D2.3: Report on scenario integration and assessment · The present document is the Deliverable 2.3...

Project ID: 768884

H2020-NMBP-CSA-2017 Mapping a path to future Supply Chains

Next generation Technologies for networked Europe

D2.3: Report on scenario integration and assessment

Disclaimer:

The NEXT-NET project is co-funded by the European Commission under the Horizon 2020 Framework Pro-gramme. This document reflects only the authors’ views. The EC is not liable for any use that may be done of the information contained herein.

WP 2: Industrial Future Scenarios for Supply Chains

T 2.3: Scenario integration and assessment

Partner Responsible: Ana Cristina Barros, Pedro Senna, Kerley Pires, Pedro Campos and Vasco Amorim (INESC TEC)

Contributors:

Rosanna Fornasiero, Andrea Zangiacomi and Irene Mar-chiori (CNR-STIIMA), Dimitra Kalaitzi, Evanthia Thanou and Aristides Matopoulos (ASTON University), Markus Stute and Saskia Sardesai (Fraunhofer IML), Victoria Muerza and Mustafa Çagri Gürbüz (ZLC), Sébastien Balech and Cemre Mutlu (PNO)

Status: Final public short version

Date: 19/01/2018

Version: 1.0

Classification: Public


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NEXT-NET Project Profile

Project ID: 768884; H2020-NMBP-CSA-2017

Acronym: NEXT-NET

Title: Next generation Technologies for networked Europe

URL: https://Next-Netproject.eu/

Start Date: 01/10/2017

Duration: 24 Months


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Executive Summary

The present document is the Deliverable 2.3 (D2.3) of the NEXT-NET project and reports the scenario assessment, including supply chain characteristics and strategies for future macro-scenarios. The project aims at establishing a cross-sectoral and cross-technological initiative at European level, looking to increase the integration between production and distribution, while also putting forward propositions of research and innovation priorities for the future of European supply chains. D2.3 has two main goals:

1. Apply economic modelling techniques to the scenario descriptors developed in D2.2 in order to assess their influence on supply chain performance;

2. Define the supply chain characteristics and strategies for the six macro-scenarios for Europe in 2030 described in D2.2.

The first objective is achieved by means of quantitative modelling that finds indicators to measure the macro-scenario descriptors defined in D2.2 and assesses their influence in the supply chain performance, measured in this study by the Logistics Performance Index. This objective was achieved with applied econometrics such as Multifactorial Analysis and Re-gression Models. The results present the trends for political, economic, social, technological, legal and environmental indicators that have more influence on the Logistics Performance Index, considering more than 40 EU and non-EU countries. The model gives preliminary results to show which are the factors most influencing supply chain, and a similar model can be used both by supply chain managers and policy makers for macro-economic analysis of the trends future decision-making. This is, thus, a complement to the expert opinion collect-ed in the previous deliverables.

The second objective is put forward in consonance with the scenario building method used in D2.2 and describes the supply chains for the future macro-scenarios according to the ap-proach of the Consequence Matrix along the dimensions of the supply chain: the idea is to provide how the trends of each macro-scenarios can influence the behaviour of the compa-nies. During activities of T2.3 a workshop with supply chain experts was held in Portugal to support the implementation of the second objective.

The result of the second objective is a description of the supply chains for the future macro-scenarios based on eight dimensions: Product & Service, Supply Chain Paradigm, Technol-ogy Level, Sourcing & Distribution, Supply Chain Configuration, Manufacturing Systems, Sales Channels and Sustainability.

The results of D2.3 provide the basis for enabling the analysis of the Challenges to be faced by the future SC Industry in Europe for T2.4 and research priorities in T3.3.


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Table of Contents

1 Introduction.......................................................................................... 10

2 Influence of Scenario Descriptors in Supply Chain Performance .. 12

2.1 Results ........................................................................................................... 13

2.2 Discussion ..................................................................................................... 16

3 Consequence Matrix creation ............................................................ 17

3.1 Methodological Approach ............................................................................ 17

3.2 Decision Fields for the Consequence Matrix .............................................. 18

3.2.1 Product Decisions ................................................................................ 19

3.2.2 Process Decisions ............................................................................... 22

3.2.3 Supply Chain Decisions ....................................................................... 25

4 Supply Chains for Macro-Scenarios .................................................. 31

4.1 Supply Chain for Macro-Scenario aSPIRANT .............................................. 32

4.2 Supply Chain for Macro-Scenario PrOCEEDINg ......................................... 38

4.3 Supply Chain for Macro-Scenario oFFsET .................................................. 44

4.4 Supply Chain for Macro-Scenario DiThER .................................................. 48

4.5 Supply Chain for Macro-Scenario UNEasE ................................................. 52

4.6 Supply Chain for Macro-Scenario ENDANGEr ............................................ 56

5 Summary of Supply Chain Strategies for Macro-Scenarios ........... 62

5.1 Supply Chain Strategic Dimensions ............................................................ 62

5.1.1 Product & Service ................................................................................ 62

5.1.2 Supply Chain Paradigm ....................................................................... 63

5.1.3 Sourcing & Distribution ......................................................................... 64

5.1.4 Technology Level ................................................................................. 65

5.1.5 Supply Chain Configuration.................................................................. 66

5.1.6 Manufacturing Systems ........................................................................ 67

5.1.7 Sales Channel...................................................................................... 68

5.1.8 Sustainability ........................................................................................ 69

5.2 Supply Chain Strategies for Macro-Scenarios ............................................ 70

5.2.1 Summary for Macro-Scenario aSPIRANT ............................................ 70


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5.2.2 Summary for Macro-Scenario PrOCEEDINg ........................................ 73

5.2.3 Summary for Macro-Scenario oFFsET ................................................. 74

5.2.4 Summary for Macro-Scenario DiThER ................................................. 75

5.2.5 Summary for Macro-Scenario UNEasE ................................................ 76

5.2.6 Summary for Macro-Scenario ENDANGEr ........................................... 78

6 Conclusion ........................................................................................... 81

References ............................................................................................... 83


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List of Figures

Figure 3-1: General methodological approach .................................................................... 18

Figure 3-2: Proposed Taxonomy for Product Dimension under NEXT-NET Project ............ 20

Figure 3-3: Proposed Taxonomy for Process Dimension under NEXT-NET Project ............ 22

Figure 3-4: Proposed Taxonomy for Supply Chain Decisions under NEXT-NET Project ..... 25

Figure 5-1: Supply chain strategic dimensions .................................................................... 62

Figure 5-2: Supply Chain Strategies for Scenario aSPIRANT ............................................. 71

Figure 5-3: Supply Chain Strategies for Scenario PrOCEEDINg ......................................... 73

Figure 5-4: Supply Chain Strategies for Scenario oFFsET .................................................. 74

Figure 5-5: Supply Chain Strategies for Scenario DiThER .................................................. 75

Figure 5-6: Supply Chain Strategies for Scenario UNEasE ................................................. 76

Figure 5-7: Supply Chain Strategies for Scenario ENDANGEr ............................................ 79


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List of Tables

Table 1-1: Summary of Macro-Scenarios for Europe 2030 .................................................. 11

Table 2-1: Number of macro-factors per topic ..................................................................... 13

Table 2-2: Model Summary ................................................................................................. 14

Table 2-3: Analysis of Variance (ANOVA) ........................................................................... 14

Table 2-4: Linear Regression Coefficients ........................................................................... 14

Table 2-5: Relation between macro-factors, descriptors and variables ................................ 15

Table 3-1: Decision fields for the Consequence Matrix ........................................................ 18

Table 4-1: Demand and Supply Characteristics for Scenario aSPIRANT ............................ 33

Table 4-2: Production and Capacity Characteristics for Scenario aSPIRANT ...................... 35

Table 4-3: Supply Chain Strategies for Scenario aSPIRANT ............................................... 37

Table 4-4: Demand and Supply Characteristics for Scenario PrOCEEDINg ........................ 39

Table 4-5: Production and Capacity Characteristics for Scenario PrOCEEDINg ................. 41

Table 4-6: Supply Chain Strategies for Scenario PrOCEEDINg .......................................... 43

Table 4-7: Demand and Supply Characteristics for Scenario oFFsET ................................. 45

Table 4-8: Production and Capacity Characteristics for Scenario oFFsET .......................... 46

Table 4-9: Supply Chain Strategies for Scenario oFFsET ................................................... 47

Table 4-10: Demand and Supply Characteristics for Scenario DiThER ............................... 49

Table 4-11: Production and Capacity Characteristics for Scenario DiThER ......................... 50

Table 4-12: Supply Chain Strategies of Scenario DiThER ................................................... 51

Table 4-13: Demand and Supply Characteristics for Scenario UNEasE .............................. 53

Table 4-14: Production and Capacity Characteristics for Scenario UNEasE ....................... 54

Table 4-15: Supply Chain Strategies for Scenario UNEasE ................................................ 56

Table 4-16: Demand and Supply Characteristics for Scenario ENDANGEr ......................... 57

Table 4-17: Production and Capacity Characteristics for Scenario ENDANGEr .................. 58

Table 4-18: Supply Chain Strategies for Scenario ENDANGEr ........................................... 60

Table 6-1: Supply Chains for Macro-Scenarios ................................................................... 82


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List of Definitions

Descriptor A descriptor is a renamed megatrend as to express a neutral heading for the future projections.

Future projections Also named development paths, future projections describe possible developments of a descriptor considering associated trends.

Macro-Scenarios Scenarios that describe the environmental setting based on the PESTLE dimensions. These macro-scenarios describe the setting within the PESTLE dimensions and hence the future industrial sur-rounding.

Impact factor A factor that measures the impact of a future projection on the supply chain.

Macro-factor Resulting from the Multiple Factor Analysis, a macro-factor repre-sents the aggregation of variables for the descriptors, also known as an economic construct. It is used in the Multiple Linear Regression as a variable.


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List of Acronyms

aSPIRANT Strong PartnershIp enables homogeneous fRameworks allowing a sustainable ANd Technological development

B2B Business-to-Business

B2C Business-to-Consumer

BRICS Brazil, Russia, India, China and South Africa

C2C Consumer-to-consumer

DiThEr There is Digital and Technological development but not Enough to compete globally.

DIY Do it Yourself

E7 China, India, Brazil, Russia, Indonesia, Mexico and Turkey

EC European Commission

E-Mobility Electrical mobility

ENDANGEr EuropeaN DisintegrAtion emergiNG Economies

EU European Union

FinTech Financial Technology

G7 US, Japan, Italy, UK, France, Canada and Germany

GDP Gross Domestic Product

IoT Internet of Things

IP Intellectual property

IT Information technology

ICT Information and Communications Technology

MINT Mexico, Indonesia, Nigeria and Turkey

oFFsET Free trade enables political and social development whereas Frag-mentation hinders Environmental and Technological change

PESTLE Political, Economic, Social, Technological, Legal and Environmental

PrOCEEDINg Political coherence, disruptive technologies and individualised con-sumerism facilitate an innovative business development

R&D Research and Development

SC Supply Chain

SMEs Small and Medium-sized Enterprises

UK United Kingdom

UNEasE UNstable political sEtting and power shifting hinder the technological and Environmental development

US United States of America


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1 Introduction

This report on task T2.3 is part of the second deliverable in the series of industrial future

scenarios for supply chains focusing on future projections. Work package 2 (WP2) aims to

develop and assess future industry specific supply chain (SC) scenarios, which are shaped

by various socio-economic, political and technological megatrends. Task T2.3 builds on the

results from the descriptors obtained in task T2.2, in order to assess the characteristics of

the macro-scenarios (quantitative approach) and to describe the SC strategies for these fu-

ture scenarios (qualitative approach).

Deliverable 2.2 generated the macro-scenarios for Europe in 2030 in terms of descriptors

and projections. The influence of the observed 22 descriptors on the supply chain perfor-

mance is studied in Chapter 2, by means of economic modelling. The Logistics Performance

Index was used, and it represents the perceptions of a country's logistics based on customs

process, transport-related infrastructure, priced shipments, logistics services, tracking of

consignments and delivery deadline compliance. Multiple factor analysis and multiple linear

regression analysis were used in order to identify the strength of the influence of the de-

scriptors, and whether the influence is positive or negative on logistics performance using

data from EU and G20 countries, in a total of 41 countries. The results of this preliminary

model show which descriptors have more influence on the supply chain performance, meas-

ured in this study by the Logistics Performance Index.

Chapter 3 explains the methodology used to define the supply chains for the macro-

scenarios (Section 3.1) and defines the decision factors used to describe the supply chains

(Section 3.2). Then, Chapter 4 describes the supply chains for each macro-scenario as from

D2.2 (two optimistic – aSPIRANT, PrOCEEDINg –, 2 pessimistic – UNEasE, ENDANGEr –,

and 2 intermediate – oFFsET, DiThER). Chapter 5 presents a list of strategic dimensions

(Section 5.1), which are then used to summarize the characteristics of the future supply

chains (Section 5.2) based on the outcomes of Chapter 3. Finally, Chapter 6 presents the

overall conclusions with the main contributions of this report.


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Table 1-1: Summary of Macro-Scenarios for Europe 2030

Dimension Descriptor Projection Code

AsP

RIR

AN

T

PrO

CEE

DIN

g

OFF

sET

DiT

hEr

UN

EasE

END

AN

GEr

Political Concord in Europe A1.1Constant development in Europe A1.2

Government collapse in Europe A1.3Protectionism A2.1

Free trade A2.2Content Union A3.1

Unstable Confederations A3.2Fragmentation A3.3

The pendelum Shifts B1.1Steady Titans US & Europe B1.2

Think global - act local B2.1Rise of born-global firms B2.2

Traditional economy persists B3.1Digital Transformation B3.2

Digital impediment B3.3Bank and Fintech collaboration B4.1

A world without banks B4.2Big 5 are the banks of future B4.3

Ageing population and acceleration of disparities C1.1Awareness of inequalities and wealth distribution C1.2

Smart Regions C2.1Smart Cities C2.2

Much and Cheap C3.1Consumption awareness C3.2

DIY Soceity C3.3Individualism - Focus on variety C4.1

Collectivism - Focus on the crowd C4.2 Investments equalise the labour market C5.1

Rapid changes cause unemployment C5.2Rapid advancement of digitisation and digitalisation D1.1

Obstacles restrain digital transformation D1.2 Dynamic development of autonomous technologies D2.1

Innate reluctance to accept autonomous technologies D2.2Established Electrification Technologies and Green Systems D3.1Ongoing electrification and alternative energy endeavours D3.2

Dominance of Global Players D4.1Start-ups and SMEs take up business D4.2

Continuous exploitation of disruptive technologies D5.1Coexistence of conventional and disruptive technologies D5.2

Promotion of laws and full product transparency E1.1Legislation is lagging behind dynamic market development E1.2

Full security for inventors and data providers E2.1Low confidentiality for data and market participants E2.2

Comprehensive regulatory framework E3.1Heterogeneous regulations E3.2

Our planet is recovering F1.1Our planet is on the brink F1.2

Countering resource depletion F2.1Rise in depletion of natural resources F2.2

Macro-Scenarios

Politi

cal

Political Setting

Trade Policies

Confederation

Econ

omic

Global Trade Shift

Global Corporate Structures

Digital Economy

Financial Innovations

Soci

al

Demographic Change

Urban Living

Consumption Patterns

Customer Orientation

Knowledge-based Economy

Tech

nolo

gica

l

Digital Transformation

Autonomous Systems

Alternative energy generation; storage and usage

Decentralised connection of information and physical

Disruptive Production Technologies

Lega

l

Consumer Protection Laws

Intellectual Property Laws

Social and Environmental Regulations

Envi

ron-

men

tal Climate Change

Environmental Resource Management


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2 Influence of Scenario Descriptors in Supply Chain Performance

This chapter presents the quantitative approach used to assess the influence of the charac-teristics of the macro-scenarios of Deliverable 2.2 (D2.2) on supply chain performance. The assessment of the characteristics of the macro-scenarios for the six dimensions of PESTLE framework (Political, Economic, Social, Technological, Legal and Environmental) was based on the descriptors introduced in D2.2.

The first stage of this process was the identification of real data to represent each de-scriptor’s contents, which were used as independent variables. Originally, 22 descriptors are defined in D2.2. Nevertheless, for this assessment, data gathering could only be done for 14 descriptors, due to difficulties related to data availability and its representation of future trends.

Supply chain performance, which was the dependent variable, has been defined according to available data representing the performance of countries in trade logistics, i.e., the Logis-tics Performance Index (LPI). Other variables have been tested to be used as dependent variables, but the quality of the final models was lacking.

Data regarding the descriptors and logistics performance considered mainly the period from 2010 to 2016, for the European Union (EU) and G20 countries. The starting point was the use of Multiple Factor Analysis (MFA), in order to define the macro-factors that better portray the descriptors. Then, a Multiple Linear Regression Analysis (MLRA) was implemented to measure the influence of the macro-factors aimed at explaining the behaviour of the LPI.

Data analysis of the descriptors is a complementary approach to the scenario planning tech-nique. The NEXT-NET Project approach to Scenario Building is based on the methodology of Gausemeier and Plass [45] aimed at predicting the influence of the characteristics of the macro-scenarios in the performance of supply chains. This was considered a challenging methodology, because the macro-scenarios represent future possibilities with high uncer-tainty and the proposed methodology used statistics based on the descriptors, which are grounded by trends. As mentioned, it was not possible to find data for some descriptors, which represents a limitation of this methodology. Nonetheless, this complementary quanti-tative approach based on historical data represents another tool to support the decisions in the next steps of the project, adding data-based conclusions to the qualitative approach supported by expert’s opinion.

There are related researches on models linking macro-factors to supply chain. For example, Fioravanti et al. [38] analysed the effect of factors such as oil prices, labour costs, currency exchange rates, and trade barriers in the performance of a global supply chain composed by factories, postponement centres and distribution centres. The authors considered a multi-stage, multi-product network optimization problem, and modelled it as a mixed integer pro-gramming. Sadaghiani et al. [99] studied the importance of contextual factors affecting the environment and sustainable supply chain management of oil & gas industry. After identify-


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ing relevant external forces, a survey was carried out to investigate the importance of each identified criterion, and a Multiple Criteria Decision Making method was used to investigate and distinguish the importance of the forces based on data collected through a questionnaire sent to academic experts.

The following sections present the details regarding results and discussion.

Results 2.1

For the Model, 43 variables were used for the descriptors and Logistics Performance Index (LPI). Focusing on data from the period 2010-2016, the MFA was conducted. The main out-puts used were the eigenvalues, the axis values for each variable specific to the year 2016, and the coordinates. These outputs supported the decision-making process for the selection of 27 macro-factors required for the MLRA, which are listed in Table 2-1.

Table 2-1: Number of macro-factors per topic

# macro-factor per topic Topic (s)

1 Political Setting; Confederation; Urban Living; Dis-ruptive Production Technology; Logistics Perfor-mance Index,

2

Trade Policies; Global Trade Shift; Digital Econo-my; Demographic Change; Knowledge-based Economy; Alternative Energy Generation; Intellec-tual Property Law; Environmental Resource Man-agement.

3 Digital Transformation; Climate Change.

In the Model, 26 macro-factors were used as independent variables and one macro-factor as

dependent variable. The MLRA was used to measure the influence of the descriptors of the

macro-scenarios in the trade logistics of the countries. The model presented multicollinearity

for three variables (macro-factors), related to Knowledge-based Economy, Digital Economy

and Political Setting, all of which were removed from the model. Therefore, the Model was

supported by 23 independent variables (macro-factors). The following information regards

the model after the removal of the three variables.

The dimension of the effect of the independent variables on the dependent variable LPI was

measured by Adjusted R Squared (Ra2). Table 2-2 presents this information in the Model

Summary and 83.9% of the total variability of LPI is explained by the independent variables

in the adjusted linear regression model. The value of Durbin-Watson is 1.982, therefore be-

ing considered appropriate.

