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.

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. 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. 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. 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. 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. 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