Executive summary...Alexandra Castro Amkor Technology Portugal, S.A Martin Christopher Cranfield...

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Transcript of Executive summary...Alexandra Castro Amkor Technology Portugal, S.A Martin Christopher Cranfield...

  • Executive summary

    This Strategic Research and Innovation Agenda (SRIA) is the result of intensive research, jointly performed by a wide network of stakeholders from discrete manufacturing, process industry and logistic sector, within NEXT-NET project. Several actors of the innovation ecosystem (i.e. companies, research organisations, DIHs, and policy makers) put forward their vision to strengthen European supply chains over the next decade.

    Exponential development of new digital technologies, population growth and urbanizations, customizations, protectionism and political instability, renewable energy sources, climate change and resource scarcity are just some examples of trends shaping and influencing European and World economies and lives. Megatrends are raising multi-facet challenges that companies, production networks, distribution centres and markets need to face in order to maintain and increase their competitiveness and their economic, social and environmental sustainability. Consequently, there is an urgent need to adapt significantly the way companies are organised and interlinked within supply chains. New roles and relationships among all the actors involved in the network are emerging, which necessarily demand an evolution of strategies and configurations of supply chains and new industrial ecosystems.

    This document was developed in coherence with European research programmes, taking into consideration what already set by H2020 and the ongoing process for the definition of the new framework Horizon Europe, to provide guidance for researchers, policy makers and industrial actors. The aim was pursued by envisioning impending horizon up to 2030, creating a cross-sectoral initiative at European level to frame future scenarios, identifying research and innovation needs and prioritising actions for the future of supply chains.

    The first part of the SRIA presents an overview of the 6 macro scenarios up to 2030, developed on the basis of the evolution of megatrends, followed by the consequent challenges and a map of the enabling technologies for supply chains. In the second part, the NEXT-NET vision for European supply chains is presented, with a detailed description of the 10 supply chain strategies identified as most relevant, and related research and innovation topics (RITs) as future developments required for the full implementation of the strategies. Finally, a set of policy recommendations are proposed, to address the key horizontal issues common to most of the strategies and requiring action at policy level.

    The NEXT-NET consortium would like to thank all the stakeholders involved along the project for the last two years. In particular, the team is very grateful for the valuable and important contributions received from the experts actively participating in the focus groups, workshops, consultation process and interviews to identify the scenarios, strategies and research and innovation priorities included in this SRIA. The consortium would also like to thank the European Commission for its support for this initiative.

    The NEXT-NET team December 2019

  • TABLE OF CONTENT

    Methodology 4Macro Scenarios for 2030 6Specific Challenges for Supply Chain 13Mapping Enabling Technologies 14Supply chain strategies for the future 17

    CNR-STIIMA (Italy)Rosanna Fornasiero

    Irene MarchioriElena Pessot

    Andrea Zangiacomi

    PNO-INNOVATION (Belgium)Sébastien Balech

    Cemre MultuRon Weerdmeester

    Zaragoza Logistics Center (Spain)Carolina Cipres

    Mustafa Çagri GürbüzAlicia Martínez de Yuso

    Victoria Muerza

    Fraunhofer IML (Germany)Saskia Sardesai

    Markus Stute

    INESC TEC (Portugal)Ana Cristina Barros

    Pedro CamposPatricia GonçalvesKerley Silva Pires

    Pedro SennaRicardo Augusto Zimmermann

    Aston University (UK)Aristides Matopoulos

    Evanthia Thanou

    WORKING TEAM

    ADVISORY BOARD

    EXPERTS

    Mihai Barcanescu SPIREFernando Liesa ALICE

    Želiko Pazin EFFRA

    Mariano Alcañiz Universidad Politécnica de ValenciaAntónio Almeida FarfetchPedro Amorim University of Porto Vasco Amorim University of Trás-dos-Montes and Alto Douro

    Irene Andrés-Moro LogistopGabriele Balduzzi LTL LensesSergio Barbarino Procter&Gamble

    Filipe Barros Supply Chain MagazineRui Barros MITMYNID

    Frank Berkers TNOJosé Bernardino IFR -Research and Training Institute for Road Transportation

    Erica Biffi PirelliAlberto Blanco Gesprolog

    Giorgio E. Bobbio Friul Intagli IndustriesLygia Bronneberg Transpetro- Petrobras

    Michel Byvoet BivolinoJavier Calvo ANSITEC

    Luis Camarinha UNINOVACarlo Campelli Procter&Gamble

    Tiago Candeias InfineonLuís Carneiro INESC TEC

    Alexandra Castro Amkor Technology Portugal, S.AMartin Christopher Cranfield UniversityLia Coelho Oliveira University of AveiroAlberto Comacchio STAFF International

    Javier Cortés CTCR-Centro Tecnologico del Calzado de la RiojaYasel Costa Zaragoza Logistics Center - ZLC

    Pietro Cuttica SedAptaMaria Teresa de la Cruz Zaragoza Logistics Center - ZLC

    Piero De Sabbata ENEAPeter Detzner Fraunhofer IML

    João Dias da Silva University of Porto

    Jan Egbertsen Port of AmsterdamJoachim Ehrental FHWN- Switzerland

    Ralf Erdmann SOLAVENTUS GmbH & Co. KGAngel Escamilla Sánchez SELISA

    Ana Ferrão Elastomer Solutions GroupLuis Ferreira University of Coimbra

    Paulo Ferreira 4GEOAndrea Gatto TRUMPF Sisma

    Tommaso Gecchelin Next Future TransportationAntonio Guadagnino Paradigma Exponential Hub

    Dinora Guerreiro Volkswagen AutoeuropaGünter Hörcher Fraunhofer IPA

    Seppo Huurinainen WuudisDimitra Kalaitzi Birmingham City University

    Jan-Philip Kopka Fraunhofer IMLGultekin Kuyzu Zaragoza Logistics Center - ZLC Emilio Larrodé University of Zaragoza

    Jon Legarda University of Deusto Luis Leitão Daimler Trucks Asia, Mitsubishi Fuso Truck EuropeAlan Lewis Smart Freight Center

    Tatiana Lopes FarfetchJoão Loureiro Grupo TrirumoMatthieu Lux Deloitte

    Laura Macchion University of PaduaMarin Marinov Aston UniversityLuis Marques DB Schenker Portugal

    Maximiliano Martín Vallve AlpegaOlivier Maugain Henkel

    María Mayer BASFIfigeneia Metaxa ATLANTIS Engineering S.A.Milos Milenkovic University of Belgrade

    Mirjana Milic Future by designEnrique Montiel Parreño EUNOVA 2001, S.L.

    Andreas Nettsträter Fraunhofer IMLStephanie Niehues TU Dortmund

    Ana Nobre Maia SONAEAngels Orduna SPIRE

    Guido Orzes Free University of BozenSilvério Paixão AXICON FranceRudrajeet Pal Swedish School of Textiles, University of Borås

    Elena M. B. Pantazi-Bajenaru Institute for Textiles and Leather -RomaniaCandido Perez Costela Zaragoza Logistics Center - ZLC

    Margarida Pina NORSJorge Pinho de Sousa University of Porto

    Ricardo Pinto SchaefferWalther Ploos van Amstel Vrije University of Amsterdam

    Brian Price Aston UniversityRicardo Reis Embraer Portugal SAPedro Rocha PRODUTECH

    Alba Rodriguez Flores Jaguar Land RoverPietro Romano University of Udine

    Beatriz Royo Zaragoza Logistics Center - ZLC Yasmine Sabri Aston UniversityNekane Sainz University of Deusto

    Francisca Santos Lira DeloitteBjörn Sautter Festo AG & Co. KG

    Sandra Schmidt Fraunhofer IMLFranco Scolari Polo tecnologico di PordenoneRogério Silva Frulact

    Konstantin Sipos RESCOLL ManufacturingAntónio Lucas Soares University of Porto

    José Soeiro University of Porto Massimo Sotgiu Quin

    Diogo Sousa Magalhães APDLMatteo Suman Safilo Group

    Edward Sweeney Aston UniversityVasco Teles INESC TECAna Torres University of Porto

    Diego Torres Goma-Camps Consumer SLUJolanda Tromp Duy Tan University

    Luca Urciuoli KTH Royal Institute of TechnologySusana Val Zaragoza Logistics Center - ZLC

    Celeste Varum University of AveiroPedro Vasconcelos Amkor Technology Portugal, S.ARodrigo Vaz-Pires FarfetchAugusto Vilarinho Critical Manufacturing