Analysis of Variance (ANOVA) presented a p-value (Sig) of 0.000. Therefore, there is at least one independent variable that has a significant influence on the variability of the de-pendent variable. Consequently, the model is significant, and is fitted to the data. Table 2-3


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presents the ANOVA results.

Table 2-2: Model Summary

Model Summaryb

Model R R Square Adjusted R Square

Std. Error of the Estimate Durbin-Watson

1 0.965a 0.932 0.839 1.045360634 1.982 a Predictors: (Constant), ERM 2 ASNRD, ERM 1 MSW, DT 1, CC 2, DT 3 MCS, DC 2 AL, DT 2, DE 2

ICTSE, IPL 2 T, AE 1, Conf, TP OSOTM, IPL 1 PAR, AE 2, UL, GTS 2 GDPg, KBE 1, TP TRAWM, GTS 1, DPT 1, DC 1, CC 3, CC 1 (see Table 2-4)

b Dependent Variable: LPI

Table 2-3: Analysis of Variance (ANOVA)

ANOVAa

Model Sum of Squares df Mean

Square F Sig.

1 Regression 252.773 23 10.990 10.057 0.000b Residual 18.577 17 1.093 Total 271.350 40

a Dependent Variable: LPI b Predictors: (Constant), ERM 2 ASNRD, ERM 1 MSW, DT 1, CC 2, DT 3 MCS, DC 2 AL, DT 2, DE 2

ICTSE, IPL 2 T, AE 1, Conf, TP OSOTM, IPL 1 PAR, AE 2, UL, GTS 2 GDPg, KBE 1, TP TRAWM, GTS 1, DPT 1, DC 1, CC 3, CC 1 (see Table 2-4)

The strength of the independent variables was evaluated using the Unstandardized Coeffi-

cients Beta (the regression coefficients), which are presented in Table 2-4. The multicolline-

arity was also analysed through the Variance Inflation Factor (VIF), and the assumptions of

the final model are considered valid and appropriate.

Table 2-4: Linear Regression Coefficients

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Toler-ance VIF

1

(Constant) -1.087E-6 0.163 0.000 1.000 TP OSOTM 0.168 0.088 0.169 1.909 0.073 0.516 1.939 TP TRAWM -0.183 0.135 -0.181 -1.353 0.194 0.225 4.438 Conf 0.224 0.080 0.224 2.799 0.012 0.626 1.597 GTS 1 -0.168 0.154 -0.168 -1.090 0.291 0.169 5.909 GTS 2 GDPg -0.150 0.311 -0.078 -0.483 0.635 0.154 6.476 DE 2 ICTSE 0.017 0.122 0.014 0.142 0.889 0.408 2.449 DC 1 0.392 0.158 0.399 2.478 0.024 0.155 6.437 DC 2 AL 0.156 0.241 0.094 0.646 0.527 0.191 5.237 UL 0.039 0.104 0.040 0.371 0.715 0.353 2.832 KBE 1 -0.063 0.111 -0.062 -0.568 0.577 0.342 2.923 DT 1 0.107 0.108 0.109 0.997 0.333 0.336 2.974


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DT 2 -0.232 0.137 -0.203 -1.693 0.109 0.280 3.567 DT 3 MCS -0.047 0.130 -0.031 -0.366 0.719 0.573 1.745 AE 1 -0.264 0.156 -0.261 -1.700 0.107 0.171 5.847 AE 2 0.146 0.129 0.120 1.133 0.273 0.356 2.808 DPT 1 0.286 0.124 0.290 2.306 0.034 0.255 3.929 IPL 1 PAR 0.119 0.123 0.120 0.970 0.346 0.261 3.826 IPL 2 T -0.301 0.217 -0.143 -1.385 0.184 0.380 2.633 CC 1 -0.144 0.173 -0.147 -0.833 0.416 0.130 7.714 CC 2 0.142 0.138 0.110 1.030 0.317 0.353 2.835 CC 3 -0.584 0.234 -0.401 -2.491 0.023 0.156 6.426 ERM 1 MSW -0.263 0.108 -0.267 -2.434 0.026 0.334 2.995 ERM 2 ASNRD 0.263 0.111 0.254 2.368 0.030 0.350 2.856

a Dependent Variable: LPI

The relation between macro-factors, descriptors and variables is presented in Table 2-5. Considering previous outputs, the following variables (macro-factors) were statistically signif-icant: Conf, DC1, DPT1, CC3, ERM1 MSW and ERM2 ASNRD, which are related to the following descriptors:

• Confederation (Conf – β=0.224); • Demographic Change (DC1 – β=0.392); • Disruptive Production Technology (DPT1 – β=0.286); • Climate Change (CC3 – β=-0.584); • Environment Resource Management (ERM1 MSW – β=-0.263 and ERM2 ASNRD –

β=0.263).

Table 2-5: Relation between macro-factors, descriptors and variables

Dimension Macro-Factor Descriptor Regression

coefficient Variable MFA’s axis value

Name of the variable

Political Conf Confederation 0.224 2016-Conf 0.9710 Subsidies and other transfers (% of expense)

Social DC1 Demographic change 0.392

2016-PA65 -0.9308 Population ages 65 and above (% of total)

2016-GI 0.6562 GINI index 2016-PG 0.6885 Population growth (% annual)

2016-PA 0-14 0.9415 Population ages 0-14 (% of total)

Technological DPT 1 Disruptive production technology

0.286

2016-MHTI 0.8784 Medium and high-tech indus-try (% manufacturing value added)

2016-RDE 0.8726 Research and development expenditure (% of GDP)

2016-HTE 0.7915 High-technology exports (% of manufactured exports)

Environmental CC3 Climate change -0.584 2016-EPC -0.8973 Electric power consumption

(kWh per capita)


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ERM 1 MSW Environmental

Resource Management

-0.263 2016-MSW 0.7790 Mineral and solidified wastes

ERM 2 ASNRD 0.263 2016-ASNRD -0.7378

Adjusted savings: natural resources depletion (% of GNI)

Discussion 2.2

All variables that present positive axis values (see Table 2-5) are directly correlated with the variance observed in LPI’s values. The three variables with negative axis values (Population ages 65 and above, Electric power consumption, and Natural resources depletion) are in-versely correlated with LPI’s values.

It is important to point out that the Legal Dimension did not present descriptors with statisti-cal significance among those analysed in the model.

The limitations regarding this approach are invariantly linked to the quality and availability of data, which is used as the basis for the produced outcomes, as well as for the definition of the best methods to be employed. Yet another limitation of this approach is the bundle of countries into groups, namely EU countries and G20 countries.

Since this is a preliminary model which requires, among other needs, data with more quality and availability (especially regarding the period considered), further studies on this topic may implement similar methodological approaches considering the countries as standalones, rather than bundled in groups. Moreover, future researches may consider different depend-ent variables, as well as independent variables, while keeping a similar methodology in order to provide valid comparisons. More importantly, the consideration of different independent variables would require previous assessment of the descriptors formulations in order to pro-mote other constructs compared to the ones devised for this report.

Further considerations regarding the connections between these results and the outputs of the qualitative analysis for the supply chain scenarios are discussed in Chapter 6.


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3 Consequence Matrix creation

This chapter describes the methodology implemented to define the characteristics of the supply chains for the macro-scenarios for Europe 2030 created in T2.2. In Section 3.1 the methodological steps are described, while the definitions of each decision fields of the Con-sequence Matrix based on the literature review are detailed in Section 3.2.

Methodological Approach 3.1

The methodological approach for establishing the SC scenarios is mostly based on phase 5 of Gausemeier et al. [44] approach to scenario building, which is the scenario transfer phase. In this stage, the objective is to analyse the effects of the macro-scenarios within the focused decision fields, which in this case are the supply chain scenarios. Hence, it is nec-essary to use a matrix where consequences of the macro-scenarios are systematically ana-lysed, with observation of possible threats and opportunities, which are valued according to importance and plausibility given the overall goal. The development of such matrix, which is referred as “Consequence Matrix”, opens the possibility to devise the characteristics and requirements for each SC scenario, distinguishing them from each other. Afterwards, there is the definition of the strategies for the decision fields based on the scenario’s general charac-teristics. The decision fields used on the Consequence Matrix resulted from expert elicitation and literature review, as well as from insights provided by the consortium members, and were defined into three major categories: Product Characteristics, Process Characteris-tics and Supply Chain Strategies. Therefore, strategies were prompted for the process and supply chain decision fields based on product characteristics, which are considered the gen-eral characteristics of a given macro-scenario. The inputs of the Consequence Matrix came from the opinions of 62 experts in the survey conducted in T2.2, opinions from SC industries’ experts gathered at the Workshop at Santarém (Portugal) in July 2018, as well as a valida-tion carried out by the consortium partners.

Lastly, the supply chain scenarios’ narratives are created in order to make a cohesive and coherent analysis, that considers demand and supply characteristics (product decision field), production and capacity characteristics (process decision field) and supply chain strategies, providing an overall description of the supply chain for the macro-scenarios. A comprehen-sive outlook of the methodological approach is presented in Figure 3-1.

To build the Consequence Matrix, the first step was to define the decision fields according to the objective to be achieved, which was accomplished through discussion and agreement between the consortium members that are, mostly, experts on supply chain research. Hav-ing defined the decision fields, the next stage was to conduct a content analysis of the data from the macro-scenarios’ development paths drawn on D2.2, while searching for character-istics that affect the supply chain industry on all three sectors: discrete manufacturing, pro-cess, and logistics & distribution; as well as characteristics that affect the different flows with-in the supply chain: material flow, information flow and financial flow.


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Figure 3-1: General methodological approach

The identification of such characteristics was followed by scrutinized analysis and separation within the decision fields, where sub-categories of analysis were drawn in order to better understand the scope and scale of each decision field.

Finally, the scenarios’ narratives were designed to provide correlations between the ob-served supply chain characteristics, the macro-scenarios development paths and the pro-posed supply chain strategies. The Decision Fields for the Consequence Matrix are further described and characterised in Section 3.2, while the SC scenarios’ narratives are provided in Chapter 4.

Decision Fields for the Consequence Matrix 3.2

The decision fields for the Consequence Matrix are organized following the Product - Pro-cess - Supply Chain framework, also called three-dimensional concurrent engineering [79]. Table 3-1 presents the overview of all decision fields that are detailed in the next sub-sections.

Table 3-1: Decision fields for the Consequence Matrix

Decision Fields Characteristics Sub categories

Product

Demand characteristics

Market Dimension Competition Variability

Variety Product Portfolio

Supply characteristics

Access Supply Sources

Lead-times Risks

Environment

Process Production characteristics Complexity

Production Efficiency

• Literature Review

• Consortium Workshop Definition of

Decision Fields

• Content analysis of macro-scenarios characteristics and requirements from D2.2

• Content analysis of the opinions of 62 experts that participated in the NEXT-NET survey (see D2.2)

• Expert workshop in SCM conference in Santarém (Portugal)

Filling in the Consequence

Matrix

• Consequence Matrix

• Consortium Workshop

Summarizing the SC Strategies for

each Scenario


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Production System

Capacity characteristics

Equipment / Capacity Investment

Technologies Labour Characteristics

Supply Chain

Sourcing strategy

Sourcing Manufacturing strategy

Company Location SC Structure

Distribution

Inventory levels Distribution Characteristics Shipping Characteristics Structure Characteristics Transport Characteristics Environmental Impacts

Supply chain integration

Material flow integration Information flow integration

and IT infrastructure Financial flow integration

Finance

Presence/absence of Intermediaries Currency Characteristics and Use

Regulations Technologies

3.2.1 Product Decisions

Considering the input-transformation-output model, products (and services) can be defined as the results of a process that transforms resources (material, information, customers) by means of people and facilities [109]. Fisher [39] defined two main types of products: func-tional or innovative. Functional are products that address the customers’ basic needs. Alt-hough they have a stable and predictable demand and long life-cycles, they belong to mar-kets with a high number of competitors and low margins. On the other hand, innovative products are those with a higher level of fashion or technology, injected to diversify the offer and target new segments.

Broadening the literature review, there are indeed more dimensions that can be used for analysing the nature of products. Lee [72] published an extension of Fisher’s dimensions under the label of “Demand Characteristics”, adding one further cluster of dimensions that he called “Supply Characteristics”. These characteristics are, nevertheless, restricted to a mac-ro-clustering, and they can be fragmented into more detailed subsections, which are de-scribed according to the proposed taxonomy for this task of the NEXT-NET project (Figure 3-2).


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Figure 3-2: Proposed Taxonomy for Product Dimension under NEXT-NET Project

3.2.1.1 Demand Characteristics

The demand characteristics concern all aspects of a product that are linked to the supply chain downstream.

Market Dimension

Demand management is the activity to link product flow with the real demand [22]. According to Fisher [39], the more fashion and technology embedded into the product, the more this product’s demand becomes uncertain. Supply chain requirements, regarding production, change substantially throughout products’ life-cycles, and vary according to products’ maturi-ty stage in the market [1, 74]. Production costs include investments for sustaining marketing strategies, especially when considering additional product versions. Market mediation costs are higher when there is demand uncertainty, since the balance between supply and de-mand is more difficult to be achieved and maintained under these conditions.

Competition

The companies’ challenge is to create the right solution to meet the needs of different cus-tomers [26]. The products’ maturity stages may induce different reactions from the compa-nies, since they must adapt their existing product portfolios and maturity levels to the re-quirements brought by demand, in order to have greater market share and market presence. Therefore, competition is largely driven by companies’ product portfolios and their adaptabil-ity to different market segments and customer requirements.

Product Dimension

Demand Characteristics

Market Dimensions

Competition

Variability

Variety

Product Portfolio

Supply Characteristics

Access

Supply Sources

Lead-times

Risks

Environment


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Variability

As the variability of the demand grows, it creates some difficulties in planning the production, the stock dimension and the capacity of the operations, for instance [1, 109]. Other factors may correlate with product variability, such as the production location, which may impact differently the product demand as well.

Variety

Product variety is a crucial dimension of business practice [92]. According to Randall & Ul-rich [93] “product variety is the number of different versions of a product offered by a firm at a single point in time”. Thus, product variety impacts on firm performance by dividing up pro-duction and market mediation costs.

Product Portfolio

The product portfolio aims at addressing the needs of customers belonging to precise mar-ket segments. Variety and variability play major role in defining the scope and aim of a given product portfolio, and companies’ look to invest in expanding their product portfolio where customization requirements are high in demand.

3.2.1.2 Supply Characteristics

The supply characteristics concern all the aspects of products that are linked with the supply chain upstream. This refers primarily to the sourcing of raw materials and components.

Access

Threats to resource’s access, such as the sources’ depletion, raw material scarcity, the polit-ical turbulences, the governments’ actions, the competition and the technological change, are motivations for implementation of different supply strategies aimed at adding value to the product and providing profitability leveraging [68]. One example of these strategies is to split replenishment orders among several suppliers, thus increasing resource’s access.

Supply Sources

Resources are purchased from the upstream side of the supply chain. Hence, the purchas-ing process can be classified into two major dimensions: the importance of purchasing and the complexity of the supply chain market [68].

Lead-times

Sourcing policies affect directly lead-times [21, 48, 118]. Hence, companies are able to pool lead-time risk together by splitting replenishment orders among several suppliers. Lead-time improvements can also be achieved through considering the geography of sourcing portfolio, i.e., the location of the suppliers. By reducing physical distance from the supplier, lead-times diminish, since the delivery time will also be decreased. Nevertheless, it should be noted that


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this strategy increases costs, as well as reduces volume flexibility [16].

Risks

Supply Chain Risk Management (SCRM) is the subject matter that concerns daily risks, as well as exceptional risks along the supply chain. It provides strategies to mitigate such risks by implementing continuous risk assessment methodologies aimed at reducing vulnerability while ensuring continuity [133].

Environment

Enhancing overall sustainability of companies is related to improved supply management. There are two major actions for triggering this bond: The Focal Firm (FF) strategy, being responsible for the sustainability problems provoked by their suppliers and partners; and value-share between the FF and its suppliers [5, 65, 105]. Moreover, supply management strategies must go beyond the “lowest material cost” strategy and include audit procedures for selection and evaluation of suppliers considering their sustainability performances [2].

3.2.2 Process Decisions

Process decisions encompass supply chain characteristics related to production and capaci-ty aspects. In this sense, production characteristics comprise concepts and methods of pro-duction systems, production efficiency and complexity, while capacity characteristics relates to equipment aspects, investments needed, technologies required and task-force character-istics. It is possible to observe the proposed taxonomy for the Process Decisions under the NEXT-NET project in Figure 3-3 below.

Figure 3-3: Proposed Taxonomy for Process Dimension under NEXT-NET Project

3.2.2.1 Production Characteristics

Process production decisions regards the connection between manufacturing procedures and environment in which firms are, thus being influence by the complexity, production effi-ciency and production systems. Details regarding these characteristics are further described.

Process Decisions

Production Characteristics

Complexity


Production System

Capacity Characteristics

Equipment / Capacity

Investment

Technologies

Labour Characteristics


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Complexity

Complexity production characteristics are based on the complex adaptive systems (CAS) theories and models, which are focused on the connections between system and environ-ment, as well as the co-evolution of these two aspects. More importantly, the system refers to the collect supply of a given part or subassembly done by a network of firms, while the environment focusses on the end consumer markets mostly relying on the exerted demand for products and services provided [24]. Within NEXT-NET scope, complexity was closely related to product variety. Thus, high complexity was assigned to supply chain scenarios that presented characteristics pertaining to wider variety aspects, such as individualism and the presence of a do-it-yourself (DIY) society. On the other hand, collectivist supply chain sce-narios are mostly characterized by low complexity within product variety scope.


Production efficiency regards the efficiency measured through the performance criteria de-scribed on D3.1, considering the agility, costs, transparency/traceability, responsiveness, reliability and sustainability. On the specific topic of the supply chain scenarios, production efficiency relates to the adoption of technologies, relying on digital economy, digital trans-formation, the adoption of autonomous systems, as well as alternative energy generation, storage and use, to establish the level of efficiency on a given supply chain scenario. Moreo-ver, it refers to the decentralized connection of information and physical devices to acknowledge the scale of facilities regarded on each supply chain scenario.

Production System

Production systems are related to manufacturing characteristics, such as the type of system employed, or the manufacturing method applied, which may also consider supply chains’ flexibility and agility requirements. They can be divided into five distinct categories: lean manufacturing systems; mass customization; agile manufacturing systems; flexible manufac-turing systems; efficient and reconfigurable manufacturing systems. Lean manufacturing is aimed at providing customer satisfaction through adding value and eliminating waste, while being implemented through a set of management practices focused in representing alterna-tive model to capital-intense mass production [57]. Mass customization is focused on broad provision of personalized products and services through modular design [40]. Agile manufac-turing aims for a comprehensive response to business challenges through the ability to com-pete and prosper within a state of dynamic change [134]. Flexible manufacturing is centred on the adaption to customers preferences, while also satisfying companies changing re-quirements and modular capabilities [67]. Efficient and Reconfigurable Manufacturing relates to decision-making and action-taking, where lower levels influence hardware changes and higher levels impact software changes or different choices of alternative meth-ods/organizational structures [15]. Some of these may be implemented with a digital variant, in order to conform to digitalization advancements observed within the macro-scenario char-


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3.2.2.2 Capacity Characteristics

Process capacity decisions impact the rate at which inputs are transformed into outputs with-in a given time period and are influenced by the equipment, the investments, the technolo-gies and the labour decisions. A more detailed description of these decisions follows.

acteristics particular to that specific supply chain scenario.


Equipment capacity and productivity significantly impact the production capacity and influ-ence the overall manufacturing performance [71]. For that reason, different strategies exist aiming to increase the overall equipment effectiveness (OEE) which indicates the actual ca-pacity of the equipment and informs how well the equipment is being used [88]. These strat-egies may target an increased production capacity or a flexible capacity and include increas-ing equipment knowledge within the manufacturing workforce, improving maintenance pro-cedures, changing procedures to reduce or eliminate setups, test procedures and idle time, making modifications to increase machine speed etc. [71, 88].

