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An approach to scenario analysis of the sustainability of an industrialsector applied to clothing and textiles in the UK
J.M. Allwood*, S.E. Laursen, S.N. Russell, C. Malvido de Rodrguez, N.M.P. Bocken
Department of Engineering, Institute for Manufacturing, University of Cambridge, Mill Lane, Cambridge CB2 1RX, UK
Received 31 January 2007; received in revised form 13 May 2007; accepted 5 June 2007
Available online 2 August 2007
Abstract
Companies aiming to be sustainability leaders in their sector and governments wanting to support their ambitions need a means to assess the
changes required to make a significant difference in the impact of their whole sector. Previous work on scenario analysis/scenario planning
demonstrates extensive developments and applications, but as yet few attempts to integrate the triple bottom line concerns of sustainability
into scenario planning exercises. This paper, therefore, presents a methodology for scenario analysis of large change to an entire sector. The
approach includes calculation of a triple bottom line graphic equaliser to allow exploration and evaluation of the trade-offs between economic,
environmental and social impacts. The methodology is applied to the UKs clothing and textiles sector, and results from the study of the sector
are summarised. In reflecting on the specific study, some suggestions are made about future application of a similar methodology, including
a template of candidate solutions that may lead to significant reduction in impacts.
2007 Elsevier Ltd. All rights reserved.
Keywords: Scenario analysis; Sustainability; Industrial sector; Clothing and textiles
1. Introduction
Work to date in the broad area of industrial ecology has
a strong focus on measurement, and if practical change is
discussed, it is usually expressed through the instruments of
policy and economics or in the language of sociology. This
approach implicitly assumes that a catalogue of potential prac-
tical changes to production, product design or product usage
exists, so that the requirements for change are related to selec-
tion and motivation. However, there appears to be a shortageof work in specifying such a catalogue of the potential changes
that should be considered.
Such a casual attitude to practical change would be justified
if sufficient changes had already been identified and were
ready for implementation, but this is far from the case. For
example, within the area of carbon emissions reduction, the
UKs Carbon Trust is committed to the UK governments tar-
get of a 60% reduction in emissions from 1990 levels by 2050
and has explored the range of changes that might lead to this.
Development of alternative energy supplies is anticipated to
contribute w16%, and the use of hydrogen based fuel cells
may extend this. However, the bulk of the reduction (more
than 60%), which is expected to come from energy efficiency
measures, is not linked to specific technologies. The Carbon
Trusts publicity material gives two examples: low energy
light bulbs and timed lighting switches, but these will makea negligible contribution. Their 2005 abatement curve [1]
which reports on potential carbon savings for the UK industry
sector, can identify only around 25% of existing carbon emis-
sions that can be saved through known technologies. While
motivation and implementation of change are important
aspects of developing a sustainable future, it appears that the
identification of practical solutions that will make a significant
change is also extremely important, but often overlooked.
In prior work, a comprehensive survey of known practical
changes that might lead to increased sustainability has been* Corresponding author. Tel.: 44 1223 338181; fax: 44 1223 338076.
E-mail address: [email protected](J.M. Allwood).
0959-6526/$ - see front matter 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jclepro.2007.06.014
Available online at www.sciencedirect.com
Journal of Cleaner Production 16 (2008) 1234e1246www.elsevier.com/locate/jclepro
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presented by Russell and Allwood [2], with a broader descrip-
tion of the context of such change in Russell [3]. The survey
attempted to provide a categorisation of practical changes to
product design, production processes and supply chain opera-
tion that have been implemented to date. However, being a sur-
vey, this work considered only what has been done previously.
Looking forwards, what are the really important changes thatshould be considered and may not yet have been attempted?
How will practical changes that lead to substantial reductions
in undesirable impacts be identified?
One approach to answering these questions is to use struc-
tured scenario analyses to consider the consequences of wide-
scale change to existing systems, and this approach is gaining
increasing attention in the pursuit of sustainability solutions.
This paper presents a methodology to apply scenario analysis
to examine the future sustainability of a whole industrial
sector and demonstrates its application in a five person-year
study of the future supply of clothing and textiles products
to meet UK demand [4].
Section 2 of the paper reviews previous work on scenarioanalysis, particularly as applied to sustainability. In Section
3, a methodology for applying scenario analysis to a whole
sector is developed, and its specific application to the UK
clothing and textiles sector is described. The results of that
study are reviewed in Section 4, and in conclusion, Section
5 reflects on the approach in the hope that it may be beneficial
for future studies of other sectors. A brief introduction to the
clothing and textiles sector is given in the Appendix.
2. Scenario analysis and its application to sustainability
A range of future techniques are used by organisationsand policy makers to gain insights into what the future may
look like, thereby laying the foundation for informed
decision-making. Pesonen et al. [5] provide a glossary of
definitions of such futures research methods which include
forecasting and scenario analysis. One of the major flaws in
analytical techniques such as forecasting is that patterns
extrapolated from historical events are imposed with the im-
plicit assumption that the world will remain relatively stable,
and the future is predicted based on events of the past. Bood
and Postma [6] suggest that the rise of (multiple) scenario
analysis has occurred due to the failure of traditional forecast-
ing techniques to provide credible results. A survey of indus-
trial corporations in the USA in the period 1977e1981 showed
that less than a third expressed satisfaction with traditional
forecasting techniques [7]. In fact, according to Wack [8], dis-
satisfaction with formal planning and forecasting techniques
led to widespread development and use of scenario analysis,
also termed scenario planning [9e11]. Schoemaker [10] gives
a comparison between scenario planning and other traditional
planning techniques.