    Andrea Vinelli University of PaduaAlan Waller EFESO Consulting

    Luis Wilbert Zaragoza Logistics Center - ZLC Xiwen Xu UPS Capital

    Gabriel Zachmann University of BremenRob Zuidwijk Erasmus University Rotterdam

    NEXT-NET VISION 17Hyper-Connected Supply Chain Strategy 19Disaster Relief Supply Chain Strategy 23Global Supply Chain Strategy 27Urban Supply Chain Strategy 31Resource Efficient Supply Chain Strategy 35Human Centered Supply Chain Strategy 39Closed-Loop Supply Chain Strategy 43Customer-Driven Supply Chain Strategy 47Service Driven Supply Chain Strategy 51Biointelligent Supply Chain Strategy 55

    Policy Recommendations 59Acronyms 66References 67

  • 544

    Forecasting future developments is essential for a promising and forward-looking strategy. In a context with a high level of complexity, plus the unpredictability of different, interdependent future events, forecasts purely based on plain extrapolations frequently turn out to be quite unreliable. The scenario planning technique differs from traditional methods and sets the focus rather on interlaced influencing factors and the concept of multiple futures. Considering the diversity or rather the complexity of future events, the scenario technique has established itself as a powerful tool for future research. The method is well suited for the systematic identification and description of complex visions of the future. A scenario is a logical and in itself consistent description of a possible future situation, which is based on a complex grid of influencing factors and their future development. As the focus is not only set on the possible future environment, but also the consequences of the development, scenarios are the ideal base for thoughts about long-term strategies and political measures. A comprehensive methodology for building external scenarios, which are employed to provide policy analysis frameworks and to support the development of strategies for a planning entity, was implemented in NEXT-NET. By comparing optimistic, pessimistic and intermediate scenarios, recommendations for actions can be yielded in advance, resulting in faster reaction times when a scenario becomes real.

    NEXT-NET is based on a structured framework to develop a comprehensive roadmap for the European supply chain for 2030 based on visions of the future that address multiple influencing factors and their inter-relationships. A multi-stage approach was applied where different methodologies for foresight are categorised, according to of four major dimensions (Popper, 2008):

    • Creativity: methods relying heavily on the inventiveness and ingenuity of the highly skilled individuals, such as the use of wildcards, science fiction, scenario writing.

    • Interaction: methods based on participation and shared views of experts and non-experts, such as workshops, multi-criteria methods, stakeholder analysis.

    • Evidence: methods based on codified information, data and indicators etc. such as literature reviews, scanning, benchmarking.

    • Expertise: methods based on tacit knowledge of people with privileged access to relevant information or with accumulated knowledge, such as expert panel, quantitative scenarios, Delphi and roadmapping.

    METHODOLOGY

    Given this general overview and important principles, the following steps are implemented in NEXT-NET:

    1. Mapping trends and megatrends: this step considers alternative futures in terms of drivers, uncertainties, trends, and possible events from several domains of PESTLE analysis (political, economic, social, technological, legal and environmental aspects). Projections for each trends are also identified to build up future scenarios.

    2. Future scenario generation: it is based on two steps 1) future macro scenarios as a combination of projections of the exogenous variables with evaluation of interrelation among the variables (i.e. cross-impact matrix among the trends in pair-wise comparison); 2) supply chain scenarios as meso-level scenarios with identification of the best supply chain features (in terms of products, processes and configuration) that could fit with the main changes expected for each macro scenario.

    3. Specific challenges for supply chains: identification of the specific challenges for supply chain scenarios derived from the global trends in terms of collaboration, operations, IT integration, management of complexity etc.

    4. Mapping enabling technologies: existing roadmaps and studies at different levels (regional, national, international; sector specific) as well as running projects are analysed to

    identify and map enabling technologies for supply chain. Technologies are mapped based on TRL, applicability scoring and implications on supply chain performance; application examples and gap analyses (technology gaps and implementation challenges) are gathered for each of the 18 identified technologies.

    5. Development of research and innovation topics: consultation with experts from industry and academia is based on brainstorming, focus groups and surveys to identify research and innovation priorities for the future in order to address future industrial scenarios. Each research and innovation topic is based on a subset of enabling technologies mapped in the previous phase. The preliminary version of the Research and Innovation Topics (RITs) is discussed and validated discreetly by representatives from manufacturing and processing industries as well as distribution/logistics during specific workshops.

    6. Strategic Research and Innovation Agenda: the identification of 10 supply chain strategies and related RITs as a path to further develop industry and Europe using various approaches, such as sustainability, customer-driven, and guiding decision makers in a path towards a new future.

  • 76

    The generation of future macro scenarios considers the full spectrum of political, social, economic, technological, legal and environmental influences and changes up to the year 2030. These macro scenarios and related narratives provide a solid foundation for the evaluation of the impact on possible developments for future supply chains.

    In general, scenarios provide a holistic and schematic methodology to describe possible future conditions. The methodology of scenario planning is specifically useful in the context of future statements with different levels of uncertainty. Scenario planning is a basis for learning through strategic conversation and it helps to build a consensus regarding certain and uncertain projections.

    The Gausemeier approach was selected to create macro scenarios for NEXT-NET. These describe the setting within the PESTLE dimensions and hence the future industrial surrounding. The Gausemeier approach belongs to the quantitative methods, and uses a cross-impact and consistency matrix to develop its set of scenarios. The major advantage of this methodology lies in the possibility of integrating several trends and megatrends as projections along with its way forward to reduce the amount of projection bundles to a few scenarios for a more detailed analysis; hence, it provides a way forward to deal with multiple futures (Gausemeier et al., 1995).

    The following steps have been processed to achieve consistent and viable scenario fields involving all consortium partner and external experts:

    • Definition of projections until 2030 based on megatrends and trends.

    • Evaluation of the impact of the projections on the supply chain via a survey.

    • Evaluation of the impact of the projections on other projections via cross-impact matrix.

    • Creation of projection bundles and selection of consistent scenarios based on a cross- impact balance analysis.

    • Expert-Workshop to validate the scenarios and to quantify their overall impact on the supply chain and its probability.

    As a result, twelve different consistent scenarios have been identified ranging from very progressive developments of all PESTLE dimensions up to rather regressing or stagnating developments. Those scenarios reflect different future states of the macro setting for the manufacturing, process and logistic industry. A discussion within a visionary workshop with experts selected six of those twelve scenarios based on their probability and impact on the supply chain. Scenario narratives detail the exact scenario settings and explain possible effects on the supply chain.

    MACRO SCENARIOS FOR 2030

    “aSPIRANT” - Strong partnership enables homogeneous frameworks allowing a sustainable and technological development

    Political concord in EU; widespread free trade; stable alliances

    US and EU as global trade leaders; digital platform economics; tech-giants dominate financial sector; globalised companies benefit

    Sustainable consumer behaviour; social balance; adjusted labour market; living in smart regions

    Digitalisation, Industry 4.0 and green systems far advanced; predominantly large enterprises push disruptive developments

    Legislative keeps pace with technological development

    Climate protection successful; resource wastage curbed

    A stable political and economic environment within the EU and neighbouring countries characterises this scenario. Free trade agreements of European countries with other economic unions support and facilitate the exchange of goods.

    Europe remains strong in exports and intensifies the role as a net investor in the world. This is further supported by the upcoming economic development of the MINT countries. At the same time, new competitors emerge from different parts of the world. Born global firms export their products or services within a couple of years after their inception and export a high percentage of their total production. This is particularly noticeable within a fast developing digital economy. The developments of collaborative platforms enable an easy share and utilisation of resources. New digital business models are emerging in many different sectors such as leisure, fashion or cosmetics.

    New service categories like the Fintech Services innovate complete industrial sectors. Within this setting, companies establish their own payment systems along with growing Fintech start-ups, similar to the current payment service Alipay by Alibaba. Trusted third party services develop their own digital currencies, taking over the “traditional” way of paying. As global companies are the pioneers in the fields of digital transformation and cyber-physical systems, this puts them into a powerful position where they are in control of a high volume of generated data. Big companies with a global reach hence determine the new payment logic. Smaller, local companies struggle with the efficient management of information overload without the benefit of either enabling technologies or the required expertise.

    A high pace of technological development presents a serious stumbling block for smaller companies to stay in the game.

    The digital economy permeates all aspects of society: helping people and companies to orchestrate, manage, and automate many of their daily activities (e.g. “virtual agents & brokers”).

    As social networks strongly influence consumer behaviour, companies have to adapt quickly on a large scale and people in the EU are more ecologically-aware and pay attention to the origin of products as well as its recycling potential. This mindset is also reflected in people moving to the countryside. As technological developments advance, suburban living offers a higher quality of life allowing more flexibility in the world of work. Fast transportation and innovation in the mobility sector support this lifestyle, for the increasingly older generation, too. Migration is now favoured, to ease the demographic inequality of an ageing population in Europe. New concepts advocate smooth integration, which is sustained by social engagement. An effective wealth redistribution ensures social stability.

