Now assume that you are among the many auto owners who have joined the “sharing economy.” You use a smartphone app to match yourself and your car with others willing to pay you for a lift. Uber, Lyft, Sidecar and others (“Transportation Network Companies,” or TNCs) offer these apps, share the fees with you and make this popular service available to thousands. 

Again, imagine the unimaginable – a collision injuring your passenger or a pedestrian. Keeping in mind that any insurance cost is ultimately passed on to the passenger, how much insurance should be required for a TNC driver?  $10,000? $15,000? $50,000 (the maximum required for private autos in any state and the minimum required in California if you allow others to rent your auto)? Or perhaps $106,841 (the value in 2014 dollars of $15,000 in 1967)? $750,000 (the minimum required of limousine companies)? Some other figure? 

Put another way, the question about how much insurance to carry is asking: How much should those who benefit from the sharing economy share the burden when the activity damages them or others? 

Unlike most driving for personal reasons, TNC driving generates cash flow. To many, it seems only fair that some of that be used to extend additional protection to those injured by the activity. What should trigger the additional protection – when one turns on the TNC’s app to seek a fare, when a “match” is made or when a passenger enters the vehicle? Also, who should carry the insurance - the TNC, the TNC driver or some combination?

Currently, these questions are debated among legislators, regulators (such as the California Public Utilities Commission, or CPUC), TNC operators and others. Requiring lots of insurance by setting a high limit may chill innovation; setting the limit too low unnecessarily burdens injured parties or others (e.g., taxpayers, who support Medi-Cal or Medicaid and may end up paying for expenses not covered by private insurance) and may unfairly create a disadvantage for competing sources of transportation that may be subject to higher insurance limits. 

Raise the price of insurance, and the price of a ride goes up. (This issue is hardly unique to TNCs. Congress is also debating whether to raise the federally mandated $750,000  truckers’ minimum insurance limit.) Not only might an increase in insurance costs for TNCs stifle a popular and convenient form of transportation, but it may lead some less safe drivers back into their vehicles (e.g., teenagers, intoxicated drivers, impaired drivers, poorly insured drivers, uninsured drivers or drivers with unsafe driving records). This, in turn, may lead to the unintended result of even more unnecessary injuries and deaths.

Much of the debate about TNCs is colored by a New Year’s Eve accident in San Francisco that occurred when a TNC driver with his app on (there is some evidence he may have been looking at it) struck and killed a pedestrian and injured several others. This is a tragic accident, but it also gives the debate an emotional overtone that may make it difficult to strike the correct balance. This accident could also have happened while a non-TNC driver was texting or talking, and there may have been minimal or no insurance available in that case. 

In this author’s view, comprehensive legislation or regulation shaping the future of TNCs is premature. These fast-moving innovations are new enough that insurers, legislatures and regulators have been caught on the back foot. At the same time that policy makers are moving forward with regulations, insurers and TNCs are developing new products and strategies to address these issues. 

While there is no shortage of those eager to express their opinions (perhaps this author included), there is little credible data on which to base sound policy decisions. Here are some of the many open questions:

--On average, how much would different limits add to the cost of a 10-mile ride? Ten cents? Ten dollars? 

--How much will new insurance products cost? 

--As the use of TNCs expands, will overall accident rates rise, or will they fall?

--If you drive to a ballgame with your daughter and a fare, will your daughter’s injuries be covered if you have an accident? (Your liability would not be covered under most personal auto policies – surprise!). Put another way, what terms and conditions will appear in any new insurance products or endorsements?

--Does the display of a TNC’s trade dress (essentially, its visual appearance) create ostensible or apparent authority should a passenger suffer injury? Would liability extend to an injured passenger who hailed a car displaying the TNC’s trade dress, even though the driver did not engage the TNC's app so he could keep the entire fare? If the TNC is liable, could it seek reimbursement by claiming indemnity against the driver?

--If you drive 12,000 miles a year, but 2,000 of those miles are driven as a TNC driver and are insured by some form of TNC policy, should your personal auto insurer base your rate on 12,000 miles or on 10,000 miles? If the latter, how are the different miles to be confirmed? 

--If you carry higher limits on your personal auto policy (e.g., $300,000 plus a $1 million umbrella), will the protection for you and anyone you injure drop to a lower TNC policy limit when you act as a TNC driver?

--One current bill in California (AB 2293 -- Bonilla) provides that the TNC must assume ALL of the driver’s liability, without limit. By contrast, the CPUC’s proposed rules do not provide for unlimited liability. When is it appropriate to impose liability on the provider of an app as if users of apps were employees or agents of the app provider? Would the operator of an app that matches homes with those who want accommodation (e.g., Airbnb) be liable should a guest trip on an unsafe carpet or step? Would the operator of an app that matches car sellers and buyers be liable for an accident during a test drive? Would an app marketing tickets be liable if the bleachers collapse or the cruise line runs aground?  

--Should liability turn on whether the app provider is more than passive? If so, what more is required? A profit motive? This would sweep up many apps. What if the app provider imposes rules on its users (e.g., vetting drivers for their safety record, adopting a zero-tolerance alcohol policy and reviewing ratings by customers)? If so, then forcing app providers to assume unlimited liability may discourage them from taking measures that could enhance safety. For these reasons, this liability provision in AB 2293 could have enormous implications and should be carefully considered.

--If, under AB 2293, the operator of the app is liable without limit, what purpose is served by mandating policy limits? If the operator of the app has sufficient net worth, it would be liable regardless of any policy limits that might be imposed.

--How, if at all, should one weigh the evolving existence of near-universal healthcare under the Affordable Care Act (Obamacare)? Covered parties who suffer injuries will at least have access to healthcare without limit and regardless of fault. Depending on any number of factors, the bulk of these health costs may fall on health insurers, liability insurers, the public or some combination.

Who knows answers to any of these questions? Without answers to these and related questions, it is likely that regulating in a partial vacuum will strike the wrong balance. Like emergency physicians, legislators and regulators should stabilize the patient but “Do No Harm.”

In the meantime, the public deserves protection. There should be no gaps in coverage (whatever trigger or limits are chosen). To keep rates reasonable and predictable, insurers also need clarity with respect to which insurers are responsible. 

Prudence, however, suggests that any current legislation or regulation should have a firm sunset date. Otherwise, like barnacles, awkward legislation sticks and impedes progress.

During this initial period, the legislature should require (not just request) that the Public Utilities Commission and the Department of Insurance gather appropriate data and report back to the legislature before the legislation or regulation reaches its sunset. Regulators and legislators may, then, make informed, data-driven decisions that strike the most appropriate balance among all of the legitimate interests.

Instead, this bundling is encouraging consumers to buy insurance based on price – rather than on what should be the real goal: shielding a home or other valuable asset from loss. The upshot: Consumers are focusing on the minimum amount of insurance they may be required to hold, say, to secure a mortgage or own a car. It’s a situation that ultimately doesn’t benefit the consumer – or the insurer’s bottom line.

Insurers can change this so that bundling is a win both for themselves and for their customers. To begin, insurers must help guide consumers to think more about protecting themselves and their assets. Companies could then recalibrate their own business model and focus more on providing advice to customers on what insurance meets their actual needs.

Some companies – including Allstate and Progressive – are taking steps in the right direction. But they’re doing so for narrow, tactical reasons. Instead, they must act strategically and become genuine partners that provide customers with the coverage they truly need to safeguard their financial security. Such an approach would set these companies apart from rivals – and arrest the downward price spiral that has turned their bundled offerings into a commoditized product.

Insurers don’t need to discard the concept of bundling to achieve this. The thinking that goes into unbundling can actually help, because it forces companies to break products down to the granular level. Those pieces can then be reassembled into packages customized to the needs of each customer.

Does discounting reflect the true value of product bundling?

