SaaS-based offerings can go a long way because they provide near-zero maintenance cost while providing enough flexibility to configure, manage and govern the data platform based on the specific needs of each insurer.

In summary, the recommendations are:

• Separate Computing and Storage — providing the ability to have unlimited computing power for isolated workloads while not worrying about storage costs.
• Auto Scaling — providing auto scale-up and scale-down based on data workloads, without manual intervention or any process delays.
• Third Party Data Exchange — providing seamless data integration with third-party data sources, whether through a marketplace or an API-enabled mechanism.
• Data Sharing — providing the ability to share data with internal and external stakeholders with the right access control mechanisms. 
• Data Integration — working with various tool sets, including cloud native connectors to integrate data from a variety of sources, such as core insurance products, mainframes, IOT and telematics.

Is it time to re-visit the methodology used by agents to determine replacement costs and re-construction costs? How confident are you that the real property replacement values that you develop are sufficient to either replace or rebuild? If a natural catastrophe hit your community, would you have the same confidence in your replacement or rebuild figures? As the increasing frequency and severity of natural disasters occur, one of the first questions in their aftermath concerns underinsurance.

In the aftermath of the Marshall Wildfire in Boulder County, Colo., the Denver press has continually explored these questions from the insured survivor’s perspective, but there has been little discussion from the insurance industry perspective. The purpose of this blog is to start a discussion on the continuing perceptions of underinsurance, especially after natural disasters, to determine if there are changes needed to better estimate the replacement costs on both personal and commercial policies that agents sell to our customers.

Insurance to value (ITV) is a basic concept that many insurance personnel learn at the outset of their careers. Although counseled that we are not appraisers, adjusters, agents and underwriters were provided with training and valuation tools, aka costimators, that seemed to work very well over the years. Conversations with many front-line agent/brokers assisting with their customer’s valuations find that these tools do not change in their basic structure and do not regularly leave customers underinsured. In retrospect, were they just lucky because they did not face many total losses, or did their continual efforts to monitor and adjust the replacement cost values (RCV) help achieve those excellent valuation outcomes.

Bottom line: This methodology and training has worked quite well over the past 50 years to assist customers with valuing RCVs. Many agents have occasionally seen competitor agents/companies use similar tools to undervalue required limits, which permitted them to underbid higher, more correct valuations. While this behavior still exists, it does not occur as frequently as it once did, and, in the new insurance marketplace used to occasional natural catastrophes, it presents another opportunity for the agent to advocate protection over lower prices.

Why does this subject matter to the author? When he was embarking into semi-retirement, he was asked to serve as a volunteer insurance consultant to the Waldo Canyon wildfire recovery team, Colorado Springs Together (CST), because he was not directly contracted with any of the insurers that faced 347 total losses and some additional damaged properties. Starting that volunteer effort, he was initially concerned about the potential for underinsurance based on other insurance catastrophes, rumblings in the local press and chatter in social media. This recovery process was a huge learning experience in many different aspects of how insurance policies deliver in a major natural disaster, but, happily, the issue of underinsurance did not prevent one of the most complete major wildfire recoveries experienced after a large urban fire.

The Waldo survivors, their builders and their companies navigated through the many different coverage “buckets” -- i.e., debris removal, law and ordinance, extended replacement, inflation guard and landscape allowances, which helped to close most rebuild gaps. In fact, the most extreme Coverage A dwelling underinsurance situation that he encountered (approximately 40%), the policy holder was able to close the gap with the above additional coverages and their company’s endorsement, which doubled the extended replacement and law and ordinance limits because the cause was a declared natural disaster.

What were the lessons learned from his CST experience? There are too many stories to recount in this short piece, but the following were most significant:

• A community-based recovery team that allows for many segments of the local community to participate in the recovery goal is an important attribute to a quick and complete recovery.
• The recovery team needs a strong leader to keep the team focused on the main task – rebuilding the neighborhood.
• A community and team focused on minimizing politics, controversy and adversarial relationships among stakeholders is a critical component of a solid recovery.
• The encouragement of the survivors to better understand their policies and limits as well as the insurance claims process facilitates quicker resolution of any outstanding issues.
• Local economic conditions can be a positive driver of the recovery. The Waldo recovery occurred during the end of the 2008 recession, so labor and supplies were more readily available to the recovery.

