MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry

GREEN CAR FUTURE 2020

l
te
Pa
sh
i le
Sa
of
k
or
w

SCENARIO IMPLICATIONS FOR THE
al

EUROPEAN AUTOMOTIVE INDUSTRY
in
rig
O

Sailesh Patel
MBA Research Project
Cass Business School , London

Cover Image: Copyright BMW AG, Munich, Germany

GREEN CAR FUTURE 2020:

l
te
SCENARIO IMPLICATIONS FOR THE EUROPEAN AUTOMOTIVE INDUSTRY

Pa
sh
Presented by:
i le
Sailesh Patel
Reg. no. 100019537
Sa

In partial fulfilment of the:
of

Master of Business Administration (MBA) degree
k
or

Submitted for:
Business Mastery Project
w
al

Presented to:
in

Dr Mohan Sodhi
rig

Cass Business School
O

Date: 30th September 2011
Word count: 14,435

2

Preface

This business research project on „Green Car Future 2020: Scenario implications for
the European Automotive Industry‟ has been conducted in partial fulfilment of the
full-time MBA programme at Cass Business School, City University, London.

The intent of this project is to provide advanced strategic foresight for the European
automotive industry, by exploring critical mid to long-term forces likely to affect
industry competitiveness, and developing plausible 2020 scenario world-views which

l
te
challenge existing policy and business strategies to facilitate enhanced strategic

Pa
options within a range of potential „green car‟ futures.

It is envisaged that the real test of this research‟s value will be its ability to prove

sh
relevant to business leaders not only in 2011, but in each year to 2020, by moving

i le
beyond historically-based trends and forecasting to provide robust scenario-based
insights that enable valuable strategic planning, thinking, and action for a globally-
Sa
competitive Europe.
of
k
or
w
al
in
rig
O

GREEN CAR FUTURE 2020: SCENARIO IMPLICATIONS FOR THE EUROPEAN AUTOMOTIVE INDUSTRY

3

Contents
Preface ................................................................................................................................ 3

Definitions ............................................................................................................................ 6

Executive summary............................................................................................................. 7

1 Introduction................................................................................................................ 12

l
te
2 Research methodology ............................................................................................ 14

Pa
2.1 Target stakeholders ............................................................................................ 14

sh
2.2 Research objective ............................................................................................ 15

2.3 le
Research outline ................................................................................................. 16
i
Sa
2.3.1 Research question ....................................................................................... 16
of

2.3.2 Research method selection ....................................................................... 18
k

2.3.3 Research method approach ..................................................................... 22
or
w

2.3.4 Data collection and analysis ...................................................................... 27
al

2.3.5 Research limitations ..................................................................................... 31
in

3 Driving forces analysis ............................................................................................... 33
rig

3.1 Scope .................................................................................................................. 33
O

3.2 Method ................................................................................................................ 42

3.3 Trends and uncertainties .................................................................................... 58

4 Scenario development ............................................................................................. 63

4.1 Mapping uncertainty ......................................................................................... 63


4

4.2 Scenarios ............................................................................................................. 65

5 Scenario implications (2020) ..................................................................................... 69

5.1 Opportunities ...................................................................................................... 69

5.2 Risks ...................................................................................................................... 71

5.3 Opportunity horizon ............................................................................................ 74

l
te
6 Recommendations (2011) ........................................................................................ 75

Pa
6.1 CAPIRE stakeholder groups ............................................................................... 75

6.2 European automotive industry .......................................................................... 78

sh
le
Appendix ........................................................................................................................... 80
i
Sa
Bibliography ...................................................................................................................... 82

Acknowledgements ......................................................................................................... 86
of

About the author .............................................................................................................. 87
k
or
w
al
in
rig
O


5

Definitions

ACEA European Automobile Manufacturers‟ Association

BRIC Brazil, Russia, India, and China: ostensibly referred to as the
Emerging Market economies

CAPIRE Coordination Action PPP Implementation for Road-transport
Electrification

CARS21 Competitive Automotive Regulatory System for the 21st century

l
CORDIS Community Research and Development Information Service

te
EC European Commission

Pa
EPoSS The European technology Platform on Smart Systems integration

ERTRAC European Road Transport Research Advisory Council

sh
EU European Union

EU27
le
The 27 member states of the European Union, comprising Austria,
i
Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia,
Sa
Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia,
Lithuania, Luxemburg, Malta, the Netherlands, Poland, Portugal,
of

Romania, Slovakia, Slovenia, Spain, Sweden and the United
Kingdom.
k

Europe 2020 The EU's growth strategy for the coming decade, aimed at
or

making the EU a smart, sustainable and inclusive economy.
w

ICE Internal Combustion Engine
al

Intelligent Car Initiative EU programme aimed at accelerating the deployment of
in

intelligent vehicle systems on European and international
markets.
rig

LCV Light Commercial Vehicle
O

NAFTA North American Free Trade Agreement: trilateral trade bloc
comprising North America, Canada, and Mexico

OEM Original Equipment Manufacturer

PPP Public-Private Partnership

RTD (Programme for) Research and Technical Development


6

Executive summary

Energy access and mass-adoption of the automobile have shaped our
environments and the way we live for much of the 20th century, creating unforeseen
opportunities for a global automotive industry to prosper and fail in often unforeseen
ways.

In 2011, the European automotive industry stands on the brink of uncertain and
potentially unprecedented change – the purpose of this report is to explore these

l
te
complex global and industry unknowns and explain possible outcomes in the form of

Pa
plausible, bounded industry scenarios, which will challenge incumbent and new
businesses to test the resilience of planned strategies, and to develop readiness and
recognise opportunities in alternative futures.

sh
i le
This report is presented for the interest of the 14 consortium members of CAPIRE, a
public-private research initiative within the framework of the European Green Cars
Sa
Initiative, one of the three Public-Private Partnerships (PPP) of the EC European
Economic Recovery Plan announced in 2008.
of

Due to time-constraints and limitations on publicly-available information, this report
k

predominantly addresses passenger car scenarios; however it is envisaged that the
or

analysis and implications will be of value to all members, irrespective of market
w

interest.
al

Europe‟s automotive industry faces paradigm challenges over the next decade,
in

during which four certain global macro forces prevail: imbalanced population
rig

growth, resource demands, rebalancing of economic power, and universal access
to information. However, uncertain and dynamic forces – political, social,
O

technological, and many more – can have a profound impact on decision-making,
hence strong differences of opinion about the future prevail and uncertainty is high,
relative to business‟ ability to predict or adjust. These differences arise because trend
and forecasting methods are limited by their bias towards statistical mapping of
known relationships, with limited incorporation of new and unexpected dynamic
forces.