Currently, insurers offer a bundling discount, also known as a cross-product discount, and position the value to the customer as “saving money.” The approach may look like a no-brainer, thanks to the marked success of the current model of selling two products together as a bundle, with the “discount” as the differentiator. Consider the following:

• Insurers selling two products together have long seen customer retention improve. Customer retention rates are higher among renters who bundle an auto policy: 91% among those who bundle vs. 67% among those who do not, according to J.D. Power.
• The perceived value of a bundle is reflected in the fact that a greater proportion of customers buy multiple products from the same insurer. According to J.D. Power, 77% of customers bundle auto policies with additional policies, and 58% bundle their auto and home insurance policies with their existing insurers.

But when we analyze the factors that go into premium calculation, real savings for insurers depend on many factors that vary greatly between insurers, states, individual customers’ own situations, etc. Those factors can produce inconsistent savings calculations for bundles, varying from 5% to 20%. Consequently, customers need to shop around thoroughly, comparing prices (both for the individual product and the bundle) and choosing the right combination from the right insurer. The various factors can work together so differently that a customer may sometimes save by buying products from two different insurers – rather than a bundle from one.

For insurers, the incremental value in all this translates into higher customer retention. There is no real incremental value realized from the product itself, which is core risk management.

How is the industry responding?

Insurers have been responding to the emerging need to serve as risk managers for their customers. And they’ve been fine tuning their bundling strategy accordingly. Some insurers, for example, have crafted their bundling strategy to make it easier for customers to manage their risk profile through a single insurer; this also consolidates billing and payment. While this is rudimentary, it still provides an easier way to serve the customer – and to increase loyalty.

The following insurers approach bundling by advising customers as well as crafting suitable packages that allow their customers to manage risk:

• Allstate provides an “all-in-one” product through its Encompass unit, which covers homes, cars and home-based business. It’s aimed at wealthier customers. For more mass-market customers, Allstate provides “Bumper to Bumper Basics,” based on states’ minimum requirements for auto insurance.
• GEICO offers an advisory tool allowing customers to build a customized policy based on their individual circumstances.
• Progressive provides a “Name Your Price” feature for its auto coverage, under which the customer states her budget, and Progressive sorts the options based on cost. The plan closest to the customer’s budget is shown first. Progressive states on its website: “Once you fine tune your price, we highlight any areas where you might have too little or too much coverage, so you can get your entire package just right.” The insurer also gives customers the option of bundling both auto and property insurance.
• MetLife Auto & Home’s “GrandProtect” program allows consumers who purchase multiple policies – such as home and auto – to pay one deductible in the event that several of their insured assets are damaged by one event, such as a storm or hurricane.

These examples underscore that while insurers are shifting toward an advisory-led coverage bundling within a product, they’re still beginning from a tactical standpoint. This narrower approach remains limited to customizing coverage within a product and tactically bundling other products with it. Though insurers have been slow to adopt product bundling on a more strategic basis – i.e., being an end-to-end risk portfolio manager – they are actively pursuing the goal of leveraging cutting-edge technical capabilities.

So, where does the potential value reside?

The real value of bundling – for both customers and insurers – lies in the individual insurance products. Every form of coverage within the bundle covers a specific risk, and so is a “mini product” on its own.

However, insurance products have become commoditized as products have become more unified so they can be sold easily to customers over the Internet. There, many customers simply select the desired coverage amount and deductible. “Save Money” and “Discount” marketing diverts customers toward an affordable premium and, often, the wrong coverage – people opt only for those policies mandated by law (like automobile liability insurance) or, in the case of a home mortgage, a lender. The deductibles chosen often are high, which can prove disastrous for a customer if calamity strikes.

Insurers can deliver real value for themselves and their customers by:

• Gathering customers’ relevant information
• Assessing their risk
• Building the right coverage mix to mesh with customers’ needs
• Suggesting customized products based on a customer’s risk profile

How might this work? Say a customer’s car is more than two years old. The insurer could recommend the customer get an extended warranty as well as a roadside assistance plan. The insurer, in short, could deliver real value by acting as the customer’s risk manager. This approach also would help the insurer to select the right customers for the right risk portfolio – and to weigh the moral hazards when a customer opts for a different package or coverage combination.

Once the individual insurance products are de-commoditized and customized to fit the customer’s risk profile, this advice-based approach can be extended to multi-line product bundling. Customers will move from a mindset of, “I’m required to have homeowners insurance to get a mortgage,” to a mindset more in line with, “I need to cover my risks and ensure a financially secure future.”

Customer retention and satisfaction will go up – along with the insurer’s revenue.

How to unlock the true potential of product bundling?

The goal of achieving strategic bundling hinges on insurers’ building their advisory capabilities and customizing coverage and products based on a customer’s risk portfolio. The core building blocks of coverage and pricing will not change – but the superstructure could be anything from a chapel to a cathedral, based on a customer’s risk profile.

Cutting-edge technical capabilities such as mobile communications, sophisticated analytical tools and so-called “big data” are among the options insurers can tap to build their customization and advisory capabilities. Extensive use of external data (e.g., credit scores and medical data) as well as internal data (e.g., loan delinquency rates) along with analytics will help insurers predict a customer’s risk portfolio with fair accuracy. Social media platforms such as Facebook and Twitter are other evolving (though not always reliable) generators of external data that insurers can use to gather customer profile, risk and behavior data.

Strategic bundling from a risk portfolio management perspective also requires customers to share personal information outright. Customers, especially millennials, seem willing to their share personal information in return for personal advice. This offers the potential for insurers to accelerate strategic product bundling.

Insurers can thus capitalize on customers’ need for advice-based risk portfolio management leveraging leading-edge technology to deliver what customers want. Insurers that show agility and speed in building these capabilities can succeed in achieving strategic bundling – and attain the coveted status of a preferred risk portfolio manager.

"We continue to test new ideas all the time,” says David Pratt, Progressive's general manager of usage-based insurance. “Our research team will come up with a theory for what would predict safe driving. With our big data set, we can test those quickly."

Few other UBI providers are as fortunate. Octo Telematics, which launched its first UBI product in 2002, also has tons of data: 194 billion kilometers of driving performance from two million drivers globally. But most other companies are making educated guesses based on more limited data combined with more traditional ratings factors.

As Nino Tarantino, CEO of Octo Telematics North America, says, "Today, there is no data standard and no clear understanding of which data and how much is required."

For example, Octo works with seven insurers in the U.S. and Canada, and each one asks for a different data set to be collected – everything from hard braking and acceleration to how many trips a driver takes and how long the trips are, as well as when and where they occur.

Actuarial guidelines often cite 100,000 earned car years as the threshold for credibility for a model, says Dwight Hakim, vice president of telematics, Verisk Insurance Solutions, a provider of underwriting data and tools for UBI. An earned car year is equivalent to one car insured for one year.

In traditional motor vehicle insurance, the number of earned car years is used to show state regulators that an insurer’s pricing decision is based on plenty of evidence. This helps reassure regulators, and helps agents selling the insurance.

"Credibility is particularly important when insurers are constructing a rate plan that might increase premiums," Hakim says. "Regulators need to see a model with high credibility if that model might result in rate increases. Assuming the insurer has a good financial position overall, modest rate decreases are easier to justify."

While using earned car years – or the equivalent in telematics driving data – may be critical when an insurer asks regulators to approve a price increase, it may not be strictly necessary to see how different UBI rating characteristics perform, Hakim says.

Trial first, price later

That is what many insurers in need of beginning to test or launch UBI programs are betting on, to avoid the need for a large data set.

For starters, insurers can assume that good drivers self-select for UBI programs. "Chances are [that] the people who try it are more likely to be safe drivers,” says Thomas Hallauer, research and marketing director for telematics consultancy Ptolemus Consulting Group. “So you know you can offer some kind of discount anyway. You also know they will probably stick longer to your contract."

Another strategy, Hallauer says, is for UBI insurers to collect an initial data set through trials, and to then revise their ratings as more data comes in. Coming up on one full year of offering UBI in the U.S., American Family Insurance used just this approach.

"We feel like we got enough to launch, but as we see the data we know we need to refine it," says Pete Frey, personal lines UBI program and product manager, American Family Insurance.

Combining telematics data with traditional rating factors, such as age and location of residence, is yet another strategy. The Hartford is one of many U.S. insurance companies to do just that, saying it makes for finer segmentation for its consumers.

