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5 Transformational Changes for Clients

In January 1993, I began preaching the Gospel of Change – its management and architecture.

One of my first presentations was to a very successful community bank’s senior management team. I said, “Today, General Motors, Sears and IBM are kings of their respective jungles. I believe in my lifetime (I was 46 at the time) one of these companies will go bankrupt!” The audience rolled their collective eyes! In 16 years, I was vindicated.

GM filed for Chapter 11 reorganization in the Manhattan New York federal bankruptcy court on June 1, 2009. The filing reported $82.29 billion in assets and $172.81 billion in debt.

Then, Sears filed for Chapter 11 bankruptcy protection on Oct. 15, 2018, with $6.9 billion of assets and $11.3 billion of debts, after a decade-plus as a train wreck in slow motion.

See also: How to Earn Consumers’ Trust  

Today, I’m not going to scare you into change – I’ll merely shine a spot light on the changes that are already occurring in the world and you decide if these innovations are friends or foes. Don’t ask what threats these changes mean for you. Ask instead what these changes mean to the marketplace – to each of us as consumers. The consumer is king, and now consumers shop in a global marketplace – when, where and how they want. Below are five transformational changes that are affecting the world for your clients and you–and a word of hope.

Generational Change: Many of us grew up in a “Father Knows Best” world. Today, the universe is more similar to a “Modern Family.”

Look at the demographics. The youngest members of the Greatest or Silent generation are nearing 75. The youngest members of the Baby Boomers are in their mid-50s. The youngest Gen Xers are in their mid-30s. And the youngest millennials are already 15.

As Paul Harvey said often, “We’re not one world.” He was so right. In terms of marketing reality – One size does not fit all.

Big Data and Artificial Intelligence: Yesterday, I opened an e-mail offering me a “deal” on a new Toyota. Within an hour, I had received similar e-mails from most other brands that I might be interested in. Big Brother (or Big Sister) is watching everything we do. Now, sophisticated sellers can anticipate your needs and be first to market with a solution for each need. Can you do this?

Global Marketplace/Virtual Marketplace: As a consumer, you can buy anything you want, wherever you want. As a seller, your competitors are not down the street – they are everywhere.

Language/Diversity: Robert Young as Jim Anderson in “Father Knows Best” was an insurance agent and also an OWGIC (Old White Guy in Charge). Today, ours is a much more diverse and multilingual world. Everyone can be in charge of their own world. Do you speak enough languages to serve this marketplace? Who is/will be your marketplace (Hispanic, Laotian, Muslim, etc.)? Remember that many “youn-‘uns” communicate very differently. If you don’t believe me, call a teen and see she answers. Text, and she will.

Innovation of Products/Services/Competitors: What, where and how you sell has no meaning. What, where and how people buy is all that matters. Remember social media, robotic surgery, driverless cars, Amazon, Expedia, Uber, Google, AirBnB: Innovations change options and in some cases bankrupt organizations and industries that are fat, dumb and happy.

See also: Why More Don’t Go Direct-to-Consumer  

Your Hope/Opportunity:

John Naisbitt developed the concept of high tech, high touch in his 1982 bestseller “Megatrends.” He theorized that, in a world of technology, people long for personal, human contact.

He was so right. Become client-defined and client-driven. Develop client intimacy. Be engaged with the people and markets you serve. Don’t sell them; facilitate their buying. Be a concierge, a friend, a shoulder to cry on and voice of encouragement. Build intimacy – be a professional, expert, trusted resource.

15 Hurdles to Scaling for Driverless Cars

Will the future of driverless cars rhyme with the history of the Segway? The Segway personal transporter was also predicted to revolutionize transportation. Steve Jobs gushed that cities would be redesigned around the device. John Doerr said it would be bigger than the internet. The Segway worked technically but never lived up to its backers’ outsized hopes for market impact. Instead, the Segway was relegated to narrow market niches, like ferrying security guards, warehouse workers and sightseeing tours.

