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Digitalization Disruption in the Automotive
Industry
By Bill Forquer, Priiva Consulting
Nov 2016
BACKGROUND
This paper was...
systems for mobile devices, namely Google (Android) and Apple (iOS)? Or with other 3rd
parties
having the experience to in...
structure and relationships for the market. Incumbents need to act quickly, double down on
their primary plan, revalidate ...
Mar 11, 2016 – GM Acquires Cruise Automation for $1B to Accelerate Autonomous Vehicles
Apr 27, 2016 - Ford and Google Lead...
operating
systems
 Regardless of the hardware decision, if and how should we license our Car OS to other car
(hardware) p...
software operating
systems
Car Mfg (Ford,
Daimler, BMW,
Audi, Toyota,
Honda, Kia, et al)
Incumbents from
USA, Germany,
Jap...
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Digital Disruption in the Automotive Industry - Nov 2016

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This paper was first presented at Stage-Gate International's Voice of the Ecosystem Summit in Jun 2016. It proposes using player-centric competitive response scenarios in a Stage-Gate model. A robust model of the digital disruption in the auto industry was developed to illustrate the power of this approach. Priiva is seeking either exclusive or a syndicate of stakeholders to develop additional variations and simulations.

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Digital Disruption in the Automotive Industry - Nov 2016

  1. 1. Digitalization Disruption in the Automotive Industry By Bill Forquer, Priiva Consulting Nov 2016 BACKGROUND This paper was first presented at Stage-Gate International’s Voice of the Ecosystem Summit in June 2016. Stage-Gate is the most widely recognized product development process in use. Practitioners of Stage-Gate manage their new product and existing product extensions using a structured sequence of gate criteria to pass to an additional round of internal funding in the next stage. Culturally, these organizations celebrate the funding stoppage of products that don’t pass their own criteria to funnel precious investment dollars to those products that optimize their gate criteria. When companies launch products, that launch will incite a reaction from the ecosystem of stakeholders – namely, current and future customers, competitors, and collaborators. And each of their reactions in turn incites additional reactions creating a cascading effect. This is comparable to an N-player chess match with each player eyeing the moves of the others, executing their own offensive attack while concurrently playing defense based on observations. Just as in chess, codifying and communicating the cascading and exponential possible outcomes quickly becomes unwieldy. Consequently, efforts tend to focus on current-state and lack a substantive forward looking view. Conference delegates were challenged to make their gate criteria more robust by moving beyond “competitive analysis” to “scenario based competitive response” using Priiva’s game-theory process for scenario modeling. This Auto Industry Digital Disruption Case Study was used to illustrate Priiva’s process and delegate reaction was quite favorable. Delegates provided additional input and validation for the model which held up to be quite robust. WHAT ARE WE SOLVING FOR? Game-theory scenario models are the most instructive when designed to optimize specific (not general – not every) strategic decisions. Forward thinking organizations may actually model a market from several perspectives to achieve the deepest insights. In this particular scenario model on the automotive industry, we are solving for the following strategic questions… 1. Do car manufacturing incumbents (aka Automotive OE’s) stay focused on that manufacturing and/or become transportation service providers? Using air transportation as an analogy, should Ford, GM, and others focus their efforts on manufacturing like Boeing or being a transportation service provider like United Airlines? Or can they be both effectively? 2. Can car manufacturing incumbents create sustainable differentiation by developing and controlling their own Car Operating System (“Car OS”) that is the heartbeat and central nervous system of the autonomous features in a driverless vehicle? Such incumbents are already managing complex systems of electronics and sensors – is a Car OS any different? Or are incumbents better off licensing or partnering with technology providers that provide operating
  2. 2. systems for mobile devices, namely Google (Android) and Apple (iOS)? Or with other 3rd parties having the experience to integrate various forms of sensor technologies? 