The recovery team had a self-imposed one-year recovery time limit because virtually all the pieces for the Mountain Shadows Neighborhood recovery were in place by the end of the year. Survivors, neighbors, the city and team members were pleasantly surprised that, despite the early alleged obstacles, an amazing outcome was collectively achieved.

See also: Dramatic Shift in Underwriting Ahead

After such a positive recovery experience, he followed many other wildfire recoveries both in Colorado and other areas in the U.S. Interestingly, he is not aware of another public-private recovery team approach that resembled what was done here in Colorado Springs. In most cases, it appears that recoveries are driven by the local governments, which tend to be slower due to the more bureaucratic approach that government must take to conduct all of its business. Why does this matter in a discussion of underinsurance? Slow recoveries exacerbate the effects of underinsurance.

As Boulder County faces its recovery from the Marshall Fire, the topic of underinsurance seems to dominate its early recovery preparations. Certainly, the recovery challenge is more than three times greater than the Waldo recovery, which will certainly further slow the recovery based solely on the scale. Without being embedded in the Marshall recovery team, it is difficult to fully access the extent of the underinsurance at this time, although there are some early warning signs of potential concern:

• The limited supply of builders needed to rebuild all the destroyed residences may be a driver of higher replacement/reconstruction costs;
• The unprecedented increases in the local building costs over the past two years may not have yet been incorporated into the costimator valuation processes;
• Initial indications of added building code requirements needed to rebuild are very concerning and would not have been included in any costimators;
• Debris removal delays will slow the actual reconstruction;
• Unusual supply chain challenges are arising;
• Popular insurance advertising promotes price competition vs. coverage adequacy;
• Other natural catastrophes compete for resources; i.e., Kentucky wildfires, California wildfires, Louisiana hurricanes, etc;
• Rebuild permitting processes aren't streamlined; and
• There is the continual reminder of underinsurance, which encourages survivors to think their recovery will be impossible.

It is critical for the insurance industry to take the lead in starting to diagnose any shortcomings in the procedures and systems for valuing properties, as well as best practices to streamline recoveries. As we know, insurance coverages/limits may differ among the homeowners policies that different insurance companies write. Perhaps, it is also time to realize that there may be different valuation needs for natural disasters. Of course, the biggest hurdle is to overcome the average consumer’s belief that “it can’t happen to me."

What can front-line agents do to start or aid this discussion? Here are some initial steps:

1. Identify either personal or commercial accounts where you think whatever costimator being used may either under- or over-insure.
2. Identify any differences within your agency on how real property valuations are done and re-train as necessary so there are consistent processes.
3. Check with local claim departments and construction businesses to determine what the going rate is to build in your community/region.
4. Double check a sampling of real property valuations periodically to make sure they are responsive to local building costs and national inflation and supply line conditions.
5. Refer any valuations that are either over- or under-valued to the insurer and ask them to check to make sure that they agree with your valuation, leading to continual conversations regarding insurance to value.
6. Start tracking any variations so valuation adjustments can be made as necessary.
7. Share any variations in values with your local agency associations so the magnitude of any underinsurance can be assessed. This is especially important in locations more frequently visited by natural catastrophes.

Agents can make great differences for both their customers and the industry. In the meantime, if you have examples of under- or over-insurance using the various costimators provided by your companies, please share them with me at jeputnam@aol.com.

This article first appeared on Bill Wilson's blog. 

Despite optimism at the outset of Q4 2021, property and auto insurance shopping trended below 2020 levels by year’s end, according to the results of TransUnion’s latest Personal Lines Insurance Shopping Report.

While the auto insurance market remained suppressed throughout 2021, the housing market had been red-hot until year’s end, when it dropped into negative territory for the first time in more than 18 months. The findings reveal that in Q4 2021 auto insurance shopping was down an average of 13%, while property insurance shopping dropped an average of 3.4%, compared with the same period in 2020.

Several factors cooled off the property market, including the resurgence of COVID-19, as well as rising interest rates and rent prices. Shopping rates had been elevated well above normal levels, and this change may have been more of a correction following a solid year.