7

There are therefore clear strategic benefits to moving beyond short to mid-term
methods, namely by mapping the development of known trends and the influence
of critical unknowns and uncertainties, such that the most likely disruptive industry
scenarios are explored, and their resultant implications used to test and develop
future policy and business strategy.

Proven methods of scenario planning were employed, adapting economic models
of national competitiveness and evidence-based research to identify and relate
critical industry driving forces and their outcomes. The following four „Green Car

l
te
Future 2020‟ scenarios were thus identified as most likely to influence the

Pa
international competitiveness of the European automotive industry:

‘Renaissance 2.0’: The European personal transport market becomes

sh
the most sophisticated and demanding in the world, fuelled by
effective wealth generation strategies and innovation through
products and services; by comparison, the rest of the world are
i le
suffering under the might of shared financial liabilities, whilst their
citizens face high unemployment and provide only undifferentiated,
Sa
price-sensitive markets.

‘Global Wealth’: In this scenario, the emerging economies transition to
of

a near-developed state, and connectedness between the East and
West facilitates effective wealth generation and redistribution. There is
k

much homogeneity between markets, and the concept of „national‟
or

automotive manufacturers becomes outdated as products and
service offerings merge to be provided by large multinationals.
w

‘Advanced Austerity’: Financial shocks hit hard and persist across the
al

world‟s economies, slowing growth and refocusing governments on
their own liabilities and debts. The international automotive industry
in

becomes an uncompetitive environment, except for small
rig

entrepreneurs realising benefits from price-sensitive consumers.

‘Yin Yang’: Wealth from the West is redistributed to the East, as BRIC
O

nations collaborate to realise liberal and sustainable business
environments, fuelling indigenous wealth generation in products and
services. In contrast, the US and Europe are burdened by financial
shocks, poor access to energy, and a loss of knowledge workers to
opportunities in the East.

These scenarios are not predictions of the most likely automotive future, however
they provide a robust indication of how far the 2020 competitive landscape may –
due to critical driving forces - sustainably differ from that of 2011.


8

Implications for the competitiveness of the European automotive industry were
derived both from the scenario-building process, which is a strategic learning
process in itself, and from the final scenarios. Three key factors were identified as
most influential to the relative competitiveness of the industry: 1. Demand of the
European market; 2. Related and supporting industries (e.g. products and services);
3. Factor conditions, such as infrastructure and advanced conditions such as R&D.

Demand was predominantly influenced by the sophistication and size of market,
and identified to be the single largest determinant of competitiveness; one whose

l
te
relative development across international borders is significantly impacted by global

Pa
uncertainties. The future competitiveness of the European automotive industry is
therefore considered largely unknown. Faced with increasing competition from
emerging nations supported by government programmes, consideration must also

sh
be given to the mutual reinforcement of international and national competitiveness.

i le
Furthermore, as the automotive industry aims to transition into delivering products
and services, it must recognise that competitiveness in services may require different
Sa
factors to manufacturing competitiveness.
of

Accordingly, the top three scenario opportunities for each of the CAPIRE
stakeholder groups were identified as:
k
or
w

• Product and service innovation
Automotive Manufacturers
• Development of supporting industries
and Suppliers
al

• Manufacturing and delivery innovation
in

• Realisation of integrated transport model
rig

City Transport Authorities • Sustainable energy efficiency gains
• Enhanced quality of life
O

• Retail model innovation
Electricity Suppliers • Supply chain innovation
• Lifestyle market penetration


9

Conversely, the top three scenario risks for each of the CAPIRE stakeholder groups
were identified as:

• Differentiation and affordability
Automotive Manufacturers
• Investment costs
and Suppliers
• Capacity and service quality

• Transport capacity
City Transport Authorities • Market cannibalisation

l
• Living costs

te
Pa
• Capacity utilisation
Electricity Suppliers • Supply chain disruption
• Retail model resilience

sh
le
Hence, recommendations for immediate action, with the intent of maximising value
i
Sa
capture opportunities and minimising risk consequences, both now and in the future,
were identified for CAPIRE stakeholders as below:
of

Automotive Manufacturers and Suppliers
k
or

I. Develop affordable, integrated personal transport solutions
II. Deliver differentiated products and services
w

III. Share innovation risk in non-core aspects; design and develop
for flexible breakeven volumes
al

City Transport Authorities
in
rig

I. Develop indispensable transport infrastructure and services
II. Improve accessibility and affordability whilst monetising service-
delivery capabilities
O

III. Maximise efficiency through integration, and learn from the best

Electricity Suppliers

I. Develop a sustainable relationship with consumers lifestyle
energy needs
II. Provide a differentiated, integrated energy service through
suitable channels
III. Develop capacity and flexibility


10

This report concludes by advising all European automotive industry stakeholders to
consider the following factors in order to enable 2020 competitiveness:

 Future planning
 Strategy
 Operations
 Competencies
 Tracking events
 Overcoming resistance

l
te
Through deeper understanding of these scenario implications, and implementation

Pa
of suggested recommendations, Europe‟s automotive industry will be better
prepared to innovate and develop agility to compete in the green car future of

sh
2020 and beyond.

i le
Sa
of
k
or
w
al
in
rig
O


11

1 Introduction

In an increasingly unpredictable, complex world, this report aims to answer the
strategic dilemma that is foremost for the European automotive industry: How to
compete in the green car future, 2020?

