IfM Review Issue 11 - Autumn/Winter 2019 by Institute for Manufacturing (IfM)

AUTUMN/WINTER 2019 | Issue 11

Manufacturing Institute for

REVIEW

Strategic approaches to digitalisation a The opportunities and challenges of the digital revolution a Driving sustained competitive advantage through technology a Low-cost digital approaches for small-scale manufacturing a Case studies revealing strategies for gaining value from digital technologies a Engaging with customers: combining digital, physical and social a Targeting the full value of digital disruption

INSTITUTE FOR MANUFACTURING (IfM) The IfM is part of the University of Cambridgeâ&#x20AC;&#x2122;s Department of Engineering. With a focus on manufacturing industries, the IfM creates, develops and deploys new insights into management, technology and policy. We strive to be the partner of choice for businesses and policy-makers, as they enhance manufacturing processes, systems and supply chains to deliver sustainable economic growth through productivity and innovation. IfM EDUCATION & CONSULTANCY SERVICES LIMITED (IfM ECS) IfM ECS is owned by the University of Cambridge. It transfers to industry the new ideas and approaches developed by researchers at the IfM. Its profits are gifted to the University to fund future research activities.

Cover image: Cover image: ÂŠ Dr Alexandra Brintup The image shows links representing supply relationships between companies in the global automotive industry, which is composed of 18,000 suppliers. Nodes are colour-coded according to the sub-communities in the network they belong to (nodes that are connected more with one another than to the rest of the network).

Contents 6

Responding to the changing face of global industry

Five steps to digital transformation

Driving competitive advantage through transformative technologies

Blockchain: Boosting productivity, traceability and customer experience

Helping SMEs towards digitalisation

Do you really know what you’re eating? Traceability in food supply chains

Customer experience: Connecting the digital, physical and social

The power of Artificial Intelligence

Using digital twins to manage assets and infrastructure

What’s coming next? Targeting value from the second wave of digital disruption

Editor: Sarah Wightman Email: sew63@cam.ac.uk Editorial advisory board: Dr Ronan Daly, Professor Duncan McFarlane, Professor Tim Minshall, Dr Eoin O’Sullivan, Dr Sebastian Pattinson, Dr Robert Phaal Dr Jag Srai, Dr Chander Velu, Kate Willsher. With thanks to Sarah Fell for content contributions.

IfM Review is published twice a year. Sign up to receive a copy by email and to hear about other IfM news at: www.ifm.eng.cam.ac.uk/research/ifm-review

Copyright © University of Cambridge Institute for Manufacturing. The content of the Institute for Manufacturing Review, with the exception of images and illustrations, is made available for non-commercial re-use in another work under the terms of the Creative Commons AttributionNon-Commercial-Share-Alike Licence, subject to acknowledgement of the original authors, the title of the work and the University of Cambridge Institute for Manufacturing.

ISSUE 11 | P1

Strategic approaches to digitalisation Welcome to Issue 11 of the IfM Review, in which we consider how digitalisation is changing manufacturing and how organisations can best develop strategies to respond. At the IfM, across our activities in research and practice, we are working closely with industry and governments in a variety of ways to build an understanding of the impact and the potential opportunities of digitalisation, often discussed under the broad heading of the ‘Fourth Industrial Revolution’. In 2016, we published Issue 6 of the Review with a focus on digital manufacturing. While many of the themes remain the same three years later (such as dealing with uncertainty, skills issues for the digital age, the impact of disruptors, and how extract value from data and digital systems, to name but a few), much has also evolved. Across different sectors and countries, many more initiatives have been tested, case studies made visible, and insights gathered. While the picture is still an embryonic one for many aspects of digitalisation in manufacturing, nevertheless more information is available which reveals the nature of the risks and the benefits, the lessons learned from adoption in different contexts, and hence provides support for better decision-making. In Issue 11, we feature a range of articles considering strategic approaches to digitalisation. For decision-makers in companies and in policymaking, it is crucial to develop digital initiatives and invest in transformative technologies not for their own sake, but because they directly support strategic objectives. But what does this look like in practice?

P2 | ISSUE 11

An article by Dr Carlos LópezGómez and Dr David Leal-Ayala from the IfM’s Policy Links Unit considers different opportunities and barriers to capturing value from digitalisation, as well as strategies to mitigate the barriers (page 6). Dr Diana Khripko from IfM Education & Consultancy Services then explains how different IfM tools and approaches are being used by companies at different stages of the digital journey, organised into a ‘Five Step’ framework (page 9). Taking a supply chains perspective, Dr Jag Srai and Dr Paul Christodoulou describe how work with industrial partners in the IfM’s Digital Supply Chains Consortium is shaping thinking on how to drive competitive advantage through digital technologies, and taking decisions on incremental versus radical initiatives (page 11). Professor Duncan McFarlane provides an update (page 17) on ‘Digital Manufacturing on a Shoestring’, an ambitious project seeking to develop lowcost digital solutions for SME manufacturers. Project momentum is gathering apace, and beginning to demonstrate how alternative options can enable SMEs to tap into the benefits of technologies without a hefty price tag. A range of insightful case studies emerging from IfM research adds strength and depth to the growing knowledge around successful approaches to implementing new technologies. These include a pilot project led by Dr Veronica Martinez

to trial blockchain at Caterpillar (page 14); an example in the food sector on improved transparency and traceability with AMT Fruit by Dr Mukesh Kumar and Rob Glew (page 21); studies on AI and supply chain analytics by Dr Alexandra Brintup (page 27); and research using digital twins to manage assets and infrastructure by Dr Ajith Parlikad (page 30). Digital technologies are also transforming the ways in which companies can interact with their customers. We share insights from research by Dr Mohamed Zaki (page 24) on connecting the digital, physical and social spaces of customer experience. We round off with an article asking what could happen next in the digitalisation revolution (page 33). Dr Chander Velu draws on his research into how different sectors have been disrupted, and where new opportunities may lie, to consider what the impact might be of a ‘second wave’ of digital disruption. We very much hope you will find the insights in this issue interesting and valuable. We always welcome you to share your thoughts and encourage you to keep in touch. Best wishes,

Tim Minshall Dr John C Taylor Professor of Innovation, & Head of the Institute for Manufacturing

IfM news

IfM Briefings events bring together leading thinkers We’re delighted to have launched the new ‘IfM Briefings’ series, which provides thought-provoking, short events which each focus on a specific topic, bringing together expertise to address common challenges in manufacturing. Our first event was ‘Innovation for Food Security and Sustainability’, and took place on 25th June at The Crystal in London, co-located with the Food Tech Matters conference, with an audience of stakeholders from across the food sector, including industry practitioners, policymakers and researchers. Talks from Tim Minshall, Dominic Oughton, Steve Evans, Gary Punter, Mukesh Kumar and Jag Srai considered how companies in the food sector can innovate effectively, harness technology, and implement change for sustainability, with examples and case studies from industry, and a panel discussion. September’s Briefing on ‘Developing Industrial Capabilities’ welcomed a large audience to the IfM, and we were delighted to host leading expert Professor David Teece as our keynote speaker. Teece explained his framework of ‘dynamic capabilities’, explaining how organisations need to build the capacity to adapt to change and deal with uncertainty. Tim Minshall’s talk then related this concept of dynamic capabilities to a familiar context, in the Cambridge innovation cluster. Insights into industrial case studies were then provided by Paul Christodoulou and Frank Wagner.

Insect protein company wins Open Innovation Forum pitching competition The Open Innovation Forum pitching event in June provided a platform for six entrepreneurial ventures in the food sector to pitch to a panel of ‘dragons’ and an audience of senior executives from over 20 multinationals. The winner from among the finalists was Protifarm, a Dutch company producing sustainable ingredients for the food industry using alternative protein from food-grade farmed insects. Pitching sessions are regularly organised by the OI Forum to provide an opportunity for innovators and technology spin-outs, start-ups and SMEs to pitch their ideas or business to some of the world’s largest food, drink and FMCG companies.

Visit www.ifm.eng.cam.ac.uk/events/ifm-briefings for information on upcoming Briefings.

Policy Links at GMIS On 10th July, David Leal-Ayala of IfM ECS’s Policy Links Unit delivered a keynote talk at the Global Manufacturing and Industrialisation Summit (GMIS) in Yekaterinburg, Russia, presenting the headline findings of a new report on the Safety and Security Dimensions of Industry 4.0. GMIS, a joint initiative by the United Arab Emirates and the United Nations Industrial Development Organization (UNIDO), is a platform that presents the manufacturing sector with an opportunity to contribute towards global good. On behalf of the Lloyd’s Register Foundation (LRF), GMIS commissioned Policy Links to explore the safety and security implications of 4IR technologies based on a review of the latest international evidence. The report can be found at bit.ly/2OOG1W5

Primary Engineer’s Celebration Event There was a buzzing atmosphere at the IfM on 20th June as we hosted Primary Engineer’s Celebration Event with 60 children from local primary schools. The budding engineers had worked in teams to build vehicles at their schools, which they brought with them to test and demonstrate to the judges in a competition against other teams. Kate Willsher and Kimberley Page from ECS were involved with judging entries for their creativity and research. There were plenty of inventive designs on show, and fantastic enthusiasm all round.

ISSUE 11 | P3

IfM news Cambridge International Manufacturing Symposium

Executive and Professional Development Executive and Professional Development activity in IfM ECS has continued to grow and develop apace. Building on our six year, award-winning partnership with Atos, we are continuing to evolve the successful ‘GOLD’ programme for technology leaders, and we are also introducing a new programme for more junior talent at Atos called FUEL. The EPD team also delivered a new week-long Cambridge module as part of an IIT Kharagpur Leadership programme for senior Indian academics, as well as a series of ‘Ideas in Practice’ workshops for Chinese Summer School groups, and welcoming back students studying at UNIST in Korea for three days as part of their international component of their Management of Technology Masters programme.

