Predicting SAAR, Deconstructing SAAR

Mike Smitka

As an economist, I avoid the prediction game. I am also wary of reading much into a single month's data. What an economist can do is to provide reasoning why over time a particular average level of sales makes sense, and levels significantly above/below do not.

Let me start with the monthly time horizon. Next Tuesday we'll get the latest sales numbers this coming Tuesday (August 2, 2016). Those numbers will tell use sales down to the last vehicle, except for Tesla, which reported sales of 2,250 for the past 4 months. That's a false level of precision. First, there's human error, though that ought to average out. A sale won't get reported, or digits will get reversed, or ... The Law of Large Numbers though means that while there will be over- and under-reporting by individual dealerships (and DMVs), those will average out and not cause much error in the total for the whole market. But one thing we know is that claiming there were exactly 1,513,086 light vehicles sold in the US in June 2016 is not true. When I present data, I try to round things off to 3 significant digits, here to 1,510,000 units.

I dutifully look at the numbers, but for the next year or so I really don't expect to learn anything from them

Then's there's the conceptual issue, that what "sold" means is less than clear. Dealers face incentives to tweak the numbers to earn "stair-step" incentives where one more vehicle can add a lot to their bottom line. Better to get the bird that's almost in hand by reporting a sale, than to carry it over to the next month when they might fall well short of (or significantly exceed) the threshold with an uncertain payoff. In Europe, discounting takes an indirect form: rather than placing cash on the dash, as it were, a car will be sold and reappear on the dealer's lot as a used car with zero mileage. They're "sold" and they're not. The data again offer a false sense of precision. Again, my sense is that an error (accidental or deliberate) in one month gets averaged out in subsequent months. But it does mean reading too much into one month is inappropriate.

Then there are the random factors, snow storms and holidays that fall midweek and ... there are such every month. Whatever the "true" level of demand, the performance in any reference period will deviate from that. Yes, we can apply seasonal corrections, and try to remember that February sales in a leap year will of course be higher, and sales in a month with 5 Saturdays may also be quite different. Such corrections however are but fancy averages, and so will never get the adjustment quite right.

So what can an economist say? There are the house economists at Ford and the others, who in conjunction with others in management need to provide a number for each product for the coming month and quarter and year for scheduling overtime and shutdowns at the plant level, for issuing purchase orders to suppliers orders for the next 30 days, and for planning capacity. In this role a house economist is as much soothsayer as professional. Formal models get combined with experience to which hunches are added, because at the end of the day there has to be a number. What will the Fed do? Over the past year, much less than the Federal Open Market Committee members themselves had predicted. But even if they bump short-term interest rates by another 25 basis points, will that affect the rates on car loans at all, or otherwise change sales? There's no reason to think they'll get this right any better than the traders who are betting billions on bonds.

why no mention of GDP: some "advanced estimate" components are good, the headline number not

An economist can however put some limits on what is likely to happen, using theory and a reading of the available data (which only show what happened last month or last quarter, never what is happening today, and absent theory tell us nothing useful about what will happen tomorrow). Here I look at two factors that influence automotive sales, interest rates and employment.

Employment first. Over the long run light vehicle sales correlate very closely with total employment, with about 1 sale for every .12 sales for every million workers, With 145 million people employed, that gives a SAAR of 17.4 million. This is not a tight relationship in the short run, and over the full period of the graph shows a downtrend. Indeed, a simple linear regression would suggest that I use .10, though for technical reasons that surely exaggerates the trend. In any case, that hints that 17.4 million is somewhat generous.

Employment continues to increase. Part of that is because the overall population continues to rise. Using age-specific population projections and the relatively stable rates of labor force participation prior to the Great Recession lets me estimate a normal level of employment, the red curve in the graph below. That's rising at about 58,000 a month in mid-2016, falling to about 50,000 by mid-2017 and 26,000 in 2018. In short, fertility plus immigration is barely offsetting the retirement of the Baby Boomers. On that basis the labor force will increase by only 900,000 workers over the next 2 years. That means we won't see SAAR rise by more than 100,000 units, which is smaller than the month-to-month volatility in the sales data.