One could well imagine such a fate for driverless cars (a.k.a. AVs, for autonomous vehicles). The technology could work brilliantly and yet get relegated to narrow market niches, like predefined shuttle routes and slow-moving delivery drones.  Some narrow applications, like interstate highway portions of long-haul trucking, could be extremely valuable but nowhere near the atmospheric potential imagined by many—include me, as I described, for example, in “Google’s Driverless Car Is Worth Trillions.”

For AVs to revolutionize transportation, they must reach a high level of industrialization and adoption. They must enable, as a first step, robust, relatively inexpensive Uber-like services in urban and suburban areas. (The industry is coalescing around calling these types of services “transportation as a service,” or TaaS.) In the longer term, AVs must be robust enough to allow for personal ownership and challenge the pervasiveness of personally owned, human-driven cars.

See also: Where Are Driverless Cars Taking Industry?  

This disruptive potential (and therefore enormous value) is motivating hundreds of companies around the world, including some of the biggest and wealthiest, such as Alphabet, Apple, General Motors, Ford, Toyota and SoftBank, to invest many billions of dollars into developing AVs. The work is progressing, with some companies (and regulators) believing that their AVs are “good enough” for pilot testing of commercial AV TaaS services with real customers on public roads in multiple markets, including SingaporePhoenix and Quangzhou.

Will AVs turn out to be revolutionary? What factors might cause them to go the way of the Segway—and derail the hopes (and enormous investments) of those chasing after the bigger prize?

Getting AVs to work well enough is, of course, a non-negotiable prerequisite for future success. It is absolutely necessary but far from sufficient.

In this three-part series, I look beyond the questions of technical feasibility to explore other significant hurdles to the industrialization of AVs. These hurdles fall into four categories: scaling, trust, market viability and secondary effects.

Scaling. Building and proving an AV is a big first step. Scaling it into a fleet-based TaaS business operation is an even bigger step. Here are seven giant hurdles to industrialization related to scaling:

  1. Mass production
  2. Electric charging infrastructure
  3. Mapping
  4. Fleet management and operations
  5. Customer service and experience
  6. Security
  7. Rapid localization

Trust. It is not enough for developers and manufacturers to believe their AVs are good enough for widespread use, they must convince others. To do so, they must overcome three huge hurdles.

  1. Independent verification and validation
  2. Standardization and regulation
  3. Public acceptance

Market Viability. The next three hurdles deal with whether AV-enabled business models work in the short term and the long term, both in beating the competition and other opponents.

  1. Business viability
  2. Stakeholder resistance
  3. Private ownership

See also: Suddenly, Driverless Cars Hit Bumps  

Secondary Effects. We shape our AVs, and afterward our AVs reshape us, to paraphrase Winston Churchill. There will be much to love about the successful industrialization of driverless cars. But, as always is the case with large technology change, there could be huge negative secondary effects. Several possible negative consequences are already foreseeable and raising concern. They represent significant hurdles to industrialization unless successfully anticipated and ameliorated.

  1. Congestion
  2. Job loss

I’ll sketch out these hurdles in two more parts to come.

How Not to Make Decisions

Nancy Newbee is the newest trainee for LOCO (Large Old Company) Inc. She was hired because she is bright, articulate, well-educated and motivated. She is in her second week of training.

Her orders include: “We’ll teach you all you need to know. Sammy Supervisor will monitor your every action and coordinate your training. Don’t take a step without his clearance. When he’s busy, just read through the procedures manual.”

Nancy is already frustrated by this training process but is committed to following the rules.

Upon arriving at work today, Nancy discovers the kitchen is on fire! As instructed, she rushes to Sammy Supervisor. Interrupting him, she says, “There’s a major problem!”

Sammy is obviously disturbed by this interruption in his routine. He tells her, “Nancy, my schedule will not allow me to work with you until this afternoon. Go back to the conference room and continue studying the procedures.”

“But, Mr. Supervisor, this is a major problem!” Nancy pleads.

“But nothing! I’m busy. We’ll discuss it this afternoon. If it can’t wait, go see the department head,” Sammy responds.

Nancy rushes to the office of Billy Big and shouts, “Mr. Big, we have a major problem, and Mr. Sammy said to see you!” Mr. Big states politely, “I’m busy now,” all the while wondering why Sammy Supervisor hires these excitable airheads.