Investment

Investment decisions are related to capital investments in technology, in production pro-cesses and in employees training. Specifically, this field refers to investments in advanced manufacturing technologies [110], to investments in dedicated or flexible production systems [23] and to investments in machinery and equipment in order firms to remain competitive [129]. Also, investments may refer to the employees training, as firms need to invest in a skilled workforce capable of operating and keeping pace with rapidly evolving technology and high-tech innovations [90].

Technologies

Numerous manufacturing technologies exist, and firms need to decide which ones to imple-ment in order to respond to emerging needs. Those technologies maybe related to new ma-terials (e.g. nanotechnology, composites), to product design (e.g. internet of things), to man-ufacturing technologies (e.g. additive manufacturing), to information technology (e.g. big data) or to business model (e.g. frugal innovation, circular economy) [106].


The labour characteristics refer to the employees’ skills. Those skills could be basic (i.e. lower-level skills), extended (i.e. elevated skills) or problem-solving skills that includes em-ployees’ ability to learn, work in teams, solve unfamiliar problems etc. [130]. Also, today’s increased rate of high-tech innovations and advanced manufacturing technologies have led to increased demand for higher-level skills.


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3.2.3 Supply Chain Decisions

Supply chain’s performance are strictly linked with products [39]. Hence, a Supply Chain Strategy (SCS) must be developed in light of considerations made upon some dimensions that depicts the nature of products [29, 75]. Thus, SC Decisions are categorized into sourc-ing strategies, distribution, integration and finance. Figure 3-4 displays the proposed taxon-omy for the supply chain decisions within the NEXT-NET project.

Figure 3-4: Proposed Taxonomy for Supply Chain Decisions under NEXT-NET Project

3.2.3.1 Sourcing Strategy

Strategic sourcing decisions should take into account operational metrics such as cost but also strategic dimensions and capabilities of suppliers [115]. For a given category, sourcing strategies identify the required number of suppliers, the relationship to be engaged, the con-ditions of contracts to be secured, and the geographical sourcing [126]. Sourcing decisions are linked with the supply chain configuration, which involves decisions regarding the manu-facturing plants, sourcing facilities, transportation modes and inventory on the global or local level [50, 122]. Different sourcing strategies have various impact on manufacturing strategy, which in turn may aid in identifying the supply chain configurations [58].

Supply Chain Decisions

Sourcing Strategy

Sourcing

Manufacturing Strategy

Company Location

SC Structure

Distribution

Inventory Levels

Distribution Characteristics

Shipping Characteristics

Structure Characteristics

Transport Characteristics

Environmental Impacts

Supply Chain Integration

Material flow integration

Information flow integration and IT infrastructure

Financial flow integration

Finance

Presence / absence of Intermediaries

Currency Characteristics and Use

Regulations

Technologies

Sourcing


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Three main sourcing strategies considered: Global, Glocal (or domestic) and Local. Local sourcing considers local suppliers in a specific region or area, presenting fewer logistical issues [123]. Glocal sourcing is similar to local sourcing, albeit with suppliers located in more distant areas within the same country, therefore requiring more distance to be covered [123]. Finally, Global sourcing encompasses suppliers which are located abroad, established in different countries, regions or continents [123]. On this strategy, companies have worldwide operations with resource purchases spammed across a global network of suppliers, which reduces costs while improving reliability, quality and access to technologies, as well as to new markets [17, 54].

Manufacturing strategy

Supply management research focused on strategies regarding the location decision for sourcing and manufacturing, thus being divided into four major categories: Outsourcing, on-shoring, nearshoring and farshoring. Nearshoring can be defined as the movement of manu-facturing plants within the company’s own region [36] or the relocation of earlier offshored production plants to a foreign country in the same region of the company’s home country [42]. Nearshoring is the exact opposite to farshoring. Furthermore, onshoring relates to relo-cating process into national or regional borders, thus reducing the distance between func-tions, processes, manufacturing procedures and end/consumers, as well as providing the possibility to keep operations on tight control. Involving transferring operational activities with aim to shorten the supply chain, while also reducing supply of services internally within a company, outsourcing is usually employed for reducing development, production and fixed costs due to using other companies for providing non-essential components/processes, or simply relocating these procedures to another facility within the same organization [60].

Company Location

Based on economic power shift, the companies’ location may have severe consequences when considering the overall macro-scenario. Thus, the companies may establish their main premises on European and American soils, with subsidiaries spread across the globe, whenever the scenario forecasts conservation of U.S. and E.U. as most prominent actors within economic and political power struggle. On the other hand, companies are more likely to have centres of excellence and operational activity set up in emerging countries when the macro-scenario predictions are lean towards a power shift in favour of emerging countries such as the MINT.

SC Structure

The complexity of the supply chain structures is inversely related to the advancement of dig-itization and digitalization, in the sense that a rapid advancement is usually met with more simple structures, given that all processes and procedures are interlinked digitally. On the other hand, whenever obstacles which restrain digital transformation are encountered, the supply chain structure faces restriction that impose more complex structures to be imple-


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3.2.3.2 Distribution

Logistics and distribution are closely related, thus being defined as a process which encom-passes planning, implementation and control of goods, regarding both flow and storage. In addition, this process considers meaningful information on the assessment of efficiency and reliability of the logistics procedure, beginning on the final production stage (at plant/factory level) until the consumption by the end consumer, thus relating important data with respect to customer requirements [30]. In this sense, the strategy is supported by the customer ser-vice goals, as well as the determination of location strategy, inventory strategy and transpor-tation strategy.

mented. Moreover, the concept of circular economy and its impact in the SC structure is also considered, which is closely related to the environmental characteristics of the macro-scenarios.

Inventory Levels

Inventory decisions are concerned with safety stocks, in the sense that companies may choose to minimize consolidated inventories into small number of locations while trying to estimate inventory levels as demand is assigned to different facilities [9]. On the other hand, companies may keep large quantities of inventory aiming to minimize stock outs, despite leading to lower turnovers [3]. A third option for companies is to keep low inventory levels, which minimizes inventory costs but may incur in the risk of sales losses [3].


Based on distribution network designs, products are distributed to customers through direct transport or via one (or more) intermediate storage points. In this sense, centralized distribu-tion includes a single distribution centre or, sometimes, direct shipment. On the other hand, decentralized distribution often entails multiple distribution channel locations in a multi-echelon system [85]. The multimodal distribution characteristic may be defined as the com-bination of various modes of transport mainly through the use of containers. Thus, multi-modal transport entails the intermodal transport which is the transportation of goods in a single loading unit (e.g. road vehicle). This loading unit uses two or more modes of transport, in succession, without requiring handling of the goods transported when changing modes [66].

Shipping Characteristics

Companies use more than one of the delivery networks by considering the product charac-teristics and the targeting strategic position [25]. Thus, the shipping characteristics take into account the product and service characteristics regarding customization, being divided into two sub-categories: personalization of shipment, used when customized products or serviti-zation are employed; and traditional shipping process for mainstream and frugal mass prod-


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3.2.3.3 Supply Chain Integration

Supply chain integration can be defined as the attempt to enhance the linkages among each node of the chain, improve the decision-making and aid companies in collaborating through more efficient manners by providing visibility [89]. Moreover, supply chain integration posi-tively impacts the supply chain performance [121]. This integrated supply chain involves four main elements: physical, information and financial flows; processes and activities; technolo-gies and systems; and integration of actors [37]. Furthermore, these categories can be dis-assembled between information systems and operational/logistics integration [54, 124, 135].

ucts, as well as the lack of servitization.

Structure Characteristics

Closely related to the SC structure of the sourcing strategy, the distribution structure charac-teristics are also supported by the digital transformation aspects of the macro-scenarios. Therefore, more complex SC structures are required when identifying obstacles which re-strain digital transformation. On the other hand, agile SC structures are needed once the rapid advancement of digitization and digitalization is present within specific macro-scenarios. The exploitation of disruptive technologies also contributes for the distribution structure characteristics, requiring new production technologies to be implemented.

Transport Characteristics

Transport characteristics regard the mobility modals to be used within the supply chain sce-nario, considering the Climate Change characteristics of the macro-scenario. Thus, when the environment shows signs of recovery, there is an increased use of electric vehicles within supply chain distribution. Moreover, electric and hybrid vehicles are used due to established electrification technologies, and green systems are detected within alternative energy gener-ation, storage and usage. Electric vehicles are considered an alternative to conventional vehicles in different logistics applications, such as intermodal networks, urban freight transport and night distribution [77, 83]. Furthermore, when smart cities are characteristics within the macro-scenario, last mile delivery transportation solutions are required.

Environmental Impacts

Sustainability characteristics surround and support the environmental impacts and aspects. Thus, sustainable or “green” logistics are considered by implementing reverse logistics, as-sessment of emissions and more sustainable aspects of logistical activities [49]. The limited resources and high cost of raw materials have imposed companies to focus on reverse logis-tics, which can be defined as the planning, implementation and control of backward flows of resources and raw materials from a distribution point aimed at recovery or proper disposal [97]. Another important aspect concerns waste management, where companies seek to achieve resource efficiency or implement just-in-time logistics, which reduce inventory costs, provide growth opportunities and improve response to customer needs [4].


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Operational/logistics integration enables companies to achieve a smooth production process [43]. Integrated operations/logistics leads to reliable order cycles and inventory reduction [103]. Buyer-supplier relationships are presented as an integration continuum [112]. Regard-ing product and material flows, coordination and collaboration enhance demand forecasts, inventory management, such as responding to the bullwhip effect in multi-echelon supply chains, and minimizes cycle times [52, 62].

Material flow integration

Material flow integration is a supply chain integration capability, being seen as a construct which addresses the integration between focal firm and supply chain partners with aims to manage the materials’ stocking and flow, as well as finished goods’ stocking and flow, from a global optimization level perspective [91]. In this sense, downstream flows are related to raw materials, subassemblies and finished goods. On the other hand, upstream flows are the rejected products (which are returned to the manufacturer), or those products that require maintenance, such as those which present manufacturing malfunctions [91]. Global optimi-zation initiatives for material flows consists of just-in-time delivery, automatic replenishment, inventory programs managed by vendors, and procuring contracts with logistics providers in order to better support inventory management services.

Information flow integration & IT infrastructure

Information sharing can enhance ordering function, minimize the risk of lower inventory lev-els and/or shortage of costs through better inventory allocation [63, 91]. Poor information technology infrastructure is a barrier for successful supply chain integration [13]. IT facilitates and coordinates the flow of information across the supply chain, such as electronic data in-terchange, enterprise resource planning and radio frequency identification [46]. In this sense, information sharing enables trust-based relationships, increase the contract duration, pro-motes efficient conflict resolution, as well as improves flexibility [64]. Thus, digital macro-scenarios imply a seamless flow of information, with integrated flows and the transparency of information about components and products. Meanwhile, macro-scenarios which present obstacles to digitalization advancements are met with Low IT integration and penetration, as well as a misalignment of IT technologies and the presence of information overload issues, requiring overall improvement of IT infrastructure.

Financial flow integration


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3.2.3.4 Finance

The flow of financial resources has received more attention after the credit crisis, which led to supply chain finance (SCF) having more prominence and importance [113]. Traditional SCF contains the buyer, centralized financial intermediaries (such as banks or financial insti-tutions), and the supplier. On this environment, banks attempt to replace paper with digital approaches by forming partnerships with platform providers and use application program-ming interfaces (APIs) to ensure the connectivity of their customers with other key providers [132].

Companies must invest in integrating manufacturing and management processes across suppliers and customers [107]. One example of such investments is the requirement (and associated costs) of compatible communication systems between companies and their sup-pliers in order to share information and promote collaboration in a secure manner. These investments, therefore, enable the integration of information flows and physical flows, while increasing trust and commitment in the buyer-supplier relationship [76]. Mostly supported by intellectual property laws and their implementation within macro-scenarios, fully integrated financial flows may be present, or untrusted SC network may be the prominent characteristic of a given supply chain based on the macro-scenario characteristics.

Presence/absence of Intermediaries

Banks continue to be the largest providers of receivables finance, but several new offerings such as financial technology start-ups (FinTech) have emerged in recent years [111]. FinTechs are offering innovative services by applying new technologies in the financial ser-vice sector [95]. They are becoming the main players in mobile transfer payments, particular-ly for small and medium enterprises (SMEs) as well as individuals [84]. Financial institutions are dependent on large tech companies to have access to critical infrastructure and differen-tiating technologies [131]. Thus, large technology companies, such as Amazon, Facebook, Google and Apple, can have a major impact on traditional banking [78]. The presence or absence of intermediaries, as well as the collaboration between traditional intermediaries (e.g. banks) and digitalized intermediaries (e.g. FinTechs) is greatly related to the macro-scenario’s characteristics regarding financial dominance and agreement.


Blockchain is the underlying technology behind cryptocurrencies, such as bitcoin and Ethereum, which are virtual currencies that can be bought with traditional money and sold against traditional money, as well as buying and selling digital and real goods and services [59]. The dominance of global players pushes for the presence of global currency, with quick transfer of financial funds, as well as cash, globally. Big companies, under these characteris-tics, should determine the payment logic. On the other hand, the introduction of complemen-tary currency, supported by collaboration of banks and FinTechs, as well as the establish-


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4 Supply Chains for Macro-Scenarios

Following the details exposed in Chapter 3 regarding product, process and supply chain de-

cisions, Chapter 4 correlates the supply chain characteristics based on the macro-scenarios.

Therefore, the following sections are dedicated to presenting narratives connecting the afore

mentioned supply chain strategies to the characteristics of the macro-scenarios described in

D2.2. For this purpose, each section of this Chapter has a short introduction summarizing

the features of the macro-scenario (aSPIRANT, PrOCEEDINg, oFFsET, DiThER, UNEasE

and ENDANGEr), and then subsections regarding product, process and supply chain char-

acteristics.

ment of cryptocurrencies, change the interaction between players regarding contracts, in-vestments, loans and safety requirements.

Regulations

The use of blockchain, which is a distributed database on a peer-to-peer perspective, agreed upon and shared among the involved peers, as well as the presence of encrypted digital signatures, guarantee safe transactions within the SC integrated network [104]. Based on blockchain a new finance solution can be offered via the smart contracts, which occur with-out human interaction and are activated when a set of conditions agreed upon are triggered, simultaneously informing and updating all parties involved regarding the contract conditions and terms [41]. As blockchain technology is still in the development stage, there is an urgent need for a regulatory system to be established to avoid certain incidents such as the hacking attack on the DAO [53]. Whenever regulatory requirements are already established, and digitalization/digitization is advanced, global regulations and secured regulatory contracts across SC are observed. On the other hand, new models for revenue and cost sharing based on the impact of data gathering and processing are related to digital potential and financial innovations of a given macro-scenario.

Technologies

FinTech offer financial advisory services with the use of automated financial advice (robo-advisor) [84]. They also offer a range of SCF techniques for the entire supply chain, such as reverse factoring and dynamic discounting, whereas bank led SCF programs are discrimina-tory in nature and particularly to small & not-creditworthy supplier, which cannot participate [114]. Apart from blockchain technology, crowdfunding efforts are also observed depending on the macro-scenario’s characteristics, as well as mobile apps increased use and the prom-inence of data gathering/sharing issues, mostly due to cyber-attacks on less secured envi-ronments.


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Supply Chain for Macro-Scenario aSPIRANT 4.1

The aSPIRANT scenario (Strong PartnershIp enables homogeneous frameworks allowing a

sustainable ANd Technological development) has a stable political and economic envi-

ronment within the EU and neighbouring countries.

Free trade agreements of European countries with other economic unions support and facili-

tate the exchange of goods. Digital economy is booming, leading to a fast development of collaborative platforms, with an easy share and use of resources. New service catego-ries, such as FinTech Services, innovate complete industrial sectors. Global companies will have a powerful position where they are in control of high volumes of generated data.

Smaller and local companies struggle with the efficient management of information

overload since neither enabling technologies nor the required expertise are available. The

digital economy permeates all aspects of society; helping people and companies to orches-

trate, manage, and automate many of their daily activities. People tend to take into account

the origin of products and adopt more responsible consumer behaviours. Furthermore,

they tend to relocate in the countryside. The political and economic settings support tech-nological developments. Emerging technologies are supported and developed by SMEs

(small and medium-sized enterprises) and start-ups, and that will assist humans to by under-

taking autonomous planning and handling tasks. Regulations are maintained updated and

support new inventions. There are clear regulations for handling of data, thus creating

transparency and intellectual property security. These will also enhance resource efficiency

processes and limit their depletion. Renewable and green energies become more and

more relevant and efficient.

From a demand standpoint in Europe and neighbouring regions, there are no political up-

heavals, calamities, or any other political risk factors that affect the demand predictability

and interrupt the flow of commerce. Consensual and market-preserving political settings,

consolidated by state unions, bring both economic flexibility and market certainty in bargain-

ing processes; whereas, soft regulations facilitate liberal trade security, easy access to raw

materials and investment finance. The aSPIRANT scenario-model also displays the rele-

vance of political stability on foreign direct investments and investment growth. Continued

and steady economic growth patterns in US and Europe bring positive Gross Domestic

Product (GDP) spill overs (e.g. social welfare and investment projects in the areas of high-

tech and education) and affect labour market governance processes in supply chains. Mac-

ro-competitive economic climate is shaped by the multiplicity and competitive capabilities of

born-global firms and platform businesses (e.g. Amazon, Google). Product portfolio will be

more standardized, with more green products. New digital business, data-driven, and data


33

monetization models, route-to-market strategies, and real- and near-time tracking/traceability

technologies contribute to the development of customized freight logistics, direct sales chan-

nels, demand pooling (leading to raw materials cost savings) and new revenue streams. In

this context, from the demand-side perspective, all these dynamics construct a tactical, inte-

grated, omnichannel, and global supply chain model.

From a supply standpoint, collective environmental concerns, growing interest in green

products/services and increasing volatility in raw material procurement have all a leverage

effect on the design of eco-efficient supply chain practices, such as the use of waste minimi-

zation and recovery technologies, design of green product portfolios, and carbon-free trans-

portation technologies and easier access to specific materials and components. Smart re-

gionalization and smart city production/manufacturing initiatives lead to distributed manufac-

turing practices, low production runs, inventory cost savings, and improved order-to-delivery

times and predictable lead-times. Low product variety increases supply chain performance in

terms of lead time and cost. In this context, agile, fast and digital supply chain structures

develop, resulting from novel differentiation-based supply chain strategies, omnichannel de-

livery and inventory optimization strategies. The increasing use of big data in logistics and

supply chain management leverage accuracy and speed in supply chain planning.

Table 4-1 describes the demand and supply characteristics of the supply chain for scenario

aSPIRANT.