Presented with long-term uncertainty, industries and businesses tend to adopt one of
three strategic postures (Knowledge@Wharton 2009):

l
te
1. Do nothing (the „zero-future‟ option): caution rules, no attempts
are made to analyse, anticipate, or predict beyond the short-

Pa
term, and major decisions are deferred until the fog of
uncertainty clears.

sh
2. Take a calculated bet on one particular future: a clear message
is presented, and bold action is taken that could play out as

le
brilliant, or fail through wishful thinking.
i
Sa
3. Separate knowns and unknowns, in order to explore possible
futures: scenarios, not predictions, are developed, focussing on
the development of agility and options.
of

Though postures (1) and (2) may prove successful, the risks for businesses committed
k

to such approaches are high, especially if the competitive business environment
or

undergoes irreversible and rapid change.
w

Hence, whilst acknowledging that „No one can definitively map the future, but we
al

can explore the possibilities in ways that are specifically intended to support
in

decision-making‟ (Shell International BV 2008) businesses that adopt posture (3) are
rig

more likely to be competitively enabled to reduce risks, and expedite effective,
informed strategic decisions in order to maximise potential benefits.
O

To provide maximum business value to the European automotive industry, this
research will be split into four principal sections:

 Developing an optimal research method to identify key driving forces and
produce relevant, applicable scenarios.
 Understanding the key trends and driving forces of change in the
automotive industry, and identifying the impacts and uncertainties.


12

 Constructing scenarios by mapping uncertainties, identifying themes, and
describing significant scenarios.
 Determining scenario implications and developing strategic
recommendations for the European automotive industry.

In doing so, it is hoped to provide a learning process; one which helps broaden and
deepen the understanding of stakeholders, and permits improved knowledge of the
trends and uncertainties which could impact the competitiveness of the European
automotive industry of 2020.

l
te
Pa
sh
i le
Sa
of
k
or
w
al
in
rig
O


13

2 Research methodology
2.1 Target stakeholders

This research is provided for business decision-makers in the European automotive
industry, with specific regard for the 14 consortium members of CAPIRE
(Coordination Action PPP Implementation for Road-transport Electrification), a
public-private research project within the framework of the European Green Cars
Initiative (EGCI), one of the three Public-Private Partnerships (PPP) of the EC

l
(European Commission) European Economic Recovery Plan announced in 2008.

te
Pa
CAPIRE aims to produce a dedicated roadmap based on an elaborated and deep
analysis of R&D needs, respective milestones and supporting measures. The project

sh
focuses on the definition of potential flagship projects which could foster the
competitiveness of the European Automotive Industry in the domain of Transport
le
Electrification as well as in the development of technologies and services to reduce
i
Sa
the European CO2 footprint. (CAPIRE webmaster n.d.)

The 14 CAPIRE consortium members, home countries, and their main business
of

activities are summarised in Table 1.
k
or

Home
CAPIRE member country Business activities
w

Car, light commercial vehicle, and truck
RENAULT France manufacturer
al

The world's largest private independent
powertrain and instrumentation systems
in

AVL LIST Austria developer
rig

Centro Richerche Fiat - Fiat Automobile
CRF Italy Group's research centre
O

Volvo Group's main technology research
Volvo Technology Corporation Sweden centre
Providers of IT innovation and technology
VDI/VDE-IT Germany services across automotive and other sectors
Suppliers of technology and services in
industrial, automotive, construction, and
Robert Bosch GmbH Germany consumer goods
OEM module and systems supplier to the
VALEO France automotive industry
Number 1 Spanish energy company, and
IBERDROLA Spain number 1 global wind power provider


14

Home
CAPIRE member country Business activities
Transport authority and operator for London's
Transport for London England public transport network
Auto supplier, covering Chassis & Safety,
Continental Teves AG Germany Powertrain and Interior
Climate and automotive components
HIDRIA d.d. Slovenia supplier
Household and personal products
Procter & Gamble Eurocor Belgium manufacturer
TÜV Rheinland Consulting Product development, certification, and
GmbH Germany approval services

l
te
Family-owned bus and tram manufacturer,
SOLARIS Bus & Coach Poland including hybrids (60% export activity)

Pa
Source: Author analysis of member websites
Table 1: CAPIRE consortium members and business activities

sh
2.2 Research objective

le
This business-focussed project, supplementing existing technology R&D programmes,
i
Sa
aims to inform and enable European automotive industry decision-makers
responsible for implementing the CAPIRE roadmap.
of

The importance of the European automotive industry to Europe‟s future cannot be
k

underestimated. Following the 2008 financial crisis, the EC‟s „Responding to the crisis
or

in the European automotive industry‟ publication recognised:
w

“With an annual turnover of €780 billion and a value added of over
al

€140 billion, it [the European automotive industry] makes a major
contribution to the EU's GDP. It exports far more than it imports, with a
in

surplus of over € 60 billion on overall exports of €125 billion. In addition,
rig

the sector plays a central part in tackling many of the key economic,
social and environmental challenges faced by Europe today, such as
sustainable mobility and safety.” (European Commission 2009b, p.3)
O

Therefore, the research objective of this project is to develop and evaluate the
business implications of plausible mid to long-term global scenarios likely to be of
highest sustained impact to the European automotive industry.


15

2.3 Research outline

In order to distinguish relevant, sustainable outcomes which challenge and
constructively inform the future strategies of the European automotive industry, the
research process must be designed to efficiently and effectively explore critical
uncertainties.

The primary resources available for this project include but are not limited to:

l
 Approximately 300 hours of MBA student time (40 hrs per week)

te
 Academic supervision to direct research and review drafts

Pa
 City University library resources
 Publicly accessible information sources

sh
In this section, a suitable research outline is determined by evaluating the five core
research elements illustrated in Figure 1. i le
Sa
Research Research Data
Research Research
method method collection and
question limitations
selection approach analysis
of

Source: Author analysis
k

Figure 1: Research outline process
or
w

2.3.1 Research question
al

The research question for this project has been formulated in consideration of the
in

goals of the CAPIRE programme, the challenges facing the European automotive
rig

industry, and the value of existing prevailing research.
O

A comprehensive literature review was performed, assessing the scope of existing
industry, academic, and public policy insights, trends, and foresights (see
Bibliography). Although a wealth of near-term insights and opinions can be readily
discerned, uncertainty about the future is commonly discernible as mid to long-term
foresights providing limited strategic direction and comparability, as illustrated by
the EC‟s sectoral overview of the European automotive industry:


16

“In the medium-term, the technological competition in this industry is
set to intensify, with different fuel and energy concepts plus intelligent
transport playing a particularly important role. […] In the long-term, the
global market for motor vehicles is set to grow substantially” (European
Commission 2009a, pp.9–10)

From a business perspective, notable anchoring biases were observed, with
research tending to assume that a product-based retail model will prevail in future,
while incorporating the substitution of emergent „green‟ technological
developments and associated infrastructure to varying degrees. E.g. J.D. Power and

l
Associates 2010, Phil Gott 2008, Housely Carr 2011.J.D. Power and Associates 2010

te
Pa
Limited consideration is evidenced from published research for the substitution and
disruptive effect of alternative product, service, and transport models, or the

sh
composite impact of political, economic, and social factors, for example.
Furthermore, consolidated research specifically evaluating the extent to which the

le
competitive position of the European automotive industry might be challenged is
i
Sa
notable by its absence.