“But, Mr. Big, the building…” Nancy interrupts.

“Nancy, see my secretary for an appointment or call maintenance if it’s a building problem,” Mr. Big says impatiently, thinking, “Where does Sammy find these characters?”

Near panic, Nancy calls maintenance. The line is busy. As a last resort, Nancy calls Ruth Radar, the senior secretary in the accounting department. Everyone has told her that Ruth really runs this place. She can get anything done.

“Ruth Radar, how may I help you?” is the response on the phone.

“Miss Radar, this is Nancy, the new trainee. The building is on fire! What should I do?” shouts Nancy through her tears.

“Nancy, call 911!” Ruth says.

Now, of course this is a ridiculous example… or is it?

See also: How We’re Wired to Make Bad Decisions  

Assuming you are the boss, try this eight-question test:

  1. In your business, do you hire the best and brightest and then instruct them not to think, act or do anything during their training, except as you tell them to do?
  2. Do you promise training and, instead, substitute reading of procedure manuals?
  3. Do you create barriers to communication, interaction and effectiveness by scheduling the new employees’ problems and inquiries to accommodate the busy schedules of your other personnel?
  4. Do you and your staff ignore what new employees are saying?
  5. Is the process more important than the result? Does the urgent get in the way of the important?
  6. Do layers of bureaucracy between you, your employees and customers interfere with contact, communications and results?
  7. Is “Ruth Radar” running your shop?
  8. Do you have any fires burning in your office?

If you answered “no” to all of these questions, congratulations!

Now go back and look at the questions again. The perfect business would have eight “no” answers, but very few businesses are perfect. If you are like LOCO, our large old company, you might be so far out of touch with your trainees, employees and customers that you won’t hear about a “fire” until it starts to burn your desk.

Look back at IBM, GM and Sears in the late 1980s. These were  the kings of their respective jungles. Yet all of these leaders nearly burned to the ground. Many thousands of employees were terminated, profits were ended and stock values fell. If you would have talked to any of these terminated employees, you would have learned that the fire had burned for a long time and that many people had tried to sound the alarm.

Remember the large old insurance companies that are no longer here: Continental, Reliance, etc. Did their independent agents smell the smoke? Did the leadership of these carriers ignore the alarm?

Sam Walton, who had reasonable success in business during his lifetime, once said, “There is only one boss — the customer. Customers can fire everybody in the company from the chairman on down, simply by spending their money somewhere else.”

Walton was right. In your business, do you or Nancy have the most direct contact with the customer — the ultimate boss? If Nancy has the most contact, is she adequately trained, motivated and monitored? Is she providing feedback? Are you listening?

Take a minute to draw a picture of your organization. Now, draw a frame around your picture. Does this frame create a pyramid? Are you, as the boss, at the pinnacle? Are Nancy and her fellow trainees at the base? Is it prudent to have the least experienced personnel closest to the customers?

Your organization was formed to meet the needs of customers. You exist to serve these same customers. Where are these customers in the organizational chart? Did you “forget” to draw them into the picture? How much distance is there between you (as boss) and the customers?

Does this pyramid model facilitate the free flow of information between you and the customers, or does it buffer you from the real thoughts and feelings of the real boss (the customer)? In your business, is the customer and his problem seen as an interruption of the work or as the very reason for your existence?

If you had to downsize your company, where would the cuts be made? At the top, middle or bottom of the pyramid? Are the people in the hierarchy of the pyramid there because they did or can do more for the consumer, or were they pushed up by the people they hired to support them? Is your company fat or lean?

See also: How Basis for Buying Decisions Is Changing  

If your employees answered all the above questions, would they agree with you? If your customers were asked, what would they say? If your customers voted tomorrow, who would be retained? Who would be fired?

Think about it!

Do you dare ask?

When Will the Driverless Car Arrive?

When Chris Urmson talks about driverless cars, everyone should listen. This has been true throughout his career, but it is especially true now.

Few have had better vantage points on the state of the art and the practical business and engineering challenges of building driverless cars. Urmson has been at the forefront for more than a decade, first as a leading researcher at CMU, then as longtime director of Google’s self-driving car (SDC) program and now as CEO of a driverless car dream team at Aurora Innovation.

