an aproach to scenario analysis

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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
mailto:[email protected]://www.elsevier.com/locate/jcleprohttp://www.elsevier.com/locate/jclepromailto:[email protected]


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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)


in the UK

(33 million per year)


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]).



10/13

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.



11/13

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,



12/13

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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Reduction

in flow

Customer supportand education

Durability in placeof fashion

New businessmodels

Second-handpurchasing

Eco-taxation

Efficiency gains

Material

Substitutealternative materials

Reduce use ofauxiliaries

Production

Processefficiencies

Reduce use ofauxiliaries

Distribution

Localiseproduction

Tariffs, subsidiesand quotas

Use

Best practicein use

Reduced impactauxiliaries

Disposal

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Recycle materials

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Smartfunctions

Fig. 6. Template of candidate solutions for large-scale change in other sectors.



13/13

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an aproach to scenario analysis

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