The development of scenario analysis has been influenced
by a number of companies and institutes including the
RAND Corporation, Stanford Research Institute, Shell and
others [12]. Shell is credited with the introduction of scenario
analysis in the private sector, where it was developed for
strategic purposes and has been in use since the 1960s [13].
The development was driven by Pierre Wack and Edward
Newland for strategic decision-making purposes.
2.1. Definitions and classifications of scenarios
There is no universal definition of scenarios. Kahn andWiener [14], who explored the possible consequences of
nuclear proliferation in World War II, define a scenario as
a hypothetical sequence of events constructed for the purpose
of focusing attention on causal processes and decision points
[15]. Godet and Roubelat [16] define a scenario as a descrip-
tion of a future situation and the course of events which allows
one to move forward from the original situation to the future
situation. Van der Heijden [17] describes scenarios as tools
to research ones understanding of the world. In line with the
critical realism paradigm the objective is to challenge ones
own mental model of the future. By stretching these vari-
ables to their limits of credibility, one tries to create a number
of possible futures which, while plausible, are significantlydifferent from business as usual. Many authors emphasise
that scenarios do not predict, rather they allow us to examine
what might happen [18]. Rienstra [19] outlines the three basic
elements of scenarios as a description of: (1) the present situ-
ation, (2) a number of future situations and (3) a number of
events that may connect the present situation with the future
one.
Godet [20], Godet and Rouebelat [16] and van Veen-Croot
et al. [21] distinguish exploratory and normative or anticipa-
tory scenarios. Exploratory scenarios developed from descrip-
tion of the past extrapolated by present trends indicate which
scenarios might happen and then proceed to describe the pos-sible future outcomes. These types of scenarios are used to
stimulate thinking about the possible futures and aim to exam-
ine what can happen. For normative or anticipatory scenarios
the starting point is the desired future situation and these types
of scenarios explore how a certain target can be reached after
which targets are set and paths that will lead to the stated
future are described. Notten et al. [22] distinguish between
normative and descriptive scenarios. Normative scenarios
(also referred to as prospective, strategy, policy or intervention
scenarios) describe probable or preferable futures while
descriptive scenarios (also referred to as baseline, reference
and non-intervention scenarios) explore possible futures.
Fukushima and Hirao [23] and Notten et al. [22] distinguish
back-casting and forecasting scenarios depending on the
vantage point from which the scenario is developed. Back-
casting scenarios reason from a specific future situation and
then explore the paths needed to be taken to move towards
that point and arrive at desirable future situations, while fore-
casting scenarios take the present as their starting point and
project todays problems, trends and realistic solutions onto
the future. Leemhuis [24] classifies scenarios based on the
time horizons used for the planning process: business cycle
scenarios for shorter periods of up to five years, archetype sce-
narios for a horizon of 10e15 years and exploratory scenarios
for very long-term periods. Ringland [13] classifies scenarios
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as external, internal or system scenarios based on whether or
not the influences are under the control of the organisation
undertaking the study. External scenarios are those that exclu-
sively consist of influences outside the control of the organisa-
tion, internal scenarios take only factors under the control of
the organisation into consideration and system scenarios which
are mixed forms of external and internal scenarios containingexternal environmental influences as well as internal guidance
dimensions. Scenarios also differ according to their subject
of study and are classified as issue-based, area-based and
institution-based [22]. Issue-based scenarios take societal issues
as the subject of study; area-based scenarios explore a particular
geographical area such as a country, region or city; institution-
based scenarios (also subdivided into so-called macro, global,
archetypal, framework, external or contextual scenarios on
one hand and focused, decision, internal or transactional on
the other) address the spheres of interest of an organisation,
group of organisations or sector.
Scenarios may also be classified based on the nature of the
data as qualitative or quantitative scenarios. Van Veen-Crootet al. [21] term the latter objective methods and the former
subjective. Notten et al. [22] further classify scenarios based
on the range of possible futures taken into account as alterna-
tive or business as usual. They explain that alternative scenar-
ios describe futures that differ significantly from one another
and often developed in an effort to raise awareness and under-
standing about new or uncertain issues, while business as usual
scenarios adhere to the status-quo or to present trends and their
extrapolation into the future, where the aim is to fine-tune
strategy rather than develop new strategy, for example.
Scenario analysis is claimed by various authors to fulfil
a wide range of functions. The functions given below arefrom Rienstra et al. [25].
The signalling function e scenarios provide better insight
into uncertain situations
The communication and learning function e scenarios
stimulate thinking about alternative futures
The exploring and explaining function e scenarios show
how solutions for specific problems may become reality,
given certain policy priorities; they also present possible
solution strategies
The demonstration function e scenarios show the conse-
quences of specific decisions
The decision support function
Additional information on other quite similar functions of
scenarios is given by Bood and Postma [6].