"Almost all programs in the U.S. augment telematics data with other carrier-specific rating factors,” Hakim says. “Assessing the degree of overlap among rating factors to avoid double-counting takes a significant amount of work, but carriers are implementing telematics because they know doing so will help them stay competitive and win market share."

But the benefit of adding more data must equal the cost, Progressive’s Pratt warns. While he agrees that UBI rating will continue to evolve and become more sophisticated, "if it costs a lot to get the information, it's maybe not worth it," he says.

Consumer acceptance is another sticking point. "Everything we use has to be something the customer thinks is fine," Pratt says. "We have to be able to explain to people why it makes sense, why it's actually fair that we do it that way."

Pooled data

Finally, insurers can get larger data sets from third-party telematics data providers, such as Verisk Insurance Solutions, Towers Watson and Octo Telematics.

Verisk offers what it calls “Driving Behavior Database for Modelers,” which makes available to statistical modeling applications: data from telematics devices; exposure, premium and loss information on insured drivers; and third-party data, including weather conditions, road type and traffic flow.

Towers Watson has a pooled data offering that collects telematics data and claims, policy, vehicle and driver information. And it uses this pooled data to score drivers and to provide those scores to insurers. Also available from Towers Watson are models that take into consideration third-party information like maps and weather, road type, population density, weather and angle of the sun.

Octo’s Insight Centre collects global, real-time data from its installed base of Clearbox telematics devices, which customers can then interrogate to inform their UBI offerings.

However, there are caveats when it comes to using pooled data.

Hakim, for example, warns that while amassing large quantities of data is critical, not all data is equally valuable. Its utility depends on its accuracy and completeness; how frequently it's sampled; and the source – whether OBD2 outputs, GPS or accelerometers in cell phones.

"Knowing how each device works and the manner in which the different technologies interact is key,” he says. “The complexities of reading the car’s diagnostic information, appending accelerometer data and then transmitting [it] wirelessly require a deep bench of experience.”

American Family Insurance’s Frey makes a similar point. The availability of aggregated, third-party data is not the issue, he says. While there are plenty of companies offering data to insurers, "carriers are just trying to figure out how to use it,” he says. “The data is almost overwhelming."

The profit question

One of the big, unanswered questions about usage-based insurance is whether insurance carriers will ultimately be more profitable than – or even as profitable as – providers of traditional motor vehicle insurance.

"It's an accepted thing that putting in a UBI program for starters is a cost,” according to Frey, of American Family Insurance. “It is about a longer-term strategy. Ideally, companies hope to achieve more growth."

Among those costs that must be taken into account are the cost of telematics hardware – if an insurer is going the route of using its own devices – and the cost of the back-end infrastructure. Adding UBI on top of an already-existing infrastructure, as major insurers must do, is extremely costly, according to Hallauer, at Ptolemus. In this respect, UBI upstarts that rely on scalable cloud solutions have an advantage, Hallauer adds.

Still, the hope is UBI will ultimately pay off.

Enabling more sophisticated pricing is one benefit. "You want to make sure you have the right rates for the right drivers,” Frey says. “One of the biggest goals is trying to create fair rates eventually."

And insurance discounts are only part of the equation, Hallauer adds. “The pricing decision is not a discount decision; it's how do you change the offering to make it enticing?" he says.

According to  Hallauer, discount-based UBI incentives will eventually evolve into a more service-oriented approach that may range from life-saving services, such as calling an ambulance after a crash, to more prosaic ones, such as allowing drivers to get a driving score.

Ultimately, he says, UBI can make the customer feel comfortable in having a stronger link with the insurer.

Value beyond discounts

Frey says American Family Insurance is looking in this direction. While it hasn't pinpointed what services it might offer, it's considering safety services, making drivers aware of their driving habits and stolen vehicle recovery.

Octo’s Nino Tarantino notes that the value-added services approach is more common in Europe, where some insurance companies offer personal safety and security services, instead of discounts.

The environment is different in North America, he says, because of Progressive. The early mover's decision to base its UBI offering on a good-driver discount established the tone for consumer expectations and shaped the market.

According to Pratt, at Progressive, the company tries to set its prices so the profit margin is the same for people who sign up for Snapshot, its UBI product, as it is for people who opt for traditional insurance.

Progressive's theory is that UBI customers will stay with the company longer – and so far that's been the case. Therefore, the lifetime revenue per customer should be higher, even though the margin is the same as for traditional insurance customers.

Progressive may also save some money through helping people drive better. The company noticed that the driving of UBI customers improved when, a couple of years ago, it added the option of turning on audio feedback in the device so that, for example, it beeps when someone brakes hard.

"We see this training effect within the first few weeks people have the device plugged in,” Pratt says. “They learn to avoid hard braking, and we have evidence it helps people avoid accidents. That could be a big change in the industry, trying to actually reduce your risk."

But the big win is likely in the life of the customer relationship. Pratt adds. “We are not trying to make ourselves more profitable with this. We are trying to attract and keep good customers for a long time."

In fact, Tarantino thinks that most usage-based insurance programs cannot succeed if they're based only on discounts because of all the additional costs associated with them. He says Octo's experience with 2.4 million insured drivers in Europe shows that "when the benefits of pricing and determining risk are combined with the benefits of the understanding the moment of loss for the insurance company – when there is a crash, that is – it will be successful."

There is never enough data

So is there any such thing as enough data?

Pratt doesn't think so. Progressive’s Snapshot considers mileage, time of day and hard braking. The company recently began a pilot using GPS-enabled devices to examine whether highway versus city street driving can contribute to predicting future losses.

Progressive has found that the measurement of how someone drives is indeed a better predictor of risk than driving record, age, gender or any of the traditional rating factors. Still, "the models can still get a lot better," Pratt says.

Say Progressive wants to find out if people who are low-mileage drivers are safer drivers. The company can segment out those drivers from its customer base and see which ultimately did have accidents and which didn't. It could go further and segment the low-mileage drivers by age to determine whether low mileage is a good predictor for all age groups.

Even with 10 billion miles driven, there may not always be enough drivers in the database to provide a meaningful segment to test a theory, Pratt says.

This article has been produced in the lead-up to the Insurance Telematics USA conference and exhibition, which will take place in Chicago on September 3-4. This conference will tackle the steps needed to take UBI programs to the mass market. Find out more here: http://www.telematicsupdate.com/insurance-telematics/

Think back to the transition from horses to cars and note that cars were initially called “horseless carriages.” Cars were defined by what they didn’t have, just as the “driverless car” is being defined by what is being removed from the equation.

But doing away with the need for horses did much more than mean it was good to be Henry Ford and no longer so good to be a horse breeder. The “horseless carriage” had far-reaching effects that not only redefined the transportation network but also provided the basis for the modern economy and even changed how we live, by making suburbs possible.

The “driverless car” will likewise change dynamics in the economy and in our personal lives in ways that are hard to predict at this remove. (The device will also get a real name, focused on what it is or does, not on what it lacks.)

Just in industries directly related to autos, trillions of dollars change hands each year—flowing to and from auto insurers, auto financiers, service and repair shops, rental agencies, taxi operators, fleet managers, oil companies, transportation and logistics companies, emergency rooms, health insurers, medical practices, personal-injury lawyers, government taxing authorities, road-construction companies, parking-lot operators and on and on and on. Driverless cars will inevitably reduce the need for a lot of that spending and throw much of the rest up for grabs.

But if history is any guide, people in these downstream industries feel that it will be decades (at least) before change is pervasive, and therefore decades before they have to worry about their own industry’s collision with the disruptive change. Until then, the reasoning goes, companies in industries peripheral to car-making can simply watch as automakers battle among themselves and with Google.

This is a dangerous point of view. It is the main failing that this series has tried to address.

The raw technology is more developed and improving faster than most observers realize. And several scenarios could dramatically accelerate commercialization and adoption.

In addition, the calculation that disruption will not happen until driverless cars are prevalent could be faulty. A modest number of intelligent cars can change the whole dynamic, long before widespread adoption of driverless cars.