Urmson’s recent “Perspectives on Self-Driving Cars” lecture at Carnegie Mellon was particularly interesting because he has had time to absorb the lessons from his long tenure at Google and translate those into his next moves at Aurora. He was also in a thoughtful space at his alma mater, surrounded by mentors, colleagues and students. And, it is early enough in his new startup’s journey that he seemed truly in “perspective” rather than “pitch” mode.

The entire presentation is worth watching. Here are six takeaways:

1. There is a lot more chaos on the road than most recognize.

Much of the carnage due to vehicle accidents is easy to measure. In 2015, in just the U.S., there were 35,092 killed and 2.4 million injured in 6.3 million police-reported vehicle accidents. Urmson estimates, however, that the real accident rate is really between two and 10 times greater.
Over more than two million test miles during his Google tenure, Google’s SDCs were involved in about 25 accidents. Most were not severe enough to warrant a regular police report (they were reported to the California DMV). The accidents mostly looked like this: “Self-driving car does something reasonable. Comes to a stop. Human crashes into it.” Fender bender results.
While we talk a lot about fatalities or police-reported accidents, Urmson said, “there is a lot of property damage and loss that can be cleaned up relatively easily” with driverless technology.
2. Human intent is the fundamental challenge for driverless cars.
The choices made by driverless cars are critically dependent on understanding and matching the expectations of human drivers. This includes both humans in operational control of the cars themselves and human drivers of other cars. For Urmson, the difficulty in doing this is “the heart of the problem” going forward.
To illustrate the “human factors” challenge, Urmson dissected three high-profile accidents. (He cautioned that, in the case of the Uber and Tesla crashes, he had no inside information and was piecing together what probably happened based on public information.)

Google Car Crashes With Bus; Santa Clara Transportation Authority

In the only accident where Google’s SDC was partially at fault, Google’s car was partially blocking the lane of a bus behind it (due to sand bags in its own lane). The car had to decide whether to wait for the bus to pass or merge fully into the lane. The car predicted that the remaining space in the bus’s lane was too narrow and that the bus driver would have to stop. The bus driver looked at the situation and thought “I can make it,” and didn’t stop. The car went. The bus did, too. Crunch.

Uber’s Arizona Rollover

Uber Driverless Car Crashes In Tempe, AZ

The Uber SDC was in the leftmost lane of three lanes. The traffic in the two lanes to its right were stopped due to congested traffic. The Uber car’s lane was clear, so it continued to move at a good pace.

A human driver wanted to turn left across the three lanes. The turning car pulled out in front of the cars in the two stopped lanes. The driver probably could not see across the blocked lanes to the Uber car’s lane and, given the stopped traffic, expected that whatever might be driving down that lane would be moving slower. It pulled into the Uber car’s lane to make the turn, and the result was a sideways parked car.

See also: Who Is Leading in Driverless Cars?  

Tesla’s Deadly Florida Crash

Tesla Car After Fatal Crash in Florida

The driver had been using Tesla’s Autopilot for a long time, and he trusted it—despite Tesla saying, “Don’t trust it.” Tesla user manuals told drivers to keep their hands on the wheel, eyes in front, etc. The vehicle was expecting that the driver was paying attention and would act as the safety check. The driver thought that Autopilot worked well enough on its own. A big truck pulled in front of the car. Autopilot did not see it. The driver did not intervene. Fatal crash.

Tesla, to its credit, has made modifications to improve the car’s understanding about whether the driver is paying attention. To Urmson, however, the crash highlights the fundamental limitation of relying on human attentiveness as the safety mechanism against car inadequacies.

3. Incremental driver assistance systems will not evolve into driverless cars.

Urmson characterized “one of the big open debates” in the driverless car world as between Tesla’s (and other automakers’) vs. Google’s approach. The former’s approach is “let’s just keep on making incremental systems and, one day, we’ll turn around and have a self-driving car.” The latter is “No, no, these are two distinct problems. We need to apply different technologies.”

Urmson is still “fundamentally in the Google camp.” He believes there is a discrete step in the design space when you have to turn your back on human intervention and trust the car will not have anyone to take control. The incremental approach, he argues, will guide developers down a selection of technologies that will limit the ability to bridge over to fully driverless capabilities.

