A Word About Culture: Part One

A recent edition of Harvard Business Review carried an article entitled, “The Hard Truth About Innovative Cultures”. At first, we thought it was about Greek yogurt. Then we read it and learned it’s about the five characteristics of effective corporate cultures. Here they are:

  1. Tolerance for Failure but No Tolerance for Incompetence
  2. Willingness to Experiment but Highly Disciplined
  3. Psychologically Safe but Brutally Candid
  4. Collaboration but with Individual Accountability
  5. Flat but Strong Leadership.

This is the first in a series of five posts in which we will examine each of those characteristics from the perspective of our own organization.

Fine Lines

Any discussion about the relationship between failure and intolerance has to start with distinctions and balance. The article says this:

A tolerance for failure is an important characteristic of innovative cultures … And yet for all their focus on tolerance for failure, innovative organizations are intolerant of incompetence.

To strike the appropriate balance, we tend to distinguish mistakes from failure. We tolerate honest mistakes resulting from clear thought, sincere intents, and unforeseen eventualities. We don’t tolerate failures resulting from thoughtlessness, carelessness, or recklessness. And we take to heart a conversation we once heard over lunch at an industry conference:

Person 1: I heard one of your people made a huge mistake.

Person 2: Yep. It cost me $50,000.

Person 1: Did you get rid of the guy?

Person 2: Why would I do that? He didn’t piss off the client. And I just paid $50,000 for his education.

As far as we’re concerned, failing to try is a bigger indicator of incompetence than making an honest mistake in a sincere, well-thought-out effort. And lessons hard-learned are often the most effective.

A Calculated Gamble

There’s no such thing as perfection. We neither demand it nor expect it. But we do expect conscientiousness. We do expect honesty, integrity, and thoughtfulness. And we do expect people’s best efforts, even as we recognize anyone’s best efforts may fall short on occasion. It’s the gamble you take in business, in hiring, in being willing to trust and observe before you judge.

That approach has worked for us since 2001. And it’s kept our culture active, even though we’re not in the yogurt business.

Changing our approach now might be a mistake … or worse.

Technology Emerges … Unless it Doesn’t

We came across an article the other day on a site called, The Frisky (we’re not making that up). The article was called, “11 Emerging Insurance Technology Trends to Watch in 2019”, and it featured, wouldn’t you know it, an infographic. It also made this prognostication:

$2 Billion will be invested into emerging insurance technologies known as “InsureTech” … to completely disrupt the way consumers buy insurance and initiation [sic] claims.

That statement stands in stark contrast, of course, to the oft-stated contention that the insurance industry operates in the technological equivalent of the Stone Age. So, where’s the middle? And is there truth in it?

The Truth is Where You Find It

The fact is the insurance industry doesn’t exist to introduce or pioneer technology. But you’d never know that from reading most of the industry literature. That would have you believe driverless cars, programmed with nanotechnology and controlled by mobile devices, were being monitored by drones carrying wearables, running applications from the cloud, connected to the Internet of Everything and fulfilling Richard Brautigan’s promise that we’ll be “All Watched Over By Machines of Loving Grace“. Not so much.

As implausible as it seems given the fact that the speed of consumer adoption of technologies far outpaces entire industry adoptions of technologies, even the retail industry is having trouble adjusting to mobile. You can create technology. But that doesn’t mean it’s ready to emerge. You have to solicit the input of the people for whom it’s intended. You have to keep it up to date and functionally capable. You have to monitor its usage. And you have to resist surprise and frustration if the tried, true, and deeply entrenched do not go gentle into that good night — especially since practicality has a considerably longer shelf-life than sensationalism.

Consider this: When’s the last time you read an article about the number of insurance companies still working on green screens? Many insurers still do. When’s the last time you heard anyone admit to still using a dial-up modem? Some people still do. When’s the last time you heard anyone in any industry say anything other than their technologies were emerging, disruptive, or innovative? And why do you think that is?

It’s because talk is cheap. It’s also less expensive and more practical than chasing the rainbow and betting the ranch on emerging technologies.

Practical Is As Practical Does

And speaking of practical, is any industry more practical than insurance? Insurance has to be practical by definition. If you’re in the business of reserving the premiums of your policyholders against potential losses, what else could you be?