    The political and economic setting supports technological developments, allowing SMEs and start-ups to participate in this global arena. Emerging technologies such as advancements in artificial intelligence (AI) assist humans by undertaking autonomous planning and handling tasks White-collar tasks change from actual decision-making to the supervision of AI based decision-making systems. An increased exploitation of these technologies leads to a highly automated and autonomous environment. Coupled with the ability to share and act upon the associated data and derived insights, new service- and production-related business opportunities arise for global players as well as start-ups. Suppliers of disruptive technologies experience exponential growth rates and existing disruptive technologies improve quickly and continuously.

    Simultaneously with developments within the technological area, regulations are maintained updated. There are clear regulations for handling data, thus creating transparency and IP-security. Regulations towards full product transparency support sophisticated recycling technologies and this limits the depletion of resources to a minimum as well as slowing down waste production.

    Since fossil fuels are depleting and becoming more expensive as time goes by, renewable generation, transmission and distributed energy resource systems are becoming even more relevant as a viable substitute for future generations. At the same time, new power grid solutions and grid transformations overcome the technological limitations of a traditional power grid and create a smart grid environment with distributed energy generation and powerful storage systems.

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    “PrOCEEDINg” – Political coherence, disruptive technologies and individualised consumerism facilitate an innovative business development

    Political concord in EU; widespread free trade; stable alliances

    US and EU as global trade leaders; digital platform economics; Bank and Fintech collaboration; global companies operate locally

    Social balance; adjusted labour market; strong consumption individualisation (DIY, variant diversity); living in smart cities

    Digitalisation and Industry 4.0 widely implemented; electrification and ecological transition far advanced; start-ups and SMEs push disruptive developments

    Legislative keeps pace with technological development

    Climate protection successful; resource wastage curbed

    Based on a political stable and economically flourishing environment, Europe is developing steadily and remains a strong net investor in the world. Europe invests heavily in upcoming technologies, which in turn is reflected in the development of digital transformation within the economy, including the trend towards a sharing economy. People take advantage of the numerous offers of a sharing economy both in business to consumer and consumer to consumer approach. Further collaborative platforms enable an easy share and utilisation of resources (hubs, terminals, etc.) within the work environment as well as in private lives. These digital platforms further support the DIY society whereby self-production of fashion, technological equipment and food become the standard. The effect of this increased consumption awareness combined with an individualised, variety based consumption pattern, motivates global companies to revise their structures adopting a “glocal” approach. Individuals want to display their singularity and have a personalised shopping experience. Accordingly, companies get culturally close to the consumer and respond flexibly to local customer needs that enables global companies to penetrate regional and local markets. Multinational companies can hence compete with local players by recognising differences in local taste and customs. At the same time, multinational companies adapt their product and services on offer to a growing number of markets. As people live in smart megacities, the distribution of the goods, mainly for DIY-Products, is facilitated.

    At the same time, the development of digitalisation is becoming increasingly integrated into the business environment, permeating all aspects of society, such as the financial sector. Fintech is evolving fast, at a pace that

    high-street banks struggle to emulate. However, people are skeptical and reluctant to assign their income solely into Fintech. Thus, Fintech is collaborating with the banks, which remain an integral element of the transactional infrastructure. Emerging technologies such as advancements in artificial intelligence (AI) assist humans by undertaking autonomous planning and handling tasks. Since many physical and intellectual tasks are increasingly being taken over by technical developments in automation and economic empowerment, this has the knock-on effect of a decrease in demand for manual labour. The more these technologies are exploited, the more highly automated and autonomous the environment becomes. The resulting knowledge-based economy labour market is characterised by cross-disciplinary, creative profiles and lifelong learning. Employers cope with flexibility demands and adopt an intercultural model partly equalising the resulting labour overflow.

    Coupled with the ability to share and act upon the associated data and derived insights, new service- and production-related business opportunities arise, especially for start-ups. While focusing on niche markets and lean organisational structures, they deal with high volumes of data flow efficiently. Existing disruptive technologies improve and additional solutions develop rapidly and continuously. These technologies not only increase the degree of freedom in manufacturing processes but also allow more efficient and effective work processes.

    These efficient work processes diminish the depletion of fossil fuels. Technological developments allow for the generation of renewable energy, as transmission and distributed energy resource systems are becoming more prevalent. At the same time, new power grid solutions and grid transformations overcome the technological limitations of a traditional power grid, creating a smart grid environment with a distributed energy generation and powerful storage systems. The time of product development and rollout is minimised.

    Most importantly, the politically-friendly situation allows for a rapid, early update on regulations mostly simultaneously with technological developments. Data handling is clearly regulated, thus creating transparency and IP-security. Along with a comprehensive regulatory framework, it supports new inventions. Regulations towards full product transparency support sophisticated recycling technologies. Together with enhanced resource efficiency, this limits the depletion of resources to a minimum while slowing down waste production.

    “oFFsET” - Free trade enables political and social development whereas fragmentation hinders technological and environmental change

    Constant development in EU; free trade; instable alliances

    Asia drives economic development; global companies act local; tech-giants dominate financial sector

    Social balance; adjusted labour market; “much-and-cheap” consumption influenced by social media; living in smart cities

    Digital transformation is slowing down due to cost and retention; autonomous systems are only occasionally successful; coexistence of conventional systems; further efforts for electrification and alternative energies

    Legislation falls behind technological development; heterogeneous regulations and low levels of trust in data privacy and market regulation

    Climate protection targets are not achieved; strong pollution; scarcity of resources

    In this scenario, the world has to deal with severe environmental problems. CO2 emissions are increasing around the world and there are the major sources of total greenhouse gas emissions. The most visible consequences are the continuous escalation of climate disasters and the increase of air, water and soil pollution. Climate change is combined with a severely ongoing depletion of resources for humankind as well as industries; the ever-increasing global population, economic growth highly contribute detrimentally to the natural resources of our planet. For example, the overall demand for water remains higher than supply, so that highly populated countries face severe issues related to water scarcity or completely lack of access to water.

    Add to this the fact that the world is increasing the production of solid, hazardous and electronic waste which have a strong negative global impact caused by the increase of consumerism. In addition, the recycling rate remains low and countermeasures to avoid high waste are not well implemented or, in most of the countries, there are not enough strong laws and policies for waste and recycling management.

    These environmental issues are reinforced by different factors coming from other dimensions. For example, the fast increment of consumerism is an effect of the increase in the global goods exchange, due to increasing free trade. Another factor affecting the planet’s ecosystems is the expansion of urban areas, resulting in the physical growth of cities, megacities caused by migration from countryside to city.

    Moreover, the population in developing countries is rising sharply and all these factors combined, lead to a worsening of environmental conditions. Nevertheless, there are some ongoing countermeasures: the use of renewable energy resources and smart grid solutions are promoted by the better connectivity and efficiency of smart cities and also in the industrial sector, green systems used for power generation, energy storage and transportation, such as hydrogen power cells and biomass, are progressively applied. Standard mutual roadmaps and common policies are missing; for this reason, solutions for smart power grids develop more slowly than expected. The same problem could arise for e-mobility: this technology could decrease CO2 emissions and reduce the greenhouse effect, but its proliferation is hindered by the lack of standard roadmaps, common policies, and a systematic upgrade of the infrastructure.

    The lack of regulations and the need for cultural transformation are the barriers for a digital transformation, not only with respect to the social and economic dimensions but also technological. Thus, there is a dominance of global players that become pioneers in the fields of digital transformation and cyber-physical systems; global players have significant resources such as brands, hard assets, customer relationships, global distribution data and many years of institutional know-how to harness the digital transformation. The global players are the main actors also in the financial innovations: the big 5 IT companies (Google, Apple, Facebook, Amazon, Microsoft) offer their own currencies to facilitate seamless payments between both people and devices: credit card companies and technological companies join forces and establish new technical payment standards including biometric identification procedures.