But as we know, the US economy has yet to fully recover from our Great Recession. Compared against the demographic-corrected trend level, employment remains about 4.3 million below the pre-recession levels. The US economy has shown steady employment growth for the past 5 years, since summer 2011. We've also seen participation rates increase for prime-age workers, though that too remains below pre-recession levels. Barring a distinct slowdown or a boom – nothing in the real estate and residential construction markets suggests either – then we will keep adding jobs for another 2 years. Using the 0.12 figure, that will push car sales up by 0.5 million units. So if I were an optimistic, I could point to a potential SAAR of 17.5 + 0.1 + 0.5 or 18.1 million units by end-2018. I think the likely sustainable sales rate relative to employment is likely closer to 0.11, while the economy faces more headwinds than tailwinds...

How about interest rates? Here the picture is quite clear: they will stay low. First, the Fed is unlikely to raise rates aggressively, given the lack of signs of either inflation or accelerating growth. Second, across the globe growth are down. The developed world, plus China, are aging. The population of Japan is falling in absolute terms, and the working age population is falling in Europe and in China. Then there's productivity: an economy grows even with a fixed number of workers as long as output per worker grows. While we have new gadgets galore, the increase in productivity from having a smart phone is less than that from having a phone. We in the developed world see some gains, but the realignment of work that access anywhen to the cloud enables is only affects a certain share of jobs, is happening only gradually, and is not leading to large gains in output. That example can be repeated for a variety of technologies; see Robert Gordon's The Rise and Fall of American Growth for a systematic analysis. [The work structure example is my own.]

All of this is reflected in interest rates: they have fallen across all maturities, as reflected in bond prices. Furthermore, the yield curve suggests no upturn in interest rates for the foreseeable future (which for US bonds is 30 years), either due to stronger growth or to inflation (or, more accurately, the sum of the two). That strikes me as an odd bet to make at 20 year time horizon, and historically long-term bonds haven't been good indicators of what will happen. In the 3-5 year time horizon, however, the story told by bonds is more credible: we won't see a boom. I have both a basic interest rate graph, and one that looks at the implied yield on 1-year bonds, calculated for example from the difference in 2- and 3-year bond yields.

The final element is energy prices. My track record is abysmal, but so to my knowledge is that of everyone else. (For my posts on energy, See "Another Fracking Saudi Conspiracy Story" and here for "Peak Oil Revisited: Did I Get Anything Right?") From the perspective of extraction costs, the era of really cheap oil is over. For now, however, fracking offers a lot of potential at intermediate prices, while demand growth has slowed and the cost of alternative energy sources has fallen, including both solar and wind. The world has more natural gas than it can consume, and while over time the ability to transport it from where it is produced to where it might be consumed via pipeline and LNG ships will affect that, it's hard to see what might affect prices of gasoline in the US through 2018.

In conclusion, next week we'll see many column inches and blog posts dissecting the latest sales report. At the firm and maybe even segment level, it could contain information, though at the monthly level I'm still reluctant to play that interpretation game. More generally, we'll have more of the same. I dutifully look at the numbers, but for the next year or so I really don't expect to learn anything from them.

Thanks to Dr. Paul Traub of the Federal Reserve Bank of Chicago, Detroit Branch and former head economist of Chrysler for pointing out the strong correlation between employment and sales. This idea can be tweaked in various ways, setting up a multiple regression framework that would incorporate changing vehicle longevity, putting in a separate variable for those employed but over age 65 and for under 25, putting in a variable for changes in gasoline prices, and for the interest rate (or perhaps, using a combination of loan rates and loan maturities and vehicle prices, monthly payments). Obviously I've not done that.

Toyota ranks highest in overall service satisfaction in Malaysia

According to the latest J.D. Power 2016 Malaysia Customer Service Index (CSI) Study released today. This is the 14th annual survey and based on the findings Toyota ranks highest in overall service satisfaction (score of 763). They are followed by Mazda which ranks second (760) and Mitsubishi which ranks third (758).

The survey measures overall service satisfaction among car owners who took their vehicle to an authorized service center and is based on responses from 3,257 new-vehicle owners who purchased their mass market brand vehicle between February 2014 and May 2015. It examines dealership performance in five factors (in order of importance),viz., 1. service quality (32%); 2. service initiation (22%); 3. vehicle pick-up (18%); 4. service advisor (15%); and 5. service facility (13%). Brand service performance is measured on a 1,000-point scale.

 Click the link to read the press release.

Book Review: Nick Kachman's Paint it red

Mike Smitka

Nicholas Kachman, GM: Paint it Red. Paperback. Buena Vista, VA: Mariner Publishing, 2015.