Table 4-1: Demand and Supply Characteristics for Scenario aSPIRANT

Decision Field Product Characteristics for Scenario aSPIRANT

Demand Charac-teristics

Market Dimension

Market expansion: • Geographical (A1.1, A2.2) • Economic growth in US & Europe (B1.2) • New customers from digital business (B1.2, B3.2)

Competition More global competitors (A2.2, A3.1, B2.2, C4.2, D4.1) Small and start-up companies are ‘born global’ (B2.2) Less differentiation, thus more competition (C4.2)

Variability Predictable demand (A1.1, A3.1, D1.1)

Variety

Low variety influenced by: • Products for new markets (geographical expansion A1.1, A2.2) • Collectivism (C4.2) • Consumption awareness (C3.2)

Product Portfolio Standardization (B1.2) More green products (C3.2, F1.1) More data-driven services (B3.2, D5.1)

Supply Charac-teristics

Access Easier access to specific materials and components (A2.2, C2.1, F2.1)

Supply Sources Many supply sources (A2.2, F2.1)

Lead-times Predictable lead-times (A1.1, A2.2, B1.2, B3.2, D1.1, D2.1)

Risks Risk of global corruption and cartels (A2.2, B4.3)

Environment New environment friendly materials (C3.2, F1.1, F2.1)


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From a production standpoint, low product variety affects positively lead-time, inventory

costs, and price competition. Industrial process automation and discrete manufacturing prac-

tices enable high-volume and low complexity production systems, leading to an increase in

industrial waste volume. Hence, cost-efficient waste minimization upcycling technologies are

required in this production context. Under demand fluctuations and product volume flexibility,

supply chain structures are flexible, reacting speedily to the changes in consumption pat-

terns. Consumer purchasing behaviour and increasing demand for mass product customiza-

tion necessitates lean, high-efficient, and customized production processes and systems due

to technology adoption. In structured global markets, large production facilities will be fa-

voured, with supply and demand predictability, data monetization market is growing, owing

to increasing digital investments for customized data-sharing models, data-driven service

designs, and in-real- or near-time third party tracking technologies. In this context, strategic

value of R&D and production process information tracking technologies is maximized for

bottom-line results. Furthermore, in production systems, waste minimization and carbon-free

energy management technologies have an integrated impact on cost of purchase, design,

and material processing, starting from raw material acquisition to end-of-life material recov-

ery. Automation process technologies and additive manufacturing techniques affect supply

chain performance positively in terms of real-time supply chain, on-demand parts creation for

critical industries.

From a capacity standpoint, along the converging digitalization and automation path of sup-

ply chains, there are explicit technology investment tracks, improving and increasing produc-

tion capacity and process efficiency. Investments in technology, processes and trainings will

be necessary. As high-volume and low production complexity increases the volume of indus-

trial waste and that raw materials are scarce, integration of carbon-free waste and resource

management technologies into production process brings resource efficiency in terms of cost

reduction (e.g. cost of purchase, direct material handling cost), inventory optimization, and

improvements in sustainability of supply chains. Another technology investment track is in

the field of industrial cybersecurity and data privacy protection, as exponential growth of data

monetization and virtualization markets threatens the connectivity infrastructure of produc-

tion facilities. Real-time monitoring tools used to track supply chain network components and

flows (e.g. delivery, material, information flows) enable easy data-sharing and decrease or-

der-to-delivery time. Finally, investments in technology-neutral connectivity systems and

carbon-free transportation technologies are growing, while improving logistics infrastructure.

As for the labour market consequences of automation in production chains, although digital


35

automation of non-value-added tasks increases the efficiency in demand planning; increas-

ing number of high-tech manufacturing jobs requires higher skill availability in labour market.

However, skills shortage of specialists for automation-age occupations widens. Company

investments in human capital are growing in the effort to close the competence and digital

talent gap. In the context of the aSPIRANT scenario-model, rate of labour force growth is

projected to increase, since redistributive policy instruments for income equality have a

growth-enhancing impact on economy. The scenario-model also attributes a positive value

to labour market flexibility as flexible work arrangements decrease unemployment and facili-

tate competence-based job matching. On the other hand, the scenario-model acknowledges

that automation creates polarization patterns in labour markets, between high-wage coun-

tries characterized by highly automated production facilities and low-wage countries where

manual production processes are still dominant.

Table 4-2 describes the production and capacity characteristics of the supply chain for sce-

nario aSPIRANT.

Table 4-2: Production and Capacity Characteristics for Scenario aSPIRANT

Decision Field Capacity Characteristics for Scenario aSPIRANT


Complexity Low complexity in production (C4.2)

Production Efficiency High production efficiency due to technology adoption (B3.2, D1.1,

D2.1, D3.1) Large production facilities (D4.1)

Production System Digital lean manufacturing systems (predictable demand and supply, low variety, large production facilities, digital technologies adoption)

Capacity Char-acteristics

Equipment / Capacity Increased production capacity (see Market Dimension)

Investment

More investments on (A1.1): • Technology (A2.2, B1.2, D5.1) • Processes • Training (D5.1)

Technologies

Automation of those non-value-added activities (B1.2, D2.1): • High automation in high labour cost country (C5.1) • Manual process in low cost country (C5.1) • Cybersecurity systems (B4.3, E1.1, E2.1) • R&D (D1.1) • Robotic process automation (D1.1, D2.1) • Electric and hybrid vehicle systems (D3.1)


Technical skills and specialized IT staff required (C2.1, D1.1, D5.1) Increased rate of labour force growth (C1.2) Increased investment on Staff (B1.2) Higher skill availability (C5.1)

From a sourcing strategy standpoint, in the context of aSPIRANT scenario-model, shoring

process and strategic sourcing strategy could be characterized as global. Thanks to the

novel digital and circular business model-designs, the organizational model of supply chains


36

has become more decentralized, circular, and distributed; whereas, global governance of

sourcing operations is further centralized, owing to the spatial concentration of large-scale

production facilities in high-wage geographies, such as Europe and the U.S. In this scenario,

the decentralized, circular and distributed set-up of supply chains, particularly for (regionally

and globally operating) companies, allows hybrid and multi-sourcing patterns, leading to

higher savings in operating costs and optimize profit margins. Companies outsource opera-

tions due to global negotiations with local adjustments and use onshoring due to technologi-

cal developments. Furthermore, integration of circular economy principles and virtualization

technologies into business operations, combined with the benefits of local and on-shoring

manufacturing, ease the access to quality and affordable raw materials as well as local pro-

duction factors. Companies’ main premises will be in Europe and in the USA and will have

subsidiaries in the rest of the world. Complementary currency diffusion also increases cost

efficiency of sourcing operations by shortening the lengths of supply chains and the rise of

circular economy.

From a distribution standpoint, the four key features of the scenario-model aSPIRANT – low

demand variability, high-volume/low-production capacity dynamics of manufacturing pro-

cess, short supplier lead time, and advanced supply chain foresight analytics – keep invento-

ry levels constant and inventory costs low. The distribution characteristics are multimodal

distribution, higher investment, automated logistics systems, efficiency optimized and in-

crease of direct sales to end users. Successful and progressive integration of high-

performance automation processes, virtual technologies, and green manufacturing practices

into logistics component of supply chain management contribute to the development of an

end-to-end supply chain ecosystem, in which omnichannel, multi-modal, and automated dis-

tribution networks optimize the administrative management of supply chain performance and

increase efficiency in customer relationship management, in terms of reduced order-to-

delivery time, new customized freight solutions, and improved post-sales logistics. Omni-

channel distribution networks, enabled by the technological advancements in automated

logistics systems and virtualization market, have various supply chain efficiency benefits:

consistency in delivery services, improved customer centricity with personalisation of ship-

ping, better customer segmentation, and omnichannel sales channels. Electric and hybrid

vehicles are common for distribution purposes. On the other hand, organization and man-

agement of distribution through omnichannel and multi-modal strategies also affect the way

companies build reverse distribution channels to recycle, upcycle and dispose waste in an

eco-friendly manner.

From a supply chain integration standpoint, automation/virtualization of supply chain infor-


37

mation transfer and in-real time traceability of supply chain data contribute to the complete

integration of the ‘flow components’ of distributed supply chains: product flow, financial flow,

supply chain (administrative) information flow, and risk flow. The full integration of financial

flows into supply chains brings capital expenditure (CapEx) cost savings; whereas material

flow integration increases control on material flow variability. In this context, soft regulatory

arrangements (e.g. industry alliances and norms) and disclosure policies are needed to op-

timize and secure product/component traceability and supply chain transparency.

While intermediary supply chain finance platforms are developing new cash flows and reve-

nue streams for the big five tech companies (i.e. Google, Apple, Facebook, Amazon, and

Microsoft) that have expanded fully into financial services, technological programming of

supply chain financing mechanisms and processes (e.g. use of complementary currency,

encrypted and cloud-based supply chain finance platforms) enables new ways of doing

business via transforming business partnership dynamics, commercial transaction transfer

channels, and commercial value exchange, especially with blockchains. Intermediaries

among the Big 5 will emerge to lead to this transformation. Complimentary currencies, when

combined with block-chain technologies, optimize transaction structures and transparent

traceability of money, while decreasing (digital) transaction cost.

Table 4-3 describes the supply chain strategic choices that address the characteristics of the

supply chain for scenario aSPIRANT.

Table 4-3: Supply Chain Strategies for Scenario aSPIRANT

Decision Field SC Strategies for Scenario aSPIRANT

Sourcing Strategy

Sourcing Global sourcing (B2.2, D4.1) Decentralised Supply Chains Global Supply Chain (A2.2, A3.1, B2.2)

Manufacturing Strategy Outsourcing (Global negotiations with local adjustments – D4.1) Onshoring (due to technological developments)

Company Location Main premises in Europe and US with subsidiaries in the rest of the world (B1.2)

SC Structure Supply chain structure simplified (D1.1) Circular economy (F1.1, F2.1)

Distribution

Inventory Levels Low and constant levels of inventory

Distribution Character-istics

Multimodal distribution (B2.2) Higher investment on distribution (A1.1) Automated logistics systems Algorithms are used extensively for optimising efficiency (D1.1) Increase of direct sales to end consumer (B3.2) Omnichannel

Shipping Characteris-tics Personalization of shipping

Structure Characteris-tics

Agile structures in the supply chain (C5.1, D1.1) New production technologies (Industry 4.0 - D5.1)


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Simplified supply chain administration (A2.2)

Transport Characteris-tics

Increased use of electric vehicles (C2.1, F1.1) Electric and hybrid vehicle systems (D3.1)

Environmental Impacts Increased sustainability of SC (D3.1) Reduced energy consumption (D3.1) Waste management (C2.1, C3.2, D3.1, E3.1, F1.1, F2.1)

Supply Chain Inte-

gration

Material Flow Integra-tion

Tracking and traceability of orders (E3.1) Supply chain tracked online and in real-time (B3.2)

Information Flow Inte-gration

and IT Infrastructure

Seamless flow of information (D1.1) Integrated flows Transparency of information about components and products (D1.1, E1.1)

Financial Flow Integra-tion Financial flows fully integrated

Finance

Presence/Absence of Intermediaries Presence of intermediaries through the “Big 5” (B4.3)

Currency Characteris-tics and Use

Global currency (D4.1) Introduction of complementary currency (A3.1) Quick and transfer of financial funds and money globally Big global companies determine the new payment logic

Regulations Global regulation (D4.1) Regulatory contracts across SC (E3.1)

Technologies Blockchain

Supply Chain for Macro-Scenario PrOCEEDINg 4.2

PrOCEEDINg (Political coherence, disruptive technologies and individualised consumerism facilitate an innovative business development) is a positive scenario in the sense that most of the trends are changing in a way which can help companies with the implementation of innovative SC models, where political and legal situations are stable and new market oppor-tunities are arising from social conditions. From the supply chain perspective, the main char-acteristics of this scenario are the following:

Political stability, combined with free trade between contended unions, opens up possibilities for wide customization opportunities. The continuity of power dominance of Europe and the U.S.A., coupled with digital transformations and collaborations between traditional finan-cial establishments and FinTech companies, encourages rapid advancement of digitisa-tion and digitalisation, as well as the dynamic development of autonomous technolo-gies. Therefore, start-ups and SMEs will take up business, while global competitors must adapt products to local culture, especially with the advent of a DIY-focused society strongly supported by individualism. Naturally, a more customized product portfolio, com-bined with broad supply sources and predictable lead-times, are required to succeed in this scenario.

Necessary investments are prominent, mostly differed to the labour market with the goal to improve workforce capability and resourcefulness, thus reducing the presence of inequali-ties and enhancing wealth distribution. High automation on developed countries, and low automation on underdeveloped countries, are expected as results, especially when consid-


39

ering the power dominance of the steady titans. The positive sustainability characteristics and stable legal framework enable the establishment of green products, as well as the im-plementation of successful circular economy as support for the supply chain. Established electrification technologies with green systems, and the continuous exploitation of disrup-tive technologies also contribute for increasing overall sustainability of the supply chain, while enabling waste management capabilities. Hence, a green, social-responsible and closed-loop supply chain is required.

From the demand perspective, we have a SC scenario based on market expansion due to firms reaching out for new markets around the globe, economic growth in US & Europe, as well as the addition of new customers into the market provided by the digital business phe-nomena. The market expansion is supported by the great number of global competitors and players, which compete through product adaptation aimed at the local culture, hence magni-fying the individualistic characteristic of the scenario. Naturally, high variety and differentia-tion of products is a key-factor in succeeding on this scenario, thus companies look for a mix of standardization and customization. On this sense, green products and data-driven ser-vices are pursued as advantages, providing companies with a competitive edge.

On the other hand of the market’s balance there are the supply characteristics, where easier access to specific materials and components aided by large variety and number of supply sources are the norm. Therefore, the lead-times are expected to be predictable, while new environmentally friendly materials and processes represent advantages for the DIY society focused in individualism, as well as for improved recovery of environmental impact combined with decreased resource depletion. Despite being supportive of market expansion and high-er variety, the free trade aspect of this supply chain scenario provides ground basis for the formation of global cartels and the rise of corruption.

Table 4-4 describes the demand and supply characteristics of the supply chain for scenario PrOCEEDINg.

Table 4-4: Demand and Supply Characteristics for Scenario PrOCEEDINg

Decision Field Product Characteristics for Scenario PrOCEEDINg

Demand Char-acteristics

Market Dimension

Market expansion: • Geographical (A1.1, A2.2) • Economic growth in US & Europe (B1.2) • New customers from digital business (B1.2, B3.2)

Competition

More global competitors (A2.2, A3.1) Global competitors adapt their product to the local culture (B2.1) Reduced competition due to needed investments on sustainability

(F1.1)

Variability Predictable demand (A1.1, A3.1, D1.1)

Variety

High variety influenced by: • Products for new markets (geographical expansion A1.1, A2.2) • Individualism (C4.1) • Product differentiation for global companies present in local mar-

kets (B2.1)

Product Portfolio Standardization (B1.2)


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Customization (B3.2, C3.3, C4.1) More green products (F1.1) More data-driven services (B3.2, D5.1) DIY-products (C3.3)


Access Easier access to specific materials and components (A2.2, F2.1)

Supply Sources Many supply sources (A2.2, F2.1)

Lead-times Predictable lead-times (A1.1, A2.2, B1.2, B3.2, D1.1, D2.1)

Risks Risk of global corruption and cartels (A2.2)

Environment New environment friendly materials (C3.3, C4.1, F1.1, F2.1) Resource scarcity in smart cities (C2.2)

The process characteristics of PrOCEEDINg supply chain scenario presents production characteristics mostly supported by high levels of production efficiency and complexity due to enabling technology adoption, product variety, and the prominence of small and medium production facilities. On the other hand, the capacity characteristics are based on flexible capacity given the individualism character of this supply chain scenario, as well as an in-creased production capacity, the rise of circular economy and wide adoption of digital ena-bling technologies to allow for digital mass customization SC. The strategies regarding the Process Characteristics of the PrOCEEDINg Scenario are aimed at a society that values individualism and the DIY concept, hence, there is the growing need for more variety, which requires a greater level of complexity from the SC point-of-view. An increased production capacity, as well as more flexibilization, are also required, due to the higher variety and to the market expansion already mentioned. These are greatly aided by an increase on produc-tion efficiency based on technology investment and adoption, while being concentrated on small and medium production facilities.

Supported by free trade political setting and the presence of disruptive production technolo-gies continuously being exploited, investments on technology R&D, technology adoption and specialized IT staff training are high. The latter refers mostly to specialist jobs to install, su-pervise, operate and maintain automation upgrades on digitalized factories, thus increasing the rate of growth of labour force overall and providing more fairness in the supply chain and business model.

With an economy being digitalized in nature and based on growing digital potential, technol-ogies based on the digitalization and digitization concepts thrive and receive more R&D in-vestments. Moreover, the rise of circular economy emphasises the focus on sustainability and the search for resource management SC processes, while also taking into account the pollution hindrance and environmental impacts, which are all complemented by the rise of electric and hybrid vehicles, environmentally friendly technologies, renewable energy tech-nologies and new electrification systems. The dynamic development of autonomous tech-nologies thrives, aided by the economic and political setting, and support investments on robotic process automation, automation of non-value-added activities, automated transporta-tion, autonomous vehicles, additive manufacturing of critical parts, cloud-based software platforms, internet of things (IoT), data science and communications infrastructure.


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Nevertheless, all investments in R&D of new technologies are combined with legal frame-work based on the full product transparency, the promotion of agreeable laws, and the full security for inventors and data providers. Therefore, there is high investments in cyber-security systems and issue-solving. The orchestrated combination of these factors, coupled with predictable demand and supply requirements, ensure a digitally flexible and reconfigu-rable manufacturing system as the basis for the production system.

Table 4-5 describes the production and capacity characteristics of the supply chain for sce-nario PrOCEEDINg.

Table 4-5: Production and Capacity Characteristics for Scenario PrOCEEDINg

Decision Field Capacity Characteristics for Scenario PrOCEEDINg


Complexity High complexity due to product variety (C3.3, C4.1)

Production Effi-ciency

High production efficiency due to technology adoption (B3.2, D1.1, D2.1, D3.1) Small and medium production facilities (D4.2)

Production Sys-tem

Digital mass customization (predictable demand and supply, high variety, Small and medium production facilities, digital technologies adoption)



Increased production capacity (see Market Dimension) Flexible capacity (C4.1)

Investment

More investments on (A1.1): • Technology (A2.2, B1.2, D5.1) • Processes • Training (D5.1) • Education (lifelong learning)

Rise in circular economy (F1.1, F2.1)

Technologies

Digital technologies (B1.2, B3.2) Cybersecurity systems (E1.1, E2.1) Robotic Process Automation (B1.2, D1.1, D2.1) Automation of non-value-added activities (B1.2, D2.1):

• High automation in high labour cost country (C5.1) • Manual process in low cost country (C5.1)

Automated transportation (B1.2, D2.1) Self-driving vehicles (D2.1) Additive manufacturing of critical parts (D2.1) Electric and hybrid vehicle systems (D3.1) Environmentally friendly technologies Renewable energy technologies New electrification systems R&D (D1.1) Cloud-based software platforms (D2.1) IoT (D2.1) Data Science (D2.1) Communications Infrastructure (D2.1)

Labour Charac-teristics

Technical skills and specialized IT staff required (D1.1, D5.1) e.g. specialist jobs have been created to install the robots and supervise produc-tion in these automated factories Increased rate of labour force growth (C1.2) Increased investment on Staff (B1.2)

The supply chain strategies for the PrOCEEDINg supply chain scenario encompasses char-


42

acteristics from sourcing strategy, distribution, integration and financial aspects. Most nota-bly, the sourcing & distribution are both global, combined with the presence of outsourcing, a simplified supply chain structure, centralized distribution centres with increase of direct sales to end consumers and the use of omnichannel distribution. There is a seamless flow of inte-gration present, aided by a centre role of IT, which provides transparency of information re-garding components and products. Monetary exchanges are intermediated through joint ef-forts of FinTechs and Banks.

From the Product characteristics and Process strategies, it is possible to devise the possible supply chain strategies for this SC scenario. Given the focus on market expansion through economic growth and the introduction of new customers, there is the need for a global sourc-ing and global distribution of the supply chain, with multiple sourcing strategies coupled with outsourcing where companies will have their main premises in Europe and US while their subsidiaries will be spread across the world to improve distribution and logistics. Also due to the circular economy present on this scenario and the rapid advancement of digitisation and digitalisation, there is the need for a supply chain structure which is simplified, boasting more agile structures and holistic planning algorithms applied to the entire SC. To aid circular economy, the presence of banks and FinTechs acting together is crucial, coupled with the introduction of complementary currency, such as the use of blockchain based cryptocurren-cy, and new models for revenue sharing and cost sharing.

The higher variety and focus on individualism, combined with a DIY society, will incur in the need for higher stocks to attend the increasing demand, which must also be personalized to respond to the variety requirements. These stocks are centralized in distribution centres with adapted logistics according to the scenario based on smart cities, which incurs in last mile transportation characteristics. The digital potential brings forth an increase of direct sales to end consumers and the personalization of shipping with flexible logistics, which are based on demand levels. The use of omnichannel distribution is also present, supporting the intro-duction of agile structures, which are the basis for a continuous exploitation of disruptive technologies within the Industry 4.0’s concept and introduction of new production technolo-gies.