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    “DiThEr” - There is digital and technological development but not enough to compete globally

    Constant development in EU; closed economic areas; collapse of alliances

    Asia drives economic development; global companies act local; digital platform economics; Bank and Fintech collaboration

    Aging society with large disparities and high unemployment; strong consumer individualisation (DIY, variant diversity); living in smart cities

    Digitalisation obstructed by cost and retention; increased use of autonomous technologies; electrification and ecological systems are well advanced; start-ups benefit from the evolving technology industry

    Legislation falls behind technological development; heterogeneous regulations and low levels of trust in data privacy and market regulation

    Climate protection successful; resource wastage contained by technological developments

    In this scenario, development in Europe is expected, but the rise in political uncertainty has led to political unrest in neighbouring countries and disagreements between unions. This situation promotes the policy of protecting domestic industries against foreign competition, entailing several trade policies such as geographic barriers, tariffs, import quotas or other restrictions on the imports of foreign competitors. These lead to complications in the logistic structure, and some companies withdraw from the market. The EU is going into crisis due to the economic situation and several countries are putting their own needs first and choosing to leave the union.

    There is a steady decline in economic growth in Europe, due to a decrease in exports. This is due to local production. Elsewhere in the world, the economic situation in Brazil, Russia, India, China and South Africa (BRICS) has slowed down to give access to Mexico, Indonesia, Nigeria and Turkey (MINT) as the new emerging economies. Despite its growth slowdown, China has overtaken current economies and establishes as the net investor in the world.

    In terms of the organisation of a business to serve a market, the predominant structure considers the adaptation of international products to local and cultural preferences. There is an increase in demand for customisation and consumer awareness. The preferences of consumers are DIY (do-it-yourself) products, aimed at the middle class who consider ecological and social aspects. Circular economy models are reinforced by companies and adopted to encourage closure of the materials cycle through better design of components, recycling and reusing, while mitigating the environmental impact.

    Although consumers are more aware of their purchase, legislation is lagging behind, due to new business models and the rapid technological development of companies and consumers do not have all requested information on products, their properties, origins or manufacturing procedures.

    The advances in technology, such as additive manufacturing, automation, the dynamic development of autonomous technology and cyber physical systems, make production of products with specific adjustments cost-effective, both for global players and SMEs. Companies try to postpone their production until the latest point possible to allow individual customisation, while the exploitation of disruptive production technologies promotes design-driven manufacturing processes and precise control in industry. Even though this technology advancement creates new jobs, emerging skills are required and the re-employment of workers becomes difficult. In particular, robots and autonomisation take over manual and white-collar tasks: the unemployment rate increases and this contributes to social and political unrest.

    Digital transformation advocates a speedy digital economy well received by the public. Digital transformation is principally advocated by multinationals who have the required financial resources to adopt the latest technological applications. Most companies come across obstacles, such as stringent legal regulations, the difficulty of evaluating their digital proficiency, challenges of data ownership, data management, lack of acceptance due to privacy or data security concerns. Data security and comprehensive data exchange via conventional business platforms is an issue because core data and business secrets are exposed, and liability regulations are missing in case of infringement. In terms of innovation management, although there are plans for IP protection, they are not carried out and IP theft is a key challenge for inventors.

    Companies, particularly multinationals, promote new business models in further sectors, innovating many industries and enabling new business-to-business (B2B) and business-to-consumer (B2C) relations. These conditions facilitate the collaboration between banks and Fintech start-ups, the promotion of better customer interaction and the development of new financial services, accessible from anywhere via mobile apps.

    The favourable development of technology and digitalisation has positive effects on environmental development as it enables a reduction of low-carbon energy supply, efficient practices in agriculture, and maintaining global warming at an environmentally acceptable rate. The development also contributes to longer, healthier lives in developed countries, especially for the upper classes. More and more people are migrating from country to city. The investment in smart cities and internet of things (IoT) lead to comforts, like access to free wi-fi in public spaces, an increase in online shopping,

    delivery of goods at home, growth in the use of renewable energy on a large scale (wind turbines, solar panels), flexible and efficient electricity infrastructure and use of hydrogen systems. Nevertheless, the worsening living conditions, scarcity of resources, problems with air pollution, clear water capacity and waste management has lead to a considerable dissatisfaction within communities.

    “UNEasE” – Unstable political setting and power shifting hinder the technological and environmental development

    Constant development in EU; protectionism; collapse of alliances

    Asia, BRICS & MINT drive economic development; global companies act local; Bank and Fintech collaboration

    Aging society with large disparities and high unemployment; strong consumer individualisation (DIY, variant diversity); living in smart cities

    Digitalisation obstructed by cost and retention; autonomous systems hardly prevail; further efforts for electrification and alternative energy sources; start-ups benefit from advancing technological development; coexistence of conventional and disruptive technologies

    Legislation falls behind technological development; heterogeneous regulations and low levels of trust in data privacy

    Climate protection targets are not achieved; strong pollution and scarcity of resources

    The political environment in Europe is unstable under this scenario; however, this instability is decreasing due to security enforcements, especially regarding terrorist attacks. Security regulations and enforcements bring about higher levels of protection increasing geographic and economic barriers. The unstable environment supports separatists’ objectives, and political fragmentation becomes both a reality and concern, since it can drive EU into crisis with several countries leaving the union.

    The lack of stability helps BRICS and MINT countries to develop and become the most significant economic players, with special attention to China’s leadership. The Chinese investments on economy and export markets further support China to overtake Europe as the world’s net investor, which is influenced by Europe’s decline in exports. Customer orientation focuses on variety and, therefore businesses emphasise individualism, providing sufficient local demand so that multinational companies can compete with local players through differentiation of taste and customisation. This individualistic focus also creates an incentive for SMEs

    and start-ups to thrive as they are able to make specific product and service adjustments, while also capitalising on local marketing strategies.

    The rise of SMEs and start-ups has legal and political concerns, due to the innate characteristic of dynamic markets created by the introduction of new business models. This hinders legislation development and increases the development of heterogeneous regulations. Also, start-ups in the financial sector are competing with traditional banking institutions by focusing on digital processes and innovation, which enables better customer interaction. However, there is a persistency of traditional economy due to the fear of data misuse by new business models, creating obstacles that restrain digital transformation. Even though a sharing process is encouraged on a consumer level, peer-to-peer services are affected by legal and political regulations that hinder sharing in the business-to-business (B2B) environment. Therefore, digital economy thrives mainly due to business-to-consumer (B2C) business model, with B2B tiers 2 and 3 levels of the supply chain heavily relying on traditional business concepts. Also, the do it yourself (DIY) concept becomes the norm, due to technological developments, such as 3D-printing and rise of sharing economy. Self-production of fashion, technological equipment and food become standard, whereas manufactured products are mostly purchased from other DIY-individuals, locally.

    Challenges of data ownership and data management must be addressed in order to realise the business potential of digital transformation endeavours, which are often faced with lack of acceptance on the consumer part, due to privacy or data security concerns. The lack of liability regulations in case of infringement provides the environment for core data and business secrets exposure. Hence, comprehensive and regular data exchange are hindered, being upheld by data sovereignty concerns, which are related to the enforcement of privacy and compliance regulations. Moreover, laws and regulations for securing IP rights do not apply to certain countries, which results in profit loss and IP theft, hence being a challenge for inventors, designers and artists.

    Legislation issues reach out to the environmental dimension, where heterogeneous regulations become the norm. The shift of political dominance to emerging countries aided by the presence of heterogeneous regulations supports a steady decline of natural resources.

    Incentives regarding ongoing electrification endeavours, which focus on green systems used for power generation, energy storage and transportation, are increasing, especially with the rise of electric and hybrid vehicles. Despite smart power grid incentives, their development has been slower than expected, with research being conducted on a variety of technologies to accelerate the rate of shift in the energy mix and improve efficiency regarding electricity generation, storage and distribution. Renewable energy is still under

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    development, which contributes to natural resource depletion, especially in the energy sector. With more people moving to the city, the physical growth of cities is prominent, leading to emerging megacities with advanced communication and sensor infrastructure.

    “ENDANGEr” - European disintegration and protectionism lead to geopolitical, social, environmental, legal, technological and economic issues that affect a company’s success

    Political instability in EU; protectionism; collapse of alliances

    Asia drives economic development; global companies act local; political instability leads to a traditional goods exchange based on crypto-currency

    Strong social inequality especially; aging society with high unemployment forces to consumption of cheap mass-market products; living in smart cities

    Digitalisation obstructed by cost and retention; increased use of autonomous technologies; e-mobility and alternative energy sources benefit from previous research; dominance of multinationals inhibits further development of new technologies

    Outdated, inhomogeneous legislation; low data privacy

    No ecological agreements; heavy pollution; scarcity of resources

    In this scenario, an instable political and social environment in Europe is assumed, while, in the meantime, countries, such as Mexico, Indonesia, and Nigeria, record significant growth in terms of GDP. Protectionism everywhere is on the rise and companies are facing several tariffs, import quotas, and trade barriers. The aforementioned political and economic setting leads to “glocalisation”. Companies, especially from Europe, get culturally close to consumers from the emerging economies in order to respond flexibly to local customer needs and to penetrate regional and local markets. Multinational companies compete with local players by recognising differences in local taste and custom.