Businesses fail all the time, indeed a new business is lucky to last 5 years. Few notice such passings. It's more puzzling why big corporations on occasion self-destruct. They command substantial resources and have professional staff to follow market developments, and to handle operational aspects of the business with a level of sophistication and specialization that the handful of individuals in a small firm cannot hope to match. In the case at hand, General Motors helped define not just the auto industry, from market segmentation and the annual model change to consumer finance and the management of styling. They also helped develop modern management, as the exemplar of the multidivisional company with the separation of staff and line and the use of return-on-investment accounting to allocate capital. It's appropriate that the business school at MIT bears the name of Alfred Sloan, the single most important individual in the transformation of the company from a flailing conglomerate to displace Ford after 1921 as the dominant force in transforming the industry. Market research, corporate-wide applied engineering that helped lower costs year after year, a strong dealer system – the company seemed to be all strengths. During the 1960s it was not only the largest manufacturing enterprise in the world, but it systematically earned a double-digit return on sales, returns on investment of over 20% and returns on equity of 40%.

Yet fail GM did, maintaining high levels of investment and an overall lack of panic as they lost 2/3rds of their 1960s market share. Unlike with smaller firms, that's horribly costly not just to investors: many retirees and pension funds were GM-heavy. It was also costly to hundreds of suppliers and customers (for a car company, that means dealerships), to a quarter million or more individuals with family members who worked there, which combined to traumatize whole communities. Unlike a small business, where the owner as manager bears both responsibility and loss, most of those hurt in GM's failure were innocent participants who had no input into the decisions that led to failure, and often little ability to insure themselves against the consequences.

So why did GM decline, year after year, with little apparent concern in the C-suite? Unions weren't responsible for cars not selling and plants sitting idle. Nor were they behind poor financial decisions, from the depletion of cash reserves (the proximate cause of any bankruptcy) to investment projects that failed.

Nick Kachman's book, ably edited by family friend Ethel Burwell Dowling, provides insights into this on two levels. First, it portrays the power plays within the company at the senior management level where accumulating personal power while undermining rivals became central to the fight for promotion. While he is not particularly analytic on this, the essence seems to be that those good at this sort of infighting were highly sensitive to anything that might leave them open to attack. In particular, several key individuals took reasoned criticism of proposals via memos and discussions at committee meetings as personal attacks and not normal professionalism.

The second, and more carefully argued part of the book looks at specific strategic decisions and how (and by whom) they were made. That GM was dysfunctional is not in itself a novel insight. Covering some of the same time period there is for instance Maryann Keller's 1989 book, Rude Awakening: The Rise Fall and Struggle for Recovery of General Motors. This however is a top-down analysis, highlighting costly strategic mistakes but not providing much insight into why and how they were made. Others, such as Steve Rattner in Overhaul: An Insider's Account of the Obama Administration's Emergency Rescue of the Auto Industry or Bill Vlasic's Once Upon a Car: The Fall and Resurrection of America's Big Three Automakers--GM, Ford, and Chrysler, provide insightful accounts of top executives and decisions more proximate to the Detroit Three's 2008-2009 crisis. Both – particularly Vlasic – point to toxic corporate cultures. They do not however provide insight into how those developed and how they molded decision making. By focusing on detailed examples Kachman makes a major contribution. At the same time that focus on detail makes it a challenging read.

Paint matters, and that is his story. As it happens I've been in paint shops at Toyota, Ford, GM and BMW. Paint was the big barrier to mass production in the 1920s; Henry Ford could assemble vehicles with great efficiency, but he was unable to shorten the weeks it took to get the paint on car bodies to dry. The development of the all-steel body by Budd and Chrysler in the 1920s changed that, as the entire body could be put in an oven to dry in hours. DuPont's new paints helped.^[note] Almost a century later paint shops remain the most expensive single section of an assembly plant, are the most energy-intensive section of a plant, are toxic, are the bottleneck in the flow of production, and are critical to visible quality. Kachman does a good job explaining that context.

So ... paint remained a headache, and it was also a target of environmental regulations, a mindset reflected in Richard Nixon's creation of the Environmental Protection Agency, which began operating in 1970. Paint goes on best when it is in a solvent, and at GM those solvents were volatile organic compounds (VOCs). They could be mitigated through better paint formulations, paint processes that got more paint onto vehicles and less on the floor, through sealing paint shops to keep fumes contained (which of course in a dust-filled factory is a good idea anyway), and through burning off the VOCs in a smokestack (and collecting waste paint and neutralizing it). But that was not the route GM took. Instead they wanted to move to water-borne paints that would eliminate the VOCs entirely.