Nonetheless, literature consensus is achieved on the core challenge facing the
of

global, and the European automotive industry – that of competing effectively in a
future in which sustainability and „green‟ (environmentally responsible)
k
or

considerations are no longer consumer preferences, but substantially business and
policy requirements.
w
al

Therefore, to inform and enable the European automotive industry, a timescale of 5-
10 years is identified as the strategic domain of critical uncertainty, urgently requiring
in

improved foresight to inform imminent mid to long-term competitiveness planning
rig

and action (see Figure 2), hence the research question for this project is formulated
O

as: „Green Car Future 2020: Scenario implications for the European Automotive
Industry‟.


17

l
te
Pa
Source: Jones 2010
Figure 2: Domains of strategic uncertainty

sh
2.3.2 Research method selection

le
To determine an appropriate research method, the common nature of the
i
Sa
challenge facing leaders in the automotive industry must be understood.
Schoemaker‟s research identifies strong parallels with CAPIRE members‟ interests:
of

“Senior executives commonly ponder such questions as "What might
k

give us continued competitive advantage?" and "What new product
or markets should we enter and how?" Both questions go to the heart
or

of a firm's strategic vision. […] Knowing the answers constitutes the
w

difference between muddling through and running the business from
day to day with confidence and foresight.” (Schoemaker 1997, p.43)
al

Thus, the dilemma for business is one of developing an appropriate strategic vision to
in

enable corporate planning for action within a range of possible future scenarios. To
rig

inform this strategy a variety of research methods may be utilised to provide future
foresight, including:
O

 Statistical techniques
 Decision analysis
 Standard forecasting
 Scenario techniques

Schoemaker‟s 1991 research describes extensively the limitations of statistical
techniques based on historically-derived, albeit complex models, which incorporate


18

multiple known variables within a simplified view of the world, or decision analysis
examining the effect of one variable whilst holding others constant. His research on
standard forecasting observed that:

“forecasts are often wrong (Smyth, 1983; Zarnowitz, 1984, 1985),
especially when dealing with the macro environment (Page, 1982;
Leamer, 1983) […] The more stable the game, the more valuable
forecasts are; the more unstable the environment, the more scenarios
may be of help.” (Schoemaker 1991, p.551)

Pierre Wack (1922-1997), a successful practitioner of scenario thinking at Royal Dutch

l
te
Shell, similarly identified the core risks of relying on forecasts alone:

Pa
“Forecasts are not always wrong; more often than not, they can be
reasonably accurate. And that is what makes them so dangerous.

sh
They are usually constructed on the assumption that tomorrow's world
will be much like today's. They often work because the world does not
always change. But sooner or later forecasts will fail when they are
i le
needed most: in anticipating major shifts in the business environment
that make whole strategies obsolete.” (Wack 1985)
Sa
Put simply, these traditional techniques produce outcomes which are to a large
of

extent bounded by the influence of known variables. For example, Thomas Watson,
chairman of IBM, predicted in 1943, "I think there is a world market for maybe five
k

computers." informed by his bounding of the future using existing market models.
or
w

However, if presented with scenarios that identify relevant and critical uncertainties,
it is unlikely that business leaders should fail to recognise and understand outcomes
al

in alternative futures. It is therefore advantageous to develop scenario techniques
in

that recognise and incorporate critical uncertainties and their driving forces, and
rig

bounds their potential impacts, opportunities, and risks in the form of relevant
scenarios.
O

Referring to Figure 3, mapping differing degrees of uncertainty, businesses can seek
to improve their knowledge of the future by:

 Firstly, identifying and developing a better understanding of the impact of
known trends – stable driving forces that will affect us and others, which
we can predict quite clearly. e.g. population growth, universal data
access, etc.


19

 Secondly, identifying and developing a better understanding of the
potential impact and driving forces of unknown trends – unstable forces
that will affect us, but that we cannot predict clearly. e.g. the price of oil,
recessionary recovery, demand for raw materials, etc.
 Thirdly, identifying uncertainties – relevant unknowns that could
significantly affect us - and developing an understanding of their potential
impact and driving forces. e.g. intelligent highways, government subsidies,
political succession, electromobility, etc.

l
te
Pa
KNOWN

sh
UNKNOWN
i le UNCERTAIN
Sa
of

Figure 3: Degrees of uncertainty
k
or

Scenario techniques can facilitate exploration of all the above degrees of
uncertainty, and to a large extent are concerned with the likely challenges and
w

outcomes of the unknown and uncertain. Though in use since the 1960s and 1970s, it
al

must be recognised that they are „a difficult technique to define and describe.‟ and
in

that their „very flexibility and widespread applicability seems to limit their general
rig

acceptance in everyday organisational use.‟ (Verity 2003, p.186)
O

Furthermore, some practitioners (such as Shell) sometimes draw a distinction
between scenario thinking, which is aimed at the exploration of uncertainties, and
scenario planning, which is aimed at applying scenarios to support decision-making,
using probabilities, decision analysis, etc, to support other strategy methods.
Henceforth in this document, „scenario planning‟ will be used interchangeably to
refer to both scenario techniques of thinking and planning, as both elements will be
valuable in order to derive implications for the European automotive industry.