Yes. Like every other industry, insurance needs to keep its eye on emerging technologies. But its first look has to be at reliable ways in which to serve its constituents, minimally risky ways in which to deliver its products and services. If insurers spent their time and attention pursuing emerging technologies, how much would be left in which to satisfy and retain their policyholders?

We love our clients. They’re in the insurance business. That’s why we’re in the technology business.

For our clients, technology will continue to emerge as it can.

The Future of Insurance

With everyone from consultants to analysts, from trade publications to software vendors, from insurtechs to FOMOs writing about the future of insurance, we started thinking we might be conspicuous by our absence. So, in the interest of living on the bleeding edge of insurance prognostication (don’t worry … we have lots of styptic), here are our modest contributions to the burgeoning breadth and bulk of literature on the topic.

Prediction #1: Some Stuff Will Change

Given the evolving nature of technology and the ever-increasing rate of change, we can expect a veritable plethora of things to become increasingly prevalent. With IoT and Big Data bombarding us with more and more information for which we have to try and find uses, we’ll figure something out. With IoT and Big Data feeding telematics devices and precipitating usage-based insurance, we’ll see more individualized rates as standard personal-lines products, in particular, become ever-more commoditized. And with GPS and insurtechs breeding the pursuit of leisure in driverless cars, there are sure to be emerging market opportunities in life insurance, if not funeral insurance.

Prediction #2: Some Stuff Will Never Change

Given the immutable nature of an industry as highly regulated yet non-standardized as insurance, technology will never be adopted as fast as the consultants, the analysts, the trade publications, the software vendors, the insurtechs, and the FOMOs say it will. State DOIs and the NAIC will reduce the number of regulations by which insurers must comply right about the time Pee Wee Herman establishes the first colony on Mars. Implementations will still have to be conducted deliberately, carefully, and expertly. And software will still need to be tested to make sure it works as well as the consultants, the analysts, the trade publications, the software vendors, the insurtechs, and the FOMOs say it will.

The Moral of the Story

The ball on which we’re all supposed to be keeping an eye is the present. We can keep the other eye on the future, of course. But there’s work to be done right now. The prognosticators will continue to make a living by prognosticating. If there weren’t a market for it, they wouldn’t do it. But the rest of us in the industry still have to do what we do in the best interests of policyholders, or we’ll all be out of business.

Who’d have thought ignoring The Next Big Thing might be the future of insurance?

The Hamster In the Black Box

Every once in a while, we like to take a look back at the insurance industry’s technical literature. It reminded us that, at a time in the not-too-distant past, it was impossible to pick up anything — trade publications, marketing collateral from vendors, reports from the analyst community, et al. — without reading about Service Oriented Architecture (SOA). It seemed as if every developer and his dog were employing and touting SOA to the nth degree.

Our exploration also led us to some architectural relatives of SOA, which we’ve listed here, in part, with their respective definitions:

  • SOA. Service Oriented Architecture is a style of software design that provides services (discrete units of functionality, accessed remotely, acted on and updated independently) to various other components through a communication protocol over a network.
  • SAP. Service Application Programming. We’re going to leave this one alone.
  • SOAP. Service Oriented Application Programming is a clean approach to software development that combines architecture, application development, and protocol programming.
  • SOUP. Service Oriented Utility Programming describes the attempt to program utility into application development; that is, to create a solution for which there is an existing problem, rather than vice versa. Utility, in this context, is sometimes used synonymously with objective.
  • SOUP TO NUTS. Service Oriented Utility Programming Tapping Objectified Neurons Under Total Secrecy is an approach to enterprise programming that’s so covert not even the people who know about it know about it. SOUP TO NUTS was also known by the abbreviation TCP: The Complete Package.

We certainly found our discoveries amusing, if not terribly enlightening. But it caused us to think a little more deeply, particularly when we found a reference to black box in reference to SOA.

What Difference Does it Make?

The reference we found defined black box as:

a device, system or object which can be viewed in terms of its inputs and outputs (or transfer characteristics), without any knowledge of its internal workings. Its implementation is “opaque” (black).