‘Shaping the future of global manufacturing supply networks’ was the theme for the 23rd CIM Symposium, held on 26-27th September in Cambridge. The packed agenda focused on how industry is delivering sustainable value for producers and consumers through digital platforms. The Symposium brings together academic researchers with industry practitioners to benefit from cross-fertilisation of ideas and case studies. This year’s industry speakers covered topics including the transformation of an entire multi-tier supply network (Haydn Powell, Caterpillar); using end-to-end digitalisation to build customer loyalty (Per Berggren, IKEA); and developing e-commerce fulfilment systems for best-in-class customer experience (Maarten Tibosch, wehkamp.nl). Microsoft’s Sophie Velastegui provided insights into what the factory of the future might look like with AI, and inspiring talks covered global operations optimisation (Frank Wagner, formerly Electrolux), and supply chain transformation (Biswaranjan Sen, Unilever). On day two, academic keynotes were provided by Professor Geoff Parker, internationally renowned expert on digital platforms; and Professor Lenny Koh on designing and manufacturing for sustainability. Dr Jag Srai, Head of the Centre for International Manufacturing (CIM), provided updates on IfM’s work with the Digital Supply Chains Consortium, and CIM’s current research themes including on digitalisation projects in supply chains. Interviews with speakers can be found at bit.ly/2oJJSZY

Babbage Forum convenes world experts to discuss industrial policy The fifth Babbage Symposium at Madingley Hall on 24-25th September gathered distinguished thinkers from across economics, engineering and management disciplines to develop new insights with the potential to underpin industrial policies for economic competitiveness and growth. The unique forum is convened by Professor Sir Mike Gregory, former Head of the IfM, with the IfM’s Policy Links Unit and the Centre for Science, Technology, Innovation & Policy. The agenda for the annual Symposium is informed by a series of smaller seminars through the year, at which policy practitioners and intergovernmental organisations meet to discuss skills, policy principles and policy challenges. The Symposium included input from Lord David Sainsbury, Chancellor of the University, who presented on his theory of production capability for economic growth.

P4 | ISSUE 11

MAKEathon A three day weekend event (19-21st of July) marked the launch of the first MAKEathon in Cambridge as part of the EIT Food MAKEit project led by Dr Shima Barakat and Dr Letizia Mortara from the IfM. MAKE-it! is a 3-year project that aims to develop an infrastructure to enable innovation and entrepreneurship in the food sector through co-creation between industry, maker spaces and stakeholders. This MAKEthon focused on creating new objects that disrupt our everyday routines and practices around sugar consumption.

IfM Postdoctoral Awards 2019 This year we introduced a new IfM Postdoctoral Awards Scheme, and are pleased to be the first place in the University to take forward such a scheme. Postdocs have sometimes been called the “invisible university” and our aim is to make their contribution more visible and help show appreciation for the achievements of postdocs at the IfM.

Cambridge Service Alliance Industry Day CSA hosted its annual Industry Day on 16th October, at which keynote speakers from some of the world’s leading companies shared their insights into the challenges and opportunities of developing digitally-enabled service businesses. The audience heard from Ashish Gupta, Corporate VicePresident, Head of EMEA at HCL Technologies, on how companies are changing their business models to achieve competitive advantage through digitalisation. Graham Budd, President and COO of Cambridge success story Arm, discussed the ‘Fifth Wave of Computing’ resulting from the convergence of three technologies: IoT, AI and 5G. Sheldon Hee, General Manager UK and Ireland, Singapore Airlines, described the customer-led digital transformation programme undertaken by his firm over the last seven years. A different perspective was provided by Alex Bazin, Managing Director of FLEC, a digital start-up joint venture with DHL which has set up a new platform-based business to help logistics firms recruit staff who want to work flexibly. Dr Mohamed Zaki, CSA’s Deputy Director, concluded the talks by explaining how the research he is leading applies machine learning to the language customers use, to develop actionable insights about the customer experience.

Vice Chancellor Award for Societal Impact and Public Engagement On 14 October, the ‘Open-Seneca’ team won the Vice Chancellor Award for Societal Impact and Public Engagement in the ‘Collaboration’ category. A team of six students, including IfM’s Sebastian Horstmann and Lorena Gordillo Dagallier are working on this project to establish air quality sensing networks on the basis of co-creation and citizen science in Nairobi and Buenos Aires this year.

We asked IfM colleagues to nominate postdocs from among research assistants, research associates, senior research associates and principal research associates, who have demonstrated excellence in (i) research, (ii) teaching or (iii) academic citizenship. We are delighted to confirm that the winners for 2019 are: For Excellence in Teaching: Dr Daniel Summerbell For Excellence in Research: Dr Thomas Bohné and Dr Lili Jia For Excellence in Academic Citizenship: Dr Niamh Fox, Dr Katharina Greve and Dr Curie Park

Sustainable Value Innovation course in Norway Doroteya Vladimirova and Ian Bamford (CIS) led a two-day course on Sustainable Value Innovation at the Norwegian Centre of Expertise iKuben in Molde, Norway. The NCE iKuben is a cross-industrial cluster that facilitates business development, with a special focus on digitalisation, sustainability and new business models for the Norwegian industry. Delegates from sixteen company members of the cluster joined this intensive cross-sector workshop. Three of the participating companies – Brunvoll, Cinderella Eco and Glamox – put forward a challenge from their company as a real-world case study, which were examined by participants in workshops through the lenses of the Value Explorer and the Sustainable Value Analysis tools developed by the Centre for Industrial Sustainability at the IfM. The participants left with several ‘a-ha’ experiences and new ideas and proposals they could take back to their businesses.

ISSUE 11 | P5

Responding to the changing face of global industry The opportunities from digital manufacturing are real – but so are the challenges The opportunities presented by technological transformation are significant, but the obstacles are challenging, and the threat of disruption from new types of competitors with innovative business models is high. How can manufacturers respond to the changing landscape, and how can policymakers best support organisations towards growth and productivity? Dr Carlos López-Gómez and Dr David Leal-Ayala of the IfM’s Policy Links Unit provide an overview of the unfolding digital revolution, and share insights from their work with governments and multinational organisations… Emerging technologies are radically reshaping manufacturing. Companies are changing how they make products, the business models they adopt, how they interact with suppliers and customers, and even how they innovate. There is new potential for enhancing productivity, for stimulating innovation, and for generating products and services which create new demand and markets. In manufacturing, digital transformation goes far beyond automation on the factory floor, also enabling faster research and development, closer integration across supply chains, and increased customisation of products and services. New technologies offer the potential to use resources more efficiently, improve the safety of production processes, and address supply constraints. The extent of the potential changes heralded by these opportunities (and competitive threats) points to the likely need for a paradigm shift in companies’ manufacturing strategies.

P6 | ISSUE 11

At governmental level, the digital revolution in manufacturing poses opportunities and challenges in key policy areas such as employment, productivity, competitiveness, and sustainability. Individual digital technologies are each likely to have a significant impact on their own, but it is their convergence and integration that makes them so disruptive. Although there is no consensus on its potential impact, estimates from the World Economic Forum suggest digitalisation could create US$100 trillion of value to industry and society over the next decade, and according to the European Commission, European industry could gain €110 billion per year from digitalisation. The digital revolution is expected to change what skills are required from the future workforce, causing significant disruptions in the labour market. High numbers of jobs are likely to be lost, displaced, or created, and while it is

difficult to put numbers against these, high estimates reflect a common perception about the large-scale impact of digitalisation worldwide1,2. There is significant variation between international studies in predicted impact on jobs due to automation: figures go from the creation of over 100 million jobs to the loss of over 200 million. Digitalisation also brings important concerns about the cyber security of industrial systems. It also threatens to disrupt business models in important sectors of the economy, and raises increased threat from new breeds of competitors gaining market share. Data and privacy are increasing concerns for firms and for consumers, with difficult questions around the ownership of the immeasurable volumes of data being generated. Fundamentally, the digital transformation of manufacturing increasingly necessitates companies, industries and countries to reassess

whether their manufacturing systems are ready to compete effectively given the potentially disruptive changes brought about by digitalisation, in the context of increasingly interconnected global value networks3.

Opportunities for value capture from digital manufacturing We have identified four manufacturing ‘dimensions’ of opportunities, corresponding to different types of innovation: a Product / service innovation – offering new and more functional products and services, and new business models that create value from digital data and capabilities. a Process innovation – achieving higher levels of factory efficiency and more flexible production processes driven by vertical digital integration.

What is the ‘digitalisation of manufacturing’? By Dr Eoin O’Sullivan, Director of the IfM’s Centre for Science, Technology & Innovation Policy (CSTI) The ‘digitalisation of manufacturing’ is also commonly termed the ‘fourth industrial revolution’ (or 4IR). It refers to the use of digital technologies, data and applications to deliver advancements in manufacturing-related operations (including the broader value chain of manufacturing activities), to enhance the performance of manufactured products (and related services) in both established and emerging sectors. The family of technologies underpinning digitalisation includes: cloud computing; advanced sensors; high-performance computing; advanced automated and autonomous systems; robotics; artificial intelligence; machine learning; augmented/virtual reality; blockchain; big data; and digital fabrication (including 3D printing), among others. The potential for improved productivity and competitiveness is emerging through the convergence of these technologies into applications and solutions, through: a Improved sensing/interacting with the physical world a Enhanced organisation/sharing/analysis of data a Better connectivity/networking/control (of industrial-innovation activities)

a Supply chain innovation – more integrated and optimised supply chain capabilities driven by horizontal digital integration. a Product / service design and delivery – superior understanding of demand, more customer-led design and delivery using digital platforms, and higher levels of customer satisfaction. The multiplicity of opportunities for value capture is taking different forms in distinct industrial sectors and types of firms. Figure 1 illustrates examples of such opportunities across the four manufacturing dimensions identified.

Examples of value capture opportunity

Organisation, sharing and analysis of data

Sensing and integrating with material / physical world

Connectivity, networking, control

The term ‘Industry 4.0’ has gained widespread international currency, including by governments, global companies, and the media. The term originates from the strategic initiative of the German government’s High-Tech Strategy (‘Industrie 4.0’). This anticipates the impact of a fourth industrial revolution whereby cyber-physical systems, the Internet of Things, and big data will more effectively connect and integrate manufacturing systems.

Product / service innovation

Process innovation

Supply chain innovation

Product / service delivery

• End-to-end solutions. • Product service customisation. • New data services. • Adding digital features & intelligence to existing products.