20

Therefore, scenario planning to reduce uncertainty for the automotive industry
appears well-suited as a research method, as Verity, arguing for greater use of
scenario techniques in business environments that are increasingly complex,
changing, and global, notes Michael Porter‟s early advocacy of scenario
techniques to achieve competitive advantage:

“As Porter (1985) pointed out: „Every plan is based on an industry
scenario in one form or another, though the process is frequently an
implicit one‟. He was an advocate for practising scenario techniques in
strategy formulation. He recognised that the assumptions managers

l
used as background to generating their strategies were rarely made

te
explicit or challenged. By acknowledging the uncertainties, he foresaw

Pa
much improved strategy outcomes.” (Verity 2003, p.188)

Advancing Porter‟s research, Schoemaker further identifies industry and corporate-

sh
level conditions favouring the use of scenario planning, as described in Table 2.

i le
Sa
of
k
or
w
al
in

Source: Schoemaker 1997 p.48
Table 2: Business conditions favouring the use of scenario planning
rig
O

Though these conditions may not reflect the views of all organisations in the
automotive industry, the symptoms have historical precedent and reflect the
uncertainties and difficulties increasingly likely to be felt by the European automotive
industry. Therefore, scenario planning is determined as an ideal research method to
achieve the objective of this project.


21

2.3.3 Research method approach

Scenario planning is a flexible, non-prescriptive technique facilitating many different
research approaches, as its practitioners have noted, „There are different schools of
thought about what scenarios are for, how scenarios should be built and when they
should be used.‟ (Verity 2003, p.186)

Consequently, there are strong reasons why managers will resist or reject using
scenario techniques. Verity explains:

l
te
“One of the reasons why scenarios are not adopted more widely is this

Pa
divergent set of methodologies and the different emphases on
quantitative or qualitative input. It is difficult for managers to sift
through the different approaches and know, with confidence, which
one to adopt for which business issue.” (Verity 2003, p.187)

sh
Hence, to effectively develop „Green Car Future 2020‟ scenarios and produce
le
implications that will be confidently received and used by leaders and managers in
i
Sa
the European automotive industry, this section will draw upon scenario practitioner
experience to clearly detail:
of

 What the scenarios will be for;
k

 How the scenarios will be built;
or

 When the scenarios should be used.
w

What the scenarios will be for ____________________________________________________
al
in

The scenarios produced by this report aim to serve two primary business needs for
CAPIRE members and the wider European automotive industry:
rig

1. Strategic thinking: by exploring and highlighting large-scale forces that
O

could push the competitiveness of the European automotive industry in
markedly different directions
2. Strategic planning: by providing scenarios that encourage decisions
made today to play out well across several different scenarios

The scenarios will provide analysis of the driving forces affecting the competitiveness
of the European automotive industry within a range of critical uncertain futures.


22

Company-specific decision scenarios will not be within the scope of this project. It is
important to emphasise that the scenarios will not be a prediction of the most
probable futures, but will aim to serve as strategic tools to permit learning,
exploration, and decision-making, best expressed by Schoemaker‟s analogy:

“Suppose you are planning to climb a mountain. Corporate planning
of the past would provide you with a detailed map, describing the
predetermined and constant elements of the terrain. Of course, this
traditional planning tool is very valuable and, indeed, indispensable in
this case. Just as geographical mapping is an honored art and
science, so corporate mapping can be very useful. However, it is

l
te
incomplete. First, the map is not the territory, but an incomplete and
distorted representation (any two-dimensional map distorts the earth's

Pa
surface). Second, it ignores the variable elements, such as weather,
landslides, animals, and other hikers. The most important of these
uncertainties is probably the weather, and one option is to gather

sh
detailed meteorological data of past seasons, perhaps using
computer simulations.

le
Scenario planning, however, goes one step further. It simplifies the
i
Sa
avalanche of data into a limited number of possible states or
scenarios. Each scenario tells a story of how the various elements might
interact under certain conditions. Where relationships between
elements can be formalized, quantitative models can be developed.
of

Each scenario should be evaluated for internal consistency and
plausibility. For example, high visibility and heavy snow drifts are an
k

implausible combination. Although the boundaries of scenarios might
or

at times be fuzzy, a detailed and realistic narrative may direct your
attention to aspects you would otherwise overlook. Thus, a vivid snow
w

drift scenario (with low visibility) may highlight the need for skin
protection, goggles, food, supplies, radio, shelter, and so on.”
al

(Schoemaker 1997)
in

How the scenarios will be built____________________________________________________
rig

A typical scenario-building exercise, illustrated in Figure 4, requires the definition of a
O

core issue, scope, and stakeholders (to provide context and a „test of relevance‟),
followed by identification of trends and uncertainties, which are then developed
into scenarios by various means, and disseminated to permit strategic thinking and
planning.


23

Define focal issue
(test of relevance)

Identify trends and
uncertainties

Develop scenarios

l
Disseminate scenarios to

te
stakeholders

Pa
Use scenarios for strategic
thinking and planning

sh
Figure 4: Overview of typical scenario-building process
i le Source: Author analysis
Sa
Numerous sources have been referred for guidance, however only Schoemaker
provides a comprehensive ten-step guide to scenario-building and dissemination,
of

which is adapted in Table 3 to provide an overview of the scenario planning
k

activities included within this project.
or
w

Scenario planning activity Implementation within ‘Green Car Future 2020’ project
Time frame: 2020 (incorporating changes in technology,
al

products, services, competition, markets, economies post-
2011)
in

Scope: scenario implications for the European automotive
industry
rig

Issues: how to compete in the „green car‟ future 2020 –
1. Define the issues understanding uncertainty to industry risks and opportunities
O

2. Identify the major
stakeholders
See Section 3
3. Identify basic trends
4. Identify key uncertainties
5. Construct initial scenarios
6. Check for consistency
and plausibility See Section 4
7. Construct learning
scenarios
8. Identify research needs See Sections 5 and 6, including scenario implications and


24

Scenario planning activity Implementation within ‘Green Car Future 2020’ project
recommendations
9. Develop formal models Not in project scope
10. Create decision
scenarios Not in project scope
Source: adapted from Schoemaker 1997
Table 3: Scenario planning activities implemented in the ‘Green Car Future 2020’ project

The main purpose is to identify dynamics of critical uncertainties and potential

l
te
business environment states that might affect the competitiveness - for better, or

Pa
worse - of the European automotive industry. Table 4, adapted from Schoemaker‟s
experience of developing and applying scenarios in industry, provides the criteria
that will be used to direct and evaluate the quality of the final „Green Car Future

sh
2020‟ scenarios.
i le
Sa
How can you assess if your scenarios are good ones?
of

1. Objective: The scenarios should cover a wide range of possibilities and highlight
competing perspectives (within and outside the industry), while focusing on
k

interlinkages and the internal logic within each future.
or

2. Relevant: To have impact, your scenarios should connect directly with the mental
w

maps and key concerns of those who will use them (e.g., senior executives, middle
managers, etc.).
al

3. Consistent: The scenarios should be internally consistent (and be perceived as such)
in

to be effective.
rig

4. Distinctive: The presented scenarios should be archetypal - that is, they should
describe generically different futures rather than variations on one theme.
O

5. Sustainable: Each scenario should ideally describe an equilibrium or a state in which
the business environment might exist for some length of time, as opposed to being
highly transient. It does an organisation little good to prepare for a possible future
state that will be quite short-lived.