So, it is important for market leaders in downstream industries to get into the game, rather than be spectators.

Even beyond the world of autos, the Google driverless car should be a wake-up call about the pace of disruptive technological change that looms for every industry. Or, taking an optimistic perspective, the driverless car demonstrates the kind of game-changing killer apps that are now possible in almost any industry.

While the Google car feels like it comes straight from some science fiction movie, it is nothing more than a mashup of widely available technological innovation—combining mobile devices, ubiquitous cameras and sensors, social media, the “cloud” and “big data” analytical tools. Similarly bold mashups can upend any information-intensive industry.

Mary Meeker, the noted venture capitalist and industry analyst, contends that technological forces are putting more than $36 trillion of stock-market value up for “reimagination” in the near future. That $36 trillion is the total market valuation of public companies in the 10 industries that are most vulnerable to change over the next few years—financials, consumer staples, information technology, energy, consumer discretionary, health care, industrials, materials, telecom and utilities. Companies will either do the reimagining and lay claim to the markets of the future or be reimagined out of existence.

No history of success will protect incumbents if they put themselves on the wrong side of innovation. Borders, Circuit City, Blockbuster and many more went from thriving business to out of business in almost no time. Think of how recently Nokia and Blackberry were on top of the world and how they’re now irrelevant. And change is still accelerating. The near future will be even more brutal and more lethal, with faster cycle times, than the recent past has been.

As I have suggested in my analysis of Google and of Big Auto, the solution for incumbents and new entrants alike is to follow the innovation roadmap that Google demonstrates: Think Big, Start Small and Learn Fast.

Thinking big means innovators must consider the full range of possible futures. Like Google, they should dare to dream big, focusing on the “killer apps,” new products that can rewrite the rules of an organization or industry, rather than just looking for incrementally faster, better or cheaper products (as Big Auto is currently doing).

Starting small means that, rather than jumping on the bandwagon for one potentially big idea, companies must investigate multiple potential ideas and break them down into smaller pieces for testing. Like Google, successful innovators defer important decisions and keep their options open until they have real data, rather than make decisions early, based on intuition and experience. In addition, successful innovators take the time to make sure that everyone—the executive team, employees, partners, any agents and maybe even customers—are working in unison, rather than having people pay lip service to a vision while actually working at cross purposes.

Learning fast means taking a scientific approach to innovation. Successful innovators conduct extensive prototyping before they even get to the pilot phase—let alone the big rollout—so they can gather comprehensive information about their attempts at innovation and quickly analyze both what’s working and what isn’t. The successes also develop the institutional discipline to set aside or alter projects as soon as it’s clear that they’re not working.

Introduction

Traffic engineers would love to unblock the clogged arteries of Southern California's freeway system, where rush hour is anything but "rush" — more like gridlock. But in a land where one's car is one's empire, one's freedom and personal statement, carpooling is a tough sell. The high-occupancy vehicle (HOV) lanes have scant occupancy. In fact, cars carrying multiple passengers are such a rarity that they, alone, raise red flags for auto insurance claims adjusters.

Operating under the radar is a fast-growing segment of the "underground economy" — organized criminal enterprises that stage automobile collisions to defraud insurance companies of medical payments. In some cases, the entire incident is created on paper, with fictitious vehicles and false identities. In other cases, the perpetrators take real vehicles with legitimate insurance policies out to vacant lots or remote fields to crash them and then fill out a report. The most compelling cases are the ones where participants intentionally ram vehicles together on city streets — often a rear-end collision in a left-turn lane — then dial 911 and wait for police and emergency medical services (EMS) to arrive. This approach triggers a police report and EMS records, which lend an air of legitimacy to the event. It really happened.

Based on instructions from a stager, the driver and two or three passengers — who are known as "stuffed passengers" — report neck and back injuries. The passengers later visit a physician or chiropractor who is in collusion with the criminal ring. The patients sign in and leave without receiving any treatment. If the insurance company balks at paying the specious claim, the claimant enlists the help of an attorney who is also party to the scheme. The attorney is tenacious, willing to go to court, generally able to bluff until the insurance company backs down and settles.

In the process, everybody except the insurance company gets easy money. Property damage to the vehicle is paid to the owner of the vehicle, while multiple players split the proceeds of the settlement for medical payments. In a typical case where the insurance company settles for, say, $6,000, each vehicle occupant might get $1,000, the lawyers and doctors collect their fees and the enterprise leader retains 50% of the professional services fees plus the balance of the claimants' settlement, if any. If the enterprise leader successfully stages dozens of such incidents a month, it's a lucrative business.

This practice exploded in Southern California in the mid-1990s. If you are a special investigations unit investigator, you are dealing with this every day. The average caseload for an adjuster or claims representative might be 150 or 200 a day, depending on the size of the company. At least 25% of that is some flavor of fraud. It's either a false claim or an embellishment to it. People are doing it. Even people who think of themselves as law-abiding are doing it, because they don't think of insurance companies as victims. This type of activity is so prevalent that our undercover investigators would hear paramedics on the scene saying, "Okay, which one of you is going to the hospital this time?"

Automobile insurance fraud is such easy money that the business is even creating unlikely bedfellows. For example, in south central Los Angeles, the Bloods and Crips — gangs that have had an intense and bitter rivalry — are now cooperating with one another in organized insurance fraud, because it's more profitable to join forces.

Six Steps to a Successful Insurance Scam

Constantin Borloff (not his real name), the former leader of a successful and sophisticated fraud enterprise that operated in San Diego, Los Angeles and San Francisco, shares his top tips for making fraud pay. Having paid his debt to society, the ringleader now tells insurance companies how he was able to steal so much money from them, who does it and why it's so easy.

Go for the Med Pay Money
Borloff would insist that vehicle insurance policies have med pay coverage — coverage for reasonable expenses to treat accident-related bodily injury. Because this coverage follows the vehicle, passengers in a vehicle that has med pay coverage will likely be covered, as well. Borloff gave vehicle owners a list of insurance companies that would freely provide these policies.

In theory, claimants are supposed to repay med pay money if they receive a settlement, but that doesn't happen, according to Borloff. "For all history, maybe two times the insurance company asked for money back. If you say you don't have money and can't pay it back, they say, 'Okay, don't pay back the money.'"

Find the Inattentive Insurance Companies
Borloff also selected insurance companies with a reputation for laxity, the ones whose claims representatives didn't take a stand and ask the hard questions. "Big companies like State Farm or Farmers have millions of policies, good special investigation units and more experienced adjusters, so that's where you would see more problems. It's better to go to the smaller company or where it's not their main business. These companies usually pay more, while the big companies usually pay a little less."

Insiders in the business share this information, so they know which companies to avoid and which ones would pay off like loose slot machines in Henderson, NV.

What would make an insurance company an unattractive target? "I don't know what will stop me," Borloff. said "All insurance companies are bound by law to pay. So for us, the system is working perfectly. The insurance company can fight, and they have a lot of resources to fight, but eventually they have to pay something. Maybe more, maybe less, but eventually they have to pay something."

Choose Participants Who Won't Raise Suspicion
In a perfect world, your participants are white American citizens with clean driving records and their own driver's licenses. Judges and juries look most kindly upon this type of claimant, according to Borloff.

It is equally important that their behavior fits accepted patterns. For instance, policies should be active for four to eight months before the staged collision. Claims should be modest, usually no more than $5,000 or $6,000. Activities were choreographed to avoid triggering red flags. "I know insurance companies have about 25 red flags," Borloff says. "What the claims adjusters know, the criminal enterprise knows twice. I knew about all these red flags, and I tried to avoid them."

Distributing the cases is one way to avoid detection, Borloff said. "If the enterprise will do, say, 20 collisions a month, the claims will go to five different insurance companies, each to a different attorney — 10, 15 or 20 different attorneys — and any given adjuster will have at most two cases to a specific attorney. Will the adjuster be suspicious about it? I don't think so. It's very difficult for the insurance company to catch these people in this situation."