Other findings in the study showed that record-breaking prices for both new and used vehicles deterred many consumers from auto shopping. At the same time, insurance premiums have continued to rise in response to increasing severity trends, prompting more consumers to switch carriers, according to a recent report by J.D. Power. 

What does this mean for 2022?

COVID-19’s omicron variant served as a harsh reminder that even near-term events are challenging to forecast. Another factor is the increase in severe weather events in December. The TransUnion report notes that damages inflicted by tornados pushed the U.S. past its predicted $105 billion in weather-related losses. The fallout is likely to include generally higher premiums and lower marketing budgets, which will reduce consumer engagement—a critical element of sales.

Despite this volatility, some projections can be offered. For example, auto lending to non-prime customers will likely grow in 2022, but vehicle inventory may affect overall originations.

See also: Property Claims: It's Time for Innovation

Also, while the housing market cooled, homeowners are still likely to take advantage of their equity gains by selling and downsizing or renting. Millennials will continue to be the most active in migration and home purchases. The report notes that there are more Black and Hispanic households within this group than in older generations, and homeownership among younger Hispanic people is growing especially fast. 

As Millennials mature and have increased earning power, they face unprecedented and unpredictable financial, environmental and social changes. Insurers should take a partnering approach by meeting people where they are in their current financial pictures and by offering flexible solutions.

To learn more, please visit TransUnion’s latest Personal Lines Insurance Shopping Report.

The U.S. market is ever-changing, with new niches expanding continuously and creating opportunities for insurers. But the IT systems of the past hold back coverage providers from expanding their product offerings.

With the increased use of digital capabilities during the pandemic, ransomware attacks have hit a record. In the U.S., the volume of ransomware attacks surged 185% in the second half of 2021, compared with the first half, while the average cost of recovering from a ransomware attack stayed at a staggering $1.9 million. The global cyber insurance sector is expected to hit $36.85 billion by 2028. Insurers need to be nimble to help clients deal with cyber attacks, including the expected surge in premiums. 

Catastrophic coverages are seeing major changes, too. In the U.S., Hurricane Ida was last year’s costliest natural disaster, with overall insured losses of $36 billion, and scientists expect extreme weather and disasters to continue to increase in 2022. In the past few years, extreme events have outpaced experts’ predictions, turning climate change into one of the top emerging risks. Experts anticipate that the P&C sector will see the highest growth in written premiums in the past 18 years. 54% of Americans say they cannot afford disaster debt, and almost half of businesses are not able to reopen after a natural disaster hits. To tap into this expanding niche, insurers need to think about leveraging flexible and agile systems. Speed, cost and flexibility are needed now more than ever.  

New risks need new systems

But many insurance companies are still leveraging systems that are primarily serving the back office. These monoliths rely on inflexible databases and have become obese systems that are difficult and costly to change. Developers have added custom capabilities and functions for each client, ending up with large code bases built by accident, not design. This has created more work for coverage providers, which now have to deal with heavy technology to develop and launch products. The downside of the monolithic architecture lies in the insurers’ inability to create products that serve expanding niches, such as cyber and climate insurance.

To maintain competitive pricing when entering niche markets, insurers have low-cost digital transformation in mind. Achieving this may seem impossible, because speed to market is key when trying to stay ahead of the competition. Insurers can balance both, by turning their attention to vendors providing platforms for curating insurance products. Software-as-a-Service (SaaS) systems are both speedy and flexible. They allow providers to customize their products without any coding or advanced technical knowledge. Insurers can save both time and money by adopting such systems and focusing their attention toward expanding their coverage umbrella.

It’s time to get personal

Personalized insurance products will be the winners in each niche market. Customer demand for usage-based insurance is on the rise: Consumers expect to have the ability to calculate premiums based on what they are using in real time. SaaS-based systems can facilitate these features 

The user-friendly interface of SaaS systems allows insurers to build products that comply with back-office requirements and fulfill customers’ demand for personalization at the same time. In this way, insurers can keep up with the changing coverage market and offer the targeted services consumers want. 

See also: Does P&C's Future Lie in Datasets?