The senior executives in charge fixated on using such paints. Those technologies now exist, but they did not in Kachman's day. With EPA deadlines looming, executives pushed ahead, without waiting for the development work that would "prove out" the processes. They weren't chemical engineers, and brushed off the concerns of Kachman, who by that point had almost 2 decades of experience and was justifiably worried that the commitments GM made would be impossible to keep. They were in addition expensive commitments, because shifting to water-based paints would entail closing assembly plants while paint shops were rebuilt. But by this time two key senior managers had bought in, one little-known outside narrow industry circles, and one of whom was the future CEO, Roger Smith. To cancel the project would jeopardize their careers. Neither chemistry nor expense mattered. Soon GM was committed to spend roughly $45 billion on new and renovated factories, with scant attention to the details of which plant would be built when and how that would affect the production of key products. Again, Maryann Keller and others had pointed out the huge investments made under Roger Smith in plants that never operated to potential. But her focus was on untried automation and failed product plans, and not on paint. As Kachman details, the addition of robots was an afterthought, something that could be done at the same time as the new paint shops to give GM a second "leapfrog" technology, while the product plans went awry in part because of the lack of planning on which plant would be redone when, leading to premature product terminations, premature introductions, or models kept in production too long. Keller and other contemporary critics focused on the robots and the cars that sold poorly, and thereby vastly underestimated the magnitude of paint decision that had more wide-ranging ramifications. They thereby also underestimated the poisoned nature of politics at the top of GM.

I won't provide more detail; I want you to read Kachman, not me. So far I have passed the book on to retired executives from a major global automotive paint firm and to a very senior person from one of GM's rivals, who worked directly with 4 CEOs. I'm a paint dilettante, and while to me Kachman comes across as someone who knows his stuff, my chemical engineering friend could attest that Kachman really does get the technical story straight. Then there's the more general management story. As my auto exec friend put it, someone who preferred overseas assignments to the politics at corporate headquarters (to which he was repeatedly promoted), "and I thought we were f...d up".

I may not use Kachman's book in my teaching, because my class is only 4 weeks long and I need to prep students in the first week for a series of visiting speakers and visits to auto companies, ranging up and down the value chain from suppliers to salvage yards. But I'm glad I stumbled across his book, thanks to meeting his editor/co-author Ethel Burwell Dowling, who ended up in the same rural Virginia community as myself. I will re-read it at some point, and keep recommending it to others in the industry. I hope to meet Kachman, too, and will ask Ethel for an introduction prior to my next trip to Michigan.

Clearing the Smoke on Tesla Deux

Mike Smitka

While Tesla the car company continues to burn through cash, Elon Musk is touting a capital-hungry vision of integration of his multiple ventures. As emphasized on Slate (The Folly of Elon Musk's New Master Plan), his core vehicle operations are crying out for operational attention. But without the battery plant, his future products won't exist, and without both the cars and the solar panels, his battery plant can't keep busy enough to make ends meet. Any one of the pieces alone is a daunting business challenge. Peer through the PR smoke-screen, and what he's saying is that none of the pieces stand alone. It's triple or nothing. That should give investors nightmares.

...[his strategy] is triple or nothing ... that should give investors nightmares...

Apropos to this blog, let me focus on the vehicle end of his house of cards. All would-be electric vehicle manufacturers continue to face the challenge that customers are uninterested in paying for being "green", outside of Musk's status symbol segment. Subsidies can kick-start the segment, but the budgets involved explode if sales prove robust, and become unsustainable politically. Even China set up its subsidies to phase out over time, or as sales (and costs to the government) rise.

His plan dismisses the competition. Musk isn't the only one aiming to reduce battery costs, but the gigafactory is a gigabet on one product. Others are ramping up in increments, as they add customers, with an "s". Now scuttlebutt from my co-blogger who lives in the vicinity is that battery plant is way behind schedule. Meanwhile if you add sales of the product pair of the Leaf and the Clio, you'll find that Nissan-Renault outsells Tesla. Their products are assembled on the same lines as standard "sister" cars. So they don't have to keep a billion-dollar factory busy with just one product. Plus when GM or R-N announce a new product to launch in 3 years, they hit that launch date, give or take a couple weeks. Not plus a handful of quarters.