    Companies individualise their products, but focus on larger groups of customers as social networks strongly influence the buying behaviour. New business models and digital innovations, such as cloud-based voice services, rise and allow companies to enter new markets/countries. Everyone makes financial transactions autonomously on the internet, rendering high-street banking services and notary services obsolete. However, the traditional way is upheld due to the fear of data misuse and legal and political

    concerns. This political instability leads to a stagnating, non-homogeneous legislation, limiting the development of emerging technologies. These issues are shaping a world where digitalisation is obstructed by retention and only main global players, that have significant resources, can afford to implement available technology applications due to high costs and risk aversion. Thus, in this new reality, several obstacles make it difficult for SMEs to develop; and as big companies dominate the business landscape, this inhibits further development of new technologies, in which SMEs play a crucial role.

    Contrary to the restriction on digitisation, autonomous technologies are progressing at a rapid pace, especially with regard to robots, drones, and autonomous vehicles. The ever-evolving world of work also creates new demands on workers. Manual tasks are increasingly being taken over by technical developments and automatisation, e.g. robots. Since whole industries are affected by the autonomisation, the overall rate of unemployment rises. The ratio shifts towards a large portion of the employed upper class and a large portion of the unemployed working class, causing strong social disparity and social unrest, which forces customers to choose cheap mass market products.

    Companies also adapt their business structure by taking into account the high population growth and that more and more people migrate to megacities, leading to rising atmospheric CO2 concentration and a shortage of resources. Renewable energy technologies, driven by climate change, fuel security, and other motives, provide more and more of our electricity, as standard, widely accepted regulatory frameworks are missing across the globe. Green systems are used for power generation, energy storage, and transportation, such as hydrogen power cells and biomass in industrial and social sectors. Despite all of the efforts, high associated costs and unclear regulations hinder a proliferation of e-mobility, especially in rural areas. Furthermore, solutions for smart power grids are developing slower than expected. Regarding resource scarcity, ever-increasing global population, non-homogeneous environmental and waste legislations and protectionism highly contribute to severely ongoing depletion of resources for all industries. For example, rare earth elements (REEs) are increasingly used in a myriad of sectors to produce e.g. electric vehicles and wind turbines. China has dominated rare earth mining since the 1990s, extracting 85 to 95% of the world’s REEs from large clay deposits in the country’s south. Thus, companies are dependent on China which tend to restrict their exports affecting the availability and continuous supply of REEs.

    SPECIFIC CHALLENGES FOR SUPPLY CHAIN

    Table 1. Specific challenges for the SC of the future (B: behavioural, O: operational, L: legal and F: financial)

    Specific challenges B O L FSCH #1 Developing new collaborative SC models √ √ √SCH #2 Resource management for a circular economy √ √ √SCH #3 Sourcing complexity management √ √ √SCH #4 Developing “leaner” and more flexible SC √SCH #5 Promoting efficient and sustainable logistics in urban environment √SCH #6 Facing changes in SC due to personalised shipment √SCH #7 Organising SC for variable and custom demand √ √SCH #8 Ensuring quality along the SC √SCH #9 Identifying talents in SC √

    SCH #10 Energy and emissions management √SCH #11 IT integration and interoperability √ √ √SCH #12 Managing IP protection issues √ √SCH #13 Dealing with digital-driven issues √ √SCH #14 Human perspective in digital transformation √SCH #15 Coping with digitalisation and globalisation in finance √ √SCH #16 Addressing problems and limitations of regulatory framework √ √SCH #17 Facing outsourcing complexity √ √SCH #18 Managing omnichannel SC and multimodality √SCH #19 Managing complex or increased information flow √ √SCH #20 Dealing with industry concentration and competition √ √SCH #21 Managing risk and disruption √ √SCH #22 Facing inventory and shipping problems √SCH #23 Policies √

    mainly interlinked and more easily identifiable by companies, but it is fundamental to consider the impact of “human decision making and interactions” (behavioural), “the policy maker’s impact on how global supply chains function” (legal), and “the difficulties associated with setting up a business or the ultimate goal of any business, which is making money” (financial) challenges. Key supply chain challenges ascribed to these issues are described as follows.

    Several supply chain specific challenges faced by European companies can be identified within each future macro scenarios. Sound proactive strategies must be designed for mitigating risks stemming from such challenges having a significant likelihood. A mix of proactive and contingency planning is instead an appropriate choice for other challenges that appear in a single or few scenarios, and therefore in less probable situations.

    Specifically, the identified challenges entail operational, behavioural, technological, financial, and legal issues, and often a combination of them. Operational challenges are

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    Enabling TechnologiesAutonomous Transport SystemsAutonomous transport systems are machines that are able to act autonomously without human interaction based on an individual sensing of the environment, to perceive this environment and to decide which route to take. Comprising the sub-technologies autonomous vehicles (e.g. trucks, trains and ships) and drones, the technology has a broad applicability across all industrial sectors. Autonomous transport systems play a key role in the development of future industrial supply chains, especially in the manufacturing and logistic sectors.Robots Having superior sensing, control, and intelligence enabling robots to automate, or assist human activities, these machines have a strong influence on the labour market, especially when combined with artificial intelligence. Main sub-technologies for robots include collaborative robots, which physically interact with humans in shared environments, and autonomous robots, designed for self-reliance and being capable of operating without human assistance or interaction.

    Cloud-Based Computer SystemsOutsourced computing power, data storage and services are part of this information technology (IT) services method, which relies on cloud connection and communication allowing for data delivery and applications’ delivery to any device connected to the internet. Sub-technologies include Platform as a Service (PaaS), Software as a Service (SaaS), Business Process as a Service (BPaaS) and Infrastructure as a Service (IaaS). Cloud-Based Computer Systems have a broad applicability and positive implications on future supply chains in all three sectors.

    Internet of ThingsClearly shown to play a major role in the future supply chain industry with regard to all sectors, Internet of Things (IoT) can be described as an autonomous collection, exchange and action of data rendered from a network of physical devices broadly embedded with sensors, software, network connectivity and computer capability. Most notable sub-technologies of IoT are Sensor Technologies, Machine to Machine (M2M) communication, Cyber-Physical Systems and Process Intelligence.

    MAPPING ENABLING TECHNOLOGIES Technology is not the only factor boosting supply chain competitiveness, which also depends on other framework conditions and decisions. Indeed, it represents a key element that make the difference in the implementation of a specific strategy.

    Existing roadmaps and studies at different levels (regional, national, international, sector specific) were analysed to identify the most important enabling technologies in the area of SC.

    The evaluation and validation of each technology aimed to define the Technology Readiness Level (TRL), the applicability scoring in discrete manufacturing, process industry and distribution and logistic sector, and the implications on supply chain performance in the following categories: agility, cost, transparency and traceability, responsiveness, reliability and sustainability.

    System Integration enables cross-company, universal data-integration networks with different subsystems, including hardware, software and communications, that need to be

    integrated (BCG, 2018; Gartner, 2018). System Integration should be carried out both horizontally and vertically ensuring different types of collaboration at different levels of the supply chain. Vertical integration focuses on integrating processes across the entire organisation, via the networking of smart production systems, smart products and smart logistics, while horizontal integration encompasses networking along the entire supply chain, from suppliers and business partners to customers, in order to achieve a seamless cooperation between companies (Werner, 2017).

    Cybersecurity needs to assure systems protection whose demand is growing due to the increased data exchange and connectivity (BCG, 2018). Therefore, there is the challenge to arrive at secure, reliable levels of protection regarding the identity and access management of machines, networks, clouds and users have to be ensured with advanced systems such as firewalls, DNS filtering, malware protection and antivirus software (BCG, 2018; Gartner, 2018).