Borloff tells of a fringe case where a woman, working against the advice of her stager, staged four accidents in a single week. She submitted claims to four different insurance agencies. All four claims were paid, but this pattern of activity could have exposed everybody in the fraud enterprise to scrutiny and discovery.

Pay More Than Lip Service to the Medical Treatment
When private investigators were first sent to wait outside medical clinics to observe and videotape (the comings and goings of visitors), the first people they caught were the ones who walked in, signed in and left within a minute. People quickly learned to stay longer inside the clinic and have follow-up visits at intervals that would seem appropriate for their injuries and type of care.

Keep Your Stories Straight
Cappers and stagers write notes for people so they can remember their stories when talking to claims representatives and, later on, if they meet with an attorney and go into depositions. Somehow, somewhere, there is a record of all this. If the ring is dealing in volume, there must be good notes, or they won't remember the details of a case, and that's how they get tripped up. Some stagers get tripped up simply by having these notes in their possession — in their offices or briefcases, waiting to be found during a routine traffic stop or search.

Insulate the Players From Each Other
These groups tend to function as classic cell networks. In an effective cell network, the claimant may or may not be exposed to the other people involved, or may be only exposed to the doctor but not to the attorney. That's how these people are protected from one another. Participants may not have a knowledge of what else the group is doing. When we arrested 72 people on a state level and brought them into interrogation rooms for 72 hours, it was pretty clear that they only knew their own activities or those of friends they had brought into the group. They had no knowledge of the bigger scheme. That's how you protect your enterprise.

The parties in these fraud rings learn never to admit to anybody that the accident was staged. Everybody in the enterprise knows it, but if you tell even one person, there's a point of vulnerability. It is especially important to insulate the medical and legal providers, because their professional licenses are critical to facilitate these claims. They take it all the way and never back down.

How often would a criminal enterprise walk away from a case because an insurance company's special investigations unit got involved? "I would not walk away, but I would accept lower settlement, for sure," Borloff said. "One time, one of my colleagues made a terrible mistake and sent 63 cases to Allstate — one attorney, same office. They came to me and said, 'What should we do now, SIU is after us?' I said, 'Don't give up, try to fight,' but they decided to give up. It was the biggest red flag. They lost money. It upset people." Giving up is tantamount to an admission of wrongdoing.

This series of articles is taken from the SAS white paper of the same name. © 2013, SAS Institute Inc. Used by permission.

The doomsday scenario is clear for the roughly $200 billion in personal and commercial auto insurance premiums written each year in the U.S. Insurance premiums are a direct function of the frequency and severity of accidents. In a world of driverless cars, where accidents are significantly curtailed, most of those premiums will go away. Sure, some car insurance will be needed, but the market might be reduced by 75% or more. Insurers make their profits on the float from their premium income, so plunging premiums spells doom for many insurers.

However, based on numerous conversations, it is clear that insurance-industry executives mostly just roll their eyes if asked to contemplate the implications of driverless cars. Even if the driverless cars are possible, conventional wisdom goes, it will be decades before they are relevant. Therefore, there is little need to worry now.

Here’s how insurers figure the math: Begin with the assumption that it will be years before the technology matures. Add several more years to sort out the regulatory complexities, including licensing and liability issues. Add some more years to gain consumer confidence. Then, given the long lifespan of cars, add another decade or more before driverless cars make up a significant percentage of the cars on the road.

On top of that, the argument goes, even if the frequency of accidents goes down, the severity will go up—as measured in the cost to fix cars with all the cameras, sensors, radars, etc., that are going into them. And, remember, even if you don’t crash into someone else, someone else might well crash into you. So, it will be decades before anyone could even imagine giving up car insurance.

Besides, there might be no short-term cost to being wrong. Fewer accidents would just mean fewer claims, and therefore greater profits, until enough actuarial data proved that driverless technology delivered the conjectured savings and forced premiums down.

Thus, the prevailing attitude is probably much like that of Glenn Renwick, CEO of Progressive Insurance, as expressed during Progressive’s February 2013 earnings call:

The technology to do an autonomous car has been around for a while. We’re now seeing them; we’ll see a lot of talk about them. The real issue is exactly how they are able to be part of the fleet of vehicles on the road in America, and that is probably not something that need keep anyone awake for quite some time.

In fact, it’s time for insurance executives to lose a little sleep over driverless cars.

For one thing, far-off doomsdays have a way of sneaking up on you. As Paul Carroll and I documented in “Billion-Dollar Lessons,” Kodak concluded through very sophisticated market research in the 1980s that it would not be threatened by digital photography for a decade or more. It was right. Unfortunately, it did little to prepare for the inevitable disruptions. When it did attempt to mobilize, the advantages that it once held had little relevance. A succession of CEOs could not stem Kodak’s decline into bankruptcy.

The more tangible danger is that Google’s driverless car program has started a technology arms race across the auto industry. If auto industry executives and boards of directors were not focused on this transition before, they are paying attention now. Most automakers are racing to differentiate their premium models with intelligent driver-assist functions like smart cruise control, accident avoidance and crash monitoring and reporting. These efforts will hasten consumer trust in driverless technology and accelerate the proliferation of the technology throughout all car models.

As an example, Volvo, an automaker known for safety but relatively small in terms of global sales, predicts that it will be able to eliminate crashes altogether for anyone driving one of its cars by 2020.

If tiny Volvo can aspire to this audacious goal, what might Big Auto be able to do?

While, as I discussed in Part 3 of this series, this incremental approach might not save automakers from their eventual business model doomsday brought on by totally autonomous cars—it will hasten the disruption for auto insurers.

Guy Fraker, a former director of enterprise innovation at State Farm Insurance and now an executive at AutonomouStuff, says most accidents happen in congested traffic. The accidents, in turn, cause more congestion and more accidents. Fracker argues that even a 25% adoption of incremental driverless technology such as smart cruise control and crash avoidance would significantly relieve congestion and reduce the number of congestion-related accidents.

Fraker’s analysis is consistent with the forecast that one large insurer shared with me. That forecast estimated that a 20% adoption rate of incremental driver-assist technology might result in significant enough reductions in accidents to trigger material reductions in premiums.

In other words, insurers will feel the effects of driverless technology long before fully autonomous cars become ubiquitous.

Because premiums lag actuarial data, insurers will face strategic choices. Some insurers will delay instituting price reductions and enjoy greater short-term profitability. Others, more focused on the transition, will use the drop in claims to be aggressive on pricing, stealing the best customers and gaining market share. The industry may well have to start making these strategic choices in the next few years.

Fred Cripe, a former head of product operations at Allstate Insurance and now an industry adviser, is more sanguine about the prospects for insurers in the short term. Cripe believes that adoption will be faster than many industry executives assume but that it will be more chaotic than predicted by advocates of driverless technology. He reasons that human drivers will become more erratic in the short term as they adjust to the technologies, sending accident rates up.

Cripe agrees, though, that in the long term, “car insurance goes away.” He also says that, to prepare, the insurance industry needs to fight its tendency to push away liability. Insurers issuing policies based on driverless technologies will be tempted to set high prices or to simply refuse to cover driverless technology at all. The danger with this approach is that it leaves an opening for someone else to innovate and create the right insurance products and business models for the emerging world where driverless cars are pervasive. Cripe argues that, “rather than trying to push the losses out of the system,” insurers should focus on product innovation to “maintain control of the losses.”

Google could use its deep pockets to offer cheap insurance, to hasten adoption and grab market share. Automakers could embrace the inevitable increase in their product liability and bundle insurance with their vehicles—rather than letting downstream players take those profits. Fraker hypothesized that automakers could grab a large chunk of the future insurance market by simply extending their warranty operations. Big Venture start-ups might accelerate the emergence of car-sharing fleets, thereby significantly lowering the need for personal insurance coverage. Or, in classic innovator’s dilemma fashion, start-ups like mileage-based insurer MetroMile might eat away at the edges of the market and be best prepared to take advantage as the disruption grows.