That prompted us to wonder about what seems to us to be the relative unimportance to the user or the consumer of any specific technology and/or its nature. To be more specific, we wondered what our prospects might say if we asked this in one of our introductory conversations: “If our system comprised a hamster, running on a wheel in a black box — but it was easy to use, processed your business efficiently cost-effectively, and improved your results — would you care?”

We never ask that question, of course. And we’re quite proud of our technology, its facility, and its adaptability. But it did make us think about the possibility that all of us might be better off if we focused on objectives and outcomes, rather than on techniques and technicalities.

If we did that, decision-makers might be able to view all technology as just a hamster in a black box.

Changing the Subject Won’t Help

We firmly believe in the notion that anything is possible. If a person puts his mind to something, or if a group of people commits to working together to accomplish something previously unaccomplished, we’re among the first to believe it can be done. But believing anything is possible isn’t the same as believing everything is possible.

By the same token, common wisdom has it that the shortest route to any destination is a straight line. Along similar lines (no pun intended), the shortest route to the resolution of any question, particularly a business question, is a straight answer.

Presuming we’re all in agreement on those two points (why wouldn’t we be?), where does that leave us? We don’t know that we can answer for everyone. But we certainly can answer for ourselves.

Function Follows Facility

We make software to perform specific functions for a specific industry. Insurance. It does lots of things insurance software needs to do: It administers policies and claims. It manages billing. It provides business intelligence. It permits access through portals and mobile devices. And it features a WYSIWYG Design Studio that lets you design, configure, and manage the entire Finys Suite; to develop and deploy products, states, and lines of business; or to quickly change any of those things with or without our help, or any degree in between, depending on your needs and desires.

As much as it pains us to admit it, the Finys Suite doesn’t make coffee. It doesn’t play the violin. It won’t make us better looking.

The fact of the matter is, we don’t want the Suite do any of those things (with the possible exception of making us better looking). Our customers don’t need it to do those things. And we’ll never tell our customers or prospects the Suite will do everything they might want it to do. With their input and a legitimately demonstrable need, we can likely get the Suite to do anything they might like it to do. But we won’t make impractical promises, avoid their questions, or give circuitous answers to those questions.

Changing the subject, or avoiding it, won’t help anyone.

Let’s Be Careful Out There

At various points in the year, we like to review some of the things that have been forecasted to take place in or be important to the insurance industry. As a result of such a review, we came across a piece from PropertyCasualty360 called, “Four trends shaping insurance in 2019.” In brief, the four predicted trends were:

  1. Virtual claims adjusting
  2. Innovative use of mobile technology
  3. Better, more powerful data
  4. Blockchain will get bigger.

The first three are pretty much indisputable. Given the capabilities unleashed by the Internet (hello, IoE), the digitalization of darn-near everything, the ubiquitous advancement of mobile capabilities, the data generated by, accessible to, and running all those things, their inevitability couldn’t have been disputed. We do, however, wonder about #4.

The Jury’s Out

In November of last year, The Register published this — “Blockchain study finds 0.00% success rate and vendors don’t call back when asked for evidence” — which is the kind of thing that grabs our attention, especially when blockchain is being hailed more optimistically in other quarters. This was hard to ignore:

We found a proliferation of press releases, white papers, and persuasively written articles … However, we found no documentation or evidence of the results blockchain was purported to have achieved in these claims. We also did not find lessons learned or practical insights, as are available for other technologies in development.

We weren’t ready to give up on blockchain’s future in the insurance industry. In fact, some people, publications, and companies like SAP still hold out hope for it. But this one hurts a little more — “Blockchain Has Been Unblocked, Unchained And Broken” — especially when you get to this part:

Hackers have stolen nearly $2 billion worth of cryptocurrency since the beginning of 2017, mostly from exchanges, and that’s just what has been revealed publicly … One does wonder why Blockchain is so wonderful, then, if in practical use, its supposed greater security is so easily circumvented … To anyone with a shred of common sense, this is a fatal event.

Don’t Panic

We can’t be any more hasty in dismissing blockchain than some folks were in embracing it. As it is with any new technology, time is our best friend. So, let’s watch and wait. We can’t be certain of the outcome. But we can be certain we’ll learn something.