The communications infrastructure needed as the backbone for the disruptive technologies becomes the basis for a seamless flow of information, while also providing environment for an integration of financial and information flows, as well as establishing the IT infrastructure as foundation for all technological developments. Moreover, it will aid on enhancing the transparency of information about components and products, thus enabling the supply chain to tracked online and in real-time through improved tracking and traceability of orders.

These strategies are supported by a robust regulatory framework, which encompasses regu-latory contracts across the supply chain and efforts on the increasing overall sustainability within the SC through reduced energy consumption, increased waste management and broader use of electric and hybrid vehicle systems.

Table 4-6 describes the supply chain strategic choices that address the characteristics of the


43

supply chain scenario for Scenario PrOCEEDINg.

Table 4-6: Supply Chain Strategies for Scenario PrOCEEDINg

Decision Field SC Strategies for Scenario PrOCEEDINg

Sourcing strategy

Sourcing Global sourcing Multiple sourcing Global supply chain (A2.2, A3.1)

Manufacturing Strategy Outsourcing

Company Location Main premises in Europe and US with subsidiaries in the rest of the world (B1.2)

SC Structure Supply chain structure simplified (D1.1) Circular economy (F1.1, F2.1)

Distribution

Inventory levels Low and personalized inventory Higher stocks (C4.1)

Distribution Characteris-tics

Centralized distribution centres and adapted logistics for smart cities (C2.2) Algorithms are used extensively for optimising efficiency (D1.1) Increase of direct sales to end consumer (B3.2) Omnichannel

Shipping Characteristics Personalization of shipping Flexible logistics, based on demand (C5.1)

Structure Characteristics Agile structures in the supply chain (D1.1, D5.1) New production technologies (Industry 4.0 - D5.1) Simplified supply chain administration (A2.2)

Transport Characteris-tics

Increased use of electric vehicles (F1.1) Electric and hybrid vehicle systems (D3.1) Last mile transportation (C2.2)

Environmental Impacts Increased sustainability of SC (D3.1) Reduced energy consumption (D3.1) Waste management (C2.2, C3.3, C4.1, D3.1, E3.1, F1.1, F2.1)


Material flow integration Tracking and traceability of orders (E3.1) Supply chain tracked online and in real-time (B3.2)

Information flow integra-tion

and IT infrastructure

Seamless flow of information (D1.1) Integrated flows Central role of IT Transparency of information about components and products (D1.1, E1.1)

Financial flow integra-tion Financial flows fully integrated

Finance

Presence/absence of Intermediaries

Reduced intermediaries and bank agencies (B4.1) FinTech (B4.1)


Introduction of complementary currency (B4.1) Reduced use of paper money

Regulations New models for revenue sharing and cost sharing based on data (B3.2,

B4.1) Regulatory contracts across SC (E3.1)

Technologies Crowdfunding New financial services accessible from anywhere via mobile apps (D5.1)


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Supply Chain for Macro-Scenario oFFsET 4.3

The macro-scenario oFFsET (Free trade enables political and social development whereas Fragmentation hinders Environmental and Technological change) can be described in gen-eral as a moderate (partially positive/ negative) scenario. It is characterised by a partially positive political environment due to open borders and reduced import and export tariffs, which enable the conditions for an agile global sourcing and distribution. On the other hand, the existence of ambiguous regulation is affecting both technology and environment. From the technological point of view, the lack of regulations has a direct impact on digital transformation, impeding a sustained development; only occasionally some technologies are successfully implemented by global companies, which can afford its adoption. Therefore, there is a coexistence of conventional and disruptive production technologies. Further-more, global players are the main players of the financial innovations and become pio-neers in the fields of digital transformation and cyber-physical systems.

Ambiguous regulations for the environment which do not face climate change, combined with increasing global population (mainly living in cities fostering the expansion of urban areas), and thus growing consumerism, are exhausting natural resources, although some countermeasures are being applied (smart cities, green systems …).

In comparison to other supply-chain scenario-models, economics (e.g. pure traditional economy) and technological dimensions (e.g. innate reluctance to accept autonomous technologies) shape the developmental path of the oFFsET scenario.

After the description provided above to shape the oFFsET scenario at a macro-level, next the following subsections descend one level and focus on a description at product, process and supply chain level for the mentioned scenario.

From the demand point of view, oFFsET scenario is driven by a moderate market expansion mainly due to a constant development of policies in Europe in a free trade setting, where emerging economies, principally from Asia, open new markets. In addition, companies’ cus-tomer portfolio is smaller because of challenges in IP protection. In this environment, more global competitors exist and less product differentiation is needed. Main competitors are multinationals with advanced IT which adapt their product to the local taste by implementing digital advancements as a way of differentiation. Because of a limited capacity to adopt digi-tal technologies, small companies will lose IT pace. Global companies which are present in local markets adopt a product differentiation strategy. Demand of sustainable products is characterised by a low variability and remains uncertain given that buying behaviours are strongly influenced by social networks in a society where standards are widely accepted but regulatory frameworks are missing. Product portfolio is characterised by sustainability for meeting conscious consumers’ needs and the existence of duplicates across regions.

From the supply point of view, the scarcity of resources, e.g. fundamental minerals, water; an easier access to specific materials and components in an already mentioned free trade setting, and uncertain lead-times are the main determinants. In this environment, a higher


45

risk associated to suppliers exists, and global corruption and cartels possibly will manage certain supply markets which lead to uncertain lead-times. Overall this occurs in underdevel-oped countries, main owners of fundamental minerals. To face this supply problem, new alternatives materials are needed. In this sense, companies implement waste management systems to recover materials, but these measures are insufficient.

Table 4-7 describes the demand and supply characteristics of the supply chain for scenario oFFsET.

Table 4-7: Demand and Supply Characteristics for Scenario oFFsET

Decision Field Product Characteristics for Scenario OFFSET


Market Dimension Moderate market expansion:

• Geographical (A1.2, A2.2) • New markets in emerging economies (B1.1)

Competition

More global competitors (A2.2, C4.2, D4.1) Global competitors adapt their product to the local culture (B2.1)

• Less differentiation, thus more competition (C4.2) • Smaller customer portfolio due to challenges in IP protection (E2.2)

Disaggregation of SC (D1.2) • Big multinational with advanced IT (D1.2) • Small companies will lose IT pace (D1.2)

Variability Uncertain demand (A1.2, A3.2, D1.2)

Variety

Low variety influenced by: • Products in emerging economies (B1.1) • Collectivism (C4.2) • Product differentiation for global companies present in local markets

(B2.1, D3.2)

Product Portfolio Duplication of product portfolios across regions (A1.2) Sustainable products for conscious consumers (E3.2)


Access Easier access to specific materials and components (A2.2) Resource scarcity (F1.2, F2.2)

Supply Sources Moderate supply sources (A2.2, F2.2)

Lead-times Uncertain lead-times (A1.2, B3.3, D1.2)

Risks Higher suppliers' risk (E2.2, E3.2) Risk of global corruption and cartels (A2.2)

Environment Resource scarcity (C2.2, F1.2) Need for new alternative materials (C3.1, F2.2) Poor waste management (F1.2)

From the production point of view, oFFsET scenario is characterised by low complexity be-cause market is driven by large amounts of standardized products, in large production facili-ties belonging to global players. Companies adopt agile manufacturing systems to face the demand characteristics (uncertain demand and supply, low variety) and additional efforts are focused on conserving water and minimise carbon emissions. Manufactures own low pro-duction efficiency due to less technology adoption in a traditional economy as some obsta-cles hinder the digital transformation, e.g. reluctance to change, cybersecurity constraints, etc. which results in a technological lag.


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Under the capacity characteristics of oFFsET scenario, only a selection of companies can afford the implementation of available technology applications. Under this scenario, more local investment in technology is needed. Because of digitalisation constraints, a technologi-cal lag is observed. Moreover, non-value-added activities are managed differently in high labour cost countries, with a high automation level, and low-cost countries, where processes are mainly manual. However, technological equipment/ capacity is underused.

Companies have a high impact on the environment. To minimise this effect, technologies such as hydrogen power cells and biomass are being used for power generation, energy storage and transportation. Lastly, within this scenario, labour is distinguished by a lack of specialized staff mainly due to the restrain of digital transformation and the production char-acteristics which involves labour growth.

Table 4-8 describes the production and capacity characteristics of the supply chain for sce-nario oFFsET.

Table 4-8: Production and Capacity Characteristics for Scenario oFFsET

Decision Field Capacity Characteristics for Scenario OFFSET




Low production efficiency due to less technology adoption (B3.3, D1.2, D2.2, D3.2) Large production facilities (D4.1) Additional efforts to conserve water and minimise carbon emissions (F1.2)

Production System Agile manufacturing system (uncertain demand and supply, low variety, large production facilities)


Equipment / Capacity Underutilization of equipment

Investment More local investment (A3.2, B2.1) Investment in Technology (A2.2)

Technologies

Technological lag Cybersecurity constraints (B3.3, B4.3, D1.2, E2.2) Automation of non-value-added activities:

• High automation in high labour cost country (C5.1) • Manual process in low cost country (C5.1)

Hydrogen power cells and biomass (D3.2) Labour Characteris-

tics Lack of specialized staff (D1.2) Increased rate of labour force growth (C1.2)

From the point of view of a sourcing strategy for this scenario it is observed that due to free trade and an increasing political unrest in countries neighbouring Europe, companies need to think glocal in terms of supply although there is a tendency towards global supply. In this sense, unstable confederations and the rise of born/global firms make it necessary to design glocal supply chains with a mix of outsourcing and nearshoring. Emerging economies, main-ly from Asia, are opening new markets, which imply the attraction of foreign investment as they are candidates for rapid growth. In this sense, an aggressive strategy could be to set up centres of excellence and operational activity in growing economies. In addition, because of the increasing depletion of natural resources and the challenges hindering the digital trans-


47

formation, more complex SCs structure has to be designed starting from the identification of alternative sources of resources.

The distribution dimension is characterised by high (multi-level) inventory levels which are maintained along the SC to face the shortage of some materials. Due to the increasing population and the growth of urban areas, with a consequent increase in the generation of waste, distribution will be mainly local and centralised by means of distribution centres and intermodal hubs and interfaces to respond quickly to the demand. Last mile transportation will have to be adapted to the characteristics of these cities. Moreover, as customers prefer standardized products, traditional sales channels and shipping processes will be chosen for the delivery. Because this scenario faces a more complex SC structure, a simplified SC ad-ministration is needed to maintain agility.

The presence of obstacles that hinder the digital transformation of the industry restrict the penetration of IT and the integration of information flows within the supply chain, and reduce the degree of automation. A low level of traceability of products is achieved because of the misalignment of IT technologies adopted by the supply chain partners leading to information overload issues and the necessity for the improvement of the IT infrastructure.

Finance dimension in the supply chain is characterised by the implementation of new pay-ment systems together with the traditional ones (paper and digital currency). Companies are resistant to change mainly because of an untrusted SC network and low data confidentiality, supported by the inexistence of regulatory frameworks. In addition, due to the existence of unstable confederations, complementary currencies are introduced and intermediaries (the “Big 5”) are needed to bring the funding sources closer to the companies. Finance is also characterised by an increased presence of blockchain and crowdfunding.

Table 4-9 describes the supply chain strategic choices that address the characteristics of the supply chain for scenario oFFsET.

Table 4-9: Supply Chain Strategies for Scenario oFFsET

Decision Field SC Strategies for Scenario OFFSET

Sourcing strategy

Sourcing Glocal sourcing (tendency for global - B2.1, D4.1) Glocal supply chain (A3.2, B2.1)

Manufacturing Strategy Mix of outsourcing and nearshoring

Company Location Centres of excellence and operational activity to be set up in grow-ing economies (B1.1)

SC Structure More complex SC structure (D1.2, F2.2) Identify alternative sources or resources (F2.2)

Distribution

Inventory levels High inventory levels Multi-level inventory Shortage of some materials

Distribution Characteris-tics

Local distribution Centralized distribution centres and adapted logistics for smart cities

(C2.2) High bullwhip effect Intermodal hubs and interfaces Traditional sales channels


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Shipping Characteristics Traditional shipping process Structure Characteristics Simplified supply chain administration (A2.2) Transport Characteristics Last mile transportation (C2.2)

Environmental Impacts Increased waste generation (C3.1)


Material flow integration Low level traceability

Information flow integra-tion

and IT infrastructure

Low IT integration Low IT penetration (D2.2) Misalignment of IT technologies adopted by supply chain partners Information overload issues Improvement of IT infrastructure

Financial flow integration Untrusted SC network (E2.2)

Finance

Presence/absence of In-termediaries

Central intermediaries (B4.3) Presence of intermediaries through the "Big 5" (B4.3)


Paper and Digital Currency Introduction of complementary currency (A3.2)

Regulations Lacking legislation and regulations (E1.2, E2.2, E3.2) Technologies Increase blockchain and crowdfunding

Supply Chain for Macro-Scenario DiThER 4.4

The macro-scenario DiThER (there is Digital and Technological development but not Enough to compete globally) is a mainly positive scenario as there is an increasing influence of digital transformation, dynamic development of autonomous technologies, establishment of electrification technologies and green systems, the continuous exploitation of disruptive technologies and investment in smart cities. Still, the digital development is obstructed by stringent legal regulations, data management and privacy issues. The increase of unem-ployment, due to autonomisation, and the acceleration of disparities create political and economic unrest. The enclosed political environment of the world leads to a policy of pro-tecting domestic industries against foreign competition. Servitization, agility and green strategies are fully recognized as important strategies by the companies.

Regarding the demand characteristics the SC scenario is based on market contraction given that this society is supported on the DIY concept of consumerism but there will also be new markets in emerging countries (especially in Asia). Due to the market contraction there will be reduced competition and global competitors will adapt their product to the local culture.

The demand in this scenario will be uncertain and there will be a high variety influenced by individualism and the product differentiation for the local markets. Based on that there will be more DIY-products, customization and sustainable and green products for conscious con-sumers. Companies must focus on more data-driven services to generate sales.

Due to protectionism and heterogeneous regulations there will be moderate supply sources causing uncertain lead-times and a higher suppliers’ risk. New environmentally friendly ma-terials will arise given the focus on individualism and DIY, but in the smart cities the resource scarcity is a problem caused by urbanisation.


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Table 4-10 describes the demand and supply characteristics of the supply chain for scenario DiThER.

Table 4-10: Demand and Supply Characteristics for Scenario DiThER

Decision Field Product Characteristics for Scenario DiThER

Demand Characteristics

Market Dimension

Market contraction (A1.2, A2.1, A3.3) New markets in emerging economies (B1.1) Decreased market size and demand of many products due to DIY society

(C3.3)

Competition

Reduced competition (A1.2, A2.1) Global competitors adapt their product to the local culture (B2.1)

• Smaller customer portfolio due to challenges in IP protection (E2.2) Disaggregation of SC (D1.2)

• Big multinational with advanced IT (D1.2) • Small companies will lose IT pace (D1.2)


Variety

High variety influenced by: • Products in emerging economies (B1.1) • Individualism (C4.1) • Product differentiation for global companies present in local markets

(B2.1)

Product Portfolio

Overlapping product development activities and portfolios across regions (A1.2) More data-driven services (B3.2, D5.1) DIY-products (C3.3) Customization (B3.2, C3.3, C4.1) Sustainable products for conscious consumers (E3.2) More green products (F1.1)

Supply Characteristics

Access Lower access to specific materials and components (A2.1)

Supply Sources Moderate supply sources (A2.1, E3.2, F2.1)

Lead-times Uncertain lead-times (A1.2, D1.2)

Risks Higher suppliers' risk (E2.2, E3.2)

Environment New environment friendly materials (C3.3, C4.1, F1.1, F2.1) Resource scarcity in smart cities (C2.2)

Due to the product variety caused by individualism and uncertain demand there will be a high complexity and mainly small and medium production facilities with flexible manufactur-ing systems and flexible capacity.

Regarding the technologies the focus, especially in the smart cities, will be on environmen-tally friendly self-driving vehicles, robots and autonomous transport systems. Although the digital transformation will have some obstacles, digital technologies will be important for the platform technology. Applications of IoT, data science and communication infrastructure will be widespread, mainly due to the dynamic development of autonomous technologies.

The SC scenario is affected by high unemployment, but the companies need multi-disciplinary staff with leadership skills due to a continuous exploitation of disruptive technol-ogies.


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Table 4-11 describes the production and capacity characteristics of the supply chain for sce-nario DiThER.

Table 4-11: Production and Capacity Characteristics for Scenario DiThER

Decision Field Capacity Characteristics for Scenario DiThER



Production Efficiency Production efficiency due to technology adoption (B3.2, D2.1, D3.1) Small and medium production facilities (D4.2)

Production System Flexible manufacturing systems (uncertain demand and supply, high variety, Small and medium production facilities, autonomous technologies adoption)


Equipment / Capacity Flexible capacity (C4.1)

Investment

Some investment on: • Technology (D5.1, F1.1, F2.1) • Training (D5.1)

Rise in circular economy (F1.1, F2.1)

Technologies

Digital technologies (B3.2) Robotics Automation of non-value-added activities (D2.1) Autonomous systems (aging population) Automated transportation (D2.1) Self-driving vehicles (D2.1) Additive Manufacturing of critical parts (D2.1) Electric and hybrid vehicle systems (D3.1) Environmentally friendly technologies New electrification systems Cybersecurity constraints (D1.2, E2.2) IoT (D2.1) Data Science (D2.1) Communications Infrastructure (D2.1)

Labour Characteris-tics

Multi-disciplinary staff (technology, market, languages, digital/analytical skills), leadership skills (D5.1) Strong unemployment possibility (C1.1, C2.2, C5.2)

Since the digital transformation is not optimally advanced, some SC structures and process-es will be complex. Due to the focus on the environmental development, circular economy will gain more attention and factories will be built near raw materials. On the one hand the levels of inventory will be lower because of additive manufacturing or demand forecasting with data science and artificial intelligence the inventory levels will also increase due the individualism which causes a high variety and the duplication of stocks caused by many dif-ferent hubs.

Regarding the distribution characteristics the focus will be on local distribution due to protec-tionism and fragmentation on the political level. A quicker delivery will be possible because of decentralized distribution centres and manufacturing freight hubs. New production tech-nologies will be necessary due to the continuous exploitation of disruptive technologies.

In the transportation sector, there will be an increased use of electric and hybrid vehicles based on established electrification technologies and green systems. The last mile transpor-


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tation will become more important because of the urbanisation and the development of smart cities, so that innovative autonomous transport systems and concepts for the last mile deliv-ery will be needed. Because of that development and the DIY society the people will have a focus on waste management and there will be a reduced energy consumption.

Due to the possibilities offered by the platform economy the supply chain will be tracked on line and in real-time. Start-ups will arise, and SMEs will take up business, so that there will a higher knowledge and more information on the consumers’ patterns. Given the market play-ers and low data confidentiality, the SC network will not be trustful.

Regarding financial innovations which will be influenced by Bank and FinTech collaboration intermediaries and bank agencies will diminish in importance and complementary currencies will be introduced. There will also be new models for revenue sharing and cost sharing on data and new financial services accessible from anywhere via mobile apps thanks to contin-uous exploitation of disruptive technologies.

Table 4-12 describes the supply chain strategic choices that address the characteristics of the supply chain for scenario DiThER.