Whatever the competition does, a traditional industry strength—underwriting—will decline in importance. For decades, insurers have invested heavily in their abilities to assess individual risk and price accordingly. As one CEO told me, “Insurers with better information make smarter underwriting decisions and slaughter those with less; that’s the nature of the business.” But driverless technology will take human error out of the equation and make underwriting less important. The basis of competition will shift to other aspects of the business, such as customer relationships, claims processing, expense management and distribution.

The shift will create openings for new competitors such as CoverHound, a well-funded San Francisco startup that has built a multiple-carrier comparison engine. Basil Enan, Coverhound’s CEO, believes that auto insurance will become much more like homeowner’s insurance, where claims are rare but very high. His view is that auto premiums will, of course, go down but that claims and other operating costs will, as well, so insurance will be a more profitable business for the survivors. He plans to manage the insurance relationship for driverless technology adopters by helping them sort out the right policies.

Such rapid progress offers great hope that the tremendous benefits in safety and savings I laid out in Part 1 of this series are attainable. The pace of progress also means that the disruptive ripple effects discussed in Part 2 might soon have strategic relevance for companies participating in the multi-trillion-dollar part of the economy that relates to cars. But we’re left with two crucial questions: How soon could the driverless car become a reality? When should incumbents, venture capitals and entrepreneurs start paying serious attention?

The short answer to both questions is: sooner than most think. This article explains why.

When estimating technology adoption, it is wise to remember Paul Saffo’s admonition to “never mistake a clear view for a short distance.” No matter how powerful a technology is, there are numerous factors that stand between technical viability and widespread adoption—cost, usability, customer acceptance, business models, entrenched interests, regulations and so on.

In “Unleashing the Killer App,” Larry Downes and I described the crucial dynamic as the Law of Disruption.

As illustrated in the figure, technology improves exponentially, but social, political and economic systems tend to change incrementally. Only when the differential between existing conditions and what is technically possible becomes large enough are human systems jolted into disruptive change. These jolts are the openings for “killer apps,” new goods or services that are so compelling that they catalyze a new generation of products. VisiCalc, the first spreadsheet, was the killer app for personal computers. Mosaic, the first browser, was the killer app for the World Wide Web. The iPad was the killer app for tablets.

Let’s look at the adoption of the driverless car through the lens of the Law of Disruption, to see both how advanced the technology is and what social, political and economic systems might delay the “killer app” jolt.

Technology is the easy part. There’s ample evidence that driverless technology from Google and others is already better than many drivers. For instance, here is a riveting video of a 95%-blind man “driving” a Google car. Keep in mind that the video is more than two years old. The car’s progress has continued at the exponential rate illustrated in Figure 1 and will even accelerate once significant numbers of cars reach the road. That’s because, while we humans learn almost entirely from our own experiences, every Google car can learn from the experiences of every other Google car.

Blanketing the roads with Google cars will also provide incredibly detailed, up-to-the second information to the “cloud” about road conditions, traffic and travel times. Each car will draw on that information and know to be extra careful at dangerous intersections or know, say, that black ice was felt at a certain spot 15 minutes earlier.

With progress so rapid, the technology in the Google car has miles and miles of open road in front of it. Even skeptics seem to believe that the question about the timing of the driverless car is less “if” than “when.”

But the social, political and economic systems that could act as a limiting function on “when” are significant. Consider some of the commonly voiced hurdles:

The car will cost too much. Estimates are that each Google research car costs more than $300,000. This means, as BusinessInsider noted, that it costs more than a Ferrari. Prices anywhere near these levels will keep the car out of reach for mass adoption.

Customers won’t buy it. There is a widespread sense that most customers would never give up their spot in the driver’s seat, or trust a driverless car. One reader, @jackarmstrong, brilliantly captured this zeitgeist in his comment to Part 1 of this series::

For most American drivers, the car is our “iconic dream machine,” and our personal freedom and status statement. Americans dream about cars, and “no” able bodied person “dreams” to be
 “driven,” by “robot cars,” no matter how persuasive the stats appear on paper.

There’s too much liability. In our litigious society, car makers would never offer products that took the human out of the loop and thus shifted the liability for accidents to themselves. Legal liability for car makers could be huge if a malfunctioning car injured or killed people.

The car violates current business models. As I laid out in Part2, the driverless car has enormous ripple effects across a number of industries—some of which are quite dire. It could be in car makers’, car dealers’, insurers’, taxicab associations, etc., best interests to delay driverless technology as long as possible. Reader @Jacob Haynes articulated this issue well:

It is not Google that will sell this technology to consumers, it is auto manufacturers. Sadly, no auto manufacturer will sell a technology that will decrease the number of times cars are wrecked and that will make it easier to share cars.

Also, in the short term, it might be more prudent for car makers to market driverless technology as expensive options to existing designs, rather than to take Google’s disruptive approach.

The transition would take decades. The fleet of cars on the road turns over roughly every 10 to 15 years, so even if driverless cars were in production today it would be many years before they dominated our highways and started delivering the promised benefits. If the driverless car takes that long to matter, it might never happen, or at least not happen in our lifetimes. After all, we’re still waiting for our Jetsons-like flying cars.

My sense is that even under incremental-change scenarios, some of these hurdles would dissolve rather quickly.

Cost is the easiest to address. The components on which the driverless car depends are improving at the speed of Moore’s Law. Following Moore’s Law, a gigabyte of memory cost $300,000 in 1981 but less than $10,000 a decade later, less than $10 a decade after that and less than 10 cents today. From $300,000 to a dime in three decades: That’s the trajectory that the electronics in the driverless car are on. Cost will also decrease as developers optimize their designs for production, as opposed to building prototypes.

Personal habits would surely slow adoption, but people could come to trust the cars as evidence of effectiveness piled up. New drivers, immersed in computing technology since birth, might be more trusting than older drivers. After all, lots of people used to be scared witless about flying, but that issue has largely faded. There’s already evidence that young people are much less interested in driving than those of us of a certain age were. It seems that being able to connect via Tumblr and Facebook reduces the need to actually drive somewhere and meet a friend face-to-face. And it might be that aging baby boomers, raised with a love of cars and independence but faced with diminishing driving abilities, would embrace driverless cars as the best of the options available to them.

The liability issue is trickier—computers are completely capable of flying planes, including takeoffs and landings, yet, for liability reasons, every commercial flight has two humans in pilot’s seats. A study by Rand Corp. concluded that existing liability case law “does not seem to present unusual liability concerns for owners or drivers of vehicles equipped with autonomous vehicle technologies.” Instead, the study predicted the decrease in the number of accidents and the associated lower insurance cost would encourage drivers and auto insurers to adopt the technology—unlike with airplanes, where deaths are rare, there are tens of thousands of preventable deaths in cars each year.

The same study did predict that manufacturers’ product liability would likely increase and that this might slow the introduction of the technology. The Rand study suggested, though, that government might intervene and mandate self-driving cars if they prove to be half as safe as Google claims. After all, almost 370,000 people died on American roads between 2001 and 2009 and millions more were injured.

I can think of three plausible scenarios that, based on the compelling societal benefits and business opportunities, might jumpstart adoption. (Please add your own in the comments section below.)

1. Google Fiber Redux. Google is the most likely player to put hundreds or thousands of driverless cars on the road to prove their effectiveness and clear away short-term hurdles. Google has a tradition of having its employees use its prototype technologies, a practice known as “eating your own dogfood.” Given recently passed legislation in California legalizing driverless cars (with backup drivers), Google might deploy hundreds of Google cars to chauffeur Googlers around the state. Google could quickly log millions of miles and accumulate mountains of evidence on the safety and benefits of the car. (According to various news reports, the Google car has thus far been hit twice by other drivers and once caused a minor accident—while under the control of a human driver.) Google could then move to pilot the technology at a larger scale, perhaps in Las Vegas, because Nevada has also approved the car. Google could use its deep pockets to invest in the necessary infrastructure, take the liabilities issues off the table (by essentially self-insuring) and make the cars available in Nevada at competitive prices. Such an effort would mirror the Google Fiber strategy in Kansas City to demonstrate the viability of high-speed fiber networks to the home.