    Enabling TechnologiesDistributed Ledger / BlockchainCombined with IoT, this technology is critical for the development of the future supply chain industry, being characterised as a distributed, shared and encrypted database focused on providing full security for information storage and communication, achieved by irreversible and incorruptible levels of data safety. Applications of the sub-technologies such as smart contracts and cryptocurrencies will play a key role in the future, especially in the logistic sector. Artificial IntelligenceArtificial Intelligence (AI) can be defined as a branch of computer science concerned with the automation of intelligent behavior such as perception, reasoning, recognition, understanding, communication, design, thinking and learning, which can be realised artificially by machine, system, or network. AI will greatly affect the performance and development of the future supply chain industry given its central role in autonomous systems, robots and data science. AI includes multiple sub-technologies such as machine learning, deep learning, natural language processing (NLP) and strong artificial intelligence. Data ScienceData Science is the application of quantitative and qualitative methods to solve relevant problems and predict outcomes using algorithms aimed at creating or extracting new information out of vast amounts of data. Main sub-technologies of data science are categorised as Data Storage and Big Data Analytics. Mobile and Wearable DevicesDevices, which can act autonomously, be non-invasive and perform specific functions, such as monitoring and support over a prolonged time-period, are considered as mobile and wearable devices. Application examples of such devices are smart glasses and smart gloves for barcode scanning. Communication InfrastructureThis technology aggregates networks and protocols required for establishment of viable communication between two or more IoT components. The current main sub-technologies are 5G and NarrowBand-IoT (NB-IoT). Since communication infrastructure enables all digitalised technologies it is one of the key enabling technologies for future industrial supply chains. Identification TechnologiesIdentification technologies focus on identifying and tracking goods by using different codes or tags, hence showing broad applicability and positive implications on the SC performance in the logistic sector. Market presence sub-technologies of identification technologies include Radio Frequency Identification (RFID) and Barcode Tags. Location TechnologiesLocation technologies are complementary to identification technologies: seamless positioning and tracking capabilities in both outdoor and indoor environments are an important requirement. They are relevant for the improvement of the future logistics and distribution supply chain industry sector. Sub-technologies include passive and active GPS tracking systems, Wireless Indoor Positioning Systems and Real-Time Locating Systems.Visual ComputingWith the focus on extracting information from images and embedding information onto images, visual computing uses image- and model-based information technology by combining computer graphics and computer vision. In computer graphics, images or multidimensional models are created, while computer vision enables a computer to see its environment by means of a camera. Visual computing includes the sub-technologies Augmented Reality (AR) and Virtual Reality (VR).Additive ManufacturingAdditive Manufacturing (AM) is a technology enabling the creation of lighter, stronger parts and systems through transformative approaches to industrial production, being considered a genuinely disruptive technology that supports customisation while also minimising waste due to more efficient use of resources. Bearing these characteristics, AM is also seen as a critical technology for the development and improvement of performance on the future supply chain industry; AM’s sub-technologies include 3D and 4D printing. Energy InfrastructureEnergy Infrastructure technology is designed to provide reliable energy coverage while also optimising energy consumption. To achieve these goals, it relies upon smart and neural grids, mainly focused on the generation, storage and consumption of electric energy, and Battery Energy Storage Systems (BESS), which are aimed towards storage capabilities of the grid.Alternative Propulsion SystemsAlternative Propulsion Systems and its sub-technologies comprise all propulsion engines which use alternative means of propulsion when compared to petroleum-based fuels. Therefore, this technology encompasses Advanced Biofuels and Electro Mobility as sub-technologies.

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    Enabling TechnologiesRenewable Energy TechnologiesBearing some resemblance to Alternative Propulsion Systems, Renewable Energy Technologies are aimed at establishing renewable energy resources as the main sources for energy systems, in detriment of emissions caused by non-renewable energy resources such as petroleum-based fuels. To achieve EU’s objectives for 2030, technologies such as Flywheel Energy Storage, Hydrogen Production and Storage Technology, and Advanced Biofuels have to be used. Smart MaterialsSmart Materials are magnetically or electrically controllable materials with outstanding mechanical properties. These materials play an increasingly important role in the development of innovative, versatile and efficient products with a wide range of new functions for customers across all industries. Smart materials can be classified into property changing and energy exchanging smart materials. NanotechnologyImproving functional systems on a molecular level and object designs, with a bottom-up approach aimed at creating sophisticated products, are the main objectives of nanotechnologies, which use material modification on atomic, molecular and supramolecular levels to achieve these goals. With this approach and objectives, there is the possibility of properties’ manipulation at the most minute levels, providing the basis for a wide variety of applications to be conceived. Sub-technologies for nanotechnology include Bionics and Nanolithography.

    Technological challenges TCH #1 Lack of technology maturity/ Underdevelopment of technology

    TCH #2 Improvement of energy systems and development of new power sources for full exploitation of some technologiesTCH #3 High cost of development and implementation of technologyTCH #4 Social acceptance and awarenessTCH #5 Lack of standardisation for the use of technologyTCH #6 Safety for usersTCH #7 Data Security and intellectual property threatTCH #8 Scarce Interoperability and difficulties in integrationTCH #9 Need for specialised workforce

    TCH #10 Limited production/ scalability

    TCH #11Limited reliability in technologies such as communication infrastructures, cloud based computer systems, IoT or additive manufacturing

    TCH #12 Technology accuracyTCH #13 Feedstock supply due to dependence of raw materials

    Table 2. Challenges for the enabling technologies

    NEXT-NET VISIONOver the next decade, supply chains will operate more and more in an ever-changing environment, shaped by different megatrends which strongly impact on the networks’ configuration and increase the level of uncertainty. Companies need to face up to multi-facet challenges raised by these trends with the support of new technologies and new approaches transforming the way they do business. This transformation requires not only changes in terms of assets and tools for distribution, logistics and manufacturing, but also the development of new roles and type of relationships among the actors involved in the supply network. This creates the urgent need for companies to adapt the way their supply chains are organized and interlinked significantly, by transforming the supply networks into resilient systems able to cope with unexpected disturbances.

    To address the dynamics of the current competitive, economic and political landscape, the NEXT-NET project envisions future European supply chains as highly integrated, resilient and sustainable networks. Coordinated actions towards the integration of manufacturing, logistics and process industries are key to strengthening real economy and to reinforcing the European system for global challenges. In this sense, the roadmapping activity in NEXT-NET has led to the definition of a set of 10 supply chain strategies aimed at supporting European industries to face future scenarios, and the proposal of priority actions with a medium/long term perspective.

    Next Generation Technologies for Networked Europe

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    HYPER-CONNECTED SUPPLY CHAIN STRATEGY (HCSC)

    Nowadays, business and society are dramatically influenced by an exponential increase in connectivity, and it is possible to talk of a hyper-connected world. It is estimated that by 2025 the number of connected devices will rise from 30 billion in 2020 to 80 billion and that the amount of data created and copied annually will reach 180 Zettabytes (IBM, 2016). Digital interconnection is expanding everywhere, so that across all industry sectors, the mastery of digital technologies in value chains offers very significant opportunities to create value for customers (Digital Industrial Platforms, 2017). Data originating within industrial contexts are considered industrial common factors and its potential lies in data-sharing collaboration in SC, since this can have several spill overs on the economy. Digital transformation is key to competitiveness in today’s world.

    The hyper-connected world of the future would comprise of environments transparently enriched with sensors, actuators, devices, machines, and computational elements that are interconnected and collaborating (Afsarmanesh et al., 2016). Several initiatives at EU level have been undertaken to connect factories through the empowerment of IT systems and share real-time information between facilities. This allows performance monitoring at a broader level, taking into consideration the relationships in networks (Connected Factories, 2018). The full implementation of technologies such as digital platforms, which enable all the entities to share information, laying on the infrastructure of companies and system nodes (machines, products, factories) communicate both horizontally and vertically, thanks to devices connected via internet, and the improvement of their integration in the future will allow autonomous optimisation of the whole supply chain. The transformation of the supply chain will allow the development of services to become more valuable, accessible and affordable. It is expected that HCSC will not only integrate physically, but also information and finance flows (Büyüközkan et al., 2018); it also allows the synchronisation of interactions between the organizations supported by intertwined digital technologies for nodes

    and edges integration. Therefore, the HCSC will enable end-to-end visibility and collaborative relationships through a massive data disposal. The aim of the HCSC is to create a collaborative and integrated eco-system where actors from all the different levels of the supply chain are involved in the process of transforming data into value to improve the performance of the whole network.

    This supply chain model has been identified for the two more positive macro scenarios aSPIRANT and PrOCEEDINg characterised by a stable political and economic situation, creating a favourable environment for deep digital transformation of society, economy and industry. However, in order to achieve the complete transformation and hyper-connection of the supply chain, the necessary steps are the starting points for other macro-scenarios where unstable conditions and reluctance for the disruptive technologies and new business models slow down the transformation.