4. Don’t let the “Trolley Car Problem” make the perfect into the enemy of the great.

The “trolley car problem” is a thought experiment that asks how driverless cars should handle no-win, life-threatening scenarios—such as when the only possible choices are between killing the car’s passenger or an innocent bystander. Some argue that driverless cars should not be allowed to make such decisions.

Urmson, on the other hand, described this as an interesting philosophical problem that should not be driving the question of whether to bring the technology to market. To let it do so would be “to let the perfect be the enemy of the great.”

Urmson offered a two-fold pragmatic approach to this ethical dilemma. First, cars should never get into such situations. “If you got there, you’ve screwed up.”  Driverless cars should be conservative, safety-first drivers that can anticipate and avoid such situations. “If you’re paying attention, they don’t just surprise and pop out at you,” he said. Second, if the eventuality arose, a car’s response should be predetermined and explicit. Tell consumers what to expect and let them make the choice. For example, tell consumers that the car will prefer the safety of pedestrians and will put passengers at risk to protect pedestrians. Such an explicit choice is better than what occurs with human drivers, Urmson argues, who react instinctually because there is not enough time to make any judgment at all.

5. The “mad rush” is justified.

Urmson reminisced about the early days when he would talk to automakers and tier 1 suppliers about the Google program and he “literally got laughed at.”  A lot has changed in the last five years, and many of those skeptics have since invested billions in competing approaches.

Urmson points to the interaction between automation, environmental standards, electric vehicles and ride sharing as the driving forces behind the rush toward driverless. (Read more about this virtuous cycle.) Is it justified? He thinks so, and points to one simple equation to support his position:

3 Trillion VMT * $0.10 per mile = $300B per year

In 2016, vehicles in the U.S. traveled about 3.2 trillion miles. If you could bring technology to bear to reduce the cost or increase the quality of those miles and charge 10 cents per mile, that would add up to $300 billion in annual revenue—just in the U.S.

This equation, he points out, is driving the market infatuation with Transportation as a Service (TaaS) business models. The leading contenders in the emerging space, Uber, Lyft and Didi, have a combined market valuation of about $110 billion—roughly equal to the market value of GM, Ford and Chrysler. Urmson predicts that one of these clusters will see its market value double in the next four years. The race is to see who reaps this increased value.

See also: 10 Questions That Reveal AI’s Limits  

6. Deployment will happen “relatively quickly.”

To the inevitable question of “when,” Urmson is very optimistic.  He predicts that self-driving car services will be available in certain communities within the next five years.

You won’t get them everywhere. You certainly are not going to get them in incredibly challenging weather or incredibly challenging cultural regions. But, you’ll see neighborhoods and communities where you’ll be able to call a car, get in it, and it will take you where you want to go.

(Based on recent Waymo announcements, Phoenix seems a likely candidate.)

Then, over the next 20 years, Urmson believes we’ll see a large portion of the transportation infrastructure move over to automation.

Urmson concluded his presentation by calling it an exciting time for roboticists. “It’s a pretty damn good time to be alive. We’re seeing fundamental transformations to the structure of labor and the structure transportation. To be a part of that and have a chance to be involved in it is exciting.”

The Uberization of Insurance

Our nomination for word of the year is, by far, “uberization.”

This term is used to describe the growing deluge of companies that offer on-demand services from cars to homes to labor, and much more. Many commentators view this economic transformation as a revolution that will see our entire economy shift from one of consumption, to one of access.

And we think they’re correct.

The Rise of On-Demand

The key to an “uberized” economy is where on-demand services meet crowdsourced labor solutions. You see it everywhere. Even traditional businesses are learning new tricks from an avalanche of high-profile acquisitions. Whether it’s Expedia’s purchase of Homeaway, GM’s buyout of Sidecar or Ford’s investment in Lyft, this shift is becoming more undeniable.

On-Demand for Insurance

Now, on-demand services are coming to the insurance industry, the most risk-averse industry, by its very nature. The insurance industry has become more nimble–mostly out of necessity, but that’s a story for another day.