Progress doesn’t have to be pricey

Having the right systems in place is crucial for entering niche markets with low-cost products. If insurers are not thoughtful and progressive with their innovation practices, they can end up spending millions on IT solutions that include features they do not even use. With SaaS systems in place, insurers only pay for the tools consumed.

Smart insurers will capitalize on the opportunities offered by niche markets, especially in the cyber and climate sectors. To stay ahead of the curve, insurers need to understand the importance of exploring new platforms. Monolithic systems are no longer a viable solution for developing flexible and agile insurance product lines: The future of insurance lies in the adoption of SaaS systems, and the forward-thinking insurer knows that.

Ours is an accidental industry in many ways. Most of us end up in the industry unintentionally; very few grew up with the aspiration of getting into insurance. Yet, once we discover the industry, most of us tend to stick around.

The accidentality of the industry doesn't stop with individual players; it expands into businesses. An accidental salesperson falls in love with the industry, finds success, goes out on their own, hires a couple of (most likely) "accidental" team members and wakes up one day with an accidental business.

Because their evolution into the industry and a business of their own is accidental, there isn't nearly enough thought given to the business model itself. They adopt the typical model they have witnessed along the way, other people's "accidental business model." 

It’s like déjà vu all over again

Your business model is the foundation on which everything rests. It determines your ability to bring in new business. It determines your ability to hold onto the business once you have it. And it determines your profitability along the way.

As the industry evolves and becomes more complex, it’s more critical to rethink your business model to ensure it is healthy, sustainable, profitable and intentional. Because nothing is good or bad except by comparison, let’s think about the typical business model that we see in most agencies today.

What you sell

Whether you own the agency or not, what is it that you're selling? Before you answer this, how would your typical prospect and client answer this question on your behalf?  

The answer is that the typical agency focuses entirely on selling insurance. Whether it's medical, dental, life, disability or any other type of insurance, too often the only thing being sold (different from the stuff you give away) to clients is an insurance policy.

The threat this poses – You have no control over the product you’re selling.

The adjustment to make – Sell your ability to solve problems. Instead of focusing on the product (insurance, benefits administration technology, compliance, etc.), focus on the problem you solve with those products.

See also: A Future-Proof Operating Model

How you sell

Now, think about how you earn new clients. What does your sales process look like?

Most agencies still fall into the trap of showing up at renewal, asking for a chance to quote, putting together a spreadsheet, going through a capabilities dump (the value-added services you give away) and praying the other guy/gal missed something. It comes down to competing with a spreadsheet.

The threat this poses – You are offering the same spreadsheet and list of additional services as everyone else, making you "just like everyone else."

The adjustment to make – Instead of showing up with pre-determined answers (aka spreadsheet and capabilities presentation), start your sales conversation by evaluating what problems a buyer may have that are hurting their business.

To whom you sell

Who are you targeting as you look to put opportunities in your pipeline and grow your business? Who are you willing to accept as a new client?

Way too often, the answer is, “anyone who can fog a mirror.” We tend to fall into the trap that any new client is a good one.

The threat this poses – You end up with too many clients who either can’t afford to pay you what you’re worth or who don’t appreciate what you offer.

The adjustment to make – Define your ideal client, both demographically and psychographically, then use that profile as a filter before allowing anyone in your pipeline.

How you get paid

Once you have a new client, how are you typically getting paid for the work you do on their behalf?

Your compensation is typically determined by the commission schedule the insurance carrier builds into the insurance policy.

The threat this poses – Someone else is determining how much you get paid.

The adjustment to make – Be sure you are the one determining how much you need to be paid on a client and add in fees if necessary.  

How you protect revenue

We already talked about earning a new client, but how do you ensure you retain those clients? How do you renew their business?  

I’m guessing you may say something about the level of service you provide. That’s funny.

It comes back to the spreadsheet. The way you earn a client is how you're going to retain them. Said another way, you will lose every client the same way you acquired them in the first place. Your sales process trains prospects and clients on how to buy your services.

If you've competed for that new client based on the spreadsheet, don’t be surprised when they invite your competitors to quote their business at renewal time. After all, you taught them that. You simply reinforced the accidental industry model.