2.2. Scenario analysis in sustainable development and
LCA studies
Interest in using scenario analysis as a means of visualising
plausible future paths for sustainable development has been
growing recently. The paradigm of sustainable development
inherently embraces futures research and thinking as the defi-
nitions and goals refer to both present and future generations
and according to Kelly et al. [26], sustainable development
is generally motivated by a real concern for the long-term
well being of humanity. Various international organisations
have developed global-level scenarios to indicate the implica-
tions of future global actions. For example, UNEP [27] in
global environment outlook (GEO-3) has developed four sce-
narios: the Market First scenario envisages a world in whichmarket-driven developments converge on the various expecta-
tions that prevail in industrialised countries; the Policy First
scenario in which strong actions are undertaken by govern-
ment in an attempt to reach specific social and environmental
goals; the Security First scenario assumes a world of great dis-
parities, where irregularity and conflict prevail, brought about
by socio-economic and environmental stresses; the Sustain-
ability First scenario pictures a world in which a new develop-
mental paradigm emerges in response to the challenge of
sustainability. The Global Scenario Group [28] has developed
three global scenarios: Conventional Worlds in which the
global system evolves without major surprises; Barbarization
scenarios which envision the grim possibility that social, eco-nomic and moral underpinnings of civilisation deteriorate;
Great Transitions scenarios which explore visionary solutions
to the sustainability challenge. Other global scenarios include
the IPCCs emissions scenarios [29].
Quist and Vergragt [30] give an extensive review of work
using back-casting to anticipate more sustainable futures.
Their emphasis is on a particular development from work
largely carried out by analysts to participatory back-casting
with extensive (and apparently in some cases, virtually exclu-
sive) stakeholder dialogue used to consider simultaneously the
definition of desirable futures and the means to attain them.
They use the SusHouse project [31] as a particular exampleof the back-casting technique, aiming to consider scenarios in
which future consumption is reduced and which includes
a study of sustainable futures for clothing care. Such a study
can clearly be undertaken effectively with a process based
on stakeholder participation e but is primarily based on opin-
ions rather than numerical analysis or modelling e for in-
stance, the economic analysis in the project was achieved by
means of a questionnaire. Such stakeholder led back-casting
based on opinion gathering might be less effective in consid-
ering more broad structural changes to a sector, such as the
location of production, selection of materials, or changes at
a macro-economic level.
Scenario analysis is increasingly being incorporated into
life cycle assessment (LCA) as a means of analysing possible
future outcomes on the environment. For example, Ubbels
et al. [32] used four globalisation scenarios to analyse the
development of the international transport sector, Tan and
Khoo [33] analysed the environmental performance of a pri-
mary aluminium supply chain and Sonesson and Berlin [34]
analysed the environmental impact of future supply chains
for dairy products.
Even though scenarios are in some sense an integral part
of LCA studies, they were not always dealt with explicitly and
as such the SETAC-Europe LCA Working Group Scenario
Development in LCA started work in 1998, with the goal of
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focusing on the use of scenarios in life cycle assessment. The
group defines a scenario in LCA as a description of a possible
future situation relevant for specific LCA applications based
on specific assumptions about the future, and (when relevant)
also including the presentation of the development from the
present to the future [5]. The two general classifications of
scenarios in life cycle assessment studies used by the groupare what-if scenarios and cornerstone scenarios: what-if sce-
narios, the more widely used of the two, are generally used
to compare two or more options in a situation familiar to the
researcher, whereby a hypothesis can be defined on the basis
of existing data. They are often studies where some specific
changes within the present system are tested and their environ-
mental impacts studied. The results of an LCA study using
what-if scenarios are typically quantitative comparisons of
the selected options, offering operational information in
short- or medium-term decision-making situations. Cornerstone
scenarios do not necessarily give quantified results comparing
different alternatives, but offer guidelines in the field of study
and typically serve as a base to further research. In LCA studiesusing cornerstone scenarios several options (which can be very
different) are chosen. The alternatives serve as cornerstones of
the specific field, allowing for an overall view of the field of
study.
3. Methodology for scenario analysis of sustainability
The introduction to this paper offered a challenge e what
would lead to major change in the impacts of a sector? The
review of the previous section showed that scenario analysis
has been widely developed and is increasingly being used
for exploring options for future sustainability. This paperaims to build on previous work in two ways.
Where LCA studies have incorporated scenarios, they
have focused on purely environmental measures. The pa-
per proposes additionally the use of quantitative economic
and social measures to develop a graphic equaliser of
sustainability indicators to allow comparison of different
scenarios.
Previous studies have used scenario analysis to consider
the future of urban or regional systems, products and sup-
ply chains. This paper attempts to apply scenario analysis
to a whole sector.
According to the classifications in Section 2.1, the paper
specifically aims at exploratory scenarios: the aim is to
explore the possibility that an entire sector could be rede-
signed and to evaluate the potential sustainability of such alter-
native designs, in order to anticipate targets to direct current
decision-making. Quist and Vergragt [30] discuss creation of
future visions but limit their discussion to scenarios which
conceptualise technological and social innovations that are
imaginable now [31] and emphasise the creation of follow-
up agendas and implementation plans. In exploring possible
long-term futures of a complex sector, such as the clothing
and textiles sector, the creation of such plans would be
difficult, and probably largely hypothetical. For this study,
the development of a transition process to connect the present
to the future scenarios was deemed less important than identi-
fying the scenarios that would lead to a major change in
impacts. This approach could be questioned: are scenarios
created in this way meaningful if a change process has not
been specified? In a specific business strategy exercise, theanswer to this question would probably be negative. However,
in considering long-term ambitions of sustainability the tran-
sition process is clearly complex, and depends greatly on the
willingness of customers. In turn, customers are influenced
by their vision of how their choices might lead to a more sus-
tainable future and what that future could be. Accordingly, the
aim of this study is to define targets to give a vector for
future decision-making and information.