Source: adapted from Schoemaker 1997 p.54
Table 4: Essential criteria for successful scenarios


25

When the scenarios should be used ______________________________________________

The industry-level scenarios, themes, and frameworks developed within this project
should be used by firm managers for four complementary purposes:

1. To test existing strategy: by applying industry level scenario planning to
existing firm-level strategy, managers will be able to test the resilience and
flexibility of their strategies within a range of critical futures. Resilient
strategies are those which are sustainable across multiple scenarios.

l
2. To develop strategy (existing and new): industry level scenario planning

te
may be used to develop understanding of opportunities and risks within

Pa
existing strategy, and to identify and test new strategic opportunities.
3. To develop organisational awareness: by propagating scenario themes

sh
within the organisation, managers and employees can together benefit
from increased organisational awareness of risks and opportunities in
critical future scenarios.
i le
Sa
4. To develop organisational agility: responsiveness during uncertainty is
often demanded of modern organisations; by propagating awareness of
of

future critical scenarios an organisation can begin preparing for
uncertainty, and learn to understand and recognise signals and signposts
k

of change.
or
w

Ultimately, scenario planning can help an organisation make better decisions, as
illustrated in Figure 5, by encouraging multiple perspectives, and striving for an
al

integrated analysis and understanding of critical future scenarios.
in
rig
O


26

l
te
Pa
sh
i le
Sa
of
k

or

Figure 5: Generic levels of scenario analysis
w

2.3.4 Data collection and analysis
al
in

The data collection methods selected for this research will be aimed at supporting
rig

the production of scenarios that:
O

 Cover a wide range of possibilities
 Highlight competing perspectives (within and outside the industry)
 Focus on interlinkages and the internal logic within each future
 Describe sustainable futures

As the „Green Car Future 2020‟ scenarios will, by definition, aim to explore
developmental (change) factors in relation to context, the data collection and
analysis method most appropriate to this project is the case study. Thomas (2011)


27

offers the following definition of case study: "Case studies are analyses of persons,
events, decisions, periods, projects, policies, institutions, or other systems that are
studied holistically by one or more methods.”

Yin (2003) further defines a case study as:

“an empirical inquiry that:

 investigates a contemporary phenomenon within its real-life
context; when

l
te
 the boundaries between phenomenon and context are not

Pa
clearly evident; and in which

 multiple sources of evidence are used.”

sh
To analyse the perspectives, interlinkages, and driving forces influencing the

le
automotive industry in a plausible, cohesive manner, it will be necessary to obtain
i
Sa
and evaluate data from a variety of sources, in a method appropriate to the
subsequent scenario-based analysis. Rosenberg and Yates (2007 pp.449-450) outline
a framework for identifying and analysing data, as shown in Figure 6.
of
k
or
w
al
in
rig

Source: Rosenberg and Yates 2007 p.449
O

Figure 6: Identifying data collection and selecting analysis methods

However, in contrast to Rosenberg and Yates‟ approach of selecting data analysis
strategies after collecting data, scenario planning requires that an analysis strategy
(the scenario building method) is selected before collecting data, after which the
required data collection methods may be identified. It is evident that scenario
building will require the collection of data supporting content, thematic, and
statistical analysis, necessitating both qualitative and quantitative input.


28

Due to time constraints, resource limitations, and the requirement to collect a large
range of unbiased data, only secondary research will be conducted. As far as is
reasonably possible, attempt will be made to use multiple sources of evidence, and
to aid scenario learning by identifying relevant assumptions and limitations of
collected data (in so doing, it may also be more readily feasible for others to
develop this research beyond the scope of this project).

It is envisaged that the nature and quantity of data required will inhibit the
derivation of purely quantitative models of relationships by which to determine

l
te
driving forces; similarly, the incorporation of qualitative data will necessitate a more

Pa
stochastic method. It is therefore reasonable to determine that a heuristic method of
scenario building will be required in order to efficiently identify and understand
significant driving forces and their relationships within the timescale of this project.

sh
Henceforth, proven qualitative and quantitative models and frameworks will be
le
utilised for analysis and scenario building where possible, and where necessary,
i
Sa
logical, bounded approximations to models will be developed and applied.
of

In order to capture a full perspective of the driving forces affecting or capable of
affecting the European automotive industry, data collection will encompass the
k

field-of-vision proposed by Day and Schoemaker, illustrated in Figure 7, aimed at
or

helping organisations1 actively capture strategic signals from the periphery.
w
al
in
rig
O

1 Although Day and Schoemaker‟s original intent was to help capture signals at the organisational
level, many of the areas identified are equivalent at industry level, and therefore these areas are
considered advantageous for identifying driving forces at industry level.


29

l
te
Pa
sh
Source: Day and Schoemaker 2007 p.22

le
Figure 7: Capturing external and internal driving forces at the organisational level
i
Sa
Research will therefore be undertaken to identify the external and internal driving
forces affecting (or likely to affect) the competitiveness of the European automotive
of

industry by exploring the following five areas:
k
or

 Political, legal, social, and economic forces
 Emerging technologies and scientific developments
w

 Influencers and shapers
al

 Customers and channels
in

 Competitors and complementors
rig

To provide perspective within each source, appropriate macro-level evidence from
O

economic, industry, and consumer perspectives will be sought, using academic,
industry, and available media sources. Where possible, insights and opinions will be
derived from multiple disciplines and industry thought leaders, thereby developing a
„richness of insight‟ that is encouraged and desired when conducting – as Shell have
done – workshop-based, global scenario building processes (Lawrence Wilkinson
n.d.). It is also considered advantageous to refer to published scenarios at the
economic, industry, and consumer foresight level, spanning multiple timelines, as


30

these research sources, despite their differing methods, will help identify core data
sources and further inform the application of scenario planning techniques.