• Improved planning and budgeting. • Increased resource efficiency (energy & materials). • Improved equipment reliability, integrity & usage. • Spare parts inventory reduction. • Higher maintenance efficiency. • Maximise quality & minimise production variability.

• Improved collaboration/ integration between suppliers and ecosystem. • Improved forecasting. • Track & trace supply. • Reduced inventory costs through dynamic inventory visibility / warehouse management. • Reduced inbound and outbound logistics costs.

• Data on customer need for business intelligence. • Increased customer access (e.g. self-services, online). • Dynamic / flexible pricing. • Integration of sales channels. • Increased customer satisfaction through better design. • Reduced time to market.

Figure 1: Examples of generic value capture opportunities enabled by digital manufacturing4 World Economic Forum (2016). Digital Transformation of Industries: Societal Impacts. The UK Made Smarter review, for example, estimates a potential net gain of 175,000 jobs throughout the UK economy over the next decade. Global value networks can be defined as complex systems of interconnected (and geographically dispersed) firms that deliver value to end users, operating across the full range of business activities. Source: Adapted from Srai, J. and Christodoulou, P. (2014). Capturing Value from Global Networks. Institute for Manufacturing (IfM). 4 López-Gómez, C.E, Leal-Ayala, D.R., Palladino, M. and O’Sullivan, E. (2017). Emerging trends in global advanced manufacturing: challenges, opportunities and policy responses. United Nations Industrial Development Organisation / Policy Links / IfM. 1

ISSUE 11 | P7

User industries

Development

Design

Supply management

Production

Distribution

After-sales service

Barriers to generation

Barriers to diffusion

• Under investment in R&D • Uncertainty of applications • Weak connections between industry and academia • Fear of helping competitors if new knowledge can not be patented

• Lack of digital norms, standards and certifications • Limited awareness among business communities • Concerns around data ownership, privacy and cyber security • Infrastructure gaps

Barriers to deployment • Low ‘absorptive capacity’, especially SMEs • Legacy systems and resistance to change • Lack of managerial and technical skills • Lack of leadership to recognise current processes

Digital technologies

Research

Figure 2: Barriers to generation, diffusion and deployment of innovation. Source: Policy Links Unit/Centre for Science, Technology & Innovation Policy, IfM

Barriers to value capture for firms However, successful deployment of digital technologies is not an easy task. In our research we have identified several types of barriers to technology deployment: a Individual people barriers: Including the gaps in the skills and competencies of workers, lack of knowledge and awareness of decision-makers, insufficient problem-solving capabilities, aversion to risk and/or change. a Organisational barriers: Including the lack of a clear plan or roadmap for identifying technologies which help to deliver business objectives, and for implementation. Organisational culture, risk aversion, lack of innovation capability, or short-term focus can be significant obstacles.

The challenges described here are just a small sample of the many difficulties that could prevent manufacturing sectors and firms from capturing value from new industrial digitalisation trends. Another helpful way of classifying the range of challenges and barriers to value capture is by framing the discussion in terms of the three fundamental stages of innovation: knowledge generation, diffusion and deployment, as shown in Figure 2.

Strategies for mitigating the barriers So how can policymakers and firms identify and mitigate barriers, and open up the opportunities presented by digitalisation in manufacturing? Our research shows that the set of barriers can vary substantially between different regions, sectors, firms, and technology applications. There are no one-size-fits-all solutions. We are working to develop and refine a framework intended to help the development of policy initiatives to support innovation and technological development. The framework can be used to evaluate which barriers are present in a given technology deployment setting, and to identify how to mitigate these barriers. For example, mitigating strategies initiated by policymakers to address ‘organisational barriers’ (as described above), might include: a Increasing strategic awareness about digitalisation trends.

a Technical barriers: Such as the lack of availability of appropriate existing solutions, and lack of technical competency for implementing new applications, as well as difficulty integrating new technologies with existing systems.

a Providing frameworks for changing business models.

a Market barriers: Including the difficulty of creating awareness and demonstrating functionality of new solutions among industrial users, or resistance among supply chain partners; or market readiness of new technologies.

a Supporting system integration.

a Supporting organisational orientation towards the problem, not the solution. a Supporting the elaboration and dynamic improvement of roadmaps. a Diagnostics related to a specific firm’s contingencies. a Using demonstrative cases for supporting cultural change. a Giving support for improving innovation capabilities.

Digital manufacturing technologies can have a cross-cutting and disruptive effect across manufacturing sectors. By understanding the opportunities, identifying the barriers to adoption and planning mitigation strategies, both policymakers and organisations can move towards exploiting the huge potential value of digital transformation.

a Economic/financial barriers: Such as uncertain or weak wider economic conditions, and limited organisational resources or willingness to invest. a Regulatory/policy barriers: Including the lack of innovation policies to support firms, heavy regulation in some sectors, or costly audits/certification requirements which make it harder to reconfigure existing systems.

P8 | ISSUE 11

Dr Carlos LópezGómez

Dr David Leal-Ayala

Five steps to digital transformation

IfM Education & Consultancy Services (ECS) works with organisations to transfer knowledge and frameworks from research into practice. Dr Diana Khripko explains how different IfM tools and approaches are being used by companies at different stages of the digital journey, organised into a ‘Five Step’ framework. In navigating the multiple challenges of digital transformation, many companies are struggling to chart a path into the unknown, and to gain the knowledge and confidence to identify which opportunities can deliver long-term value. A clear strategic approach is essential for the success of the digital transformation process, and for helping to unpick the complexity of the options available. Based on our deep experience in supporting organisations from multinationals to SMEs, across a wide variety of sectors, IfM ECS has pulled together our frameworks and tools which can help signpost the digital transformation journey, and ensure initiatives are aligned with business strategy. Our Five Step framework aligns multiple areas of digital transformation, helping organisations to approach decisions systematically. Depending on where an organisation is now, and what the strategic needs for digital transformation are, the Five Steps can be tailored accordingly and appropriate tools/methods selected to suit unique needs. The framework is note intended to be prescriptive or linear, as digital transformation is typically an ongoing process, given the continuing pace of digital technology development.

The Five Steps 1

Explore the potential: Explore where and how digital technologies in your sector are currently deployed, what their readiness level is, and what the most useful technologies are for your organisation.

Understand the value: Having this base knowledge of the different digital technologies, the following step is to understand the value proposition of ‘digital’ within your specific ecosystem.

Define where to go: These two preparation phases lead to the definition of ‘what digital vision looks like for your organisation’. Starting with defining the ideal end point, the strategic direction can be established. As with all strategyrelated measures, it will involve or impact several interest groups, so agreeing a clear end point helps reach commitment from all interested parties and reduce the barriers and risks.

Identify pathways: Consider, plan and map your digital journey with key stakeholders across your organisation to create clarity and buy-in for the next steps you need to take. Different transformation pathways can lead towards the envisioned future. Find your priority pathway that addresses key aspects of your strategy including external drivers, internal drivers and capabilities to arrive at a a blueprint for your digital transformation and select solutions, projects and technologies that will deliver the most value to your organisation.

Implement projects: To achieve your digital future, you might need to develop the capabilities and decide whether you will develop the digital expertise in-house or source it from a third party.

ISSUE 11 | P9

IfM Tools and Approaches

EXPLORE THE POTENTIAL

Discover where and how technology can help • Learn from examples of digital implementations relevant to your business.

• Education and training on digital technologies

• Raise awareness of existing technologies and their readiness level.

• Case studies

• Evaluate the technologies that are currently deployed in your sector.

• White papers

• Create a basic narrative setting out when current and emerging technologies could be most useful.

• Reports

• Develop confidence and understanding in what your digital future could look like. 2

• Value mapping tool

UNDERSTAND THE VALUE

• Business ecosystem mapping • Service assessment

Explore and create a compelling business case • Identify ways to improve and create new value for your customers by working innovatively with organisations in your business ecosystem. • Assess the sustainability (triple bottom line) model for new technology adoption or markets. • Assess digital capabilities across your organisation, analyse performance and highlight areas for improvement. • Identify, design and prioritise potential innovations in your production and business processes 3

• Portfolio prioritisation • Industrial resilience audit • Business model innovation

• Scenarios

• Achieve consensus as an organisation about where you are going, developing a crossstakeholder aligned vision of your digital future.

• Visioning • Automation Assessment • End-to-End Supply Chain Modelling and Simulation

• Explore potential digital scenarios for your sector. • Assess your digital capability.

• E-Procurement and E-Commerce

IDENTIFY PATHWAYS

Map out where you are now and where you want to get to • Consider, plan and map your digital journey with key stakeholders across your organisation to create clarity and buy-in for the next steps you need to take. • Address key aspects of your strategy including external drivers, internal drivers and capabilities to arrive at a blueprint for your digital transformation. • Select solutions, projects and technologies that will deliver the most value to your organisation. 5

• Creativity and innovation in digital manufacturing

DEFINE WHERE TO GO

Create your organisation’s digital vision

• Information disruption

• Digital transformation strategy • Digital supply chain scenarios • Roadmapping • Digital solutions prioritisation

• Make vs buy

IMPLEMENT PROJECTS

• Designing services

Develop the capabilities to achieve your digital vision

• IP strategy

• Decide whether you will develop the digital expertise in-house or source it from a third party.

• Professional development courses

• Consider what, when and how to automate your operations.

• Roadmapping implementation planning

• Develop an IP strategy that protects your digital investments. • Use professional development courses to build the right capabilities across your organisation.

To find out more about the tools and approaches, please contact Dr Diana Khripko, dk530@cam.ac.uk

P10 | ISSUE 11

Dr Diana Khripko

Driving competitive advantage through transformative technologies

The IfM’s Centre for International Manufacturing has been working with a group of international manufacturing companies to develop strategic approaches to digitalisation across production and supply chains, focused on driving competitive advantage. Dr Jag Srai and Dr Paul Christodoulou provide insights into the work of this group—the Digital Supply Chains Consortium—including developing the decision criteria for implementing incremental or radical transformations… As the industrial landscape is transformed by digital technologies, abundant opportunities are emerging for organisations. But the ‘right’ path forward is not clearly signposted, may be untrodden by others, and is fraught with risk. For organisational decision-makers, on the one hand the range of technology options can be so overwhelming as to result in paralysis, and on the other hand there can be perceived urgency to implement change across several operating areas of the business at once, in a rush to avoid being left behind by fast-moving competitors. So how can decision-makers get to grips with where their priorities should lie, and set a strategic direction focused on delivering improved business performance and customer experience?