See also: How On-Demand Economy Can Prosper  

Insurance carriers are learning quickly that they need to adapt to the demand of, well, on-demand services. And the integration of the gig economy is the next step in the business evolution of the traditional insurance sector.

Tough Questions for the Insurance Industry

What does the “uber of insurance” mean? What opportunities and challenges does it bring to the industry? The gig economy, sharing economy, 1099 economy, on-demand economy or whatever you want to call it isn’t going away, and consumer participation continues to grow.

Earners, consumers and the old guard of the supply chain are eager to find ways to diversify and optimize business solutions.

How do you satisfy the demand for on-demand data gathering? Claims handling and processing? How does the insurance industry gather the data it needs effectively, efficiently and accurately?

Uber, Lyft, and Airbnb have not only demonstrated that they fill a need in the marketplace, but often they do it better than the traditional options – as uncomfortable a thought as that may be for the old guard in the supply chain.

Can this model work for the insurance industry? It can, and this is how.

Hug Your Smartphone, Save a Tree

Mobile technology is your new best friend when it comes to data gathering for claims handling and processing. The insurance industry is traditionally paper-intensive. Paper is no longer a security blanket, but a wet blanket weighing down processes and impeding efficiency.

Candy Crush and Capturing Data

It’s easy to marvel at the innovation of smartphones from the most addictive apps to the most useful. I won’t get into my Candy Crush addiction; I’m seeking professional help.

The point is to make smartphones work for you and your business processes. Today, smartphones are essential to the daily lives of most of us, providing communication, connectivity, schedules, entertainment and even our wallets. Think about how you can leverage people’s familiarity and affinity for their smartphones by merging it with your smart application development and deployment.

Capturing data has never been easier than point and click…Oops, I mean a finger swipe.

Now more than ever data can be captured, optimized and automatically entered into your data systems and processes. This new process can facilitate the seamless flow of data into business processes without risking it getting stuck to the bottom of someone’s shoe, misfiled, misplaced or eaten by the proverbial dog.

For the notepad next to your computer: seamless data integration at the point of data capture.

It sounds like a dream, doesn’t it?

Sharing Is Caring

First referred to as the sharing economy or the gig economy, the “uberization” of the workforce didn’t originate with Uber. But I’m still voting for “uberization” for word of the year. Merriam-Webster is next on my contact list.

People have always done odd jobs that fit their skill set, hobby, or need. Uber, Turo, Airbnb and WeGoLook through mobile technology have taken this tried-and-true individual entrepreneurship spirit not only to the next level, but to a measurable impact on the economy. Just consider recent sharing economy industry projections made by PwC. I won’t spoil it for you, but you’ll soon be acquainted with the word “mega trend.”

See also: Uber’s Thinking Can Reinvent the Agent  

Crowdsourced labor solutions not only provide diversified earning opportunities, but they also provide options to workers, consumers and businesses alike. Remember our talk about being nimble?

All parties can scale up or down as they choose. They can also select where and how they participate in the gig economy and leverage it to provide for their financial or business goals.

As these on-demand solutions grow, expand and diversify, companies and consumers will have the opportunity to test and identify the best solutions for them, all with a swipe of their smartphone.

Free Market for Solutions

Some will argue the gig economy is the free market at its best, others will argue it’s at its worst. Like anything, it comes back to how individuals and companies strategically apply these solutions to their business challenges.

In the insurance industry, data gathering and claims processing will always resolve around how you can do it faster and better and with fewer mistakes. As the saying goes, “time is money.”

With the help of technology, the reach of smartphones and crowd labor — insurance companies can standardize and streamline data gathering, claims processing and other simple tasks while controlling costs.

For instance, why dispatch an employee across the metro, county, state or even country, incurring all the related expenses, time delays to gather data and take pictures when you can dispatch someone who’s already there?

Not only do you save time travel, and employee productivity, but thanks to the near-universal familiarity with smartphones and standardized mobile apps, you don’t have to train workers.

What if there was an Uber of Insurance? It’s not really a matter of “if” anymore, but of “when” and “how.” The when is now, and the how is through the growing relevance of the insurtech disruption.