Together, the above approaches are intended to reduce bias errors when exploring
areas we don‟t know (second class – see Figure 3), and areas which are unknown to
us (third class), as observed by Schoemaker:

“Various biases - overconfidence, narrow framing, the tendency to
look for confirming evidence-plague all three classes, but by far the
greatest havoc is caused by errors of the third kind (Russo &

l
Schoemaker 1992). Although no fail-proof techniques exist to avoid

te
them, much improvement can be garnered by focusing our attention

Pa
on classes two and three.” (Schoemaker 1997, p.68)

By reducing systemic errors when collecting data in the realm of uncertainty,

sh
scenario planning is more likely to achieve effective understanding and learning
since, as Schoemaker (1997 p.68) described “it is essentially a study of our collective
ignorance.”
i le
Sa

2.3.5 Research limitations
of

To achieve the aim of this research project using available resources, the research
k

scope is intentionally limited to focus on the driving forces affecting the passenger
or

car market only; LCVs (Light Commercial Vehicles) and buses will not be explicitly
w

analysed. This decision is considered appropriate because, during 2009:
al

 14 million passenger cars were produced in the EU by 17 countries, in
in

comparison with only 1 million LCVs produced by 10 EU countries.
rig

 Truck production accounted for 0.25 million units, whilst buses represented
only 0.035 million units of production.
O

Source: ACEA 2009 p.70

Although EU production figures alone do not reflect the full interest of the European
automotive industry, the above data illustrates the greater significance of its car
production activities. Furthermore, as the market for LCVs and trucks is primarily
concerned with demand for transport of goods and not people, it is desirable to
separate this element from analysis of the market for cars and mobility, unless
determined as a key driving force. Nonetheless, it is envisaged that the analysis and


31

implications presented in this report will be of value to all members, irrespective of
market interest.

Implicit research limitations likely to influence this project will arise due to behavioural
bias; namely, the author of this report will, by definition, incorporate individual biases
into data collection, scenario development, and analysis, hence every attempt is
made to identify assumptions and minimise errors by seeking a broad range of
relevant perspectives. To mitigate against researcher bias and inexperience, the
final report will incorporate comments and changes advised by an experienced

l
te
academic professor.

Pa
Following the preliminary completion of this report, it may be desirable to solicit and
incorporate feedback from CAPIRE members, however to achieve these activities

sh
within the project timescale is unfeasible, therefore this intention may instead be
considered as the scope of a follow-on research project.
i le
Sa
of
k
or
w
al
in
rig
O


32

3 Driving forces analysis
3.1 Scope

This section details the scope and method used to identify the competitive
environment, major stakeholders, basic trends, and key uncertainties.

Focal issue ______________________________________________________________________

The focal issue is to identify the significant drivers of change that could result in

l
te
critical scenarios likely to strategically impact the competitiveness of the European

Pa
automotive industry in 2020. An overview of the approach to developing scenarios is
shown in Figure 8.

sh
i le
Sa
of
k
or
w
al
in
rig

Figure 8: Building blocks for scenarios
O

Drivers of change will include basic trends and key uncertainties, the significance of
which will be evaluated based on their likelihood of change and the sustained
impact this might have on the competitiveness of the European automotive industry.

Competitive environment ________________________________________________________


33

As the „Green Car Future 2020‟ project addresses the competitiveness of the
European automotive industry within a global environment, an understanding of the
scope and nature of the competitive context is warranted:

In 2005, the global automotive industry made over 66 million cars, vans, trucks and
buses. If vehicle manufacturing (only) was a country, it would have equated to be
the sixth largest economy in the world. (OICA 2006)

In 2011, the six major competing global automotive industry suppliers, defined by

l
economic interest and development are:

te
Pa
 The European automotive industry (EU)
 The North American automotive industry, including Mexico (NAFTA)

sh
 The Japanese automotive industry
 The South Korean automotive industry
 i le
The Emerging Markets automotive industries (BRIC)
Sa
The global market share by volume of each competitor is illustrated in Table 5,
describing relative 2009 passenger car production. Note that these figures do not re-
of

domicile overseas production by national car manufacturers, either through joint
k

venture production or wholly-owned overseas factories. Furthermore, there may be
or

a surplus between passenger car production and actual sales.
w
al
in
rig
O

Source: OICA
Table 5: Passenger car production worldwide - 2009


34

The relative share of total global sales is shown in Figure 9, describing total worldwide
motor vehicle registrations for 2010, and illustrating how the EU represents a market
for one in four vehicles sold in the world.

l
te
Pa
Source: ACEA 2010 p.77

sh
Figure 9: Motor vehicle registrations worldwide - 2010

i le
Sa
Trade between economic blocs provides an important global import and export
market for each competitor‟s business activities. The European automotive industry is
of

a net exporter of business activities, generating net value for the EU as highlighted
by the EC:
k
or

“With an annual turnover of €780 billion and a value added of over
€140 billion, it [the European automotive industry] makes a major
w

contribution to the EU's GDP. It exports far more than it imports, with a
surplus of over € 60 billion on overall exports of €125 billion.” (European
al

Commission 2009b, p.3)
in

The importance of the industry to Europe‟s prosperity is underscored by the scope of
rig

its network of business and economic activities, acknowledged by the EC:
O

“The European automotive industry is one of Europe's flagship
industries. It is a key driver of growth, exports, innovation and jobs. Its
impact filters down across a wide variety of other sectors. And it has a
particularly important cross border reach, with suppliers, manufacturers
and sales and servicing downstream creating a web of mutual interest
that touches every one of the EU's Member States.


35

As a consequence, the value of intra-Community trade in automotive
products is substantial with around € 360 billion in 2008. Any downturn in
the automotive sector therefore strongly affects other sectors and all
EU Member States. ” (European Commission 2009b, pp.2–3)

Highlighting the importance of exports, Figure 10 illustrates the relative contribution
by value of EU passenger car exports, whereby North America, Asia, and Eastern
Europe represent approximately 80% of total export value of €40 billion (down from
€60 billion in 2008).

l
te
Pa
sh
i le
Sa
of
k
or
w

Source: Eurostat
Figure 10: Relative value of EU passenger car exports – 2009
al
in

Overall, the domestic European market (illustrated as „EU‟ in Figure 9) represented
rig

the largest market for the European automotive industry, registering 16.6 million
passenger cars in 2009, of which 2.3 million cars were imported from non-European
O

automotive industries, primarily Japan and South Korea, as shown by units of sales in
Table 6.