Incremental or radical transformation? Priorities for digitalisation are unique to each company, depending on their sector, strategic objectives, and existing capabilities. In our research into the transformation programmes being implemented by manufacturing firms, two distinct types of digitalisation project emerge: incremental and radical. For most organisations, the initial forays into digitalisation are typically cautious – small-scale ‘pilots’ and low risk. They may involve implementation of relatively localised applications, maybe in one geographic location, or in one limited operational area. Perhaps they will follow in the footsteps of external partners or competitors who have implemented similar applications with evidence of improvement. These projects are valuable in helping to identify attractive opportunities. They also enable a test-bed approach, trying

something out without too hefty an investment or too great an uncertainty, identifying and ironing out issues. These then form ‘use cases’, which can be used to demonstrate return on investment. For senior executives, these are the most obvious development projects to back – with scope to demonstrate their ability to deliver successful projects and to be more confident from the outset that the results will be good. Projects with initially limited scope can then be extended across sites or operating areas. Incremental progress is made towards digitalisation, risk is managed, and the business case is strengthened. But what about taking a more radical approach? And why would seeking out more difficult projects, with associated higher risk and uncertainty, be an appealing path? Difficult, radical projects are more experimental, usually requiring higher investment and carrying higher risk of

ISSUE 11 | P11

things going wrong. But as a result, they also provide greater opportunities to strike out ahead of the competition. This type of implementation is where pioneering companies like Amazon and Uber thrive. And when they get it right, the results can be much bigger than if they had stuck within the ‘safer’ boundaries of easier, incremental development. Radical digitalisation projects offer the potential to create a sustained competitive advantage by doing something which is difficult for competitors to replicate.

Choosing priority areas for digital initiatives So what evidence is there about the projects already being undertaken? At the Centre for International Manufacturing in Cambridge, we have been working for the past three years with a Consortium of multinational companies to look at digital transformation of their manufacturing supply chains. We are guiding firms to think about the range of digitalisation options available to them, and to achieve this we have developed ten ‘Digital Transformation Scenarios’ spanning the end-to-end supply chain. This provides a starting point for considering the technologies that could be implemented.

Figure 1: Ten Digital Transformation Scenarios describing the strategic benefits of digital technologies. © Dr Jagjit Singh Srai, Centre for International Manufacturing, Institute for Manufacturing, University of Cambridge

Since developing the framework, we have analysed technology interventions of these manufacturers by partnering with each of our Consortium members, helping them to undertake an assessment of their current ‘digital maturity’ within each of the ten scenarios (see Figure 1). These assessments have enabled identification of particular digital applications being developed by our partner companies in each of the scenarios, and an articulation of the business benefits of those applications. These can be split into four broad areas: inbound, internal, outbound and endto-end. Crucially, in each of these areas, the focus must be on implementing technologies to deliver on clearly defined business needs and benefits.

Identifying uniqueness It is vital that each firm recognises its uniqueness and the need to chart its own route rather than simply following in the wake of others. This is the real nub of the issue: making appropriate decisions and identifying the firm’s unique priorities is a complex matter. But it is only by doing so that creating a sustained competitive advantage is possible.

P12 | ISSUE 11

Figure 2: Emerging hot spot combinations

From our assessments of digital maturity in the Consortium, we have been able to identify two important patterns. The first is that each company has its own combination of areas in which it is focusing its effort. These are determined by the firm’s business strategy and understanding where it can make the biggest improvements. As shown in Figure 2, Firm A’s combination of priorities, shown in green, is distinct from Firm B’s priorities, shown in blue. Secondly, we have seen the emergence of ‘hot spots’ where companies with similar product supply chain configurations are clustered around certain priority areas. For example, a business-to-consumer producer of household products is

likely to have a different focus from a manufacturer of industrial machinery, or a pharmaceuticals manufacturer. But even where sector clusters emerge, nevertheless each company will have different priorities depending on its current digital maturity and its unique business objectives.

Digital backbone and the value of data Both radical and incremental digitalisation projects will be more effective if underpinned with robust data foundations, constructed from well-developed digital platforms that can span and connect business areas and share data between locations and across supply chain partners. The real value lies in specific data relevant to a given manufacturing supply chain, so how can the data be meaningfully exploited?

Here the concept of the ‘digital backbone’ is valuable, referring to connected data and architecture across different business functions. Investing in one shared data infrastructure which supports numerous applications can be a much more efficient and cost effective approach than treating each application development separately with separate data infrastructures. Develop robust data architecture once, and it can be extended across the different applications.

IKEA’s route to digital transformation

The digital backbone itself becomes the interconnectedness, facilitating different systems across the business to be built on a common, connected platform. As part of our current research, we are working towards improved identification of where these interconnections may lie. This will help companies to think strategically about what applications a digital backbone needs to support within each unique company context. We have been developing a gamification app to identify such connections across digitalisation application projects, which we are refining by drawing on the real industrial experiences and challenges of Consortium members. The app helps to identify pairwise comparisons to provide a view of how closely different sub-elements of our ten scenarios model are connected, ultimately identifying opportunities to capitalise on these connections through informed design of the digital backbone. The most creative disruptors are capitalising on the power of connections, and looking for ways to enable radical digital transformation. Navigating successfully through the myriad of transformative technologies is challenging, but it involves avoiding paralysis through never ending pilots, instead seeking connections, combining incremental improvement with bolder strategic plays that support competitive advantage. Looking forward, the next phase of our research is focusing on understanding the barriers to implementing the more radical supply chain transformations that might underpin sustainable competitive advantage. Indications are that these barriers include prerequisite supply chain capabilities, digital skills and assets, and upstream/downstream connectivity: an expanded Consortium provides a valuable vehicle for testing these research concepts and also supporting members with their transformation programmes.

Per Berggren, Industrial Strategy Manager at IKEA Industry, has been working as part of the Institute for Manufacturing’s Digital Supply Chains Consortium. He shares his perspective on IKEA’s technological transformation strategy… We are running an extensive digitalisation programme at IKEA to introduce Industry 4.0 capabilities. Our journey has led us from exploration of technology options, through development, into piloting and now going into roll out across our 40 manufacturing plants. Digitalisation for us is about helping our customers, making it easier for them to buy from us, and making the interactions between shop floor and customers as smooth as possible. Our promise to our customers is to be a low-price retailer with creative products which improve everyday lives. As a business we serve mass consumer markets, and we want to grow our reach, and digitalisation can certainly help us to do both of these better. We have four key strategic objectives for our digitalisation programme. Our first objective is to improve the customer experience, reduce cost and friction, reach more people, and keep our prices low. Secondly, digitalisation brings more stable processes, which in turn bring improved quality service capability. Thirdly, digitalisation enables us to ‘meet’ customers in new ways – making sure we become more accessible and more relevant to customers. Fourthly, we have been considering digitalisation strategies across our supply chain, and how we can improve the flow of goods between supply chain partners as well as integration of systems. To create the most value from the potential of digital technologies we need to look across the supply chain at integrated solutions. This is a monster undertaking, but we have prioritised steps towards achieving it! Looking at digitalisation only in terms of operational improvements will provide limited advantage for a short period, maybe two to five years – mainly because a lot of companies are still struggling with introducing digital technologies. But to achieve a sustained advantage for a longer-term period, companies need to make more fundamental changes and re-engineer their business models.

This article draws on research by Dr Jag Srai, Dr Ettore Settanni and Dr Harri Lorentz, and on work from the Digital Supply Chain Consortium hosted by the Centre for International Manufacturing. To find out more about the work of the Consortium, please contact Dr Paul Christodoulou: pac46@cam.ac.uk Dr Jag Srai

Dr Paul Christodoulou

ISSUE 11 | P13

Blockchain Boosting productivity, traceability and customer experience in supply chains How can new technologies be tested to demonstrate effectiveness? IfM’s Dr Veronica Martinez, a University Lecturer in the Cambridge Service Alliance, explains how she collaborated with Caroline Burstall and Andrew Noblett at Caterpillar to develop a pilot project to show how blockchain could deliver significant supply chain benefits for the company. Since blockchain burst onto the scene in 2008, its evangelists have told us that – just like the internet – it will fundamentally change how we all live and work. And it clearly does have that potential. So far, blockchain has mainly been used for cryptocurrencies, with bitcoin the most wellknown example. But this digital technology is much more versatile and has a very broad set of potential uses across a range of sectors. It essentially enables traceable transactions to take place over a distributed database, with records that cannot be changed and are therefore highly secured.

P14 | ISSUE 11

Because blockchain is an open platform, companies can use it to build their own applications customised to their own needs and customers’ needs. Some are already considering how they can innovate parts of their business operations in the form of ‘private’ blockchains. Indeed, blockchain’s versatility means it has been attracting attention as a potentially valuable technology for supply chains. Its ability to handle secure and traceable transactions could strengthen trust amongst supply chain participants as they can keep track of shipments, deliveries and product quality during transport. Blockchain is one of the top technologies that will significantly change the way consumers and providers operate. US, China, Germany among others have placed blockchain at the centre of their industrial digital transformation.

Barriers to adoption Having a resilient, secure and traceable distributed database through which data – and payments – can be shared within and across organisations will be transformational. Firms are worrying about the consequences if they don’t get on board. So why are we not seeing a race to adopt it? One major hurdle is the cost of

implementation (particularly for those firms who have recently invested millions in state-of-the-art ERP systems) which currently outweighs its perceived but as yet unquantifiable benefits. Another is the sheer scale of the task needed to integrate it into existing company-wide systems and processes. On top of that, most firms lack blockchain expertise and think they need to bring in consultants to help them implement it. Some of these consultants are being a little overenthusiastic in their sales pitches which is resulting in even greater circumspection among their potential customers. Adopting expensive, one-sizefits-all solutions could be a mistake for an organisation, particularly if such solutions don’t integrate with existing systems. Even those firms that are convinced of the benefits are wary of embarking on an exercise which cedes control of the technology to a third party. Outsourcing is not only costly throughout the whole life of the implementation (making minor modifications in line with changes to the business quickly gets prohibitively expensive), it also prevents organisations from developing their ownership and understanding of the technology.