3. How important is the consumer’s pre-existing mobile device or home automation operating system in the selection of an autonomous vehicle operating system? This consumer sentiment establishes if autonomous vehicles come pre-configured with a Car OS via exclusive licensing arrangements (i.e., limited consumer choice similar to the brand of tires that are pre-equipped on a new model) or if the consumer has full choice in choosing and configuring any Car OS? 4. Apple has backed off their manufacturing ambitions. Tesla has not. Google continues to position their intention to own and control the full stack of the Car OS and to manufacture cars as well. Is this real or just credible signaling on their part as they complete testing and fully determine their strategy? INITIATING A GAME THEORY PROCESS At the core, game theory scenarios encompass a relatively simple three-step process that identifies who the key players are, the things that they each can do, and the things that they each want to happen. THE NATURAL OUTCOME AND ITS INSIGHTS The Natural Outcome is an output of Priiva’s simulation software. The Natural Outcome is the first stable outcome achieved when all players pursue their natural interests as expressed in the preference trees. Priiva’s software revealed a Natural Outcome that aligns well with the interests of the Tech Player, Car-as-a-Service provider, and Federal Government. The interests of the Car Manufacturing Incumbent, GM, and Car Disruptor are not well aligned with the Natural Outcome. The Natural Outcome and some of its insights are listed below… 1. Disruption Prevails Over Status Quo. Incumbents are unable to hang on to the status quo as two forces dramatically disrupt the auto industry. Firstly, the decline of personal car ownership driven by digital players like Uber and Lyft who are ushering in a new era of on-demand transportation as a service much like the airline industry is shaped today. Secondly, autonomous driving features elevate the role and influence of Car OS Providers and diminish the power and influence of traditional manufacturing incumbents. Expect more commoditization, consolidation, and partnerships amongst these traditional players. 2. Two Power Players. The majority of power sits firmly in the hands of the federal governments and Tech Players providing the Car OS. All other players are highly sensitive to the actions of those two. 3. Incumbents Must Act Quickly. Those two largest power players both exert their own options early and without much sensitivity to others. Their assertiveness establishes the long-term ThePlayers Who is involved? Which players can affect the outcome of this game? Players'Strategic Options What can they possibly do? What range of potential options is under their control? Players' Preferences What each player wants to happen? What are the individual player's preferences for the available options?
  3. 3. structure and relationships for the market. Incumbents need to act quickly, double down on their primary plan, revalidate their contingency plans, and ensure their primary or contingency plans including alignment with the power players, AV sensor suppliers, and other market disruptors. 4. No market slow-down. There are no standoffs or deadlocks where this market will slow-down or freeze. All players execute their own strategic options in due time across four cascaded waves. The market will move as fast as autonomous vehicle technology becomes available including the requisite government regulations that accompany it. 5. Short-Term Innovations Could Stave Erosion of Personal Car Ownership. Consumers have a love affair with their automobiles. Incumbent manufacturers can use near-term innovations to keep that love affair fully in heat and not giving consumers a reason to give up their personal vehicles entirely. 6. Got Deals? Federal government has lots of tradeoffs with various players to negotiate deals related and unrelated to autonomous vehicles. TRACKING PREDICTED OUTCOMES Events are the chessboard moves in any market. Events, often overlooked as a strategic metric, are fundamental to tracking assumptions about players, preferences, and predicted outcomes. Priiva always works with its clients to track actual events against its models. This model was completed in June 2016. Time obviously marches on and events have occurred that validate two key insights, namely, that the market is moving fast and that disruption will prevail over status quo. July 6, 2016 – BMW Promises Fully Driverless Cars by 2021 in Partnership with Intel and Mobileye Aug 18, 2016 – Uber’s First Self Driving Fleet of Volvo XC90s Arrive in Pittsburgh for Testing Aug 31, 2016 – Google Takes on Uber with its Own Car Pooling Service Based on Waze Oct 17, 2016 – Apple Scales Back Ambitious Plans to Build Vehicles Oct 30, 2016 – GM’s OnStar to Integrate with IBM’s Watson Oct 31, 2016 – Ford Expands Commitment to Blackberry’s QNX as their Car OS THE CURRENT STATE The current state of the market is modeled in the formulation of players and their future options. Strategic choice by a player that has already occurred is never included in the model as a Player Option. Rather, that is now part of the core fabric of the player and the player’s future strategic options. The Priiva team, without any unique knowledge of the automotive market, began by monitoring market events to formulate the scenario model. Below are some material events that shaped that model and provided context around the current state. Many more earlier events are cited here in Wikipedia which provides an excellent overview. May 20, 2013 - Federal Highway Transportation Safety Agency Establishes Classifications for Vehicle Automation Jun 3, 2015 - Google Announces It Has Surpassed 1M Test Miles by its Autonomous Vehicle Fleet Nov 20, 2015 – Microsoft and Volvo Announce Partnership to Co-Develop Autonomous Vehicles Jan 20, 2016 - GM Invests $500M in Lyft