    • Technology Integration for seamless connection (SCH#11-13-19, TCH#G-H)

    • Dealing with complex data environments (SCH#19)

    • Real time visibility and traceability in HCSC (SCH#15)

    • Role of humans in hyperconnected environment (SCH#1)

    Specific Challenges for HCSC

    RIT_HCSC.1: Towards the implementation of Data Driven SCRIT_HCSC.2: Platform based SC to support the creation of collaborative ecosystemsRIT_HCSC.3: Future transportation within connected SCRIT_HCSC.4: Methods and approaches to increase traceability and transparency of SC processesRIT_HCSC.5: Cybersecurity to enable protection of data in supply chainRIT_HCSC.6: New approaches and tools for SCs to face increasing uncertainty and complexity

    The set of strategies highlights the need to develop and implement a series of solutions, approaches and models exploiting the potential of new technologies, collaborative mechanisms and global dynamics where European companies will operate in the immediate future. Some of these strategies are already well-known and future trends indicate they will remain fundamental for the next 10 years. As for the newest strategies, the related challenges demand innovative, cutting-edge actions to be implemented, based on technological and organisational development.

    In the following chapters, each of the 10 supply chain strategies is framed into a set of Research and Innovation Topics (RITs) which are mapped with enabling technologies. Moreover, for each strategy, a timeframe is set to indicate

    the expected development throughout the next 10 years of the RITs, together with a brief description of the impact on several important key performance indicators.

    These strategies represent a way of maintaining activities that add value in Europe, in order to enhance solid industrial skills, creativity, encouraging research and innovation to generate employment and wealth. With the full implementation of these strategies, European companies should invest in both tangible and intangible assets to face the opportunities arising from the competitive international dynamic. Transformative paths can be defined by implementing and combining one or more of the identified strategies according to the specific long-term objectives and resources and capabilities, in the continual striving for success.

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    RIT_HCSC.1: Towards the implementation of a Data-Driven approach

    The valorisation of data along the supply chain is quickly evolving into an essential operation for companies to build collaborative models. The objective is to encourage coordination and maintenance of information symmetry across different supply chain entities, with the final goal of creating agile and responsive supply chains. They will become more and more dynamic networks: each actor generates an exponential amount of data from cyber-physical systems, IIoT (Industrial IoT), monitoring sensors from any tier of the chain, any shop floor, any distribution centre through to the eventual consumer and transportation system. The full implementation of a data-driven model requires developing new solutions to increase the quality of data, which has be accurate and consistent, and ensure timeliness and completeness. This will enable the harmonisation and enhance the quality of data coming from heterogeneous sources. Improved AI solutions, machine learning and deep learning solutions can help to extract meaningful information from multi-variant and multi-scale data, for unambiguous decisions in every day production, and delivery decision assuring quality and trust and it can also help to find unexpected patterns for the optimisation of the supply chain processes.

    RIT_HCSC.2: Platform based SC to support the creation of collaborative ecosystems

    Digital platforms make data from factories, logistics centres, and transportation providers easily accessible and shareable. Platforms allow the full integration and alignment of the actors in collaborative eco-systems and allow the creation of supply chain digital twin, demonstrating the real-time status of the network to obtain an overview of the entire chain and drill down along it. Further developments are required for:

    • Upstream supply chain platforms to integrate suppliers and outsourcers, until the alignment, and monitor the network distribution.

    • Downstream supply chain platforms to integrate warehouses, distribution centres, and all sales channels to create a stronger relationship with market and reinforce customer loyalty and involving customers during design, production, and delivery of the product.

    • Create horizontal platforms for human resources management to exchange information with employees on tasks, training sessions as well as monitoring safety and skills, while respecting their privacy.

    The ecosystems enabled by platforms are based on the integration of different technologies and it is necessary to assure seamless and secure data-sharing for all platform users and consequently guarantee the interoperability between cloud systems and other information systems.

    Both open and closed platforms should be studied taking into consideration specific needs. The adoption of reference architecture, semantic technology and standardised frameworks will increase not only the interoperability but also the collaboration and trust throughout the chain.

    RIT_HCSC.3: Future transportation within connected SC

    In recent years, progress in the development of autonomous technologies and its application in different fields like transportation and mobility has exponentially grown.

    However, there are still challenges to be faced like level of autonomy, complexity, safety, availability, controllability and comfort (ECS, 2019). It is important to further research on how autonomous systems react in challenging and unpredictable situations (as for example unavoidable crash), analysing autonomous behaviour in increasingly complex environments (INTEND project, 2019). The development of autonomous systems depends not only on the improvement of their functions , but also on their capability of connecting with other types of autonomous transport systems, to develop large-scale and cross-border connected systems of autonomous transport, for example drones, autonomous trucks, trains and cars.

    The autonomous systems involved in outbound and inbound logistic activities require an innovative and resilient communication infrastructure, an integrated network of sensors and a deep digital transformation for urban areas to guarantee optimised management of the transportation as far as the end of the chain, with the consumer in modern cities. Moreover, user awareness and acceptance of the autonomous transport system has to be increased (ERTRAC, 2018).

    CASE STUDYFarfetch is an English e-commerce business platform in the high-luxury fashion industry, with around 3200 employees worldwide and revenues of 543,3 M € in 2018. It has established partnerships with a worldwide supply base including 614 world leading luxury retailers and 375 brands, and delivers a large portfolio of luxury fashion items in more than 190 countries.Farfetch offers a powerful 4PL supply chain platform for real-time data sharing, monitoring and tracking from product and content creation to global fulfilment network in integration with its partners.The company sets up measures for protection of personal data, privacy and information security of eventual customers. Data are collected from and used by multiple touch points in the luxury fashion ecosystem. This enables relevant personalised services such as last mile logistics, more accurate delivery time estimates for a seamless buying experience, and bespoke marketing and advertising, thanks to sophisticated, autonomous Artificial Intelligence and Machine Learning algorithms.

    RIT_HCSC.4: Methods and approaches for the traceability and transparency of SC processes

    Integrated track and trace solutions to ensure monitoring of products and processing of information at different levels of the network are needed; the issue is twofold: on the one hand, it is important to ensure efficient data collection; on the other, it is necessary to implement solutions to verify the product and information along the chain.

    Infrastructures to collect information from different tiers within the network right through to the final consumer are necessary: new IIoT, advanced sensors and location technology will ensure monitoring products and processes, collecting data in real time. Moreover, the development of new smart products ensures continuous integration to consumers to offer new services and collect data to measure product performance until (and after) the end of its life.

    Decentralised systems such as a distributed ledger solution (i.e. blockchain) increases supply chain transparency, reinforcing credibility of the information, with real-time tracking enhancing the safety of the products along the network (Tian, 2016) and also the transparency of the financial flow. Blockchain technology ensures stored records are accurate and from a verifiable and single source. There remain technical limitations to be overcome, such as scalability problems, computing power requirements and high energy consumption.

    RIT_HCSC.5: Cybersecurity to enable protection of data in supply chain

    HCSC requires high level of trust between all the actors involved and poses significant challenges in terms of data security since the deep connection along the entire network forces each actor to exchange digital information with the outside world: seamless flow of data and cybersecurity represent relevant challenges.

    The development of tools and services guaranteeing an adequate level of data security for digital collaboration in value chains is a priority. These tools need to be usable and resilient to ensure secure communication in digital transactions and data integrity during data exchange within and across the chain, and developing a stronger communication infrastructure. A system-centric view on security and privacy needs to be complemented with a data-centric view because the protection of data cannot stop at each system’s border but have to be applied over the full lifecycle of the data and therefore along the entire network (ECS, 2019). The management of cybersecurity has also to provide transparency on where data resides, who has access to it, and for what purpose it is used: Continuous Monitoring and Certification systems of Data Integrity and security are requested.

    Security Service Level Agreements need to be designed at each level of the supply chain identifying the model and policies on how data can be used between actors without compromising business privacy. This serves another valuable purpose: to maintain a good relationship with customers, who themselves are evolving naturally into more and more data sources, taking into consideration the new regulations promoted by EU Commission regarding data privacy (i.e. the new General Data Protection Regulation-GDPR)

    CASE STUDY Friul Intagli is one of the largest manufacturers of components and kits for the furniture industry worldwide, with around 2.000 employees and a turnover of 550 M€ in 2018. Its supply chain includes almost 230 suppliers worldwide and a huge logistic volume to serve the main international large-scale retail chains. The company shows a very high level of integration, leveraging on trust and transparency at logistic, informative and organizational level with both upstream and downstream supply chain, from the co-design of new products, processes and dedicated production technologies to the full traceability of the products along the logistic flows, including the packaging. The more advanced production lines are fully automated, with collaborative robotics and a Data Exchange framework for machine-to-machine integration. While automated vehicles are adopted for internal logistics, the company is shifting to an intermodal transportation system to further consolidate/ integrate the activities with the suppliers worldwide.

  • Technology Map

    The table below lists the most relevant technologies for each RIT for the full implementation of the supply chain strategy.