Table 4-12: Supply Chain Strategies of Scenario DiThER

Decision Field SC Strategies for Scenario DiThER

Sourcing strategy

Sourcing Strong local SC (A2.1) Single and Multiple sourcing

Manufacturing Strategy Outsourcing and onshoring

Company Location Centres of excellence and operational activity to be set up in growing economies (B1.1)

SC Structure More complex SC structure (D1.2) Circular economy (F1.1, F2.1) Factories near raw materials

Distribution

Inventory levels Low levels of inventory Higher stocks (A2.1, C4.1)


Optimized distribution, continuous cycle Decentralised distribution centres and manufacturing freight hubs will

support quicker delivery Automated logistics systems Local distribution (A3.3) Increase of direct sales to end consumer (B3.2) e-commerce reduces direct sales Omnichannel

Shipping Characteristics Personalization of shipping

Structure Characteristics More complex SC structure (D1.2) New production technologies (Industry 4.0 - D5.1)

Transport Characteristics Increased use of electric vehicles (F1.1) Electric and hybrid vehicle systems (D3.1) Last mile transportation (C2.2)

Environmental Impacts Waste management (C2.2, C3.3, C4.1, D3.1, E3.1, F1.1, F2.1) Reduced energy consumption (D3.1)

Supply chain inte-

Material flow integration Tracking and traceability of orders Supply chain tracked online and in real-time (B3.2)


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gration Information flow integration and IT infrastructure

Higher knowledge and information on consumer patterns (D4.2) Misalignment of IT technologies adopted by supply chain partners


Finance

Presence/absence of Inter-mediaries

Reduced intermediaries and bank agencies (B4.1) FinTech (B4.1)


Introduction of complementary currency (B4.1) Reduced use of paper money

Regulations New models for revenue sharing and cost sharing on data (B3.2, B4.1)

Technologies Crowdfunding New financial services accessible from anywhere via mobile apps (D5.1)

Supply Chain for Macro-Scenario UNEasE 4.5

Scenario UNEasE (UNstable political sEtting and power shifting hinder the technological and Environmental development) describes an unstable political environment in which compa-nies have to face protectionism, economic uncertainty and alliance collapse. This scenario is also characterised by poor legislations in different fields: from the heterogeneous environ-mental regulations which cause a continuous resource depletion, to the laws to protect intellectual property and customer data which are lagging significantly. This creates obsta-cles for a complete digital transformation of society and companies, mainly in the busi-ness to business environment: the traditional economy persists, as do the traditional pro-duction technologies which coexist with the disruptive ones often used by big players. But SMEs and start-ups can compete in the local markets where they are able to create a large variety of products to answer to customer individual needs and to the DIY trend, which is rising.

Therefore, this scenario presents supply chains with customized products, leagile SC par-adigm, glocal sourcing and local distribution strategies. Mostly given the low-tech (tech conservatives) characteristic of this scenario, supply chain configuration is based on urban manufacturing strategy, aided by flexible manufacturing and traditional sales channels. Regarding environmental and social strategies, resource-efficient and humanitarian SC strategies are employed with aim to react to possible disastrous environments.

UNEasE scenario is compelling companies to rethink their Supply Chain and their process-es. Indeed, Supply Chains are strongly affected by the surrounding to which they belong and relate. Customization will become a pivotal instrument to meet customer needs above the barriers created by protectionism and cultural differences, and this will demand more flexibil-ity in the supply chain logistics for delivering the consequent product mix. Hence, the variety of the demand will spread, and companies will be asked to manage wider product portfolios. From the supply perspective, supply chains will be required to comply with lower costs of sourcing and inbound logistic. From the demand perspective, SCs need to adapt to the resizing of market dimensions and geography due both to the growing protectionism caused by the nationalist reaction to the increasing instability and crisis of the European political asset, and also to the ascent of BRIC and MINT as industrial powers and net investors.


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The supply management will be primary affected by the scarcity of resources. For instance, the scarcity of resources will compel companies to consider changing products’ components or to develop partnerships with strategical suppliers. The abovementioned unstable envi-ronment will force companies to manage and low risks connected to the flow of materials in the upstream of the SCs, via a reduction of the sourcing lead time, for example. Given the bad environmental situation, companies will be challenged to make extra effort to achieve a higher level of sustainability performance also at product level, in a scenario which is loom-ing outdated in terms of legislation and policies that favour technological advancements.

Table 4-13 describes the demand and supply characteristics of the supply chain for scenario UNEasE.

Table 4-13: Demand and Supply Characteristics for Scenario UNEasE

Decision Field Product Characteristics for Scenario UNEasE


Market Dimension

Market contraction (A1.2, A2.1, A3.3) New markets in emerging economies (B1.1) Decreased market size and demand of many products due to DIY society

(C3.3)

Competition

Reduced competition (A1.2, A2.1) Global competitors adapt their product to the local culture (B2.1)

• Smaller customer portfolio due to challenges in IP protection (E2.2) Disaggregation of SC (D1.2)

• Big multinational with advanced IT (D1.2) • Small companies will lose IT pace (D1.2)


Variety

High variety influenced by: • Products in emerging economies (B1.1) • Individualism (C4.1) • Product differentiation for global companies present in local markets

(B2.1, D3.2)

Product Portfolio

Duplication of product portfolios across regions (A1.2) Customization (C3.3, C4.1) Sustainable products for conscious consumers (E3.2) DIY-products (C3.3)


Access Lower access to specific materials and components (A2.1) Resource scarcity (F1.2, F2.2)

Supply Sources Less supply sources (A2.1, E3.2, F2.2)



Environment Resource scarcity (C2.2, F1.2) Need for new alternative materials (F2.2)

From the production point of view, this scenario is characterized by high complexity due to the increased level of product variety. Low levels of new technology adoption, derived by the prevalence of small and medium production facilities, affect production efficiency, and re-quest additional efforts to minimize resource consumption, especially concerning water, and carbon emission. One of the most suitable opportunities to face this issue is offered by alter-native energies, such as hydrogen power cells and biomass. Flexible manufacturing systems


54

are strongly implemented to cope with an uncertain demand and supply and other peculiari-ties of this scenario as the high product variety.

Also, capacity needs to be flexible to adapt to the characteristics above-mentioned. Invest-ments are reduced due to the economic uncertainty and lagging regulations on IPR, leading to less innovation in products and processes. Cybersecurity constraints also affects the digi-tal transformation and the related implementation of new technologies due to the relevance of protecting customer data, especially when dealing with personalized production. Besides that, in fact, the adoption of technologies as addictive manufacturing is increasing in order to enable the exploitation of the rising DIY trend and support the realization of personalized products according to individual needs. And this will have an impact both on internal and external processes. Within this scenario labour is characterized by the need for flexible and specialized staff, able to handle such kind of production and systems. IT Specialized staff with proper skill set for the full implementation of the DIY paradigm in SC is still lacking with an increased unbalance between labour offer and demand impacting on the risk of unem-ployment.

Table 4-14 describes the production and capacity characteristics of the supply chain for sce-nario UNEasE.

Table 4-14: Production and Capacity Characteristics for Scenario UNEasE

Decision Field Capacity Characteristics for Scenario for Scenario UNEASE




Low production efficiency due to less technology adoption (B3.1, D1.2, D2.2, D3.2) Small and medium production facilities (D4.2) Additional efforts to conserve water and minimise carbon emissions (F1.2)

Production System Flexible manufacturing systems (uncertain demand and supply, high variety, Small and medium production facilities)


Equipment / Capacity Flexible capacity (C4.1)

Investment Less investment leading to less innovation in products and processes (A2.1)

Technologies

Cybersecurity constraints (D1.2, E2.2) Additive manufacturing (F2.2) Rise of sharing economy (B4.1) Hydrogen power cells and biomass (D3.2)

Labour Characteristics Flexible and specialized staff Lack of IT Specialized staff (C5.2, D1.2) Increased unemployment possibility (C1.1, C2.2)

Due to protectionism and political fragmentation companies in this scenario need do think global but adopting local supply chains with glocal and single sourcing. To maintain their market share and be competitive also in the emerging economies, according to the shift of economy power, it will be in fact necessary to rethink the supply chains with different strate-gies of sourcing and shoring, finding the right balance among onshoring, nearshore and far-shoring. A conservative strategy can be to increase the level of inventories to cope with re-source scarcity, but it will have to match also with the need of providing a high variety of


55

products and customization requirements, which calls, on the contrary for higher stocks. An-other strategy to face the problem of protectionism is represented by farshoring which means to move the SC to countries where there are no duties or specific resources/materials necessary in the production process are available. When dealing with growing economies, centres of excellence and operational activity will have to be implemented in order to fully exploit business potentials. Thus, the supplier location will play a crucial role to optimise in-ventory and logistics costs, access to resources and minimise environmental impacts. As already underlined, another factor that impacts on location and configuration decisions is the increase in demand of personalized products and the rise in the adoption of the DIY para-digm, since there will be the need to realize personalised components /products near the customer or by customer her/himself. For this reason, cost has not a relevant role in the supply decision process and parameters on which outsourcing is based are mainly quality level, service level, capability to manage strict requirements and short delivery times.

For what concerns the distribution, even if traditional sales channels are still widely adopted, companies have to take into consideration the increase of direct sells to customer caused by the implementation of digital economy in the relationships business to customer (B2C) and supported by the increment of the DIY trend. This increase the needs of centralized distribu-tion networks near located to the reference market to respond quickly to demand and to deal with the expansion of the urban areas and the rise of smart cities, developing last mile deliv-ery to implement the just in time distribution through adapted logistics. This can help compa-nies to reduce the uncertainty of lead times: sometimes it will be necessary to combine glob-al sourcing strategies with a local distribution network or create a complete supply chain in local market to protect the market share from global risk.

Due to the presence of many obstacles for the complete digital transformation of industry, there are difficulties in the integration of the flows along the supply chain. The traceability of goods and materials and the real time collection of information from the different network partners are reduced also because there is lack of common ICT infrastructure and misalign-ment of IT technologies adopted, which affects trust between the SC players. This problem is even more relevant for companies that have to decentralize part of their supply chain in faraway countries, while in Europe autonomous factories are progressively becoming the standard, enabling the integration of the flows along the local-regional supply chains.

Since in this scenario the digital transformation is mainly implemented in the B2C level and less in B2B, also finance resources are characterized by the contemporary presence of tradi-tional banks for B2B tiers in the SC and FinTech start-ups which will provide venture capital based on digital currencies for the final tiers of SC where mobile apps and smart contracts represents also technologies widely diffused.

Table 4-15 describes the supply chain strategic choices that address the characteristics of the supply chain for scenario UNEasE.


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Table 4-15: Supply Chain Strategies for Scenario UNEasE

Decision Field SC Strategies for Scenario UNEasE

Sourcing strategy

Sourcing Glocal sourcing (tendency for global - B2.1) Local SC (A2.1) Single sourcing

Manufacturing Strategy Onshoring, nearshore and farshoring


SC Structure More complex SC structure (D1.2, F2.2) Identify alternative sources or resources (F2.2)

Distribution

Inventory levels High inventory levels (A2.1, B3.1, C4.1)


Local distribution (A3.3) Just-in-time distribution (B3.1) Multi-channel distribution (B2.1) Centralized distribution centres and adapted logistics for smart cities

(C2.2) Traditional sales channels

Shipping Characteristics Traditional shipping process

Structure Characteristics More complex SC structure (D1.2, F2.2)

Transport Characteristics Last mile transportation (C2.2)

Environmental Impacts Waste management (C2.2, C3.3, C4.1)

Supply chain inte-

gration

Material flow integration Reduced supply chain traceability


Low IT penetration (D2.2) Misalignment of IT technologies adopted by supply chain partners IT infrastructure to support processes


Finance

Presence/absence of In-termediaries

Centralized banking system (B4.1) Conservative adoption of FinTechs (B4.1)

Currency Characteristics and Use Introduction of complementary currency (B4.1)

Regulations New models for revenue sharing and cost sharing (B4.1) Lacking legislation and regulations (E1.2, E2.2, E3.2)

Technologies Use of mobile apps and smart contracts

Supply Chain for Macro-Scenario ENDANGEr 4.6

The ENDANGEr (EuropeaN Disintegration ANd protectionism lead to Geopolitical, social, Environmental, legal, technological and economic issues that affect companies’ success) scenario can be considered as a pessimistic scenario since companies are facing an unsta-ble political environment in Europe, a ‘global trade shift’ from advanced economies to-wards emerging market economies, as well as protectionism. Moreover, climate change, resource scarcity, and the lack of environmental and digital regulations are putting compa-nies to high risks and challenges.

The impacts of these megatrends and trends lead to frugal mass products, risk-hedging, glocal sourcing and local distribution, medium-tech, simple production systems in emerging markets, efficient and reconfigurable manufacturing systems, traditional sales


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channels, resource-efficient, industrial symbiosis and humanitarian supply chains.

Regarding the demand characteristics, markets are composed of different segments that have their own distinct needs and preferences. For example, companies particularly from Europe (collapse and disintegration of the EU, euro fall sharply against the dollar and the yen) adapt their products to respond to customer needs from emerging economies and con-sumers are becoming not only environmentally conscious, but environmentally responsible and they are considering the environmental impact of their purchases. Moreover, buying behaviours are strongly influenced by social media i.e. recommendations and posts from family and friends. As different buyer segments appear and disappear companies face an uncertain demand. In all these segments there are mass-market products and consequently companies are selling the same product to everybody. Companies are creating only minor variations of a similar product across different regions. Since products are similar enough, competition exists as there are groups of related products that can be considered to be close substitutes. In terms of IT products and services, the political instability leads to a non-homogeneous legislation where digitalisation is obstructed by retention. Big multinational that have significant resources, can afford to implement advanced IT whereas these con-straints obstacle the IT development in SMEs.

Concerning the supply characteristics of the ENDANGEr scenario, supply chains face pro-tectionism (e.g. tariffs on imported goods and import quotas) and resource scarcity. These two megatrends inhibit the accessibility to specific materials and components and thus in-crease prices as companies are forced to find more expensive, or lower quality, domestic supplier, or find a new overseas supplier. With tariffs limiting the access to foreign markets and resource scarcity limiting access to key raw materials, there are higher suppliers’ risk and uncertain lead times, requiring new alternative materials, waste management practices, price renegotiations and buyer-supplier relationships to be built from scratch.

Table 4-16 describes the demand and supply characteristics of the supply chain for scenario ENDANGEr.

Table 4-16: Demand and Supply Characteristics for Scenario ENDANGEr

Decision Field Product Characteristics for Scenario ENDANGEr


Market Dimension Market fragmentation (A1.3, A2.1, A3.3) New markets in emerging economies (B1.1)

Competition

Reduced competition (A1.3, A2.1) • Global competitors adapt their product to the local culture (B2.1, D4.1) • Less differentiation, thus more competition (C4.2) • Smaller customer portfolio due to challenges in IP protection (E2.2)

Disaggregation of SC (D1.2) • Big multinational with advanced IT (D1.2) • Small companies will lose IT pace (D1.2)


Variety

Low variety influenced by: • Products in emerging economies (B1.1) • Collectivism (C4.2) • Product differentiation for global companies present in local markets


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(B2.1, D3.2, D4.1)

Product Portfolio Duplication of product portfolios across regions (A1.3) Sustainable products for conscious consumers (E3.2) Mass-market products


Access Lower access to specific materials and components (A2.1) Resource scarcity (F1.2, F2.2)

Supply Sources Less supply sources (A2.1, E3.2, F2.2)



Environment Resource scarcity (C2.2, F1.2) Need for new alternative materials (C3.1, C4.2, F2.2) Poor waste management (F1.2)

When considering process characteristics, in the ENDANGEr scenario there is a high con-sumption of cheap goods (high volume / low complexity production) that require large pro-duction facilities to be produced. Reconfigurable manufacturing systems are designed to quickly adjust production capacity (i.e. increased production capacity due to market segmen-tation) and functionality in response to changes in market or in regulatory requirements. Due to protectionism and the political instability in Europe companies are not willing to heavily invest and thus the products and processes in production are characterised by insufficient levels of research and development and innovation.

Companies apply lean and efficient process settings to minimise logistics and material costs. Climate change and resource scarcity lead companies also to streamline their operations, incorporate more sustainable and lean practices such as recycling and adopt certain tech-nologies (e.g. hydrogen power cells and biomass, robots, autonomous systems, IoT and data analytics, 3D printing) to minimise carbon footprints and achieve a moderate production efficiency. Advances in automation and robotics eliminating the need for low-skilled workers whereas increasing the need for employees with specialised skills and knowledgeable in the latest technologies. However, there are digital challenges regarding the protection of valua-ble intellectual property and business information that restrain process digital transformation and require investments in research and development.

Table 4-17 describes the production and capacity characteristics of the supply chain for sce-nario ENDANGEr.

Table 4-17: Production and Capacity Characteristics for Scenario ENDANGEr

Decision Field Capacity Characteristics for Scenario ENDANGEr




Moderate production efficiency due to some technology adoption (B3.1, D1.2, D2.1, D3.2) Large production facilities (D4.1) Additional efforts to conserve water and minimise carbon emissions (F1.2)

Production System Reconfigurable Manufacturing Systems (high uncertainty in demand and

supply, low variety, large production facilities, autonomous technologies adoption)


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Equipment / Capacity Increased production capacity (see Market Dimension)

Investment Less investment leading to less innovation in products and processes (A1.3, A2.1)

Technologies

Robotics Automation of non-value-added activities (D2.1) Autonomous systems Automated transportation (D2.1) Self-driving vehicles (D2.1) Additive manufacturing of critical parts (D2.1, F2.2) Cybersecurity constraints (D1.2, E2.2) IoT (D2.1) Data Science (D2.1) Communications Infrastructure (D2.1) Hydrogen power cells and biomass (D3.2)

Labour Characteris-tics

Lack of specialized staff (C5.1, D1.2) Increased unemployment possibility (C1.1, C2.2)

As the global centre of economic activity (in terms of GDP growth, population growth and disposable incomes) is shifting towards emerging economies such as BRICS and MINT countries, companies are moving their production and adapt their capabilities to be close to most important new markets. China is currently the largest economy followed by India, the market is fragmented, protectionism is on the rise, and there is political instability in Europe that cause a shift towards local supply chains. Considering the structure of supply chains, supply chain operations will shift to new countries to reach customers in the emerging econ-omies since business will be more difficult to grow within the EU. Companies source locally or/and outsource their business operation to companies in a nearby country. Glocal sourcing and nearshoring minimise the distance and transportation time, thus the costs and carbon emissions are reduced. Shorter local supply chains enable companies to achieve supply chain transparency (e.g. tracking and traceability of orders) and accurately predict delivery times and supply and demand issues. There are low levels of inventory based on demand, however for certain scarce resources companies keep high inventory levels or avoid the use of these resource in their production lines such as rare earth materials, metals due to price volatility so there is no need to be stockpiled. Resource scarcity and protectionism lead also companies to search for alternative resources and different suppliers.

From the logistics point of view, deliveries from suppliers are moved to a central location (full load quantities). Loads consolidated and delivered to the branches. Local warehousing and local distribution are used to deliver the products to the final recipients. Just-in-time distribu-tion strategies are used such as cross‐docking. These strategies minimize inventory levels and lead times. As cities become more and more populated and with the increase of e-commerce, there is a rise of the last mile logistics. In the last mile delivery, the most wide-spread transport mode adopted is road that accounts for a high generated traffic volume in the urban area as well as negative environmental impacts i.e. greenhouse gases (GHGs). Established freight transport companies and courier firms are responsible for the shipping of the products in the big cities. Automated logistics systems i.e. computer software and/or au-


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tomated machinery are used such as automated storage and retrieval systems and industrial robots. Supply chain integration in terms of information flow integration and IT infrastructure is low and there is a misalignment of technologies and software solutions adopted by supply chain partners. Issues with quality and delivery of the products are caused by this misalign-ment. Moreover, companies are facing cyber-attacks such as service disruptions, IP theft, data leakage, thus data collection and sharing impacted followed by reputation loss and ser-vice outages.

Apart from the issues with information flows, there are issues with the integration of financial flows due to the market players and low data confidentiality. As financial processes such as smart contracts are handled from individual to individual, they have far-reaching implications in several legal fields, such as contract law (e.g. consumer protection), liability for damage resulting from incorrect or incomplete code, regulatory concerns and data privacy issues.