2. The China Card. Although there are too many imponderables and cross-industry conflicts to imagine that the U.S. federal government would get involved any time soon, one can imagine scenarios where more interventionist governments, like China’s, might intervene. China has greater incentives to adopt driverless cars because its rates of accidents and fatalities per 100,000 vehicles are more than twice those of the U.S., and its vehicle counts and total fatalities are growing rapidly. In addition, the Chinese government could be motivated to accelerate the adoption of driverless cars because of the trillions of dollars that it would save by building fewer and narrower roads, by eliminating traffic lights and street lights and by reducing fuel consumption. And then there is the competitive dimension. A driverless car initiative would fit into several of the seven strategic industries that the government is supporting. Chinese researchers have already made significant progress in the arena. And, of course, if China perfects a driverless-car system, it could export that system to the rest of the world.

3. The Big Venture Play. In this scenario, a startup steps into the market to launch a large-scale, shared, driverless transportation system. While this might appear to be the most outlandish of the three scenarios, the outline of a profitable business case has already been developed. The business plan was designed by an impressive team led by Lawrence Burns, the director of the Program on Sustainability at Columbia University’s Earth Institute and former head of R&D at General Motors. The plan is based on expert technical and financial analysis and offers three sustainable market-entry strategies. For example, the team did a detailed analysis of Ann Arbor, MI, and concluded that a shared-driverless system could be fielded that offered customers about 90% savings compared with the cost of personal car ownership—while delivering better user experiences. Analysis of suburban areas and high-density urban centers, with Manhattan as the case study, also yielded significant savings potential and better service. Such dramatic results promise tremendous business opportunities for a “NewCo”:

This is an extraordinary opportunity to realize superior margins, especially for first movers. In cities like Ann Arbor, for example, NewCo could price its personal mobility service at $7 per day (providing customers with a service comparable to car ownership with better utilization of their time) and still earn $5 per day off each subscriber. In Ann Arbor alone, 100,000 residents (1/3 of Ann Arbor’s population) using the service could result in a profit of $500,000 a day. Today, 240 million Americans own a car as a means of realizing personal mobility benefits. If NewCo realizes just a 1% market share (2.4 million customers) in the United States alone, its annual profit could be on the order of $4 billion. NewCo’s Business Plan explains how this idea can be realized quickly, efficiently and with effective risk management.

There are, of course, many assumptions built into such plans, but my review leads me to believe that it is a robust platform for serious exploration: In some form, the driverless car is coming soon. 

What businesses would Wal-Mart target? It already has a large database of companies -- think Sam's Club. Sam's Club has more than 47 million members and is the U.S.'s eighth largest retailer. Those numbers do not even count the Wal-Mart shoppers.

The 47 million are not all business members, but the number of businesses shopping at Sam's must be staggering. So, the market for cheap workers' comp insurance could be big for Wal-Mart. The buying power of the agency Wal-Mart runs would be enormous.

The agency that Wal-Mart will use for car insurance has a track record of providing goods and services to Wal-Mart, so it has made it over the first critical hurdle of establishing a vendor relationship with Wal-Mart. That is not an easy task.

Agents and brokers should keep their eye on Wal-Mart, as it may soon provide very stiff competition in the world of business insurance -- business liability and owners polices could be another ripe area for Wal-Mart to exploit. 

Where there is profit, Wal-Mart tends to go.

The fact is that a driverless car would slash hundreds of billions of dollars of annual revenue, or even trillions, from all sorts of entities: car makers, parts suppliers, car dealers, auto insurers, auto financiers, body shops, emergency rooms, health insurers, medical practices, personal-injury lawyers, government taxing authorities, road-construction companies, parking-lot operators, oil companies, owners of urban real estate and on and on and on.

At the same time, the driverless car will create enormously lucrative business opportunities to serve new customer needs.

I’ll turn first to the revenue that is in peril and then examine the opportunities. (I invite you to offer your own ideas on potential business threats and opportunities. Please share them in the comments section below.)

While car sales might initially boom, as the fleet shifted to driverless cars, sales would then fall off a cliff -- and new and used car sales add up to a $600 billion-a-year business in the U.S. Any drop in sales would also affect auto finance companies, which write loans for almost 70% of new car purchases and half of used car purchases. Many parts would disappear from cars: Who needs airbags if you aren’t going to crash, or backup assistance when the car parks itself? The amount of steel used in cars would drop, because cars wouldn’t need to be as massive and sturdy. Body shops would mostly disappear for lack of business.

Auto insurers, which collect more than $200 billion in personal auto premiums each year in the U.S, would initially see profits rise as accidents declined and payments to customers dropped. They would, however, eventually see something like 90% of premiums disappear. In fact, the U.S. model of mandatory personal auto insurance might become archaic.

Emergency Room by French-Danish artist Thierry Geoffroy (Photo credit: Wikipedia)

Emergency rooms would lose millions of patients a year, and hospitals would have hundreds of thousands fewer people who needed to stay overnight. Health insurers would have to give up revenue as car-related injuries plummeted.

Personal-injury lawyers would see car-related cases all but disappear. In fact, the trend is already moving in that direction because the spread of cameras and sensors in cars makes it much easier to document who is to blame in an accident and removes the gray areas where lawyers may get involved.

If cars are in nearly constant use and can come when called, the need for parking almost vanishes. One MIT study claims that, in some U.S. cities, parking lots cover more than a third of the land area. Other estimates are that there are as many as 2 billion parking spaces in the U.S., about the size of Connecticut and Vermont combined. Much of this valuable real estate could be reclaimed for more beneficial social and economic purposes. At the same time, property values, especially in cities, would decline as additional supply becomes available.

Governments would lose fines, because cars would all obey traffic laws. At the same time, though, governments would save by not having to pay police officers to write tickets. They would also save by not having to set up traffic lights or to light streets—the Google car can see in the dark. Governments could spend less on prisons, because there would be no such thing as a drunk driver. Any new roads could be narrower, and thus less expensive, than current roads, because driverless cars don’t need nearly as much spacing between vehicles as those with sometimes careless drivers do.

Governments could also cut way back on widening and expanding roads to reduce congestion, because the switch to driverless cars would make such a huge difference. At the moment, a freeway operating at maximum efficiency is about 5% covered with cars, but driverless cars can be packed together in platoons, with just inches between the bumpers -- if the lead car has to slow down, it can simultaneously activate the brakes of all the cars behind it. The federal government spent $6 billion in 2009 on road widening and expansion, and state agencies spend more than $22 billion annually, so the savings on road work would be huge.

As government saves, though, utilities will lose as those traffic and street lights go away. Construction companies will lose as roadwork dives. Producers of cement and asphalt will likewise see business plunge.

Gasoline sales would tumble not only because of fewer cars but because they would operate more efficiently. Drafting behind another car can save more than 25% in fuel consumption.

Add up all the pieces -- $450 billion related to crashes, $600 billion of car sales, $200 billion in auto-insurance premiums, the hundreds of billions of dollars of health insurance that plausibly relate to car accidents and so on -- and you pretty easily get to about $2 trillion in revenue associated with cars each year in the U.S. Just about all of that revenue could be thrown up for grabs -- the result might turn out to be true cost savings or, at the least, a major shuffle among competitors.

On the opportunity side, driverless vehicles will allow for the reconceptualization of cars, car-related business models and competitive dynamics.

Expect styling to come to the fore, as vehicle design is less influenced by safety considerations like visibility, window placement, strength and stiffness of materials, bumpers, crumple zones, collapsible steering columns, air bags, seat belts and padding. In the short term, driverless cars will look much like today’s cars. Over time, as driverless cars dramatically reduce human error (which is the No. 1 cause of accidents) and more people accept the concept of shared cars, the possible car designs will explode.

Without having to worry about distracted driving, electronics companies and app makers could outfit cars with all the distracting entertainment they wished and earn billions off the now-free time in self-driving cars.

Lots of opportunities to coordinate use of cars would also appear. Companies could provide services to organize those platoons on highways or to share cars as part of a fleet -- all while charging hefty fees. One study found, for example, that an average two-mile taxi trip in New York City costs $8 to $13, depending on traffic conditions. It estimated that a fleet of 9,000 driverless cars could replace the city’s fleet of Yellow Cabs and operate for an average of 80 cents for a 2-mile trip. A more than 10-fold difference leaves a lot of room for profit!