What is blockchain? Blockchain is a revolutionary digital technology that has so far been largely applied in the financial sector particularly in cryptocurrencies such as bitcoin and smart contracts, but has much wider potential application. Essentially, blockchain is a decentralized distributed database which appends records with timestamps. Information input into the blockchain cannot be changed, so trust amongst participants is solidified. This allows peer-to-peer transactions, and has four unique characteristics: (1) resilience, (2) safety, (3) traceability and (4) irreversibility. Other applications include services in supply chain management, insurance, digital knowledge management and e-commerce, land management, and marketspace among others.

Low-cost blockchain pilot with Caterpillar Our research group at the IfM has been working with Caterpillar, who were interested in exploring blockchain as a potential solution to address a business issue. One part of Caterpillar’s business sells a range of diesel and gas engines which tend to be customised to meet each customers’ needs. Managing these customer orders has remained a largely manual process over the years with modifications to the customer’s specification coming in through a variety of channels including phone, fax (yes really!) and email. These requests would then be checked by Caterpillar’s production team to make sure they were deliverable.

This back and forth process of specification and negotiation can last several days, involving six employees and, with information being stored in different formats, in different places by different people, and can be inefficient with plenty of potential to go wrong. Blockchain was identified as a possible way to streamline this process, making it more efficient while also preserving secure, accurate information. The technology’s characteristics matched the business needs, offering ‘traceability of transactions’ – tracking who, what and when an order was placed or modified. Furthermore, it secures ‘irreversibility’ of records, offering a safe bridge of ‘trust’ between the customers and suppliers. Caterpillar was interested in running a pilot as an initial exercise to explore and demonstrate

what blockchain can offer, without heavy time and cost investment. This presented us with an exciting opportunity. Could we build our own blockchain in such a way that Caterpillar could see what it is capable of and learn from the experience without having to make a huge organisational commitment to it? Our mission was to build and use blockchain to automate the interactions between the customer (demand) and the manufacturing site (supply). We wanted the customer to be able to place orders and make modifications easily, in other words to have a better customer experience. For Caterpillar, the aim was to harness the control and traceability that blockchain offers both to deliver that enhanced customer service while reducing the time and cost of providing it.

ISSUE 11 | P15

What we acheived:

65% of manual work 90% hours eliminated 48 hour or faster response time 50% saving on jobs

reduction in the time taken to process customer orders

Do-it-yourself blockchain The project had two key elements: programming the blockchain and simulating the business process. For the programming, we were starting with a blank sheet of paper. With no prior experience, our first task was to decide which technologies to use, bearing in mind that one of Caterpillar’s requirements was to keep everything as simple as possible so that its employees could learn how to do it themselves. We reviewed the options and picked the most basic: Hyperledger Composer for the back end (building the blockchain) and React for the user-interface. Both applications happen to be free. It took four of us (three students and myself) six weeks and a lot of coffee to learn how to do it (mainly from online videos) and to write and de-bug 5,000 lines of code. The other part of the process was to map the complexity of the existing system – identifying all the touch points between the firm and their customer and where the data was being stored – and to specify a more streamlined, blockchain-enabled approach. After much trial and error, we achieved our goal: a real-time method of sharing and managing data in a single record.

Greater trust from customers and other supply chain partners Less frustration for customers and account managers at Caterpillar Insight into new technology and its capabilities Opportunity to redeploy staff into more fulfilling roles

Achieving supply chain benefits Once we had our blockchain in place and had tested it with one of Caterpillar’s customers, we carried out a ‘before and after’ analysis to show what we had achieved. By automating the process, we had reduced the number of storage points from twenty to two, we had reduced the time taken to process a new order by two thirds and we had halved the number of people needed to carry out the task. And we had a very positive response from the customer who was now using a bespoke user-interface which we had co-designed with its procurement team. The final part of the project was to identify a number of potential blockchain developers (and evaluate their costs) who could work with Caterpillar to take this project forward.

What did we learn? Our research is the first to demonstrate that blockchain improves the efficiency of the processes involved in our pilot project: it reduces the number of operations, reduces the average time of orders in the system, reduces workload, shows traceability of orders and improves visibility to various supply chain participants. Moreover, we improved the overall customer experience. The pilot showed that it is possible to implement blockchain in-house at a small scale and manage its growth within your business in a way which starts to give you quantifiable benefits but without introducing massive disruption and cost. Of course, there were challenges along the way, but the benefit of this approach is that you are able to learn from those challenges, grow your own expertise in-house and develop the technology in a way that integrates with your existing systems and processes.

Caterpillar’s leads on this project are Andrew Noblett, Supply Chain Planning Engineer, and Caroline Burstall, Supply Chain Manager, Industrial Power System Division, Caterpillar Inc. Reference academic paper: Martinez, V., Zhao, M., Blujdea, C., Han, X., Neely, A. and Albores, P. (2019), “Blockchain-driven customer order management", International Journal of Operations & Production Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOPM-01-2019-0100

P16 | ISSUE 11

Dr Veronica Martinez, vm338@cam.ac.uk

Helping SMEs towards digitalisation

Small-scale manufacturing the smart way Since we first introduced ‘Digital Manufacturing on a Shoestring’ in IfM Review Issue 9, this major new project has been gathering pace to develop low-cost digital solutions for small to medium-sized enterprise (SME) manufacturers. Professor Duncan McFarlane, project lead and Head of the IfM’s Distributed Information and Automation Laboratory (DIAL), provides some updates on progress… ‘Digital Manufacturing on a Shoestring’ overview Digital technologies promise exciting new possibilities in manufacturing. There are many opportunities for improving productivity and efficiency, both on the factory floor and in the back office. All of these improvements can help manufacturers operate more efficiently, drive down costs and strengthen customer relationships. But there are major barriers for SME manufacturers looking to reap the benefits of digitalisation. Cost, complexity and the need for digital knowhow often make extensive digital transformation too difficult for small companies. Most efforts in the digital manufacturing space have been focused on large-

scale solutions for big companies. Such solutions typically require significant initial investment and ongoing operating costs, as well as a need for digital skills within the organisation. In addition, they may require upgrades of industrial computing and communication environments to support advanced technological solutions. Cost and disruption are high. This situation risks leaving SMEs behind, and a different model is needed to support them as a vital part of the manufacturing sector. ‘Digital Manufacturing on a Shoestring’ is an ambitious project seeking to break down these barriers for SMEs. Funded by the Engineering and Physical Sciences Research Council (EPSRC), our research team at the Institute for Manufacturing, University of Cambridge, is collaborating with researchers at the University of Nottingham and with SME manufacturers.

SMEs are looking for inexpensive and easy digital manufacturing solutions to specific problems. They typically haven’t got large specialised IT departments. So, as well as being low-cost, solutions need to be easy to use. Our aim is to enable these firms to harness the benefits of digitalisation without the excessive risk and cost of implementing systems designed for large companies.

The Shoestring project is investigating how existing and readily available digital technologies can be implemented on a low-cost basis to support growth and productivity in SMEs.

ISSUE 11 | P17

The Shoestring approach a Helping SMEs implement digital solutions to improve productivity a Solutions must be accessible, pragmatic, useful, affordable a Based on low-cost components a Accounting for regulations, safety, security a Engaging students and local IT community a Solutions are repeatable, reusable, integrable

We are working with a large number of SME manufacturers to identify requirements, and create a catalogue of customisable digital solutions, complying with regulatory, safety and security requirements. The solutions will be based on commercially available technologies for mobile computing, sensing and AI, identifying how these can be exploited, and tackling the issues associated with integrating these safely and securely into a small scale manufacturing environment. The project involves partners such as Raspberry Pi and Siemens, along with teams of developers. It also brings together researchers in industrial information and control systems, machining and automation, asset management and maintenance, and draws on interdisciplinary expertise from computer science, economics and data analytics. In direct partnership with industry, we are working closely with manufacturing networks including the Scottish Manufacturing Advisory Service (SMAS), Make UK and the Nottingham Manufacturing Network, with involvement from SME partner companies from the start.

P18 | ISSUE 11

Our approach The project has several phases, starting with understanding the needs and priorities of SMEs, before moving on to development, testing and pilots. Phase 1: Digital requirements assessment In the first project phase, we are spending time listening to SME manufacturers, to understand their needs and to identify common requirements between companies. This is happening through requirements gathering workshops around the UK and in other countries. In the workshops, SMEs are being asked to discuss their priority business areas for digitalisation and provide scores to rank their operational requirements. We are also conducting onsite visits to partner SMEs to evaluate digitalisation â&#x20AC;&#x2DC;readinessâ&#x20AC;&#x2122; and needs. From these activities, the research team is classifying SME challenges and priorities, and creating a list of top priority requirements for proposed low-cost digital solutions.

Phase 2. Solutions development Requirements gathered in phase 1 are being fed into development of lowcost digital options. This stage involves designing, modelling and developing architectures for low-cost component integration and infrastructure options.

evaluation, using SME industrial scenarios, will be done in labs at Cambridge and Nottingham. This will involve statistical assessments of prototype operations. Following this, there will be pilot studies onsite at partner SMEs, with the creation of case studies of early solutions.

The idea is to create ‘building blocks’ of existing low-cost technologies which can be connected into integrated digital architectures. Solutions incorporate consumer-grade components (such as Raspberry Pis) and low-cost sensors (such as bluetooth low energy beacons, offthe-shelf sensors, OS sensors and motion cameras).

Phase 4: Incremental integration The team will identify how solutions can be implemented and integrated successfully within manufacturing environments. They will be looking at how solutions can be added one by one - in an incremental manner. This is to minimise infrastructure investment up front, and to maximise the ability for new solutions to make full use of services already provided in existing ones.