One additional piece: inventory. To survive Musk will need dealerships that can provide service. Currently he has to haul cars that need repairs to and from one of his handful of shops, and provide "loaners" in the interim. As he moves downmarket, people won't have multiple "drives" in their car warehouse, and that will be both unacceptable to customers and too expensive relative to the cost of the product. Tesla dealers will also need 30-60 days of cars, and an ability to take trade-ins and provide finance. All these functions require real estate, too.

Carmakers have tried direct sales on and off for the past 100 years, including Henry Ford himself, and at Ford in 2000 (under Jacques Nasser). Now the success of dealership groups shows that it is possible to manage dozens of stores; dealerships don't have to be family businesses dominated by locally-based entrepreneurs. But Tesla ranks at the bottom in surveys of the quality of dealerships. If he is to move towards the mass market in the next 5 years, he really should be rolling out sales points, building service bays, hiring better managers, and spending hard cash on training now. After all, by the time he gets to market there will be multiple electric vehicles available. Customers may come to him, but as it stands his distribution system will drive them away.

...Musk is set to run out of cash and credibility, much the same thing...

The capital requirements for distribution are daunting. In the aggregate in the US there is $230+ billion in inventory for new cars. Real estate adds tens of billions more. Thanks to just-in-time production, inventories in manufacturing are but $30 billion, and that includes parts suppliers and not just vehicle manufacturers. If Tesla wants 2% of the market – 320,000 cars – then Musk will need to raise a lot more cash than he has to date, perhaps $5-6 billion just for distribution. Or he has to admit that his vision was illusory, and change his business model. He's running out of time – unless his next model really won't be ready until 2020. In that case, he'll have run out of cash and credibility, much the same thing.

To his credit, Musk has shown that thanks to the capabilities of supply chain and independent engineering houses, the entry barriers into manufacturing motor vehicles are lower than they have been in a century. The Chinese firms Chery, Geely, BYD and Great Wall, among others, provide additional testimony. Manufacturing however isn't enough; 30% of the industry's costs lie downstream, while keeping factories busy requires a careful product strategy that can roll out new vehicles on time and on budget. For new firms, those vehicles also have to be consistent good sellers. Musk has shown little or no recognition of those barriers, which have been the death of the visions of 4,000-odd ventures since the start of the industry. Tesla will make 4,001.

Transformation On Wheels: The Sentient "Car-Bot"

Bill Boldt                                                                                                   
Business Development Manager, Securirty
BlackBerry
                       

TRANSFORMATION... ON WHEELS

Cars have been a society transforming technology whose impact has rivaled that of  public sanitation, antibiotics, jet travel, telephone, and electricity.   Over time, the car has functioned as a status symbol, a rite of adolescent passage, provider of personal freedom, enabler of the formation of the middle class, and the catalyst of mass assembly and consumerism.  

THE EMERGING CAR-BOT

The next transformative event involving cars is already upon us, and it is a really big deal; namely, the "Car-Bot."    Cars are becoming self-propelled robots, and the Tesla with Autopilot is the poster child car-bot.   Autopilot truly does take the wheel and completely drive the car under certain conditions, like the highway. That is simply amazing.  Beyond Tesla, every car company, including new ones that are popping up, are going after assisted and autonomous driving. The established carmakers (or "OEMs" in auto-industry argot)  are just slower to make that happen since they actually have to run an industry with an existing manufacturing and distribution infrastructure and not just conduct a large scale science project that hit the road.  When the big guys get going we will see even more amazing things and on a scale that will change not just individuals' lifestyles, but cities, economies, and society itself.  

SOFTWARE-DEFINED VEHICLE

All car makers know the car of the future will be defined mainly by the software that gives it personality, purpose, and features.   The “software-defined car" will catalyze transformation including new ownership models such as shared or fractional and updatable performance and features.  There are already signs of fractional ownership and pay as you go usage. That is the Uber-effect.  Designs are already being presented for small buses ("bus-bots") that drive themselves to help ameliorate the crush of urbanization.  The bus-bot can solve important problems that urbanization poses, such as better resource utilization, reducing pollution, improved road safety, and less road congestion.