New financing opportunities will arise. For instance, some company might offer a shared car for free in return for a multiyear contract to have that company operate the car -- an analogue to what mobile phone operators do now when they subsidize the purchase of phones.

New insurance models would arise, as insurers get smart about how to underwrite and distribute insurance in this new world. Imagine a day when a “driver” taps out his destination using Google Maps, and the system holds a real time auction for that trip. Insurers could, in real time, make their bids based not only on the driver’s risk parameters but also other significant factors including time of day, choice of route, weather conditions and who else is on the road. At some point, the liability model will flip -- with insurance becoming more of a manufacturer responsibility than the car owner’s -- because liability will be more dependent on the driving skills of the car than the owner.

In general, cars could be seen as a platform rather than as individual vehicles. Cars make for great antennas, and they have all the battery power they need for communication, so it would be easy to integrate them with each other. Car makers have long complained that they’re left selling the metal, while all the profits have migrated downstream to the people who provide the service, the repairs, the insurance and so on. If the car makers can position themselves as the fleet manager, they could recapture the profits because they would have control over the service, the repairs and everything else.

Car makers may also open their cars up in the same way that makers of smartphones have, so that lots of bright people could write apps that would make the use of a car more productive or enjoyable. A friend who works for a major car maker and who has access to its APIs has written an app that texts his wife and lets her know when he’s 10 minutes from home and is considering writing an app that will tell him when his wife’s gas tank is down to one-quarter full, so he can fill it for her. He has also written an app that texts his teenaged daughter and lets her know when she is 10 minutes away from having to leave wherever she is if she is to make it home before her curfew. (He says she appreciates the reminder.)

Thinking about cars as a platform raises the prospect that someone could produce a sort of operating system for that platform and capture a huge share of the value, as Apple did with its iPod and iPhone and as Microsoft did with personal computers. It also opens up vast potential for new products and services that ride on top of that operating platform -- an opportunity that is, no doubt, not lost on Google.

These thoughts are just the start of the changes that will come with driverless cars.

The bottom line: Driverless cars provide an opportunity to either make or lose an awful lot of money. The companies that understand and best prepare for this new world will win over those that don’t.

In fact, the driverless car has broad implications for society, for the economy and for individual businesses. Just in the U.S., the car puts up for grab some $2 trillion a year in revenue and even more market cap. It creates business opportunities that dwarf Google’s current search-based business and unleashes existential challenges to market leaders across numerous industries, including car makers, auto insurers, energy companies and others that share in car-related revenue.

Because people consistently underestimate the implications of a change in technology -- are you listening, Kodak, Blockbuster, Borders, Sears, etc.? -- and because many industries face the kind of disruption that may beset the auto industry, I’m going to do a series of blogs on the ripple effects that the driverless car may create. I’m hoping both to dramatize the effects of a disruptive technology and to illustrate how to think about the dangers and the opportunities that one creates.

In this installment, I’ll start the series with a broad-brush look at the far-reaching changes that could occur from the driver’s standpoint. In the next installment, I’ll show just how far the ripples will reach for companies—not just car makers, but insurers, hospitals, parking lot operators and even governments and utilities. (Fines drop when every car obeys the law, and roads don’t need to be lit if cars can see in the dark).

After that, I’ll explore how real the prospects are for driverless cars. (Hint: The issue is when, not if—and when is sooner than you think.) In the last installment, I’ll go into the strategic implications for every company thinking about innovation in these fast-moving times.

To begin:

Driverless car technology has the very real potential to save millions from death and injury and eliminate hundreds of billions of dollars of costs. Google’s claims for the car, as described by Sebastian Thrun, its lead developer, are:

1. We can reduce traffic accidents by 90%.
2. We can reduce wasted commute time and energy by 90%.
3. We can reduce the number of cars by 90%.

To put those claims in context:

About 5.5 million motor vehicle accidents occurred in 2009 in the U.S., involving 9.5 million vehicles. These accidents killed 33,808 people and injured more than 2.2 million others, 240,000 of whom had to be hospitalized.

Adding up all costs related to accidents -- including medical costs, property damage, loss of productivity, legal costs, travel delays and pain and lost quality of life -- the American Automobile Association studied crash data in the 99 largest U.S. urban areas and estimated the total costs to be $299.5 billion. Adjusting those numbers to cover the entire country suggests annual costs of about $450 billion.

Now take 90% off these numbers. Google is claiming its car could save almost 30,000 lives each year on U.S. highways and prevent nearly 2 million additional injuries. Google claims it can reduce accident-related expenses by at least $400 billion a year in the U.S. Even if Google is way off -- and I don’t believe it is -- the improvement in safety will be startling.

In addition, the driverless car would reduce wasted commute time and energy by relieving congestion and allowing cars to go faster, operate closer together and choose more effective routes. One study estimated that traffic congestion wasted 4.8 billion hours and 1.9 billion gallons of fuel a year for urban Americans. That translates to $101 billion in lost productivity and added fuel costs.

The driverless car could reduce the need for cars by enabling efficient sharing of vehicles. A driverless vehicle could theoretically be shared by multiple people, delivering itself when and where it is needed, parking itself in some remote place whenever it’s not in use.

A car is often a person’s second largest capital expenditure, after a home, yet a car sits unused some 95% of the time. With the Google car, people could avoid the outlay of many thousands of dollars, or tens of thousands, on an item that mostly sits and, instead, simply pay by the mile.

A study led by Lawrence Burns and William Jordon at Columbia University’s Earth Institute Program on Sustainable Mobility showed the dramatic cost savings potential. Their analysis found that a shared, driverless fleet could provide far better mobility experiences than personally owned vehicles at far radically lower cost. For medium-sized cities like Ann Arbor, MI, the cost per trip-mile could be reduced by 80% when compared to personally own vehicles driven about 10,000 miles per year -- without even factoring in parking and the opportunity cost of driving time. Their analysis showed similar cost savings potential for suburban and high-density urban scenarios, as well.

Driving could become Zipcar writ large (except the car comes to you).

Looking worldwide, the statistics are less precise, but the potential benefits are even more startling. The World Health Organization estimates that more than 1.2 million people are killed on the world’s roads each year, and as many as 50 million others are injured. And the WHO predicts that the problems will only get worse. It estimates that road traffic injuries will become the fifth leading cause of worldwide death by 2030, accounting for 3.6% of the total -- rising from the ninth leading cause in 2004, when it accounted for 2.2% of the world total.

If Google could give everyone a world-class electronic driver, it would drastically reduce the deaths, injuries and direct costs of accidents. The driverless car might also save developing countries from ever having to replicate the car-centric infrastructure that has emerged in most Western countries. This leapfrogging has already happened with telephone systems: Developing countries that lacked land-line telephone and broadband connectivity, such as India, made the leap directly to mobile systems rather than build out their land-line infrastructures.

China alone expects to invest almost $800 billion on road and highway construction between 2011 and 2015. It is doubtful, however, whether even this massive investment can keep up with the rising accidents and traffic congestion that the country endures. And road construction won’t deal with the issue of pollution, to which the massive car buildup contributes and which is becoming an ever more politically sensitive issue.

How might China and other developing economic powers’ massive car-related investments be redeployed if fundamental assumptions were viewed through the lens of the driverless car?

In sum, the Google driverless car not only makes for a great demo; it has worldwide social and economic benefits that could amount to trillions of dollars per year.

Insurers will feel major effects because hundreds of billions of dollars of reductions in losses obviously mean reduced requirements for insurance in all sorts of areas: auto, life, P&C, health and more; even workers' comp needs will diminish because so many claims that would have stemmed from car accidents simply won't happen. The locus of power in some parts of the insurance industry will shift, too. Why should a driver buy insurance if the car is doing the driving? Instead, car makers will likely take on the responsibility, and perhaps as part of their traditional approach to product liability, rather than working through auto insurance companies as they are currently constituted. I'll look at those issues and others next time.