The literature contains various models for constructing sce-
nario analyses, all with a similar basic structure. Fig. 1 pres-
ents the process as described in this paper. The blocks at the
left of the figure are typical of such processes in the literature,
and are adapted from Bood and Postma [6]. The process is asfar as possible undertaken sequentially, but it is an interactive
and iterative process where final scenarios are constantly being
refined to come up with an agreed set of scenarios to examine
for a particular situation. The right side of the diagram empha-
sises the significance of dialogue between the project team and
representatives of stakeholder groups across the sector.
The remainder of this section describes key components of
the process of Fig. 1.
3.1. Understanding the sector as it is
A first requirement for analysing the future of a sector is to
characterise its operation at present. For most sectors, associ-
ations and analysts will have this knowledge, so from literature
searches it is possible to develop an initial map of the range of
businesses required to allow completion of final consumer
products. However, such a map is in fact a snapshot of how
the sector operates at present e and represents only one stage
in its evolution. The current arrangement of businesses, their
location and size, capabilities and culture, have evolved over
time to balance various objectives, and will continue to
change. The objective of scenario analysis is to consider
whether a different form of the sector would allow a different
balance between these objectives, specifically as far as this pa-
per goes, balancing the objectives of the triple bottom line.
Accordingly, an influence diagram can be prepared e to char-
acterise the major influences that have led to the current
format of the sector, and its consequences. Strategy courses
in business schools typically use a PEST (Political, Economic,
Social, Technological) framework for analysis of the external
forces acting on a business or sector e or in a more extended
form a PESTLECH framework (adding Legal, Ecological,
Cultural and Historic factors). In the context of sustainability,
the consequences of the operation of the sector can be grouped
according to the economic, environmental and social measures
of the triple bottom line.
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information) is required to allow comparison between the sce-
narios. A difficulty in all discussion of sustainability is that
by definition many different measures must be considered, often
with different units. In order to assist in comparing the impacts
predicted for each scenario, the different measures will be pre-
sented in a consistent form using a graphic equaliser.
Environmental assessment of scenarios was conducted using
a standard LCA approach based on the Danish methodology for
SERVICE
PROVIDERS
APPAREL
INDUSTRY
CHEMICAL
INDUSTRY
RETAIL
NON-CONVENTIONAL
TEXTILE PROCESSING
CHEMICAL FIBRE
INDUSTRY
AGRICULTURETEXTILE
INDUSTRY
Fibre Yarn FabricFinished
fabric
Interior andhome
textiles
Textile applications
Clothing
(fashion)
Distribution and retail
Textileservices
Private use /consumption
Commercialuse
- transport- construction- furniture- agriculture
- hotels- hospitals- public services
- high street- specialist- independent store
- supermarket- online shop
POST-CONSUMERRECOVERY
ANDDISPOSAL
Fig. 2. Sector map for the clothing and textiles sector (from Well dressed?, Allwood et al. [4]).
Climate change - laundry
Toxic chemicals - cotton agriculture,pre-treatment, dyeing, printing
Waste to landfill
Water consumption - cotton
7% of world exports
~26 million direct employees
Volume growing prices dropping
Major export earner for somecountries
Working hours, safety, child labour
Labour insecurity
Minimum living wage/ legal wage
Rights to association
AGRICUL-
TURE
+MINERALS
Economic
Environmental
Social
Historical
Cultural
Ecological
Legal
Technological
Sociological
Economic
Political
INFLUENCES EFFECTS
RAW
MATERIALS
FIBRE
FABRIC
PRODUCTS
RETAIL
USE
DISPOSAL
REUSERECYCLE
RECOVER
Fig. 3. Influence diagram for the clothing and textiles sector.
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environmental design of industrial products. Calculations were
performed using the GaBi-EDIP software. The data used for the
analysis was based on that collected from the Danish EDIPTEX
project [35] and is believed to be the most comprehensive foranalysis of clothing and textiles products. Boundaries around
the analysis were set to include inputs of energy, water and
auxiliaries, but exclude capital goods, services and infrastruc-
ture. Typically, LCA studies report many impact categories.
However, in aiming to present measures across the triple bot-
tom line of sustainability in a comprehensible format, some se-
lection was required to limit the number of environmental
impacts reported. Three categories were chosen to attempt to
represent overall impacts: climate change impact (reported in
thousand tonnes of CO2 equivalent), waste volume (reported
in thousand tonnes) and an aggregated environmental index
which gave a single measure of ozone depletion, acidification,
nutrient enrichment and photochemical ozone formation. The
impacts within this aggregated index are usually reported sepa-
rately, so were expressed in Person Equivalent Targeted
units e normalised to the fair share of one person e and
weighted according to political reduction targets. Strictly, LCA
studies are only comparable within identical boundaries e so
the use of LCA for scenario analysis which might includealternative processes, materials or locations could be mislead-
ing. To attempt to minimise discrepancies from such changes,
it was assumed that all electrical energy was generated accord-
ing to the profile of a single country. No formal third party
review of the study and the results has been carried out as this
is not required by the ISO 14044 standard. However, the LCA
model and the final results have been discussed with experts
at LCA center, Denmark. Based on the spot sample carried
out no significant errors were identified and the overall approach
was judged to be well suited to fulfil the goals of the study.