AUTOMOBILITY PLATFORM

The platform formerly known as the car is becoming a networked, sensing-actuating, connected, computer system of systems .  Sensors and actuators will communicate over a range of evolving electrical communications buses to act in a coordinated organic way, controlled by sophisticated integrated software and hardware inside and outside of the platform/vehicle.  The software and hardware must be cryptographically super-secure to create a truly safe system (i.e. one with very few crashes).  Cryptographic security means that mathematical algorithms like those used to secure electronic commerce web sites will be embedded into the vehicle and used to communicate to the vehicle.  This is known as Public Key Infrastructure (“PKI”) and ensures that the signals that sense and control things cannot be hacked, corrupted, or monitored. 

Cryptography maintains the confidentiality, data integrity, and authentication (the three pillars of security) of the various signals inside the car, between cars, and between cars and infrastructure to ensure safety, security, and reliability.  More on that later.                                                   

ORGANIC EVOLUTION 

The move to the car-bot started fairly humbly with in-vehicle entertainment, but will end up growing into a virtual organism of transportation-communication-and-lifestyle.   It is as if car radios, GPS, and cell phones were like single-cell organisms that materialized independently, but then linked up into multi-cell organisms.  More linkage is happening and the organism is evolving further.  Infotainment (the first linkage) is already linking with instrument clusters, ADAS, and more.  Hypervisors are making this happen.

What really made the linkage of segregated systems possible was the right kind of operating system.  And, in the case of a car it had to be safe, secure, and reliable.   Those three items cannot be over-emphasized.   Just ask car companies that made the mistake of not using the right type of operating system and had to go back to the drawing board. 

In parallel to the cockpit electronics evolution, there were other evolutionary branches on the locomotion and safety fronts that included Electronic Control Units (ECUs).   ECUs are little computers that intelligently control physical things like mirrors, lights, seats, AC, and other things in the body or cockpit.   More importantly, ECUs made for better control of brakes, engine systems, airbags, and other things that make the car stop and go and become safer.   

ECUs started out as discrete items that did one thing, but quickly became connected via in-car networks of various types such as CAN, LIN, MOST, Ethernet, etc.  These networks are like the prototypical spinal/nervous system in early vertebrates.  In addition,  ECUs (little brains) are becoming larger and capable of doing many more things at once (bigger brains).   This is represented by emerging domain controllers that are leveraging the amazing advancements in multi-core processing and architecture.    

                                                                             

BECOMING SENTIENT

Now that electrical automotive vertebrates have shown up, the evolutionary stage is being set for the omega point (i.e. the ultimate stage of evolution): Sentience.    Sentience means self-aware and self-controlled.  However, it is not just the vehicle that will become self-aware, it is the entire ecosystem that contains the smart vehicle, the cloud, and the smart/communicating cyber-physical infrastructure that interacts with it.

Note again that none of this can be possible without robust cryptographic security. Security is a leitmotif that will show up throughout the entire system. It must be everywhere at all times.  The sentient car-bot ecosystem will contain smart sensors, distributed processing systems, multi-level security, transmitters and receivers, and service providers, among others.  The bottom line is this:  No security, no sentient car for you.

THE TRIAD:  SAFETY, SECURITY, AND RELIABILITY

There are strong forces that are driving the software-defined, sentient car-bot evolution.  What underpins all of these forces is that each will require the triad of Safety, Security, and Reliability.   The triad must be present in all the systems in the vehicle from infotainment to instrument clusters, to body control, to engine control, etc..    The triad must be present at all times when the systems communicate with each other, with other vehicles, and with the infrastructure. The systems have to be secure even at rest to fight off attacks.   Service providers must provide services that are safe, secure, and reliable.  

Subscribers and vehicle owners will abandon products and services that are weak on any of the parameters.  The invisible hand of the market (as coined by Adam Smith) will kill companies and solutions that are not safe, secure, and reliable.   Respect the Triad!

Safety, security, and reliability must be forethoughts.  They are not products or features that can be offered as options.   They cannot be bolted on.  All three must be infused into everything at birth.    It is not hard to see that the parts of the triad are inseparable, meaning you cannot provide one without the other:  Can something be safe if it is not secure?   Can it be reliable without being safe?  Can it be reliable without being secure.  Clearly not.  The triad is the DNA of the software-defined car.  

Other articles will explore how designing with the triad in mind can make the software-defined future easier to create.  Hint:  it will require a safe, secure, and reliable operating system and end to end security.

In the meantime, please take a look at the QNX operating system and the security products from Certicom that secure the manufacturing supply chain and securely manage cryptographic keys and certificates.  Doing so will help you understand how another triad, QNX, BlackBerry Security Services, and Certicom, makes things not just secure, but BlackBerry Secure.