We’re not saying blockchain is dead or dying. All we’re saying is let’s be careful out there.

Business Objectives

Some businesses have lists of objectives that are better measured in yards, rather than word-counts. If there’s a way to prioritize and manage that many objectives, maybe that’s okay. We, on the other hand, tend to think there are two business objectives that (should) supersede all others:

  1. Acquire customers by developing the right product
  2. Retain those customers by delivering the right service(s).

While it may not seem like it, #1 is the easier of the two objectives. Creating a new product is like spring training: It’s a new season, a fresh start. Everything is fresh, green, hopeful, and eminently possible. With a win in front of us and the wind at our backs, all we imagine is succeeding. But that success precipitates the challenges manifest in #2.

The Day After

After developing the product and earning customers, the product has to be kept functionally relevant. Since we can’t eliminate change or anticipate the needs of every customer, #2 requires the constant accommodation of change and constant communication with customers. It takes a profound working knowledge of the industry (or industries) in which the product is expected to perform. It takes a combination of open-mindedness and decisiveness to know the product may, at some point, do this, but it will never do that (regardless of the precise definitions of this and that), as well as the courage to tell customers what the product will and won’t do — and why or why not.

Most important, perhaps, is the willingness and the determination to look ahead. No one can predict the future. But communicating with customers, listening to their needs, anticipating others, and demonstrating a commitment to remain professionally concerned and functionally relevant goes a long way to achieving two of the so-called soft objectives — the trust and confidence of your customers. Look at it this way: Functionality can always be added after the fact. But trust can never be back-filled.

First steps are crucial. Next steps are make-or-break.

It’s About Philosophy

Business objectives are great. Good intentions are terrific (and the stuff, of course, of which a particular road is paved). But over-promising and under-delivering is not a philosophy by which to earn long-term success.

That’s why we’re thinking about making a poster out of this strip:

 

 

 

The Decreasing Increase

Based on some of our recent reading, there seems to be a disparity of opinions as they pertain to the employment market:

  • Exhibit A: According to an article in PropertyCasualty360, “The number of insurance professionals aged 55 years and older … increased 74 percent [between 2006 and 2016].”
  • Exhibit B: According to a study published by Deloitte, “Few millennials are familiar with the insurance industry and only 10 percent are ‘very interested’ in choosing insurance as a career.”
  • Exhibit C: According to a study published by The Jacobson Group, “The mass talent shortage is here, and insurers must take action.”
  • Exhibit D: According to the LinkedIn Talent Blog, “The U.S. will be hit the hardest by the talent shortage, losing $435.69 billion in unrealized economic output—or 1.5% of the whole U.S. economy.”

But those alarmingly bleak perspectives don’t appear to be commonly held, let alone unanimous.

The Plot Thickens

In fact, according to a piece published by the United States Census Bureau in April of last year — “Older People Working Longer, Earning More” — the aging of the workforce and the rise of the millennials might not be so bad after all, particularly for the increasing numbers of  … uh … seasoned folks in said aging workforce.

Here’s a sampling of comparative statistics in monthly wages alone:

  • 17 percent for workers aged 14-24, a $245 increase from $1,431 to $1,676.
  • 20 percent for workers aged 25-34, a $600 increase from $3,049 to $3,649.
  • 32 percent for workers aged 35-44, a $1,254 increase from $3,939 to $5,193.
  • 32 percent for workers aged 45-54, a $1,390 increase from $4,363 to $5,753.
  • 41 percent for workers aged 55-64, a $1,629 increase from $3,928 to $5,557.
  • 80 percent for workers aged 65-99, a $1,816 increase from $2,276 to $4,092.

So, what is there to learn from this seemingly conflicting information? In fact, much.

Cutting to Reality

This much is indisputable: There are demographic shifts taking place in all industries. In the insurance industry (and others), those shifts mean younger people — who are more familiar and comfortable with technology — will enter, and older people — who have the requisite domain knowledge and experience — will exit. But it won’t happen all at once.

Because it won’t happen all at once, there will be knowledge-transfer between those demographic groups. Technology in general and good systems in particular will abet that knowledge transfer, ensuring that the application of technology serves and is informed by the institutionalization of material domain knowledge.