Economic assessment has been carried out via a simplified
set of National accounts calculated for each country involved
in the scenario. The accounting system is based on the Euro-pean System of Accounts (ESA) 1995 framework as applied
in the UK [36] and illustrated in Fig. 4. For each product,
an account of costs is created, showing the build up of the
retail price to UK consumers in which all profits taken by
companies in the supply chain are recorded as costs. Transfer
prices are calculated as the product passes between tiers of the
supply chain. Relevant components of the accounts are allo-
cated to the country in which each activity occurs (it is
assumed that all companies are owned within the country in
Table 1
Themes and scenarios used for analysis
Theme Scenarios
Production structure Localise production in the UK
Localise production in the UK and use innovative
labour saving technologies
Localise production in the UK, use innovative
labour saving technologies, and base productionon locally recycled materials
Consumer influence Extending the life of clothing
Best practice in clothes cleaning
New materials
and processes
Alternative fibres
Green manufacturing
Smart functions
Government influence Reduced barriers to free trade
Imposition of eco-tax
Table 2
Three case study products
Knitted cotton T-shirt Woven viscose blouse Tufted polyamide
carpet
Cotton farmed
and spun in the USA
Viscose made from
cellulose harvested
and processed in
India
Polyamide face fibres
and polypropylene
primary backing
made in the USA
Latex secondary
backing made in
the UKYarn knitted, dyed, cut
and sewn in China
Fibre is spun,
woven, dyed,
cut and sewn
in India
Carpet tufted
and dyed in the
UK largely
using automated
machinery
Wholesale and retail
in the UK
(460 million per year)
Wholesale and retail
in the UK
(33 million per year)
Wholesale and retail
in the UK
(8.5 million m2
per year)
Twenty-five washes
at 60 C with
tumble drying and ironing
Twenty-five washes
at 40 C with
hang drying and no
ironing
Vacuum cleaning
only in use over a
10-year life-span
Incinerated after disposal Incinerated after
disposal
Landfill after
disposal
Cost of farming/mining
Transfer price (material)
Cost of material processing
Transfer price (fibre)
Cost of spinning etc
Transfer price (yarn)
Cost of weaving/knitting
Transfer price (fabric)
Cost of making up
Transfer price (wholesale)
Cost of retail
Price to consumer
Country 1 Country 2 UK
+ /
+
+/
+/
+
+
Gross National Income
Balance of Trade
Operating surplus
People employed
Fig. 4. Economic model for scenario assessment (example for cotton T-shirt).
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which they operate). A contribution of the product to gross
national income of each country can be calculated. In addition,
for the UK, the balance of trade and an operating surplus are
calculated.
A key decision in developing an economic model for use in
this context is to determine how consumer prices vary as pro-
duction/supply-chain costs change. There are several possibili-ties: prices could be held constant, so that any change in cost is
reflected in a reduction in profits; profit margins could be fixed,
sothat any change in cost is reflectedin a change in final price to
the consumer; a market model could be used to predict the
proportion of changed costs that would be passed to the con-
sumer, and to incorporate some form of price elasticity to
show sales volumes changing with price. Naturally, the
simplest choice (fixed prices) assumes unrealistic consumer
behaviour, while more complex models are strongly dependent
on their assumptions. The intention of this work was to find
a simple way to link predictions across the triple bottom line
so a simple model was required. Given that the three case study
products are commodities, the price is largely determined bycompetitors, so the model used assumed fixed consumer prices
with all intermediate profits (for instance to raw material sup-
pliers) treated as costs. Thus a change in supply chain costs leads
to a change in the profitability of the retailer in the UK, and
hence to the UKs operating surplus, but the product price and
demand volume is assumed to be constant. The economic quan-
titative predictions of the analysis should, therefore, be inter-
preted as indicators of effects that will create change, not as
accurate predictions of the final change e the retailer would
not continue to sell commodity products at a loss and would
either change supplier or increase the price.
Quantitative social assessment is problematic as most of thesocial consequences of operation of the sector are difficult to
quantify in a way that could be meaningfully related to the eco-
nomic model. However, a reasonable prediction can be made of
the number of people employed due to the case study products
based on figures for productivity andworking hours. This is only
partially meaningful e if a country has full employment then
any new jobs created within a sector must be substitutes for
other jobs e so will cause loss of activity elsewhere. However,
in the case of the clothing sector, in agriculture and production
in particular, this approach is reasonable, as most jobs are
relatively unskilled and low paid, so will be available to those
who might otherwise struggle to find employment.
For each theme, the quantitative measures described abovewere calculated for the basecase (production of the case study
products as at present) and under the conditions of each sce-
nario. The full results are presented in Allwood et al. [4]
with further details in the associated technical annex to that re-
port. A summary of the quantitative results of the analysis for
the cotton T-shirt in the basecase and scenarios for theme 1 (as
described in Table 1) is given in Table 3, demonstrating the ex-
tensive data generated by the process.