The toolbox components can be combined with existing cloud computing platforms, human-machine interaction (consumergrade AR/VR technologies), IIoT suites and interfaces such as iPads and Alexa (Amazon Echo) to create standard combinations which can form adaptable solutions. Phase 3: Prototyping and pilot testing The Shoestring team will be building proof-of-concept demonstrators both in research labs and in SME partner operations. A comprehensive testing and validation programme will demonstrate evidence of effectiveness of proposed digital solutions. Initial testing and

Connecting solutions is integral to the project’s approach. While it may seem cost effective to solve problems one at a time, the challenge is to avoid creating isolated, unconnectable solutions which won’t integrate with future developments. The Shoestring team is seeking to develop frameworks which allow for future integration. The project team plans to work with BSI and others to support different types of standards across data, communications, services and architectures. They are also accounting for security and compatibility.

Phase 5: Engagement and dissemination During the project, there will be open engagement with as many SMEs as possible, and firms are actively encouraged to get involved. We will be running regular open workshops – the first of these took place in Cambridge on 24th September and was well-attended by SMEs, providers and manufacturing networks. A key outcome from the project is to create a ‘library’ of solutions which can be accessed widely by SMEs, as well as sharing lessons learned from exploring low-cost digitalisation. The team plans to develop a demonstration platform, to provide examples and visibility for addressing specific challenges within individual SMEs.

Digital solutions development: Engaging IT SMEs, students and hackathons Fitting the entire ‘Shoestring’ approach, the project is actively engaging with IT solutions SMEs in the development processes, including workshops and events involving IT developers and start-ups. Student participation is also strongly encouraged, with hackathons for engineering and computer science students, competitions for low-cost digital manufacturing solutions, and potentially sponsorship of relevant student projects.

ISSUE 11 | P19

Examples of Shoestring component development Working from the priority list of solutions from the SME requirements gathering workshops, the team is already busy building solutions. Here are a few examples.

a Part detection and tracking Dr Lavindra de Silva

a Augmented reality status viewer Dr Greg Hawkridge

This solution uses QR codes to detect and keep track of parts in a factory. When parts are received from suppliers, a QR code is attached to each part and they are placed inside boxes or trays with an ID. The boxes are placed flat on a tote, which the operator then manually ‘scans’ under a webcam or low cost camera that is connected to a Raspberry Pi and screen. The system will then identify all of the parts inside the box, scanning all of the QR codes simultaneously, and store selected information about each of the parts. The information can then be searched later, so the contents of the box can be checked. New parts can be scanned individually and matched with boxes containing similar parts.

Enabling a factory supervisor to view the status of the shop-floor systems, such as inventory management, this solution uses augmented reality on a smart phone/tablet. It can overlay status information from machines, such as stock levels, on a tablet or mobile device when the screen is held up to look at the machine. The idea is that a worker or manager can be walking down the shop floor and look at a particular machine through the app on their mobile device, and get an instant status check.

a Voice assisted assembly Dr Greg Hawkridge a Machine monitoring Dr Yedige Tlegenov This solution provides a low-cost machine monitoring system that can be attached to machines, such as a 3D printer or a CNC machine, using sensors attached to Raspberry Pis and open source software libraries. It can obtain the status (such as temperature, through put, run time, etc) of the machine. Data from the sensors is sent to an open source cloud-based platform to provide monitoring information, including alerts of machine errors, and can be viewed real time on any device.

This solution uses a digital voice assistant to help a worker complete an assembly task. The worker can request particular fasteners (nuts and screws) from an Alexa-enabled device which processes verbal commands. This is integrated with a turntable via a programmable logical controller. The system will provide them with the correct item and give them verbal feedback saying what the fastener or part is that’s been provided. This makes workers jobs easier and reduces errors.

See these demos in action in a series of videos here: www.digitalshoestring.net/how/demos-and-examples/

To join the ‘Shoestring’ movement… If you would like to be involved in this project, register your interest by emailing dial-admin@eng.cam.ac.uk Stay up-to-date on the progress of this project, including dates and times of workshops and demonstrations by signing up to alerts through the website: www.digitalshoestring.net

P20 | ISSUE 11

Professor Duncan McFarlane

Do you really know what you’re eating?

Using data to improve transparency and traceability: A case study from the food sector

Supply chain transparency and traceability is increasingly becoming an imperative for producers of fast moving consumer goods. But what approaches are working for creating value from this process, rather than just sinking costs? Dr Mukesh Kumar and Rob Glew from the IfM’s Industrial Resilience Research Group share insights into a recent IfM collaboration with citrus fruit suppliers AMT Fruit, a company which has successfully implemented data-driven transparency and traceability systems with dramatic benefits for its revenue as well as positive outcomes for its partners up and down the supply chain. In 2013 the ‘horse meat scandal’ hit parts of Europe, with the revelation that horse meat—and other undeclared ingredients including pork—had been found in mislabelled processed ‘beef’ products. The controversy caused a consumer outcry, and resulted in an increased focus on standards and transparency by food safety authorities across a number of countries, as well as a negative impact on customer trust for food producers and retailers.

In turn, the need to rebuild consumer trust has driven many of the large supermarkets and retailers to demand higher standards from their suppliers. This has in some cases included the demand for complete transparency, with suppliers being asked to open their books. For suppliers, this presents more than a simple request; it entails significant work and investment, both in terms of technological solutions and working practices.

Alongside the fallout from this scandal, an increasing focus on environmental sustainability has led to mounting consumer pressure for traceability across supply chains, with greater public demand for food retailers to provide clear, transparent information about the provenance of the products we consume.

So how can a supplier turn this cumbersome requirement into an opportunity? What strategies have successful suppliers adopted to move beyond the necessity for transparency just being an expensive burden, and instead learned how to create value from their data?

AMT Fruit: Remodelling as an information provider? One firm that has embraced a simple, profit-maximising approach to supply chain traceability and transparency is AMT Fruit. Based in Newmarket, Suffolk, the company is one of the UK’s largest citrus specialists. Working in close partnership with a major UK supermarket, AMT Fruit operates in a fresh fruit and vegetables supply network with over 250 growers across Europe, Asia, Africa and South America to supply 11 million boxes of citrus (including clementines, satsumas, mandarins and oranges) each year. When their key retail client introduced the requirement for suppliers to share open-book, fully transparent processes,

ISSUE 11 | P21

AMT Fruit was faced with a daunting and potentially enormously costly hurdle. But managers realised that the new requirements could be turned to their advantage by using them to address some key challenges of fresh fruit supply. The citrus fruit supply chain is characterised by particular issues: competition is high; forecasting is difficult and often results in supply surplus or shortage; quality can vary through the year, and there is not always a clear link between cost and quality. Decision makers at AMT Fruit realised that gathering, analysing and using data from increased supply chain transparency could give them better information to support forecasting and pricing accuracy, as well as to reduce waste by better understanding supply levels. Naomi Pendleton, Head of Technical at the company, was tasked with building a traceability system on a tight budget. Impressively, she developed a bespoke system for less than £20k, which provides a very detailed view of traceability in ethical labour. AMT have also developed data-driven capabilities for reducing food waste, and for better forecasting which has enabled improved information for quality control and pricing. IfM researchers worked with AMT Fruit to assess the effectiveness of the new systems. We collected and analysed the data, then identified the value propositions through interviews and observations. AMT Fruit’s initiatives have multiple benefits, as the IfM’s analysis helped to reveal: a Quality control: Sharing detailed product quality information with suppliers and farmers has enabled them to develop a deep understanding of fundamental causes of quality issues. a Customer satisfaction: Fruit are split into different high, middle and low market product lines depending on their quality characteristics, with the new quality data from traceability and transparency allowing AMT and their supermarket client to make better categorisation decisions. The result has been a 75% reduction in customer complaints related to product quality since 2014, when the system was first rolled out. a Optimised pricing: Data from farmers has helped to optimise AMT’s sourcing strategy. The information can then also be shared with AMT’s supermarket client, and used to improve pricing – more carefully defining the quality specifications for their different price levels of citrus fruit.

P22 | ISSUE 11

a Better forecasting: There is more readily available data on crop size and quality from farmers, improving the accuracy of forecasting. a Ethical working practices in the supply chain: AMT has been able to insist on strict standards for ethical labour across their supply chain. Farmers and fruitpackers who do not conform can be quickly identified and dropped, leaving no room for violations and reducing the risk of political fallout to AMT Fruit and their customers. a Reducing food waste: No less impressive is the benefit to the environment from AMT’s data-driven tactical decisions. Food waste has become a major public issue as consumers push firms to be more sustainable. In the four years since the new system was deployed, AMT has reduced food waste by 35%. In real terms, this means 200 tonnes less fruit is going to waste. Across the whole business, AMT Fruit has seen revenues double between 2014 and 2018. This is particularly impressive when supermarkets—at the retail end of the supply chain—are seeing revenues plateau or even fall.

“The value of AMT’s role in the supply chain has evolved into being an information provider in addition to the traditional role of supply chain wholesaler intermediary.”

The success of AMT Fruit exemplifies what is possible where firms build traceability and transparency systems with a clear and proven business case in mind, carefully manage the volume of information in the system, and use it to drive tactical decision making. Understanding how to extract the value from its data has proved beneficial not only to AMT Fruit itself, but also to its key client supermarket, which is able to improve pricing, reduce waste and increase customer satisfaction. It is also benefiting all the suppliers and farmers further up the supply chain, who are able to secure more certainty about the prices they will receive for fruit, reduce waste, and strengthen their position as ethical suppliers. As such, the value of AMT’s role in the supply chain has evolved into being an information provider in addition to the traditional role of supply chain wholesaler intermediary.

The business case for supply chain traceability: 10 value propositions So to what extent is it becoming easier for companies to identify how to extract value from supply chain traceability data? In the past few years, there has been large investment across manufacturing, pharmaceutical and food industries in initiatives to improve supply chain traceability and transparency, with spending topping $10bn in 2017. Until recently, most initiatives have focused on regulatory compliance, such as chemical treatments in food supply chains, or on sustainability, such as the forestry commission scheme.