The threat this poses – You become too vulnerable at renewal time, once again depending on something you don’t control. 

The adjustment to make – Have a mid-year planning session with the client that focuses on the various problems you are helping solve. Of course, this follows the adjustment we suggested above in the “how you sell” section.

Ensuring profitability

Last business model question, going, literally, to the bottom line. How is it that you guarantee profitability on any particular account?

The typical response here is, “Huh?” Accidental agencies don’t think about profitability, at least at the individual client level. They go out and write as much business as possible without evaluating whether this is a client relationship that can be profitable.

The threat this poses – You are losing money on a significant percentage of your clients. In turn, your highest-paying clients are used to subsidize your least-paying clients.

The adjustment to make – Establish fair compensation for each client based on the services you provide to them.

See also: New Operating Model for Insurers (Part 2)

Is there really a choice?

As you think about your answers to these questions, does it make you a bit uneasy? Let’s put the answers to the questions into overall descriptions and see which is the right business model for you, an accidental business model or one that is more intentional.

With an accidental model, you . . .

• don’t control what you sell
• have no differentiation from your competition
• accept any new client, no matter how small or misaligned
• depend on someone else to determine your value, and
• are unprofitable on a sizable percentage of clients

Compared with an intentional model in which you . . .

• sell based on your ability to solve problems
• are differentiated (by process, focus and impact) from your competition
• are selective about who you are willing to work with
• establish your own level of compensation based on the value you deliver, and
• ensure profitability on every client.

At best, the accidental model is antiquated; we just don't recognize that fact until we break it down. It is a model that effectively leaves your business in someone else's hands.

If you feel as though everything about your business model needs to change, don’t allow yourself to be overwhelmed. At the same time, for the sake of your future business, commit to getting started.  

Decide what is it about your current model that scares you the most and start there.

The insurtech industry is hot with data gathering, analytics, automation and all-things digital. And for good reason. As more people prefer online experiences and are accustomed to intent marketing practices that “know” your online moves, it’s inevitable that carriers will also know and mine digital movements like purchasing, enrolling and filing claims. Does all this digital transaction insight and big data mean that human touch or consult has gone by the wayside? Not at all. In fact, all these seemingly impersonal digital insurance transactions further underscore the criticality of personalization. The transformative opportunity is to pinpoint the exact moment of need in the insurance buying and filing experience.

With increasing integration connections to sources of customers’ information as well as investing in analytics, carriers are poised to create the perfect blend of automation and personalization. It’s critical that a carrier consistently proves that they understand the customer and can streamline their needs. It all hinges on clearly understanding the customer’s journey. 

Carriers that understand the customer’s motivations for buying insurance and filing claims will reap the benefits of the nexus between automation and personalization. It’s short-sighted to think of the customer as a single-touchpoint transaction, such an enrollee or a claimant for a single product. Rather, they are on a life journey that includes a variety of experiences where insurance can assist. Understanding this balance creates opportunities for customer loyalty to, and engagement with, a carrier. 

The Journey of Employee Benefits

Take employee benefits. This journey begins when the employee enters the workforce and ceases on retirement or their death. Each employee begins with enrolling in benefits, continues the journey through life experiences that cause them to file for claims, such as short-term disability or paid family leave. As the employee’s life and career matures, they may make further investment in benefits. This journey with employee benefits typically ends with accessing retirement plan benefits. Upon death, their beneficiary files for the death benefits from the employee’s life policy. 

Understanding the employee’s journey is the first part. The next is to home in on the employee’s motivations to consider each employee benefit through that journey. Savvy insurance carriers understand this. 

See also: Why Customer Journey Mapping Is Crucial

Enrollment: The Journey’s First Step 

Because an employee is excited to embark on their career, they are less focused on employee benefit enrollment upon hire. Creating an easy, informational enrollment process is key. Carriers can use their decades of data coupled with connected census and policy information to create an automated yet personalized experience. Layering in AI-enabled informational touch points for the typical questions an employee raises during enrollment adds the right level of human intervention. Auto-enrollment in certain benefits such as 401(k) retirement or low-cost life insurance is even better. At this juncture, the carrier has provided an automated but personalized experience. 