  4. 4. Mar 11, 2016 – GM Acquires Cruise Automation for $1B to Accelerate Autonomous Vehicles Apr 27, 2016 - Ford and Google Lead Lobbying Coalition Apr 28, 2016 – Google and Fiat-Chrysler Nearing Tech Agreement May 5, 2016 – Ford Invests $182M in Pivotal to Strengthen Mobility Software May 14, 2016 – Apple Invests $1B in Didi May 24, 2016 – Uber & Toyota Confirm Strategic Investment and Leasing Deal These events clearly show technology providers entering the automotive market either directly or via partnership and incumbent car manufacturers securing a toehold against future technology disruption. PLAYERS AND OPTIONS A fundamental decision in model design is the decision to include or not include a player. A simple litmus test to include a player (or not) in the model is to evaluate if that player has the ability to impact the behavior of another player already in the model. If a player’s own actions can influence the behavior of other players, they warrant being in the model. If that same player doesn’t influence the behavior of others, then that player can confidently be omitted from the model. Design experience has shown the most instructive models are those having 7-10 players and less than 30 total options across all players. For larger models, the mathematical algorithms hold up just fine but often the domain experts providing input don’t. A technique to validate model completeness is to formulate the best, likely, and worst case outcomes as three data points along a spectrum of outcomes (there could be 2**n possible outcomes where n is the total number of player options in the model). If the model expresses all three of those outcomes, then it passes the simple test for completeness. Another technique to simplify the model, particularly for a macro-view of a scenario, is to introduce the concept of a “composite player” whereby a single player in the game model actually represents two or more actual players whose strategic abilities and interests are identical or similar. For example, our model uses the composite player “Car Manufacturing Incumbent” to represent Ford, Toyota, Honda, etc. Priiva verified that the use of composite players didn’t over-simplify the model simply by developing a preference tree for Ford, Toyota, and Honda. If those preferences are identical or highly similar, then the use of composite players doesn’t degrade the model design. Note that our model calls out GM individually and doesn’t include GM in the composite player definition of Car Manufacturing Incumbent. The thinking was that the GM’s investment in Lyft and its Onstar customer base were strategic toeholds that that separated them from the rest of the pack of Car Manufacturing Incumbents. In fact, GM is the only individual player in our model. All other players are actually composite players. Each of the players, their high level persona, and the strategic questions relevant to our model are listed below. Player Persona Strategic Questions Tech Player (Google, Apple, MSFT) Aggressive technology disruptor that currently provides software  Since the mobile device market is saturated, are automobiles as devices our next competitive frontier?  Do we manufacture our own automobiles to drive adoption of our Car OS? E.g., with the Mac, iPod, and iPad, Apple has always controlled the hardware. Whilst Google/Android is far more open to hardware players. Will their historical behavior continue?
  5. 5. operating systems  Regardless of the hardware decision, if and how should we license our Car OS to other car (hardware) providers? How exclusive should be become to any given manufacturing incumbent?  Do car manufacturing incumbents have the ability to develop their own Car OS that interoperates with mobile devices thereby cutting us out of this new market?  Will the federal government under- or over-regulate our efforts to deploy our technology? Car Mfg (Ford, Daimler, BMW, Audi, Toyota, Honda, Kia, et al) Incumbents from USA, Germany, Japan, Korea, etc.  Will the Tech Players manufacture their own vehicles as a hardware device and thereby become a new, formidable, direct competitor?  Incumbents are already accustomed to integrating sensor technology in their vehicles. Is a Car OS supporting AV features just an evolution of that? Can we win with our own Car OS? Should we continue to develop our own or hedge our bet? Should we exclusively license a Car OS from a Tech Player or one of our existing sensor technology providers? Should we non-exclusively license? Will consumers care about their Car OS the same way they care about their mobile device?  Car-as-a-Service (CaaS) providers want to end personal car ownership thereby decreasing demand. How can we block, forestall, or join their ambition?  If Car-as-a-Service providers are successful, how do we adjust our business model to align to fleet buyers rather than individual consumer buyers?  Will the federal government provide regulations that favor us given the economic impact of our industry? GM Incumbent with connected car toehold via OnStar  All the same questions as the Car Mfg incumbents above apply equally to GM.  How do we best leverage the brand and customer base of Onstar? Is it the basis for a future Car OS or is it an advanced infotainment system? Car Disruptor (Tesla, Faraday Future) Disruptive with autonomous features as well as electrification, business model, and driver experience  All the same questions as the Car Mfg incumbents above apply equally to the Car Disruptor.  