Presentation of the results of the analysis in a table requires
very careful reading to evaluate the trade-offs between mea-
sures of quite different impacts. To assist in this interpretation
and provide a visual means to aid discussion of the compro-
mises implied by a triple bottom line, the results have beenpresented with a graphic equaliser as illustrated for the
data of Table 3 in Fig. 5. The intention of this display is to
demonstrate firstly, which scenarios lead to significant change
in key measures, and secondly to allow comparison between
changes in different measures. Thus the display is intended
primarily to allow comparison of relative change in magni-
tudes, not to make decisions about whether one particular
measure is more important than another. Accordingly, a scale
factor was defined for each of the measures e so that the
graphic equaliser display was consistent between all case
study products and all scenarios. The resulting images allow
visual comparison between scenarios, across measures andbetween countries. Both Table 3 and Fig. 5 give the same
information, but from Fig. 5 it is immediately clear that, in
the case of the cotton T-shirt: energy use is dominated by laun-
dry (in the UK); the major economic benefit is in the UK (due
to the high gross margins of retail); shifting production to the
UK would cause a surge of jobs in the UK and extremely high
Table 3
Summary of quantitative results from scenario analysis for the cotton T-shirt in theme 1
Environment Social Economic
Climate change
(1000 tonnes CO2equivalent)
Waste
(1000 tonnes)
Environmental
impact(PET/1000)
Employment
(in thousands)
GNI (m) Balance of
trade(m)
Operating
surplus(m)
USA Basecase 969 161 313 10 252
Scenario 1 954 161 307 10 252
Scenario 2 876 148 281 9 231
Scenario 3 448 75 144 2 47
UK Basecase 1918 208 266 26 2,318 902 1,887
Scenario 1 2239 220 301 173 2,968 252 111
Scenario 2 2169 222 293 27 2,989 231 2,541
Scenario 3 2523 255 330 32 3,174 46 2,645
China Basecase 374 12 88 108 650
Global total Basecase 3261 381 667 144
Scenario 1 3193 381 608 183
Scenario 2 3044 369 575 36
Scenario 3 2971 331 474 34
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costs (shown in the low operating surplus) which could be
avoided by new labour saving technology; shifting production
to the UK has little environmental benefit, but manufacturingwith recycled materials would be significant.
3.4. Stakeholder dialogue
The scenarios of Table 1 were analysed according to the
measures of Section 3.3, and the results were presentedas a draft
report, including box stories of associated information indi-
cating major impacts or consequences of each scenario that
arose from the influences diagram of Fig. 3 but were not cap-
tured in the quantitative model. This draft report was circulated
widely to stakeholders across the sector with a request for feed-
back. The feedback proved strongly valuable e in identifying
results that were partial or misleading, and confirming or chal-lenging the conclusions from the quantitative analysis. In fact, it
appears that the highest quality of feedback could be achieved
once a draft report was completed e as it presented, in some
cases, a challenge to existing views. A time limit was set for
receiving comments, and the final report prepared from the draft
after all feedback had been considered.
4. Results from analysis of the UK clothing and textiles
sector
The graphic equaliser displays for each scenario were
used to draw conclusions about the future of the sector,
and for each scenario, discussion based on the influences di-
agram of Fig. 3 allowed consideration of other consequences,
and of the challenge to implementing such change. An obvi-ous question arising from each scenario is whether it is likely
that this might develop e and this led to the realisation that
any of the scenarios considered could become reality if the
UKs consumers collectively wished it. From this, it was
possible to develop a description of the ideal behaviour
of consumers that would drive change in the sector. Having
done so, it becomes possible to structure a discussion about
existing barriers that inhibit development of such
behaviour e and hence to means by which the barriers might
be overcome.
4.1. Scenario assessment
Analysis of the effects of changed production structure
showed that for the cotton T-shirt, energy consumption is dom-
inated by the use-phase, so changes in production structure, in-
cluding recycling have little effect on energy use e as the
same use requirements remain. As the energy required for
laundry typically comes from electricity, this means that waste
volumes (dominated by mining waste from extracting fossil
fuels) are also largely unaffected. However, for the viscose
blouse and the carpet, where energy requirements are concen-
trated in the material phase, recycling is beneficial. The use of
energy for transport is proportionately low in all three cases so
localisation on its own has little benefit, and shifting cutting
CCI WASTE EI
BOT
OS EMPGNI
United Kingdom: impacts
CCI WASTE EI
United States of America: impacts
EMPGNI
CCI WASTE EI
Global: impacts
CCI WASTE EI
EMPGNIBase case
Changing the locationof existing operationsChanged location withnew production technologyChange location with new produc-tion technology and local recycling
Key
China: impacts
Fig. 5. Example of the graphic equaliser display of triple bottom line effects (from Well dressed?, Allwood et al. [4]).
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and sewing operations from Asia to the UK, causes the loss of
jobs in Asia and economic loss in the UK due to the high costs
of employing such labour. However, if labour saving technol-
ogy can be used, the UK would benefit from such a shift. Such
technologies are being developed e 3D knitting machines
capable of manufacturing whole garments without manual
intervention are now common in producing underwear, swim-wear, sports wear and T-shirts amongst others. The global
proportion of seamless underwear production rose from 2%
in 1998 to 18% in 2003. Automated production of clothes
from recycled materials would potentially be economically
attractive in the UK and globally environmentally beneficial
at the cost of lost jobs in Asia.
Analysis of changed consumer behaviour showed that
a consumer decision to reduce the energy used in laundry, par-
ticularly of cotton products, would be highly significant. The
two key areas of change arise from switching from tumble
drying to hang drying (preferably outdoors to avoid any
demand for increased heating), and washing at lower temper-
atures. For products in which the material or productionphases dominate impacts, consumer change to extend the
life of products would be immediately beneficial. Some exam-
ples of this occur with hiring clothes (for weddings, or for
work uniforms) which could be extended, and the centuries
old tradition of clothes repair could be renewed through design
for repair, labour saving technologies and new approaches to
the supply of spare parts.