    TECHNOLOGIES RITs

    Artificial Intelligence RIT_HCSC.1-3-6

    Autonomous Transport Systems RIT_HCSC.3

    Cloud Based Systems RIT_HCSC.1-2-5

    Communication Infrastructure RIT_HCSC.1-2-3-5

    Data Science RIT_HCSC.1-5-6

    Distributed Ledger RIT_HCSC.2-4-5

    Internet of Things RIT_HCSC.1-2-3-4

    2222

    RIT_HCSC.6: New approaches and tools to face increasing uncertainty and complexity

    The coordination and configuration of the supply chain has to take into consideration the numerous external variables and drivers which have a strong impact on the strategic and operational decisions but which companies cannot govern. These variables increase the complexity of the network and make it more difficult to optimise decisions. We need new models to analyse the influence of exogenous changes to supply chain processes more effectively. The supply chain is similar to a complex adaptive system, because it is non-linear and dynamic, where the interconnected entities have to proactively respond to changes from both the external environment and the system. Although each actor operates at a different level and follows different objectives, the resilience of supply chain is a collective outcome (Tukamuhabwa, 2015); moreover, when a disruption occurs, the systems has to learn to be anti-fragile: it would not lose but profit from the effects of disruption (Zitzmann, 2014). Therefore, for a HCSC, it is necessary to create new tools and models to hook up the changes and consequently adapt the product, processes, production and delivery systems in a coordinated and systematic way. Principals of cognitive adaptability, self-diagnosis and self-resilience need to be put in place through the development of new tools and models supporting forecasting, production planning as well as inventory and transportation management.

    Time Frame for HCSC

    The figure below represents the time frame of the RITs for the supply chain strategy indicating the time horizon (short term: 1-3 years, medium term: 4-7 years; long term: 8-10 years) for the expected development.

    TIME FRAMEShort Medium Long

    HCSC.1

    HCSC.2

    HCSC.3

    HCSC.4

    HCSC.5

    HCSC.6

    Expected Impact

    The table below lists the most significant impacts expected from the development of the RITs. Each KPI is linked to one or more RIT representing the future impact of the proposed solutions on SC performance.

    KPIs RITsIncrease of timeliness of data elaboration and sharing for the decision making process

    RIT_HCSC.1-2-4

    Reduction of processing time RIT_HCSC.1-3-6

    Increase of data accuracy RIT_HCSC.1-3-5Increase of allignment between production and logistics data

    RIT_HCSC.2-3-6

    Increase of capabilities to face cyber attacks RIT_HCSC.5

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    DISASTER RELIEF SUPPLY CHAIN STRATEGY (DRSC)

    sector and relief organisations (Balcik et al., 2010). Given the increasingly unstable conditions characterizing the coming years, the DRSC is not only useful to face humanitarian emergency, but it can also be applied by industrial networks in order to reduce the disruptive impact of uncertainty and unpredictable events on production and distribution. At the firm level, companies should use the multiple sourcing model (Abe and Ye, 2013) to reduce the risk of supply disruptions. Also, firms need to invest into long-term continuity of the supply chain focusing also on mitigation strategies, prevention of emergency and on recovery (Day, 2014). At the supply chain level, Abe and Ye (2013) suggest the need for public-private partnerships in order to enhance information and experiences sharing on disaster risks in order to improve the resilience of the networks.

    The DRSC strategy is linked to the UNEasE and ENDAGEr macro scenarios that are characterised by unstable political and economic conditions and social and environmental concerns where disasters (natural and human-driven) may be more prominent.

    Specific Challenges for DRSC

    Nowadays, modern supply chains are more cross-border and integrated than ever before, and as a result they can be more vulnerable to disasters (Abe and Ye, 2013). Disasters damage infrastructure, disrupt the supply chain, cause huge economic losses and negatively affect the global economy (Altay and Ramirez, 2010). The global disasters in 2017 cost $306 billion (Rathi, 2017) and the recorded losses from climate extremes in Europe in the period 1980-2013 cost EUR 393 billion: on average EUR 11.6 billion per year (European Environmental Agency, 2017). Damages are projected to increase in the future in line with continued climate change (Schwartz et al., 2014).

    Disaster relief and humanitarian supply chains are employed in disastrous scenarios. They have a short, unstable existence, providing emergency aid as well as longer term development aid depending on the scale of the disaster (Oloruntoba and Gray, 2006). The DRSC can have non-profit objectives and involves logistics that account for 80% of relief operations (Van Wassenhove, 2006) and are primarily reactive, being performed through ad hoc design with extensive advance planning (Tomasini and Van Wassenhove, 2009; Jahre et al., 2009; Balcik et al., 2010; Dubey and Gunasekaran, 2016). There are three phases within disaster management that supply chains follow, namely preparedness, immediate response and reconstruction/rehabilitation (Van Wassenhove, 2006; Kovacs and Spens, 2007). Information management, collaboration and agility can help to reduce complexities (Tomasini and Van Wassenhove, 2009; Oloruntoba and Gray, 2006) due to uncertainty and limited knowledge of the disaster, such as matching demand with supply. Therefore, it is important that common language, quick information sharing through innovative technologies and increased visibility shall be proposed to facilitate the collaboration between the many different actors (Tomasini and Van Wassenhove, 2009). Because of the number of stakeholders involved in relief effort there is an increased need for the future to form partnerships between private sector companies, public

    • Improved collaboration in facing emergency (SCH#1)

    • Develop “leaner” and more flexible supply chain (SCH#4)

    • Identifying talents in supply chain during the first aid (SCH#9)

    • Facing inventory and shipping problems integrating 3PL capabilities (SCH#22)

    • Managing risk and disruption of unexpected events (SCH#21)

    RIT_DRSC.1: Multi-actor collaboration platforms for emergencyRIT_DRSC.2: Crowd-help open platform for first aidRIT_DRSC.3: Models and tools to assure prompt response after emergencyRIT_DRSC.4: Models and tools to handle valuable data for prevention and forecast

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    RIT_DRSC.1: Multi-actor collaboration platforms for emergency

    The development of multi-actor collaboration platforms can assure the management and coordination of goods and information flows to enhance collaboration between parties and inventory systems. Multi-actor platforms, supported by a resilient communication infrastructure, can facilitate information sharing on the status of the emergency in terms of location of people in trouble, location of goods and resources for first aid in real time. Moreover, these platforms can manage donations, increase visibility and integrate all the actors involved (i.e. governments, aid agencies, private companies, donors, military, NGOs) who get more accurate information. The use and integration of information derived from different systems can help the management of inventory and resources, transport and load consolidation; this helps to organise the delivery of goods for first aid and the reconstruction phase individualizing which is the country or organization with the right resources to ship straight away to the site of the disaster. The resources to be shared are both goods and technical staff able to support people during an emergency and organise the first aid. Integration of autonomous systems is also necessary to assure delivery of goods under bad conditions. It is necessary that this kind of platform also supports collaboration with commercial supply chains to organise the activities in a coordinated way when responding to disasters. Finally, these multi-actor collaboration platforms could be also used and enhanced in the preparedness phase (e.g. risk assessment, training and skills development), not only in the response or recovery phases.

    RIT_DRSC.2: Crowd-help open platform for first aid

    A crowd-help open platform for first aid could enable citizens to share information in real time, help to create digital volunteer networks and to detect the actual needs of the affected populations which in turn helps to mitigate the influx of unsolicited donations. This platform could promote horizontal collaboration during an emergency. Citizens could be connected to the platform, through their smart devices to share not only their position, and instant information on needs and their health but also to receive information on how to behave when an unexpected problem arises, how to reach the nearest secure place or other information about changing environmental conditions. The use of mobile devices to communicate in a peer-to-peer way through collaborative platforms is a must to ensure the possibility of reaching any people anywhere. Moreover, this kind of platform could facilitate the process of managing donations, ideas and solutions as well as helping governments and NGOs to implement fast solutions not only during the immediate response but also during reconstruction. The crowd help open platform could also be used to train citizens and prepare them to deal with possible future emergency situations creating digital volunteer networks. It would also provide virtual courses to improve the skills of the volunteers and the professional staff who always have to be prepared to support population wherever necessary. However, verification/moderation mechanisms or technologies (e.g. artificial intelligence and machine learning techniques) need to be implemented to avoid fake content.

    RIT_DRSC.3: Models and tools to assure prompt response after emergency

    Every disaster requires the configuration of agile/responsive supply chains, planning standards in advance to overcome cultural differences. This could be enhanced by models and tools to ensure a prompt response after an emergency, such as the adoption of different technologies to accelerate the re-building phase incorporating disaster risk