Claim Filing: The Journey Continues

When it’s time to file a claim against the employee benefits, typically years after enrollment, the employee likely experienced a dramatic event in their life. This could be exciting like welcoming a new child or enrolling in a graduate program or stressful like an illness or workplace injury. Now, the employee’s motivation is to avail themselves of the benefit quickly so that the benefit assists them with navigating the life experience. But, due to the complexity of the employee’s life change, the employee likely has questions that need answering quickly and easily. At this point in the journey, carriers must provide the human consultation, the empathy and critical thinking necessary to assist the employee through the benefit-filing process. 

At this stage in the journey, automation expedites the filing process, including surfacing the relevant and eligible customer products and employee census information. In the example of the employee giving birth, personalized automation should quickly present short-term disability, paid parental leave or FMLA, or trigger health insurance requirements like adding the baby to the policy. When a carrier delivers a personalized but automated approach to the employee’s life situation, the employee gains a sense of understanding of their specific wage replacement and job-protected benefits, or their out-of-pocket costs.

Industry data is clear that online claim filing is trending, but the majority of claimants still prefer personal communication when filing and questions answered by humans. Optimal insurance experiences are often found when humans and machines work together. Integrating transfer points between technology and carrier staff along with real-time data access is key to creating a balanced approach.

Additional Benefits: Advancing the Journey

Later, as the employee settles into their career and begins to further consider their finances and potential additional benefits, carriers again have an opportunity to leverage the employee’s motivation. This is an opportunity to delight employees by understanding this stage of their journey by automating information, or even enrollment, around retirement benefits, family care leave and life insurance.

Even at this stage, though, carriers must remember that customers often don’t understand the complexities of insurance, such as how the benefits available to them might meet their personal goals, risk adjustment and what goes into quoting and underwriting. Employees are primarily focused on their personal life advancement, not details of their insurance. Therefore, it’s essential that benefits are characterized in a way that is relatable to a customer’s stage in their journey. This includes not only accessing information about the benefit (online versus a consultative broker or HR professional), but actually accessing the benefit itself. Auto-enrolling new hires into a company 401(k) plan was once controversial; now, it’s deemed as a brilliant and helpful way for employers to ensure employees’ financial future. Automation such as auto-enrollment at certain stages of an employee’s journey provides incredible value. Auto-enrollment at certain points in an employee’s journey is well worth considering, especially for long-term disability or paid family leave when an employee reaches a certain tenure or adds a family member to insurance.  

See also: Why Cyber Strategies Need Personalization

Cashing Out: The Final Stage

Finally, filing for retirement or life insurance benefits comes from an obvious different motivation than filing for benefits around an illness or family-related life event. With these end-of-career benefits, carriers can again easily automate to expedite benefit decision and payment. Connecting with fraud detection sources allows further acceleration of benefit processing. 

Chatbots and AI can be a bridge to human interaction as well as provide a 24/7 convenience. When used well, AI can manage high-frequency inquiries in a way that feels natural to users. By now, customers expect the carrier to have information about them readily accessible. As the “conversation” progresses, AI can use workflow to route the claimant to a trained human resource professional.

The Market Is Changing, but Human Basics Remain

This increase in the use and demand for relevant and pinpointed insurance requires that carriers rise to the occasion. By focusing on the customer journey, not the insurance product, insurance carriers have an opportunity for life-long relationships with customers. Carriers can apply automation and ecosystem connection to adapt to rapidly changing market expectations and create positive insurance experiences by leveraging technology-enabled information, as well as human consultation and empathy. This benefits customers and carriers alike. 

In this new era of insurance, carriers can replace siloed, product-focused and human-heavy interactions with state-of-the-art, responsive personalized ones. The result is a contemporary and financially beneficial experience. In doing so, carriers provide easy access to needed benefits and helpful services, thus creating loyal customers for years.

Digital transformation is difficult because it is as much a business change management issue as a technical challenge and often requires a truly compelling event to propel such a sweeping project. The COVID-19 pandemic caused such a compelling event in employee benefits.