Profit Revenue Price

Cost

Quality

• Price / quality link

• Product quality

• Promotions

• Producer feedback • Shelf-life improvements

Growth Data Analytics

• Volume growth

Forecasting • Business security • Joint planning

• Product insight

Risk reduction

Efficiency

Waste

Resource use

• Health

• Logistics movements

• Unusable products

• Packaging

• Product recall

• Complex communication

• Regional issues

• Water / resources

• Labour ethics

• Unnecessary testing

• Specification flexibility

• Chemical monitoring

• Business efficiency

• Fairer claims

Security • Trust • Consistency

Figure 1: Ten value propositions for traceability and transparency systems

Decision makers are faced with difficult choices around justifying investment, as well as data interoperability and scalability, in designing and implementing these traceability systems. With the barriers to development often high, it’s vital that there is a clear business case for implementing systems to deliver traceability and transparency. Recent research from the Industrial Resilience Research Group has assessed the link between increased profits and supply chain traceability and transparency systems, by identifying business cases and linking them either to an associated reduction in cost, or to an increase in revenue. Our analysis of AMT’s initiatives helped to highlight what the key lessons were that could be generalised for other practitioners. This can help other firms take deliberate steps towards maximising value based on the value propositions best suited to their supply chain. We grouped the business cases around 10 wider value propositions, which translate across industries (see Figure 1). Firms should focus on which of those value propositions relate most closely to their strategic priorities. For example, companies in highly competitive markets with a high degree of product differentiation should use traceability to create a link between quality and price. But for firms producing standardised products, such as pharmaceuticals, it is more likely that risk reduction and security are higher importance.

Once managers have identified the business case that holds the most value for their firm, they are in the position to begin design of the system. Our research has identified that the format of data used in the system is the most critical design decision. Many of the companies we work with operate international, multi-tier supply chains that generate hundreds of thousands of data points for every product. Previously, the approach has been to collect all the available data in the belief that every data point has value. This led to sky-high costs to develop, use and maintain systems.

We are actively seeking industrial partners to work on this challenge with us. If you would like to know more about our workon industrial resilience, including data-driven approaches to strategic supply chain decisions, please contact Rob Glew, rg522@cam.ac.uk.

Information overload can be avoided by identifying the few types of data that are relevant to each firm’s individual supply chain traceability business case.

Extending the use of data to strategic decision making

Dr Mukesh Kumar

Rob Glew

How businesses collect, manage and use information about their supply chain has a growing effect on the bottom line. At present, much of the focus has been on making improvements at the operational or tactical layers of decision making. However, managers must develop capabilities to make use of this information in the board room, as well on the level of day-to-day operations. Addressing this, the next step for this research is to understand how the data produced from traceability can be bought into the strategic level of decision making. Does this information have value in supporting critical decisions such as where to open a new plant or where to source products from?

ISSUE 11 | P23

Customer experience:

Connecting the digital, physical and social New technologies and new business models have already changed the way organisations interact with their customers. In the not-too-distant future, developments such as AI, robots and virtual reality will be a completely normal part of the customer experience. However, these new ways of engaging with customers will not replace face-to-face encounters but will work alongside them, making already complex service systems even more so.

P24 | ISSUE 11

In this world, managers will need to understand customer experiences across the digital, physical and social â&#x20AC;&#x2DC;spacesâ&#x20AC;&#x2122;. Until now service research has looked at these three distinct service environments separately but organisations increasingly need to understand how they come together to create satisfying customer experiences and to design their services accordingly.

The digital space Digital technologies such as virtual reality, AI, blockchain and digital twins will transform the customer experience. Digital platforms have already taught us to expect highly personalised services and instant responses, 24/7. The speed of digital, its reach, its interactivity and the quantity of data it can handle, will continue to affect customer behaviour. The role of humans in service delivery is also likely to change, as they are supported or, at times, even replaced by digital experts.

The physical space The digital revolution notwithstanding, services will continue to be delivered in the ‘real world’, in, for example, bricks-and-mortar shops, hospitals or airports. We know that the right physical environment can positively affect the customer experience. As organisations develop their digital spaces they may borrow aspects of their physical spaces to recreate those positive customer experiences. At the same time, the digital is increasingly invading the physical world through, for example, self-service kiosks to virtual reality simulators.

The social space Interactions are at the heart of the customer experience, whether in person (in a physical space) or online (in a digital space) and whether they are human-to-human or human-to-robot. The social space is about creating shared experiences, whether that’s between the organisation and its customers or among the customers themselves. As digital technologies become more pervasive, these roles are likely to become blurred. For example, on platforms such as AirBnB users can switch between being a customer and a service provider. We need to understand the implications of having multiple identities in the service context.

Why is it so important to think in terms of these three digital, physical and social spaces? The simple answer is that doing so will enable organisations to design better services for – and with – their customers. It will also help them avoid potential pitfalls. Not thinking about these connections when dealing with complex service systems can have serious consequences. A good (or bad) example of this is when a small electrical fire started at Atlanta’s airport (in its physical space) in 2017. The back-up power system (in its digital space) responded by shutting itself down which in turn stopped the emergency teams (in its social space) from dealing with the fire. Result: passengers were going nowhere fast. Each of those systems responded to a local issue in a logical way but a lack of integration ended up escalating the problem rather than solving it.

Services 2050 We know service delivery is going to change over the next 30 years thanks to new technologies. To get a better idea of what that will mean in the digital, physical and social spaces, we consider the likely trajectory of three different service sectors. Asset-heavy B2B services In sectors such as construction, energy and transport services it is common for maintenance and repair services to be part of the package when customers buy or

lease an asset. These services take place in the physical space (onsite at a building or in a workshop) and in the social space (working with a team of experts). However, digitalisation is also becoming an important part of this landscape. All large assets are expensive to run and those that are part of our national infrastructure, such as power stations, bridges and railways are critical both to the economy and to people’s health and safety. As a result, they are using real-time data sensing and analytics to pre-empt problems and keep services running smoothly. Over the next 30 years we see this sector moving from conventional support services to services derived from digital twins. Rolls-Royce, for example, has announced a project to create digital twins of its ships so that their safety and performance can be digitally monitored throughout their lifetime. Healthcare Similarly, healthcare has been centred on the schedules and settings of the clinical team and hospital infrastructure, in other words, in its physical and social spaces. However, over the next 30 years we are likely to see more and more healthcare taking place in the digital space. Patients will be able to make more choices about how and where they receive their care. Treatments will become more

personalised with advances in genome pattern sequencing and diagnostic techniques. Healthcare providers will be using AI, 3D printing, sensory technology and real-time data processing to design and deliver services. Robots will help on the wards and in the operating theatre and take on social roles such as companions for the elderly. B2C, retail and professional services This has been an area of intense innovation in recent years, with retail often leading the way, moving from a highly physical and social model to a highly digital one. But there is an interesting convergence going on here as some conventional bricks-and-mortar retailers are bringing digital channels instore and some online retailers – like Amazon – are opening bricks-and-mortar shops. Whichever route they take, they recognise the need to create a highly personalised, consistent and integrated shopping experience. In professional services, the World Economic Forum is predicting a huge shift to online platforms with customers expecting 24/7 access. In the legal profession, virtual courtrooms are already replacing physical ones and we have seen US law firm Baker and Hosteler using an AI lawyer to handle its bankruptcy practice. In all three sectors, therefore, we anticipate a shift to the digital to exploit the opportunities it brings for creating new value propositions, and the convenience

ISSUE 11 | P25

it offers its customers. But what does this mean for organisations and how should they be designing their services to deliver a satisfying customer experience across these different spaces? This needs careful thought as the connections between devices and platforms can quickly create very complex service environments which can cause some unintended consequences. At the same time, one of the major barriers preventing the integration of the three service spaces is the number of different hardware, software, platforms and networks that organisations have within their own businesses, let alone across different organisations.

How can organisations connect across the digital, physical and social spaces? We have developed a framework that allows us to categorise services according to how digital, physical or social they are and the levels of complexity they have in each space. This allows us to identify areas of opportunity and of potential conflict and to devise ways to resolve them. At the most complex end of the spectrum, where services are highly physical, digital and social, organisations are going to have to manage the relationships between the spaces very carefully in order to deliver the right service to the right customers. Customers will choose which elements they want from which space: organisations will need the systems in place to cope with that seamlessly. Where the move is towards a greater social presence in a digital space we anticipate a number of challenges, including arriving at a better understanding of how human customers are going to react to robot assistants. We are used to getting help from Siri or Alexa and researchers are developing robots that can show signs of empathy, recognising someone’s emotional state and showing emotion in response. These kinds of robots will affect the customer experience in ways we do not yet understand.

Where do we go from here? Taking a digital, physical and social perspective changes the way organisations need to think about service design. Here are just some of the issues service providers will need to address: Connect across the three spaces to meet your customers’ needs Organisations must develop the capabilities and resources to support service innovations across all three spaces, ensuring that the right information is

P26 | ISSUE 11

available to the right people at the right time. Better data management is going to be needed to connect the spaces and to understand customers’ preferences in order to determine the appropriate mix and sequences of services that will be most effective in creating value for both parties. Develop good practice around personal information Organisations can only develop the kind of personalised services that firms such as Disney are pioneering if customers trust them with their data. This is already a serious issue in the B2C world. B2B organisations are also waking up to the fact that they need to get better at securing sensitive data. Know when to launch Getting this right is critical but not easy. Microsoft learnt this to its cost with the launch of its chatbot, Tay, which had to be closed down after only 24 hours of activity. Use our model to address ‘base of the ‘pyramid’ challenges If all three spaces are at a low level of development, it suggests that all resources are scarce. In this context, our model can help develop innovative solutions such as tapping into local knowledge, resources and capabilities to create alliances or using digital technologies to develop new business models which allow customers to share a service and its costs, to buy smaller packages or to benefit from microfinance or loan programmes.

kind of attention whatever the context.

The future of services Services are about relationships between customers, suppliers, employees and a range of other human (and non-human) participants in increasingly complicated ecosystems. New technologies have the potential to make organisations much more efficient and to improve their customers’ experience. But not all technologies will be welcomed by customers. Organisations may have to trade off the efficiency new technologies can bring against their potential for alienating customers. Understanding which ones will work in which situations is going to be critical in a future of multiple technological possibilities. Being clear about the relationships between the digital, the physical and the social will mean you are more likely to make the right choices. One thing’s for sure. In an era where AI, robots and digital twins are part of the service landscape, the customer experience is going to change. We need to make sure it’s a change for the better.