Table 4-18 describes the supply chain strategic choices that address the characteristics of the supply chain for scenario ENDANGEr.

Table 4-18: Supply Chain Strategies for Scenario ENDANGEr

Decision Field SC Strategies for Scenario ENDANGEr

Sourcing strategy

Sourcing Glocal sourcing (A3.3, B2.1) Shift towards local Supply Chains (A1.3, A2.1)

Manufacturing Strategy Outsourcing (Workshop) Nearshoring


SC Structure More complex SC structure (D1.2, F2.2) New SC structure to counterbalance the mission of central government Identify alternative sources or resources (F2.2)

Distribution

Inventory levels High inventory levels (A2.1, B3.1) Low levels of inventory based on demand Avoid the use of scarce resources in production to stock (C2.2, F1.2)


Just-in-time distribution (B3.1) Local distribution (A3.3) Distribution carried out by a few companies in the big cities (B2.1, C2.2) Centralized distribution centres and adapted logistics for smart cities

(C2.2) Automated logistics systems Traditional sales channels

Shipping Characteristics Traditional shipping process

Structure Characteristics More complex SC structure (D1.2, F2.2)

Transport Characteristics Last mile transportation (C2.2)

Environmental Impacts Increased waste generation (C3.1)

Supply chain inte-

gration

Material flow integration Tracking and traceability of orders


Lower development of IT infrastructure Misalignment of IT technologies adopted by supply chain partners Issues with quality and delivery of the products


Finance Presence/absence of Inter-mediaries Absence of intermediaries (B4.2)


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Encouraged social useful behaviour through complementary currency (B4.2) Difficult to finance projects in emerging countries (B4.2) Unsecured transactions (B4.2) Very difficult cash-flow management (B4.2) Faster payment processes (B4.2)

Regulations Financial processes are handled from individual to individual (B4.2)

Technologies Data collection and sharing cooled down (cyber-attacks)


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5 Summary of Supply Chain Strategies for Macro-Scenarios

In this chapter, a list of strategies aggregated in different strategic dimensions is presented. These strategies help to summarize the most important characteristics of the supply chains per each of the six macro-scenarios as they were collected during the work in Chapter 4.

Supply Chain Strategic Dimensions 5.1

The supply chain strategic dimensions herein addressed relate to the characteristics de-scribed throughout Section 3.2 of this deliverable. Moreover, they were selected by cross-check analysis between the afore mentioned characteristics and the macro-scenarios devel-opment paths presented in D2.2. From this cross-check, 8 supply chain strategic dimensions were identified, containing 32 different strategies, as further shown in Figure 5-1. The SC dimensions are: Products & Services; Supply Chain Paradigm; Sourcing & Distribution; Technology Level; Supply Chain Configuration; Manufacturing Systems; Sales Channel; and Sustainability. On this section, a brief definition of these dimensions and their strategies is presented.

Figure 5-1: Supply chain strategic dimensions

5.1.1 Product & Service

The products and services dimensions consider characteristics regarding, mostly, strategies focused on the Products Decisions related in 3.2.1. Therefore, it comprises strategies aimed at satisfying three product categories, which were observed within the supply chain charac-teristics: mainstream products, customized products and frugal mass products. Moreover, the services have been correlated with the presence or absence of servitization, mostly re-


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lated with the data driven services in digitalized macro-scenarios.

5.1.2 Supply Chain Paradigm

The supply chain paradigm dimension refers to four major aspects of the supply chain strat-egies namely efficient supply chain, leagile supply chain, agile supply chain and risk-hedging supply chain based on different combinations of demand and supply uncertainties.

Mainstream products

Mainstream products are characterized, generally, by presenting life cycles within maturity stages, medium/high production volume and cost related strategy. Moreover, they usually are more inclined towards customized products rather than to standard products, with a wide product range portfolio. In addition, they present initial-to-intermediate value profile with high monetary density. Regarding market aspects, mainstream products present longer relative delivery time, frequency and uncertainty. They are also characterized for being implemented with large economies of scale and little to none special capabilities [86].

Customized products

Customized products are personalized, especially considering the final stages of manufac-turing, and require production infrastructure which is component-based and involves large number of suppliers that determine the effectiveness of product delivery for the final con-sumer [47]. Thus, successful customized products’ strategies require an integrated supply chain system, where information of the personalization requirements is effectively provided to all members of the chain in real-time, combined with the production at minimal costs for the consumers [47]. Therefore, customized products are present on high variety scenarios, being supported by individualistic societies and products designed for new markets.

Frugal mass products

Frugal products and services are those that reduce total ownership costs, combined with low maintenance and repair, while also providing robustness, user friendliness and economies of scale, thus being mostly focused on low cost characteristics [18, 96, 119]. In this sense, macro-scenarios with low variety supported by collectivism, combined with duplication of product portfolios across regions and mass-market products, require application of frugal mass products strategies.

Servitization

Being closely related to the capability of offering services as complements, or even substi-tutes, for available products, the servitization strategy mostly refers to the transformation of products as stand-alone selling items towards package based customizable products with services attached [31]. Therefore, it is more prominent on supply chain scenarios which pre-sent high levels of digitization and digitalization. It also greatly benefits from customization aspects, despite not requiring them to be implemented.


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5.1.3 Sourcing & Distribution

The sourcing and distribution strategies are supported by the supply chain scenarios’ char-acteristics as described on sections 3.2.3.1 and 3.2.3.2 of this deliverable. It should be noted that, despite describing characteristics regarding both sourcing and distribution, the selection of strategies considers particular aspects of the supply chain scenarios, therefore, sourcing and distribution strategies may coincide (for instance, both global sourcing and global distri-bution). However, these strategies may also be different from one another (for instance, local sourcing with glocal distribution). This differentiation was done aiming at providing compa-nies with mixed strategies, in order to better assess multiple possibilities of environments in which they are placed, as well as to better conform with characteristics from the supply chain scenarios themselves.

Efficient

The efficient supply chain paradigm considers functional products and a stable supply pro-cess. There is low demand and supply uncertainty and that means that predictions can be accurate. For that reason, the supply chain is mostly cost-driven [56].

Leagile

The leagile supply chain paradigm is a combination of lean thinking and agile practices in managing the supply chain where lean supply seeks to develop a value stream to eliminate waste, and agile supply uses market knowledge to exploit opportunities in a volatile envi-ronment. The materials supply side focuses in leanness in order to achieve a smooth sched-uling in production while the customers’ side uses agile strategies in order to respond to the volatile market demand. The leagile supply chain paradigm is an effective management par-adigm in continuously changing environments [56].

Agile

The agile supply chain paradigm considers innovative products and an evolving supply pro-cess. There is high demand and supply uncertainty and that means that predictions cannot be accurate. However, the agile supply chain can adapt in changing market conditions (e.g. changes in trading regulations, technology, production processes) and volatile markets. It combines strengths of responsive and risk-hedging strategies to be able to respond to the uncertain customers’ demand while minimizing the supply interruption risk. Also, the agile supply chain can use market knowledge to exploit the volatile market opportunities [56].

Risk-Hedging

The risk-hedging supply chain paradigm considers functional products and an evolving sup-ply process. Risk-hedging strategies try to share the risk of interruption in the supply process by solutions such as transhipment and use of multiple sources of supply [56].


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5.1.4 Technology Level

The technology level is closely related to digital mastery, which comprises technology-enabled initiatives regarding customer experience and internal operations, combined with leadership capabilities including vision, governance, engagement and IT-Business relation-ships. Thus, this supply chain dimension is divided into four strategies: Digital Masters (High-Tech), Tech Fashionistas (High-Tech), Tech Beginners (Medium-early-adoption-Tech) and Tech Conservatives (Low-Tech) [20].

Global

The globalisation trend affects logistics management and supply chain as a hole, in which global companies source their raw materials and components in worldwide fashions, while products are generally manufactured offshore. Distribution also occurs in worldwide terms, with products being sold in different countries, which may or may not incur in local customi-zation at the final stages of manufacturing [27]. Thus, global sourcing and distribution strate-gies were considered regarding the decentralized supply chains, multiple sourcing capabili-ties, as well as multimodal distribution combined with investment levels.

Glocal

A glocalized sourcing and distribution strategies concerns the mix between global and local supply chains. In this sense, an example of glocal network would be a firm, which is geo-graphically centred on a given region, and boasts production’, infrastructure’, community’, environment’ and lifeline’ characteristics, being further surrounded by suppliers and/or dis-tributors, forming a localized and globalized logistics network [6]. Thus, glocal networks have important implications regarding sustainability and resilience aspects of the supply chain logistics [6]. Thus, glocal sourcing and distribution strategies were considered regarding the centralized & decentralized supply chains (depending on the supply chain considered), sin-gle and/or multiple sourcing capabilities, high bullwhip effect, as well as intermodal hubs & interfaces combined with traditional sales channels.

Local

Local sourcing and distribution regard the nearby areas surrounding a given firm. Most nota-bly, local strategies may concern an area that encompasses a city, a region, or even a coun-try, depending on the supply chain studied. It is commonly referred as the opposite to global sourcing and distribution strategies. Therefore, local supply chains tend to have nearshoring manufacturing strategies, local distribution based on centralized distribution centres (which may or may not be multichannel in nature), as well as just-in-time distributions capabilities.

High-Tech (Digital) / Digital Masters

High-tech, or digital masters, refer to a strong overarching digital vision employed with good


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5.1.5 Supply Chain Configuration

The supply chain configuration dimension refers to four major aspects of the supply chain strategies namely hyperconnected factories, modular systems, urban manufacturing and simple systems.

governance, aided by many digital initiatives. These initiatives generate business values which are tangible and are also measurable. Moreover, there is a strong digital culture em-ployed [20].

High-Tech (Digital) / Tech fashionistas

Tech-fashionistas involve a high digitalized framework, with many advanced digital features. Nevertheless, there is a lack of overarching vision, with underdeveloped coordination and a digital culture which is only present in segmented niches [20].

Medium-Tech (early-adoption-tech) / Tech beginners

Tech beginners present management which is sceptical of the business value regarding ad-vanced digital technologies. Thus, companies with this strategy implemented carry experi-ments and research on technology on rare occasions and only with very particular require-ments. Therefore, the digital culture is lacking maturity and integrity [20].

Low-Tech / Tech conservatives

Despite presenting an overarching digital vision, this view is extremely underdeveloped and presents few advanced digital features. There is a strong presence of traditional technolo-gies and a lack of research and development investment, with strong governance [20].

Hyperconnected factories

Hyperconnected factories (or smart factories) refer to hyper-connected network-based inte-grated manufacturing systems. They acquire all information on manufacturing facilities in real time through the Internet, autonomously change manufacturing methods, replace raw materials and ultimately implement optimized dynamic production systems. The key success factors of the hyperconnected factories are the integration of production system (capability of vertical integration), the integration of product lifecycle through complete information ex-change (capability of integrating product life-cycle) and the integration of inter-company val-ue chain and information network (horizontal integration) [87].

Modular Systems

Modular systems refer to the efficient organisation of complex products and processes by decomposing complex tasks into portions to allow the tasks to be managed independently and yet work together as a whole without compromising performance. Physical changes can be implemented more easily without adding tremendous complexity to the manufacturing


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5.1.6 Manufacturing Systems

Manufacturing systems are closely related to production systems within production charac-teristics. Thus, they regard the manufacturing characteristics considering, mostly, the supply chains’ flexibility and agility requirements. Therefore, most of the strategies herein described are supported by the characteristics observed and detailed in Section 3.2.2.1 of this deliver-able.

system. Also, savings can be gained through economies of scale and product changes such as upgrades are easy to be made [88].

Urban Manufacturing

Urban manufacturing refers to the rise of small-scale manufacturing in urban areas. Compa-nies that want to expand or relocate, try to find smaller spaces in urban areas instead of large facilities that employ hundreds or even thousands of people. That happens mainly be-cause manufacturers can gain proximity to the workforce [101].

Simple Systems

Simple systems are employed as supply chain configuration on environments that present low maintenance and repair, with low-to-medium levels of digitalization and a focus on low cost [96]. Therefore, they are implemented on supply chain scenarios that regard frugal mass products, risk-hedging paradigm, combined with an efficient and reconfigurable manu-facturing system.

Digital lean manufacturing

Lean manufacturing main objective can be regarded as providing customer satisfaction by adding value and eliminating waste. The long-term relationship between manufacturer and supplier is also considered. Moreover, it is based as a set of management practices and techniques focused on waste generation and alternative model representation compared to capital-intense mass production. In this sense, digital lean manufacturing systems are ob-served within supply chain scenarios that bear highly digital capabilities tangled with main-stream products and an efficient supply chain.

Digital mass customization

Mass customization is mostly focused on broad provision of personalized products and ser-vices by modularizing design, having flexible processes and allowing for integration between SC members. Therefore, it mostly develops from on lean-agility framework, where producers must achieve agile responses to personalized demand and provide affordable customization. Moreover, agility may be seen as a condition for mass customization, while lean production systems and mass customization can be considered pre-requisites for agile manufacturing. The different configurations aforementioned depend greatly on the sector studied and ap-


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5.1.7 Sales Channel

The sales channel dimension refers to three major aspects of the supply chain strategies namely omnichannel, consumer to consumer and traditional sales channels.

proach intended. On the NEXT-NET case, digital mass customization is related to highly digitalized supply chain scenarios that present product customization characteristics as well as leagile supply chains.

Agile Manufacturing

Agile manufacturing is a comprehensive response to business challenges of profiting from rapidly changing, continually fragmenting, global markets for high quality, high performance, customer configured goods and services. Hence, it relates to the ability to compete and prosper within a state of dynamic change. Aimed towards satisfying customers by configur-ing to order, it allows for unpredictability with strategies to face uncertainties. Therefore, agile manufacturing within NEXT-NET project is perceived within supply chain scenarios that pre-sents mainstream products combined with agile supply chains and modular systems configu-ration.

Flexible Manufacturing

Mostly aimed towards adaptation to customers preferences and changing needs, flexible manufacturing must react with little penalty time, being either reactive of proactive in nature. On the reactive form, it is used to contradict environmental uncertainty, whereas the proac-tive form refers largely to the organization’s desire to redefine market uncertainties in order to influence consumers’ preferences. Within NEXT-NET, flexible manufacturing systems are employed on supply chain scenarios that present customized products combined with leagile supply chains and urban manufacturing configuration.

Efficient and Reconfigurable Manufacturing

Classified in terms of the levels regarding decision-making and action taking, efficient & re-configurable manufacturing systems encompasses the ability to reconfigure hardware while also controlling resources at all functional and organizational levels. It is, therefore, aimed at quickly adjusting production capacity and functionality as a response to sudden changes in market or in regulatory requirements. Thus, efficient & reconfigurable manufacturing systems are observed, within NEXT-NET, on supply chain scenarios that bears frugal mass produc-tion, risk-hedging supply chain and simple systems’ configuration.

Omnichannel


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5.1.8 Sustainability

The sustainability dimension refers to four major aspects of the supply chain strategies: envi-ronmental issues, closely related to the environmental dimension of the macro-scenarios; social-responsibility, being supported by demographic changes’ characteristics from the macro-scenarios; emergency related supply chains, which are addressed within macro-scenarios that present a combination of political instability and environmental concerns; and circular supply chains, which are employed whenever digital economy and environmental dimension characteristics are observed on the macro-scenarios.

Omnichannel is an integrated multichannel approach to sales and marketing. It refers to the strategy that provides customers with a fully integrated shopping experience by exploiting the internet, mobile devices, and social media enabling customers to research and shop anytime and anywhere. In this strategy the customer is in the centre [55].

Consumer to Consumer (C2C)

Consumer to consumer (C2C) refers to the sales channel where consumers interact directly with each other and do business. Generally, C2C transactions involve products sold through a classified or auction system and products sold are often used or second hand. In most cases, a third party facilitates the C2C transaction who manages the transaction to make sure goods are received and payments are made. In that way, some protection is offered for consumers taking part in C2C [32].

Traditional Sales Channels

The traditional sales channel refers to the strategy where the company is in the centre and defines the product and the channel. The company traditionally sells products to customers regards their preferences and focuses on product quality and cost to increase the sales. [33].

Green

Green supply chain is correlated with reducing environmental and ecological impacts of product/process design and development [11]. This SC strategy entails the combination of traditional supply chain management approaches with environmental components (which may consider managerial practices). Most notably, these environmental components include green purchasing, green distribution, green manufacturing and eco-design. The overall ob-jective is to improve environmental and economic performances [51]. Green supply chains are herein addressed when environmental dimension characteristics from the macro-scenario demonstrate a positive impact on the supply chains.

Closed-loop

By simultaneously considering forward and reverse supply chain operations, closed-loop supply chain systems bear relation with circular economy, especially within productive sys-tems [69, 128]. Moreover, closed-loop systems aimed at waste management processes, with


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Supply Chain Strategies for Macro-Scenarios 5.2

5.2.1 Summary for Macro-Scenario aSPIRANT

emphasis on functional delivery and on value in use, as well as being supported by man-agement methods related to collaborative or shared consumption model, are the main focus of this supply chain strategy [11]. In this sense, closed-loop is mostly concerned with restora-tive flows of materials, and can be differentiated from reverse logistics due to the scope and opportunity for innovation [11]. In this sense, supply chain scenarios that present digital po-tential combined with environmentally positive impacts presented closed-loop supply chains.

Resource-efficient

Resource-efficient are mostly related to reducing environmental and ecological impacts re-garding the use of resources with strict methodologies. It was employed, on this Deliverable, as opposed to Green supply chains, aimed to be a downscaled supply chain strategy for environmental dimension characteristics with negative impacts on the supply chain scenari-os.

Social-responsible

Following the European Commission definition for corporate social responsibility, which states that companies must integrate social and environmental concerns within their busi-ness operations, as well as in their interaction with stakeholders, on a voluntary basis [116], social-responsible supply chains are aimed at creating shared value for the companies and the society, while also incorporating ethical frameworks to evaluate positive and negative social engagements [34, 116]. With this concept in mind, social-responsible supply chains are observed on supply chain scenarios that are characterized by the awareness of inequali-ties and the requirement of wealth distribution.

Humanitarian SC

Humanitarian supply chains are employed on disastrous scenarios, i.e., when a disruption that affects physically human society, threatening its objectives and needs, which can be either man-made or natural [125]. For this purpose, humanitarian supply chains must pre-sent five key aspects: human resources, knowledge management, process management, available resources, and community participation [125]. This strategy presents non-profit objectives and involves logistics which are primarily reactive, being performed through ad hoc designs, with extensive advance planning [8, 35, 61, 120]. Thus, humanitarian supply chain strategy is implemented on supply chain scenarios with political instability and nega-tive environmental characteristics, where disasters’ occurrences may be more prominent.


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Figure 5-2: Supply Chain Strategies for Scenario aSPIRANT

In the context of the aSPIRANT supply chain scenario-model, consensual political settings,

continued economic growth patterns, and dialogue-driven soft trade law increase market

certainty and demand predictability, while easing the market access to raw materials and

investment finance. Harmonic co-existence of circular, shared and digital business design-

models in coopetitive partnership settings create value synergies across supply chain busi-

ness processes, while decreasing CapEx and OpEx costs and optimizing profit margins and

supply chain flows. Increasing volatility in raw material procurement and globally acknowl-

edged climate-change concerns generate green and eco-friendly manufacturing practices

and production systems, in which waste minimization and management technologies have a

key role to play. Technology-neutral industrial connectivity and automated logistics solutions

contribute powerfully to the development of on-demand and distribution manufacturing

channels and high-volume/low-complexity production systems. Digital talent and specialist

skills gap for automation-era occupations, emerging flexicurity measures targeting labour

productivity, and job polarization between low- and high-wage countries affect the labour

market governance of global supply chains. In this macro-competitive politico- and techno-

economic context, the supply chain structure is agile, tactical, distributed, integrated, multi-

modal, hybrid, and omnichannel; whereas, sourcing strategy is hybrid, combining local and

global sourcing practices to increase cost efficiency of sourcing operations. Multi-model and

omnichannel distribution channels shorten supplier lead time; lower inventory costs; improve

customer centricity; create omnichannel sales channels; and, consistency in delivery ser-

vices. In the conceptual future aSPIRANT, distributed nature of supply chains means that

Mainstream Products & Servitization

Efficient

Global SourcingGlobal Distribution

Digital Masters

Hyperconnected Factories

Digital Lean Manufacturing

Omnichannel

GreenSocial Responsible

Closed-LoopSupply

Chain for aSPIRANT


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there are various flow components: product flow, financial flow, supply chain (administrative)

information flow, and risk flow. Of these flows, specifically material flow integration (increas-

ing control on material flow variability) and financial flow integration (increasing capital sav-

ings) bring total-cost-of-ownership benefits to supply chain governance. The use of crypto-

currency and distributed ledger technologies transform transfer channels and commercial

value exchange practices, while decreasing transaction costs and increasing traceability and

transparency of trade transactions.