36

l
te
Pa
Source: Eurostat

sh
Table 6: Origin of EU passenger car imports – 2009

le
However, when compared by value received (see Table 7), Japan (€8 billion) and
i
Sa
the Unites States (€3 billion) were the largest non-European industry competitors,
differences attributable to a higher average cost of cars sold.
of
k
or
w
al
in
rig
O

Source: Eurostat
Table 7: Value of EU passenger car imports – 2009

Nevertheless, the European automotive industry remains a net exporter for the EU,
representing a trade balance of nearly €26 billion in 2009 (down from €40 billion in


37

2008), as shown in Table 8. Note that these figures classify geographically European,
non-EU countries within the European Free Trade Agreement (EFTA) - Turkey,
Switzerland, etc - as export markets.

Source: Eurostat

l
Table 8: Trade balance of EU automotive industry passenger car sales – 2009

te
Pa
‘Green’ context _________________________________________________________________

The US, Japan, China, Korea and the EU have given priority to reducing the climate

sh
impact of automobile production and use by developing programmes which target
two outcomes: i le
Sa
1. Reducing primary energy requirements: Growing dependency on
primary (naturally sourced. i.e. non-fusion) energy sources suggest this
of

factor is very likely the most motivating one. “In the EU, 73% of all oil (and
about 30% of all primary energy) is consumed by the transport sector.”
k

(EGCI Ad-hoc Industrial Advisory Group 2008)
or

2. Reducing greenhouse gas effect on climate change: Vehicle emissions
w

are contributing to the increased concentration of gases that lead to
al

climate change; Figure 11 illustrates the global contribution of road
in

transport to total man-made CO2 emissions in 2007.
rig
O


38

Source: OICA 2007
Figure 11: Global contribution of Road Transport to man-made CO2 emissions

These „electromobility‟ and „green car‟ programmes primarily focus on developing
integrated transport methods to reduce the energy and climate cost of personal
mobility, and the production of commercially-viable electric vehicles, which can be
powered from „clean‟ energy sources and are estimated to reduce energy demand
beyond that achievable by internal combustion engine (ICE) cars:

l
“A comparison with the situation ten years ago shows that in the last

te
decade the technological evolutions have radically changed the
impact of the electrical vehicle on primary energy consumption: from

Pa
about 30% higher primary energy consumption as compared to the
ICE in 1998 to about 25% energy savings in 2008. These figures do not
yet take into account the potential for energy harvesting e.g. by

sh
modern low cost on-board photovoltaic technology.” (EGCI Ad-hoc
Industrial Advisory Group 2008)

le
Nonetheless, traditional fuelled vehicles are widely expected to prevail by 2020.
i
Sa
Figure 12 illustrates the relative proportion of climate impact during the production
and use of a typical vehicle in use for 8 to 10 years.
of
k
or
w
al
in
rig
O

Source: WWF-UK 2006
Figure 11: Distribution of energy demand/carbon consumption throughout the life cycle of a
typical car

Major stakeholders ______________________________________________________________


39

Scenario stakeholders will be international or national groups or individuals who
have, or potentially will have, an interest in the drivers of change and their
implications for the European automotive industry, including those who could
significantly influence change.

Figure 12, adapted from Schoemaker (1991), provides an overview of the macro
and industry-level forces likely to affect industry, which will be utilised as a taxonomy
to identify influential stakeholders, with direct interest on driving forces inferred for
industry stakeholders and indirect interest for world and country stakeholders.

l
te
Pa
sh
i le
Sa
of
k

or

Figure 12: Typical industry-level driving forces
w

Interested and influential industry stakeholders include:
al
in
rig

 Suppliers European automotive manufacturers2
 Customers Private transportation buyers
O

Business transportation buyers

2 The vehicle manufacturing business is highly complex. It is not limited to the assembly of vehicles and
production of engines. The same manufacturers engage in testing, sales/marketing and distribution,
maintenance, recycling and disposal. Most also make components – although the degree of vertical
integration varies. They also have separate finance arms. These finance companies can provide
finance to their dealer network, leasing activities and to final customers (captive finance). In recent
years these non-automotive parts of a vehicle manufacturer's business have tended to generate more
profits than their core manufacturing assembly operations and in some years may have been the only
source of profits, thereby supporting the loss making automotive arm.(IHS Global Insight 2009)


40

Public transportation buyers
 Competitors Non-European automotive manufacturers3
 Substitutes Public transport suppliers
Alternative forms of personal transport suppliers
Alternatives to travelling suppliers (e.g. e-retailers)
Table 9: Major automotive industry stakeholders

Potentially interested and influential world and country stakeholders include:

l
te
Economic Related and supporting industries (e.g. energy)

Pa

Automotive industry employees
Aftermarket industry (servicing, parts, accessories)

sh
Automotive industry investors
Aftermarket industry investors
le
Related and supporting industry investors
i
Sa
Externality industries (e.g. infrastructure)
Customer stakeholders (e.g. employers, etc)
 Political Governments
of

Politicians
k

Regulators and legislators
or

 Social Non-profit externality industries (e.g. healthcare)
Society at large (male, female, young to old)
w

 Technological Automotive industry suppliers
al

Aftermarket industry suppliers
Related and supporting industry suppliers
in

Public transport suppliers
rig

Alternative forms of personal transport suppliers
Alternatives to travelling suppliers
O

Table 10: Major world and country stakeholders

3 There is no straightforward delineation of ownership interest between European and non-European
automotive manufacturers, as shared engineering, manufacturing, ownership, and joint ventures are
extremely common across the global automotive industry, as depicted by the „Tube Map‟
representations presented as Exhibits 1 (2005 environment) and 2 (2010) in the Appendix.


41

MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry

MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (20)

Similar to MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry

Similar to MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry (20)

Recently uploaded

Recently uploaded (20)

MBA Dissertation - Green Car Future 2020: Scenario implications for the European Automotive Industry