Conventional cotton agriculture requires intense use of
toxic chemicals in growth and prior to harvesting. The toxic
impact of cotton would be greatly reduced by a switch to
organic cotton, and although this would lead to higher prices
(organic cotton is currently around 50% more expensivethan conventional cotton) the total cost of cotton in a typical
7 T-shirt is around 0.28, so the price rise is not significant
if other processes are unaffected. Currently capacity for or-
ganic cotton growing is constrained, but potentially this can
be overcome. A switch from man-made to natural fibres in
carpet manufacture would have mixed economic and environ-
mental effects, and the analysis was inconclusive. However,
innovation with smart functions able to change the behaviour
of fibres in use appears to be valuable: nano-technology coat-
ings that extend the life of man-made carpet could reduce
demand for production of new products and hence have
a net benefit; novel smart functions able to allow more
wear of a garment between laundry cycles would have benefit
for all materials. A potential drawback from such innovations
is that they may inhibit recycling and they are some way from
gaining consumer confidence.
If all remaining trade barriers were removed, production
structures would be unlikely to change significantly, but
the removal of current cotton subsidies in the USA (equal
to roughly 25% of the market price) would make USA cot-
ton less attractive and allow increased cotton trade from
poorer countries. In the past five years, removal of trade
barriers has led to reduced prices for UK consumers e
and more liberalisation would be likely to promote this effect
further.
4.2. The ideal consumer
For many of the environmental impacts of the clothing and
textiles sector, change depends largely on consumer choice e
to launder clothes in a different way, and to buy fewer of them.
Based on the assessment of the sector, it is possible to propose
a model of ideal consumer behaviour.
Second hand purchases, leasing items that would other-
wise not be used to the end of their natural life, and repair-
ing (or updating) old garments are all environmentally
preferable to purchasing new products requiring new
materials. For cotton this behaviour would significantly
reduce toxicity and for man-made materials, it would
significantly reduce energy requirements dominated by
production.
Purchasing decisions should be based on accurate infor-
mation about the environmental impacts of their produc-
tion and the social conditions of those involved in their
production. Clothes should be washed less frequently and less inten-
sively, hang drying and ironing should be avoided where
possible.
Used clothing and textiles should be disposed through
recycling businesses that would return them for second
hand sale where possible, but otherwise recycle the yarn
or fibres.
4.3. Barriers to change and means to address them
The ideal behaviour described above depends on collectiveaction e heroic behaviour by a few purchasers would have lit-
tle benefit e and it is inhibited by several barriers.
Consumers in the UK are generally wealthy enough to
purchase clothing and textiles as much for fashion as func-
tion, and to replace them before the end of their natural
life. Recently, prices have dropped and consumers have
benefited from fast fashion introducing new styles
more than four times per year, so may be reluctant to
pay extra for more responsibly made products. UK con-
sumers do not necessarily see a connection between their
purchases and negative (but invisible from the UK) social
and environmental consequences.
At present, the profits of UK businesses involved in the
clothing and textiles supply chain are generally linked to
volume of sales, so reduced volumes will inhibit profitabil-
ity unless prices rise.
UK government policy on the environment considers only
impacts created within the UK, yet in many of the scenar-
ios, for global environmental indicators to show an im-
provement, UK indicators must worsen.
Repair is generally labour intensive and expensive, and the
rise of fast fashion has led to a flow of cheaper but lower
quality garments into the UK that are more difficult to
repair.
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UK used clothes collection could be increased with im-
proved infrastructure, and textiles and clothing recycling
could be improved with better technologies.
Most clothes washing aims to remove odour but uses a pro-
cess capable also of removing stains. A reduced intensity
process that removes odour but not stains would allow a re-
duction in current washing frequencies.
Various possible mechanisms for overcoming these barriers
emerged through discussions with stakeholders.
Consumer motivation towards the ideal behaviour could
be promoted by education e with high quality information
provided by educators, journalists and campaigners as well
as by business and government.
The people who help to develop fashion leadership could
build the idea of durability into future styles.
The flow of new material driven by the sector could be
halved without economic loss if consumers paid twice as
much for products which last twice as long. Retailers e who are the strongest players in the clothing
and textile supply chain and are largely UK based e can
seek alternative forms of revenue through new business
models including repair services, supply of novel coatings
and fashion upgrades as an alternative to sales related to
material flow.
Investment in technology will support development of
improved recycling technologies, lower temperature wash-
ing and coatings or other processes to extend product life
and reduce washing intensity.
An eco-tax could penalise products using virgin material
and be used to fund development of material re-use.Legislation may be able to inhibit some toxic impacts
but is difficult to apply internationally. The UK govern-
ment could assert environmental and social responsibility
as part of its negotiation of future international trade
agreements.
5. Discussion
The paper has presented a methodology for triple bottom
line scenario analysis of large-scale change to a sector, and
applied it to the supply of clothing and textiles to the UK.
The results presented in Section 4 have been validated
through extensive stakeholder dialogue and appear sensible,
although it is impossible to estimate how complete this set
of suggestions is, until time has passed. This section attempts
to reflect in two ways on the approach that has been proposed:
how effective was the methodology? Can the results of this
study be used to anticipate useful strategies in other sectors?
5.1. Assessment of the methodology
The challenge of providing a methodology to consider
wide-scale change to a sector is to find a means of analysis
that is tractable e that can be completed within reasonable
timee
but which is sufficiently comprehensive. A sector,
such as that for clothing and textiles, is sufficiently complex
to be beyond the comprehension of an individual, so a com-
prehensive view depends on collaboration across the sector.
Broadly, the approach offered here e to map the sector, iden-
tify an influences diagram, create scenarios based on case
study products, analyse them using the triple bottom line
graphic equaliser and present draft analysis to stakeholdersfor feedbacke appears to be a sensible solution. The experi-
ence of the study on clothing and textiles supply to the UK has
emphasised the importance of the stakeholder feedbacke par-
ticularly once the draft analysis was complete, as this proved
to be the trigger for releasing crucial expert insights, often
when the draft report presented an opposite to a conventional
(or convenient) view. Future studies should certainly be struc-
tured to ensure sufficient time is allocated to gather and pro-
cess such feedback.