How do we best leverage our most disruptive features? Car as a Service (Uber, Lyft, Car2Go et al) Disruptor wanting to end personal car ownership  Will consumers indeed “give up” their love affair for the automobile?  Can our CaaS model extend to more than personal transportation? For example, for home delivery, long-haul of goods and services, etc.  What backlash will occur when we cancel contracts with all our 1099 drivers once driverless vehicles are generally available?  Will the federal government provide regulations that inhibit our efforts given the economic impact CaaS could have on the automotive industry? Federal Govt Regulates transportation and safety  Can we help our home team incumbents gain competitive advantage during this period of disruption?  How safe is this technology? STRATEGIES AND INTERESTS OF EACH PLAYER ARE EXPRESSED AS PREFERENCE TREES Lexicographic preference trees (see definition) were used to codify the interests and reverse engineered strategies of each player in the model. A small number of technology and automotive domain experts were consulted to develop each such preference tree. The preference trees are used as input to Priiva’s proprietary simulation software which generates the sequencing of outcomes and insights on player behavior. The syntax of those preference trees is intentionally omitted from this paper but a more human-friendly narrative matching each player’s preferences is in table below. Player Persona Strategy Narrative Tech Player (Google, Apple, MSFT) Aggressive technology disruptor that currently provides Wants every car depending on their Car OS. Wants government to impose light regulations. Will manufacture cars (ie, the full stack) if that is the pre-requisite to winning every car. Doesn’t want incumbents or Car Disruptors developing their own OS, but are not overly sensitive to that because they believe those players will fail doing so.
  6. 6. software operating systems Car Mfg (Ford, Daimler, BMW, Audi, Toyota, Honda, Kia, et al) Incumbents from USA, Germany, Japan, Korea, etc. Favors status quo and fears disruption. Fears Tech Players entering with a full stack. Fears that govt will be light handed but wants them to be heavy handed to slow down others giving themselves more time to develop their own Car OS. Needs to win new car sales of CaaS fleets. Does not view Onstar as a viable Car OS. Tech Players need to fail at manufacturing so they become more amenable to partnering for the Car OS should their own Car OS dev efforts fail to be differentiating. GM Incumbent with connected car toehold via OnStar Not as fearful as Car Mfg incumbents as Onstar and Lyft investment provide disruption toeholds. Fears the government will be light handed but wants them to be heavy handed to slow down others and would like others to fail at their own Car OS efforts falling back to OnStar partnerships triggering more aggressive Onstar development. Car Disruptor (Tesla, Faraday Future) Disruptive with autonomous features as well as electrification, business model, and driver experience Fears Tech Players entering with a full stack. Fears heavy regulations and wants light regulation to favor autonomous features and electrification. Wants to win new car sales of CaaS fleets and is prepared to develop their own OS to do so. Not fearful of the actions by Car Mfg incumbents, GM, and does not view Onstar as a viable Car OS. Car as a Service (Uber, Lyft, Car2Go et al) Disruptor wanting to end personal car ownership Wants government out of the way and all parties to succeed getting genuine driverless cars to market which triggers their purchase of a fleet of driverless vehicles from multiple vendors and eliminates their expense of drivers. Federal Govt Regulates transportation and safety Wants all their own national players to be successful achieving driverless status as a means for their home team to regain worldwide dominance in the auto industry. Especially true for the USA. Will exert moderate regulations so as to not stifle innovation and not compromise safety. NEXT STEPS AND FOR MORE INFORMATION The model as developed is robust and provides an excellent high-level perspective of disruption in the auto industry. Priiva is seeking either exclusive or a syndicate of sponsorships to develop additional variations and simulations. Possibilities include… 1. Perform sensitivity analysis by varying the preferences of key players, in particular the Federal government, to determine if and how that changes the outcome. 2. Expand the set of players likely to slow down this innovation, namely insurance industry. 3. Expand the set of new entrant tech players beyond just the Car OS to include players providing hardware and sensors like Intel and Mobileye. 4. Consider if any car manufacturing incumbents warrant being called out as individual players (like GM is now) instead of being lumped inside the composite player definition. 5. A specific focus on product liability and the “free pass” that new entrants have received thus far contrasted with the litigious operating environment for incumbents. For further information about this report or sponsoring additional models, please contact: Bill Forquer Priiva Consulting Email: bill.forquer@priiva.com Twitter: @billforquer Web: bio

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