The building blocks of the aSPIRANT supply chain strategy are defined as follows:

• Efficient supply chain network design, based on low uncertainty in demand and sup-ply, enabling to operate cost-efficiently along the supply chain.

• High-tech manufacturing: Servitisation strategy used in designing the busi-ness/operating model of manufacturing processes which are based on the digital.

• Global sourcing procurement strategy, enabling to standardize and centralize supply chain process management and develop economies of scale.

• Low-inventory/high-margin product strategy and omnichannel demand forecasting practices in the effort to provide cost-efficiently direct-to-consumer fulfilment services.

• Dynamic pricing strategy, due to a double-fold production strategy: i) make-to-stock production strategy for base demand (i.e. high-volume, stable demand products); and, ii) make-to-order production strategy for surge demand (i.e. unstable demand products).

• Omnichannel inventory management strategy and direct-to-consumer fulfilment ser-vices, empowered by the Consumer Goods Technology and predictive analytics.

• Circular and closed-loop product-services business innovation strategy, enabling to develop circular supply chain operations.

• Reverse logistics practices and centralized distribution networks, enabling to close the loop of the product lifecycle.


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5.2.2 Summary for Macro-Scenario PrOCEEDINg

Figure 5-3: Supply Chain Strategies for Scenario PrOCEEDINg

The new digital business models and models based on circular economy call for a strategy highly technology-oriented with digitalization and digitisation. The rise in circular economy exposes the need for a closed-loop SC archetype, which concerns the circularity in SC con-figurations with restorative and regenerative processes, both required for the circular econ-omy scenario [11]. This archetype can be integrated with the Green SC, which relates to scenarios where the decision-making is made based on environmental concerns without much focus on the financial performance [70, 81, 108]. Moreover, the use of global sourcing and global distribution strategies not only contributes to better financial flows (which are also part of the circular economy concept), but also aids companies which are beginning to act on different regions and new markets [12, 80].

Lower levels of uncertainty in demand and supply coupled with low and personalized levels of inventory require an Efficient SC strategy. The balance between standardization and cus-tomization calls for strategies which can be either make-to-order (MTO - going as far as the purchasing phase) or assemble-to-order (ATO – reaching the fabrication point), which will provide differentiation and customization while also dealing with relatively large orders [98].

On a similar analysis, since firms have a need for differentiation of offering and enhance-ment of customer engagement due to customization, servitization strategies are employed [127]. Since the scenario has predictable demand and supply, high variety of products due to customization and standardization, the rise of SME’s and Start-ups as players on the market and the adoption of technologies heavily based on digital concepts, a combination of Digital flexible manufacturing systems and digital reconfigurable manufacturing systems is needed in order to respond to the changing demand characteristics and distribution challenges. Also,

Customized Products & Servitization

Leagile

Global SourcingGlobal Distribution

Digital Masters

Hyperconnected Factories

Digital Mass Customization

OmnichannelC2C

GreenSocial Responsible

Closed-LoopSupply

Chain for PrOCEEDINg


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the use of omnichannel serves as basis for the referred logistics needed on the described scenario [10, 15, 67].

5.2.3 Summary for Macro-Scenario oFFsET

Figure 5-4: Supply Chain Strategies for Scenario oFFsET

Based on the product, process and supply chain characteristics described in the above sub-sections, the oFFsET scenario is described as follows:

• Product differentiation for global companies which are present in local markets. • Agile supply chain network design because of a high uncertainty in supply and de-

mand, allowing the adaptation to customer needs. • Low-tech manufacturing and technology conservative strategy due to the low digital

transformation. • Glocal sourcing and glocal distribution strategy leading to more complex supply chain

structure management. • Flexible supply chain service levels and enterprise architecture leading to the use of

modular production systems in large factories mainly in emerging economies. • Use of agile manufacturing systems to face low variety and high uncertainty. • High inventory levels, use of intermodal hubs through the use of traditional sales

channels in the effort to provide agile services in an uncertain demand context. • A resource- efficient and social-responsible SC design because of the scarcity of re-

sources such as minerals and rare earth elements, mainly sourced by countries out-side the EU (e.g. China, Brazil, Australia and USA). This dependency leads to the re-use and recycling of materials in a circular economy context (passive closed-loop).

• Reuse and recycling of materials as a strategy to face the scarcity of resources.

Mainstream Products Agile

Glocal SourcingGlocal Distribution

Tech Conservatives

Modular SystemsAgile Manufacturing


Resource-efficientSocial Responsible

Supply Chain for oFFsET


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5.2.4 Summary for Macro-Scenario DiThER

Figure 5-5: Supply Chain Strategies for Scenario DiThER

Since the scenario is characterized by a platform economy which involves new digital busi-ness models servitization strategies will be employed [127]. Servitization is mostly based on data services and companies have the possibility to improve their turnover and achieve a higher customer loyalty due to the combination of products and services. These services are being successfully developed mainly by start-ups and SMEs, which results in these compa-nies taking up business. In addition to servitization and due to the DIY society, the custom-ers expect individual and customized products.

Due to the developments in this scenario, such as smart cities, individualism and DIY society a leagile supply chain paradigm with a focus on customization is needed. A leagile supply chain strategy is a combination of lean and agile paradigm. Agile supply chains are charac-terized by the ability to respond flexibly to the diverse and unpredictable customer needs while minimizing the risk of supply failures by bundling inventories or other capacity re-sources [72]. Lean supply chains are characterized by cost and time efficiency due to the elimination of all waste, including time, along the value stream.

Due to the trends of protectionism and heterogeneous regulations there will be a predomi-nant local sourcing and glocal distribution. The SC scenario is characterized by a high tech-nological level in general (advanced digital features such as data science & Internet of Things), but there is a lack of an overarching vision and coordination and cooperation in the SC (tech fashionistas).

Since the scenario is characterized by DIY society, individualism with a focus on variety and a continuous exploitation of disruptive technologies, flexible manufacturing systems are de-cisive in order to respond to the individual and unpredictable demand characteristics and the

Customized Products & Servitization

Leagile

Local SourcingGlocal Distribution

Tech Fashionistas

Urban ManufacturingFlexible Manufacturing

C2C

GreenClosed-loop

Supply Chain for DiThER


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distribution challenges. The development of many smart cities will also increase the im-portance of urban manufacturing. The development to a DIY society will lead to increased C2C (consumer to consumer) sales channels.

The new business models based on circular economy can be integrated with the Green SC, which relates to scenarios where the decision-making is made based on environmental con-cerns without much focus on the financial performance [70, 81, 108].

5.2.5 Summary for Macro-Scenario UNEasE

Figure 5-6: Supply Chain Strategies for Scenario UNEasE

In light of the forecasted scenario, supply chains strategies are an important lever to consid-er for companies. The main characteristics that supply chain strategies are required to ad-dress under such conditions has been identified as follows:

• Customer-driven orientation: each action or decision made in a supply chain, from the up to the down-stream level [100], has to be driven by consumers’ needs due to the rise of customization and DIY trends. Consumers want to express their own sin-gularity through even more personalized solutions, not only for the physical products itself but also, for example, for what concern the shopping experience. Moreover, ac-cording to the DIY paradigm, they are enabled to design, realize or assemble prod-ucts by themselves. This forces companies to be ready in detecting needs and wish-es of different customer segments and in reacting efficiently to the high variability of demand for specific and customized components and even materials, especially when dealing with addictive manufacturing technologies. To put it place such ap-proach, actors of a supply chain should be aligned, and information should be shared through all the nodes in the chain. This way, companies are able to ensure that sup-

Customized Products Leagile

Glocal SourcingLocal Distribution

Tech Conservatives

Urban ManufacturingFlexible Manufacturing


Resource-efficientHumanitarian SC

Supply Chain for UNEasE


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ply and demand are in sync, and to deal with the peaks and troughs of demand, crossing over constraints and problems.

• Resilience is a characteristic of a supply chain that can be measured when an un-foreseen and negative event happens. Precisely, it can be seen as the capability of the system to cope with unexpected disturbances, and to quickly recover and return to the standard performance level [7, 19, 94, 102]. In this scenario, being able of jumping out of disruptive situations faster than the competitors is a strong weapon companies can use. In the UNEasE scenario, protectionism and the collapse of alli-ances will segment market on national bases, stressing differences in consumer cul-ture and preferences and legislations across borders thus creating a high environ-mental risk, which could cause disruptions along the supply chain. The economic un-certainty with contemporary increase of strength of the emerging economies, and the problem of resource scarcity also increases the risk level along the supply chain, forc-ing companies to create a more flexible and reactive structure to improve the respon-siveness of the whole network.

• On the same page, Agility is a feature of a system that is able to adapt itself to changes in the market condition. Indeed, many markets are depicted by demand characterized by high standard deviations, seasonality and, consequently, not stable and predictable, and for this reason they require flexible manufacturing system that are able to absorb these turbulences [7, 19, 28, 117]. An agile production system (APS) is well suited for high variety and a low volume product offer, as in the UNEasE scenario. In fact, companies operating under such kind of conditions have to imple-ment the ability to respond quickly to the varying customer needs and to deal with the peaks of demand. Since in this scenario there is reluctance in the implementation of new and disruptive technologies, which often coexist with traditional ones, compa-nies, especially SMEs, have to find the best trade-off between costs, being effective and efficient.

• Urban manufacturing: a new trend is taking place in manufacturing: the rise of small-scale facilities in urban areas supported by smart city infrastructures enabling the evolution and integration of facilities and systems. Urban Manufacturing is a new production strategy for products with a high degree of specialization, a high ratio of value to volume, and which require new skills to be performed. Indeed, the aging en-visaged society, will highlight some disparities, as the lack of qualified personnel, par-ticularly in rural areas [73]. In this scenario urban areas are increasing, and compa-nies move from older large facilities to smaller spaces in urban areas with shorter dis-tances to final customer, in order to be able to better accomplish his/her needs. This represents also an approach to respond to the need for more flexibility due to the in-crease of labor shortage and of customization. The rise of small factories in smart cit-ies regards small-scale production of high value, design-oriented, complex and spe-cialised goods, for niche markets. Due to the diffusion of the DIY trend, small plants can act also as service centers, to directly support the final customer in the stage of


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production or assembly of his specific and personalized product. The location of facili-ties in the city will force companies to be less polluting and more resource efficient too. At the same time, the realization of centralized distribution centers and adapted logistics for smart cities will be essential in order to implement efficiently last-mile transportation and assure just-in-time distribution of materials and components.

• Resource-efficient: The UNEasE scenario deals with environmental problems due to a wide resource scarcity and the increase of air and land pollution. A resource effi-cient supply chain has to be: resource aware, resource sparing, resource sensitive and resource responsive. In this sense, the supply chain for this scenario should con-sider developing new flexible manufacturing systems to reduce waste and ensure minimal consumption of scarce resources. Companies need also to find alternative sources in terms of energy and materials and create new sustainable and customized products. The use of additive manufacturing can help to face this issue, but more ef-fort is required and it would be necessary to implement also other strategies like in-dustrial symbiosis to close the loop of material and energy flows with a more accurate waste management approach. In smart cities, the adoption of electrical vehicles and green solutions is ongoing, however the lagging of clear regulations doesn’t help a spread implementation of these technologies that should be adopted not only in the most populated cities but also in other areas.

• Humanitarian SC: The characteristics for the UNEasE macro-scenario and the de-tailed aspects for the supply chain scenario based on this macro-scenario, relates to an environment of political instability. More specifically, the presence of protectionism, fragmentation aspects and unstable environment on European grounds, combined with a shift towards emerging markets and the persistence of traditional economy, render this supply chain scenario to have proclivity for political and economic instabil-ity. Moreover, the lack of strong regulations and environmental concern forecast pos-sible disasters, both natural and human-driven. In this sense, humanitarian supply chain strategies are observed, especially related to reacting to disastrous environ-ments such as this supply chain scenario predicts.

5.2.6 Summary for Macro-Scenario ENDANGEr

Based on the product, process and supply chain characteristics that described in the above sub-sections, certain supply chain models are utilised by companies in the process, discrete manufacturing and logistics and distribution industry. Frugal mass products, risk-hedging, glocal sourcing and local distribution, medium-tech, simple production systems in emerging markets, efficient and reconfigurable manufacturing systems, traditional sales channels, re-source-efficient, industrial symbiosis and humanitarian supply chains are the supply chain models that companies adopt in order to response to new market conditions.


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Figure 5-7: Supply Chain Strategies for Scenario ENDANGEr

In the ENDANGEr scenario, the rise of new business models and digital innovation, the con-tinuous efforts to reduce products’ prices, and the resource scarcity lead to the development of frugal mass products. Frugal products are redesigned products aiming to reduce complex-ity and cost, minimise the use of natural resources while at the same time maximise the val-ue for the customer [14, 96]. So, companies will use frugal mass products to respond to the lack of necessary resources and/or infrastructure and meet their customers’ needs in con-strained environments [82].

Also, the political and social instability, which leads to “glocalisation”, impacts significantly the demand and supply risks. Regarding the demand side, companies respond to local needs which are strongly influenced by social networks and are easy to identify and so, the demand uncertainty is low. Regarding the supply side, international supply chains face diffi-culties as protectionism policy restricts international trade and so, the supply uncertainty is high. Consequently, the supply chain is characterised as a risk-hedging supply chain with low uncertainty in demand and high uncertainty in supply.

As protectionism policy restricts the international trade and companies will face barriers and several tariffs, local supply chains will be developed. That means that upstream in the supply chain, companies will source glocally by forming new partnerships and downstream in the supply chain, companies will sell their products locally. So, with regards to sourcing and dis-tribution dimensions, the supply chain model is characterised by glocal sourcing and local distribution.

Regarding the technological dimension, the political and social instability limits the develop-ment of emerging technologies. Due to high costs and risks, the digitalisation is only afforded by big companies. However, that gives the chance to SMEs to develop autonomous tech-

Frugal Mass Products Risk-hedging

Glocal SourcingLocal Distribution

Tech Beginners

Simple SystemsEfficient & Reconfigurable

Manufacturing



Supply Chain for ENDANGEr


80

nologies and become tech-beginners.

As described above, there will be frugal mass products which aim to reduce complexity and costs and also there will be a medium technology level which gives the opportunity to SMEs to become tech-beginners. That means that there will be emerging markets but companies will have limited manufacturing capabilities to respond and companies will develop simple production systems in order to respond to the local market needs and gradually start devel-oping technological innovations. Moreover, the risk-hedging supply chain with low uncertain-ty in demand and high uncertainty in supply along with the adoption of autonomous technol-ogies will support the development of efficient and reconfigurable manufacturing systems.

Considering the how and to whom companies will sales their products in the ENDANGEr scenario, a traditional sales channel will be used, which is about the typical channel with the physical stores and less about the e-commerce stores, the on-line ads and the digital sales. Spe-cifically, the medium technology level, the obstruction of digitalisation, the frugal, low cost and low variety mass products as well as the low uncertainty in demand justify the domination of a traditional sales channel.

Regarding the sustainability dimension, companies will be forced to become resource-efficient due to the depletion of resources and they will learn to use the resources in a sus-tainable manner. Also, the rise of the overall rate of unemployment due to automatization, leads to strong social disparity and social unrest. So, social concerns will be raised and it will lead to the development of humanitarian supply chains. Finally, the development of local supply chains due to the protectionism policy, will lead to industrial symbiosis where local synergies will be formed to respond to the local market needs.


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6 Conclusion

The results of this report are twofold. First, it proposes a quantitative method to identify the macro-variables that most influence supply chain performance. The specific model devel-oped for this task was based on an in-depth analysis of several statistical sources to ex-trapolate the most representative variables to properly characterise the trends of different dimensions (as from PESTLE analysis), to evaluate their impact on the Logistics Perfor-mance Indicator (LPI).

It is important to notice that this quantitative model doesn’t aim at being normative and gives preliminary results on which are the descriptors/variables most influencing the supply chain. The results are based on a data set over a seven years period (2010-2016) with a projection on 2030 and for more than 40 countries. For this reason, finding variables that are consistent with all countries was a challenge. A further analysis done per country can show a different impact of the variables on the LPI displaying the peculiarities of each country.

It was not possible to cover the comprehensive list of descriptors identified in D2.2 (see Ta-ble 1-1) because of missing statistics, either partial (not covering the full historical period 2010-2016) or none at all, about new trends only recently emerged (i.e., the presence of FinTech for financial innovation, trends of autonomous systems in logistics/production, data on personalised production, and consumption trends in terms of awareness increase).

Another difficulty met during model development is linked to missing good macro-economic indicators to represent supply chain performance, or general impact of supply chain on val-ue-added of a country. The chosen indicator (LPI) represents part of the supply chain pro-cesses – mainly logistics and distribution –, but all information from the integration between companies, as well as the value generated by a certain type of production network, are still difficult to measure at a macro-economic level. In fact, most of the industry performance is based on a single company and not on the value of a network.

The second result of the task describes the supply chains for the six future scenarios in Eu-rope 2030, in eight strategic dimensions: Product & Service, Supply Chain Paradigm, Tech-nology Level, Sourcing & Distribution, Supply Chain Configuration, Manufacturing Systems, Sales Channels, and Sustainability. Table 6-1 shows the overview of the supply chains for each macro-scenario.


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Table 6-1: Supply Chains for Macro-Scenarios

The results of D2.3 provide the basis for defining the technologies that are needed in each of the future scenarios (T3.2), which will then lead to the analysis of Research Priorities (T3.3) and Public Policy Recommendations (T4.2) for the future supply chains in Europe 2030.

Strategic Dimensions

SC for scenario aSPIRANT

SC for scenario PrOCEEDINg

SC for scenario oFFsET

SC for scenario DiThER

SC for scenario UNEasE

SC for scenario ENDANGEr

Product & Service

Mainstream products and servitization

Customized products and servitization

Mainstream products

Customized products and servitization

Customized products

Frugal mass products

Supply ChainParadigm

Efficient Leagile Agile Leagile Leagile Risk-hedging

Technology Level

High-techDigital Masters

High-techDigital Masters

Low-techTech conservatives

High-techTech fashionistas

Low-techTech conservatives

Medium-techTech beginners

Sourcing & Distribution

Global sourcing, Global distribution

Global sourcing, Global distribution

Glocal sourcing, Glocal distribution

Local sourcing, Glocal distribution

Glocal sourcing, Local distribution

Glocal sourcing, Local distribution

Supply Chain Configuration



Modular systemsUrban

Manufacturing Urban

Manufacturing Simple systems

Manufacturing systems

Digital lean manufacturing

Digital mass customization

Agile manufacturing

Flexible manufacturing

Flexible manufacturing

Efficient and Reconfigurable Manufacturing

Sales channel OmnichannelOmnichannel

C2C Traditional sales

channelsC2C

Traditional sales channels

Traditional sales channels

SustainabilityGreen

Social-responsible Closed-loop

GreenSocial-responsible

Closed-loop

Resource-efficientSocial-responsible

GreenClosed-loop




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