Despite the best efforts of some to convince us there’s a crisis-level shortage of capable insurance-industry personnel on the short-term horizon, it might be much ado about nothing.

As have generations before us, we’ll just do our best to keep up with time and change. Chances are we’ll be just fine.

Be Careful What We Wish For

We’re tech people. We’ve always thought we’re tech people so insurance people wouldn’t have to be tech people. And we’ve always felt like we were alone in that thinking. But the tide may be starting to turn.

The February edition of Best’s Review ran an article entitled, “Generation Next”, contending that the traditional focus of the insurance industry on technical competence (though not limited to technological competence) may be too narrow to carry it into the future. As Limore Zilberman, a consultant at the executive search firm, Russell Reynolds Associates, put it:

People were hired because of their technical prowess and because of their technical acumen and their technical contribution … [but]  the landscape of leadership is going to change. The expectations of leadership are going to change. Our technical talent is not necessarily well-poised to take on broader leadership capabilities.

That seems about right. To put it another way: With all the bigger fish insurers have to fry, technical talent may be a red herring.

Leaders Lead

In arguing that the insurance industry focus on specialists needs to broaden sufficiently to include generalists in leadership positions, Zilberman elaborates on the characteristics of the people she believes are better suited to fill the leadership roles of the future:

They’re agile, they’re adaptable, they’re quick learners, they’re good problem solvers, they’re forward-looking … Those types of people can be put at the helm to manage the lower ranks of the organization that might carry more of that technical expertise.

At risk of seeming to quibble with terminology, we take issue with Ms. Zilberman’s notion of managing the lower ranks. (We even find lower to be a tad condescending; although, we do take her point.) We take issue because leaders lead. Managers manage. And those two jobs, along with their respective responsibilities, are quite different.

But that difference in perspective on vocabulary notwithstanding, Ms. Zilberman and the article are correct. The insurance industry does need to think more broadly. And it does need to embrace well-rounded, critical-thinking generalists as its leaders.

If continue to favor leaders whose strength are technical (linear) thinking, as opposed to general (conceptual) thinking, we should be careful what we wish for.

Tight Lips Sink Ships

If you’re familiar with the expression, “Loose lips sink ships,” you understand why too much information (TMI) can be a bad thing. By the same token, too little information (TLI) can be equally bad. Case in point: The insurance industry seems conspicuously tight-lipped when it comes to information about implementations. As a result, there’s precious little data on failed or failing implementations, to say nothing of blown budgets, blown dates, and undue expectations as they apply specifically to the insurance industry.

Fortunately, there are two other things from which to derive meaningful and applicable perspectives: (1) A plethora of data on ERP implementations. (2) Extrapolation. Let’s have a look.

The Numbers Are In

Here are just three citations from the volumes of information about EPR implementations available on the Web: First, here just five of the failures listed by ERP Focus in “Ten ERP failure statistics that highlight the importance of getting it right first time round“:

  1. 60% of ERP projects fail.
  2. 57% of ERP systems take longer than expected.
  3. 54% of ERP systems exceed projected budget targets.
  4. 40% of ERP systems experience at-large operational disruption.
  5. 41% of enterprises fail to achieve more than half of the expected benefits.

Second, according to this infographic from Technology Evaluation Centers:

  • Nearly 50% of ERP implementations fail the first time around.
  • On average, 30% of ERP implementations take longer than estimated.
  • Most implementations cost three to four times what was budgeted.
  • About 65% of the time, budgets go over because the system needs modifications to improve usability. But companies realize this only after the implementation has started.

Finally (for now), Management Consulting Now reports ERP implementations:

  • Take longer than expected (61%)
  • Cost more than expected (74%)
  • Fail to deliver more than 50% of the expected benefits (52%)
  • Leave their respective organizations unhappy with the results (59%).

While all of those sources and studies might not agree, we can agree all of their statistics are dismal … and unnecessary.

Why Settle?

These numbers may be dire, but they need not be leading indicators, as we say in the biz. With some initiative, some diligence, some foresight, and a clearly articulated set of shared expectations, these statistics can be greatly improved. Oh, and let’s not forget clear and open communication between the parties involved.

Remember: Tight lips sink ships.