A recent Zurich Sigma study of life, accident and health insurance (Swiss Re sigma 3/2021 - World insurance: the recovery gains pace) projects an increase in life protection insurance premiums such as disability, hospitalization and critical illness. At the same time, the nature of work is changing based on the global need to quarantine during the height of the pandemic. In a recent Bloomberg article, Prathima Choudhury, a Harvard School professor and expert on remote work, says, “We will probably in 10 years stop calling this ‘remote work.’ We’ll just call it work.” 

Employee benefits insurers seek to enhance their operational processes, provide better customer service across their customer base as well as within their partner ecosystem and quickly bring new products to market. Addressing these goals requires a range of digital capabilities including software-as-a-service (SaaS) platforms that remove constraints around location and physical access; smart process management based on machine learning; better analytics and modeling tools; and user experience options that go beyond the traditional interface.

Making 'Work from Anywhere' Possible 

Spurred by the pandemic, there has been a slow move toward “work from anywhere” models in the workplace, especially in the software world, but for a variety of reasons many companies have been slow to change. The employee benefits business is well-suited to this model due to the virtual nature of the product/service model and the recent advances in knowledge worker tools. However, some critical issues must be addressed.

Most insurers are still struggling with core insurance processing systems that are decades old and, in many cases, built before the internet became an essential element of commerce. Those systems were designed to support one product and aren't capable of enabling service-based products such as government-mandated paid family leave and new business models such as voluntary worksite products. 

Employee benefits carriers have done an admirable job wrapping their homegrown legacy systems with workflow software and robotic process automation (RPA) tools to provide some levels of digital process management and customer service. Nevertheless, the result is usually awkward to use and manage. Also, these hybrid systems are still mostly on-premise, requiring a physical data center or expensive custom hosting. Insurers tend to cling to these older systems because they have decades of insurance process and product expertise layered in.

The good news is that new SaaS systems and a wide variety of new technology from insurtechs and traditional software providers can meet the needs of the next-generation carrier. Here are a few key areas where new technology is helping:

• Modern SaaS core systems: There are core systems available today that serve the employee benefits market that were either “born in the cloud” or have become “naturalized citizens.” They go beyond basic hosting to leverage the natural advantages and inherent capabilities of the SaaS model. These systems tend to interoperate better with other SaaS-based systems used by brokers, benefit administrators and HR systems. The systems are capable of supporting the new, broader definition of employee benefits products.
• Machine learning: Employee benefits is one of the most complex insurance segments, with a B2B2C business model that has multiple value chain partners providing services to the employer, the employee and, in some cases, each other. Products have many options and are often heavily configured by the broker and presented in mixed portfolios across multiple insurers. Machine learning, which has been heavily employed in claims fraud and underwriting risk scoring models, is now being deployed in transaction segmentation, automated workflow and advanced user experience support.
• Rethinking the user experience: The employee benefits ecosystem has a lot of stakeholders, including the insurer, brokers, benefit administrators, consultants, enrollment firms, employers and, of course, the employee. That employee often gets the least attention in the broader user experience discussion. If all goes well for them, they have the least day-to-day interaction with the ecosystem, with the employer acting as the “customer.”

The introduction of voluntary benefits and workplace selling models has changed the dynamic. Employees have more options under their direct control when making plan choices, and some of those options require more understanding of the benefits and their interaction with others. For example, an employee needs to understand what combination of HSA funding and voluntary accident, hospital and critical illness insurance provides the best protection at the best price, all of which goes beyond their major medical insurance and company paid disability plans. 

See also: Thinking Big for True Transformation

Employees need help in making these decisions, but insurance carriers realize that too much information can often be as bad as too little. The goal becomes to create a balanced user experience where employees get the information they need without being forced down a narrow path of a few standard choices. The same approach of balanced user experience applies to the claims process, where employees want as little friction as possible while still getting the full benefit they deserve. Using machine learning, purpose-built core systems and the right digital connections, a user experience could be as simple as a text from the insurance carrier informing the employee that their $10,000 claim payout was just deposited into their account and enabling issue resolution options as simple as a reply text to be connected to a case worker.

Employee benefits insurers have an opportunity to gain real competitive advantage and better serve their customers, and the pandemic has created the compelling event to make it happen.