The economic analysis of the sector is obviously simplistice
but appeared useful in predicting major effects on National
income of the scenarios for all countries involved. Calculation
of an operating surplus for the UK proved a valuable way toindicate the likelihood of a particular scenario being adopted e
for instance, in showing the significance of novel production
technologies in facilitating a more localised production system.
While such aggregated national measures are obviously crude,
they seem more realistic than attempting a more micro-
economic analysis which would require many more assump-
tions to provide sufficient data.
The environmental analysis e as with all properly con-
ducted LCA e was arduous. While not a universal solution,
one observation from the results was that in virtually all the
scenarios, the three environmental indicators used in the
graphic equaliser were highly correlatede
suggesting thata simpler measure of energy use would in this case have
given a similar quality of information with less effort. This
arises specifically for this sector as most energy is used in
the form of electricity, and most waste is assumed to be
incinerated e so mining waste dominates the waste category,
and most non-climate change indicators are largely related
to burning fossil fuel. The exception to this simplified
approach for the clothing case was in the significance of tox-
icity in cotton growing e which required detailed analysis, and
was data intensive. No general rule can be applied to simplify-
ing the analysis, but probably there is by now sufficient anal-
ysis of most sectors to allow short-cuts to be taken e analysing
only those effects which are known to have a large impact.
The quantified social analysis was restricted to an estimate
of employment e because of the difficulty of providing quan-
titative predictions of any other measure. With a much more
complex micro-economic model, it might be possible to
predict the impact of investment in training on working condi-
tions e but this would require vastly more detail in the anal-
ysis, and would again be highly dependent on assumptions.
Evidence that this broad approach can be translated to a dif-
ferent situation is provided by Russell [3] who has used the
same methodology to consider the effect of localising produc-
tion of two case study products on the island of Jamaica.
Although that requires a regional rather than sectoral study,
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a big picture scenario analysis is similarly required, and
apparently gives insightful results.
5.2. Anticipating the outcomes for other sectors
Development of the methodology presented here, and the
associated analysis of the UK clothing and textiles sectorrequired five person-year work. Is it possible to anticipate
the candidate solutions that might apply to other sectors?
Broadly, two categories of change have been explored in
this paper: those which aim to reduce the flow of new material
entering the sector; those which aim to make the processes
within the sector as it is, more efficient. These solutions are
summarised in Fig. 6, which may prove a useful template
for future studies of wide-scale change in other sectors.
Acknowledgements
The analysis of the clothing and textiles sector described in
Sections 3 and 4 of the paper was funded by the UK landfill tax
credit scheme administered by Biffaward through RSWT with
a 10% contribution from the UK clothes and food retailer Marks
and Spencer. The work of Suzana Russell was supported by the
Commonwealth Scholarship Commission. The Delphi study
mentioned in Section 3.1 was completed by Marisa de Brito
who worked on the first half of this project.
Appendix. A brief introduction to the clothing and
textiles sector
The clothing and textiles sector represents about 7% of
world cross-border trade, leads to sales of over US$ one
trillion and employs over 26 million people worldwide just
in production [37]. Production in the sector is dominated by
Asian countries, with over one million people employed in
each of China (7.5 million), Pakistan, Bangladesh, India and
Indonesia, but with significant activity virtually in every
country e including more than four million in the EU and
Mediterranean region and two million in North and SouthAmerica [38]. Products in the sector are predominantly
made from either cellulosic materials such as cotton or poly-
ester, with one third of world cotton exports from the USA
[39], aided by government subsidies. The sector has been sub-
ject to many international trade agreements, most well known
being the quotas limiting exports (Multi-Fibre Agreement
1974e1994 and Agreement on Textiles and Clothing 1995e
2004) which were phased out since 1st January 2005. The
removal of these quotas has led to a marked drop in prices
in the UK, while spending has increased, so UK consumers
have increased the number of garments they have bought by
one third over four years. The clothing and textiles sector leads
to a flow of around 3.2 million tonnes of materials through theUK, of which 0.9 million tonnes are exported, 1.8 million
tonnes are sent to landfill, and the remaining 0.6 million
tonnes are split between recycling, and emissions to air fol-
lowing incineration.
The major impacts of the sector according to the triple bot-
tom line of sustainability are as follows.
Environment: energy use associated with laundry (particu-
larly of cotton products), operating production equipment,
and production of materials; use of toxic chemicals, partic-
ularly in cotton production; release of chemicals in waste
water, particularly from pre-treatment of fibres, dyeing,finishing and laundry; solid waste as illustrated above.
Social: employees in the clothing sector, who are generally
relatively unskilled and receive a low income, may have
precarious contracts, be vulnerable to abuse from em-
ployers, and often do not have proper representation.
Leading retailers are working with first tier suppliers to
develop codes of practice for employment, but it can be
difficult to impose these on subcontractors.
Economic: for developed economics, shifting production
to other countries has not had a significant economic
impact, as the largest gross margins occur at the wholesale
and retail end of the supply chain. However, for develop-
ing countries, the sector may be the major source of export
earnings e with Cambodia, Haiti, Bangladesh, Pakistan
and Lesotho all receiving more than 70% of export earn-
ings from the sector [40].
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Material
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