Co-create a coherent customer experience Whether in the digital, physical or social spaces, employees (human or digital) play a key part in attracting and retaining customers. Rapport and empathy influence the customer experience and business outcomes. Organisations will need to make sure that their customers receive the same

Dr Mohamed Zaki

The power of Artificial Intelligence Improving supply chain efficiencies Artificial Intelligence (AI) offers huge potential for supply chains, helping to reduce disruption and improve efficiency. So far, however, there has been a lack of practical examples and case studies demonstrating how data-driven approaches can be implemented effectively. Research from the IfM’s Manufacturing Analytics research group, led by Dr Alexandra Brintup, has been addressing this gap by running pilot studies and highlighting the opportunities and potential pitfalls. Alexandra explains what her research reveals and the lessons for organisations…

Supply chain analytics isn’t a new concept – in fact the manufacturing sector has long been an enthusiastic adopter of data-driven techniques. So apart from a fancy new name, what is really new? A combination of three emerging developments is changing the game: The first is computational power, enabling us to do calculations real time; secondly, powerful new algorithms can automate analysis and decision-making; and crucially, new and previously untapped sources of data are emerging. ‘Supply chain analytics’ is an umbrella term, referring to a multitude of capabilities. There is no single solution that works for every organisation – it depends on the nature of the supply chain, the organisational strategy and priorities, and the information that is available. And not every capability is appropriate for every organisation – they should not be viewed as a to-do list! Instead, firms can pick and choose which capabilities to develop to suit particular supply chain functions and business needs.

ISSUE 11 | P27

However, there are some common questions that organisations can address in order to understand how supply chain analytics and AI can best be deployed in their own context. How much data and from what source? Where does your data come from? Traditionally in supply chains weâ&#x20AC;&#x2122;ve had enterprise resource planning (ERP) systems taking structured sources of data (which are mostly manually populated but also drawn from some automated processes). Now we have data from a larger array of sources: smart products that provide data with status updates on their use, location, and condition, through sensors and IoT connectivity; GPS location tracking data; and even unconventional sources such as social media. Much of this data can be obtained in real time, and can be gathered from beyond your immediate organisational boundaries â&#x20AC;&#x201C; whether from supply chain partners, external organisations or customers.

Descriptive analytics

Predictive analytics

Prescriptive analytics

How will the data provide valuable information? Data volume can be overwhelming, so understanding and focusing on what will genuinely add value is essential. How will you use the data to create a better understanding of what is going on? Itâ&#x20AC;&#x2122;s also important to consider how data from different sources can be integrated to provide a dynamic overview. This can, for example, enable predictive analytics to reduce disruption. How does the data improve decision- making? Improved data availability offers the potential for much greater awareness of systems. But what will you do with the new-found awareness - what kinds of decisions will the data be used to improve? Can you identify ways to optimise current processes, or about how to redesign systems in the future? Is the focus primarily on streamlining day-today operations, or on tactical areas, or strategic decisions? And can data be used collectively across the supply chain to improve efficiency?

It will take 5 random supplier failures for X to halt production

0.7 likelihood that A supplies gears to B

Inject 5% safety stock in at least three hubs

Figure 1: Identifying and reducing disruption in the supply chain through data analytics

P28 | ISSUE 11

How does this support automation or semi-automation of tasks? Data analytics can allow hidden patterns and trends in the data to be uncovered and acted upon, in order to improve supply chain operations. The automation or semi-automation of mundane operational tasks, identified through the data, can have a transformative impact on optimisation in the supply chain.

Supply chain analytics in practice: Real-world examples Our Manufacturing Analytics research team has conducted several studies on supply chain analytics with partners from the automotive, and aerospace industries as well as FMCG and other sectors. The goal was to map the supply chain structure, understand how disruptions may cascade and impact this structure, and then use this knowledge to inject resilience after predicting hidden dependencies and supplier deliveries (see Figure 1).

These studies reveal five key lessons for using supply chain data analytics: 1 Don’t underestimate the power of descriptive analytics to lead to more realistic solutions The very first lesson is about not underestimating the potential benefits that can be gained from exploratory, descriptive analytics before moving onto solution finding. The insights we gained from exploratory studies provided greater depth than we expected. For example, the hub-spoke structure that emerges in supplier-manufacturer connections and the density of connections told us that there is a higher than expected likelihood of tier one suppliers connecting to one another, unbeknownst to the original equipment manufacturer (OEM).

By mapping the supply chain data, we were able to spot patterns, and predict what failures were likely to occur, and therefore take much better precautions. In one of the studies we worked with a large FMCG corporation, and we able to spot where inventory could be injected to provide a buffer against likely stock shortages. In fact, we found that some types of network structures require much less inventory to ride out the same level of disruption - so we could map out what level of inventory is needed for a particular type of network structure to reduce disruption without unnecessary stockpiling. 2 Don’t go crazy! A minimalist approach may yield the best results The second lesson is about staying focused and avoiding overcomplicated solutions. For example, one company we worked with wanted to find out which of their suppliers were supplying to each other – as this is a problem for reliability of supply. Where were there hidden dependencies amongst suppliers? Initially we tried to identify this with sophisticated methods: using time series data, and trying to tease it all out with deep neural nets, recursive nets, and other techniques… but nothing worked. Then we went to back to basics, and asked ‘What is likely to connect suppliers to each

other?’ If they produce these products, maybe their models are compatible, so they supply the same OEMs. This worked. Getting back to fundamental patterns was key. 3 One solution doesn’t fit all Often data across supply chains can quickly become too complicated. In our studies, variables such as suppliers, parts, delivery times, volumes, locations, routes, level of confidence – all added up to a very large data set that became too complex. We found that it was essential to divide the problem into more digestible chunks, considering one or two elements at a time to produce more meaningful and useable information. 4 Domain knowledge is golden It is crucial to work with the operational team to decipher patterns in data – for example in a supplier disruption prediction project, what we initially thought was noise in the data turned out to be new product configurations, which helped us understand how the system may stabilize over time. 5 Strive to create traceability, accountability and buy-in The fifth and final lesson? It’s about trust. AI is wonderful, a life-long passion of mine, but it’s clear that not everyone trusts AI. And they are right to ask these important questions. When it goes wrong, who will be accountable? Can we place mechanisms to make it transparent? These are big questions without straightforward answers, at least for now.

even negotiate with suppliers and run auctions. But the questions asked by the real people involved were pertinent: Exactly how do you arrive at these solutions? What if our people want to negotiate with suppliers themselves? Are you automating me? So due to the valid questions raised about trust, the solution that had been developed was patented but will take a lot longer to be implemented. The key lesson perhaps is that we need more research to build transparency of algorithms and understand how and when they should be used.

We are currently working with several companies to understand how these concepts can be applied to a variety of sectors. Please contact ab702@cam.ac.uk to find out more.

Dr Alexandra Brintup

In our research, we worked with an aerospace company to create a selforganizing system using what we call ‘software agents’ (essentially what drives Alexa and Siri) to automate spare parts procurement. The system would take data from sensors, analyse them to understand what part is expiring or deteriorating by when, then find the best supplier to schedule aircraft maintenance depending on when and where it is flying. This is a complicated problem, and the analytics could provide optimal solutions. It could

ISSUE 11 | P29

Using digital twins to manage assets and infrastructure Creating a digital replica of a physical entity is a capability which offers exciting and wide-ranging potential. Researchers in the Asset Management group at the IfM, led by Dr Ajith Parlikad, have worked with partners to build a digital twin of the IfM building as part of a UKwide programme to create a digital twin of national infrastructure.

P30 | ISSUE 11

Figure 1: Digital 3D model of the IfM building

Digital twins are realistic digital representations of physical assets and systems. What distinguishes a digital twin from any other digital model is its connection to the physical twin. Such a connection could be through live data flows from sensors and feedback into the physical twin via real-time control systems. The term was coined almost 20 years ago, but only more recently have digital twins become accessible and affordable to more organisations thanks to Internet of Things (IoT) technologies, and their potential value has been garnering increasing attention. Digital twins can play a beneficial role in managing assets, providing real-time data about the condition, status and environment of an asset, and how it is being used. The technology can also be used for designing and testing new physical entities – for example NASA is using digital twins to test and build equipment in a virtual environment. It can also enable simulations to be run for new processes on existing assets with reduced costs, avoiding physical damage or interruption to operations. Companies are already using digital twin technology for many purposes, including to improve existing operations and to test new products and processes before implementing more expensive physical tests. In manufacturing, digital twins can be used for predictive maintenance: helping to reduce maintenance of machines and ensure optimal production output by monitoring in real-time and providing advance warning of potential

failures before they occur.

A digital twin of the UK The technology is also a valuable tool in construction and in managing and connecting large infrastructures. In fact, such is the potential of digital twin technology that it is being tested and deployed for infrastructure planning at national level in the UK, as part of efforts to increase the resilience of infrastructure for coping with uncertainties such as climate change and population growth. Recognising the importance of data for the national economy, the UK National Infrastructure Commission published the ‘Data for the Public Good’ report in 2017, setting out a series of recommendations for the government including development of a ‘National Digital Twin’. Dr Ajith Parlikad of the IfM’s Asset Management research group explains:

“The National Digital Twin is not meant to be one colossal twin of the whole national infrastructure. Instead it will be made up of many smaller twins representing assets or systems at different levels, which can then be brought together to generate greater value.” To support this national goal, the Centre for Digital Built Britain (CDBB - a partnership between the Department of

Business, Energy & Industrial Strategy and the University of Cambridge to deliver a smart digital economy for infrastructure and construction in the UK) is working to develop the information management framework that will need to underpin the creation of a national digital twin. In the meantime, there is still work to be done on developing the technology, which is in its relative infancy.

IfM twin pilot project To demonstrate its value for facilities management, productivity and wellbeing, CDBB is funding a project to create a digital twin of the University of Cambridge’s West Cambridge site, including the IfM building. The project involves University researchers with specialist external partners. As Ajith explains: “The West Cambridge digital twin project is bringing together researchers and a number of specialist companies to create a 3D digital model of the site using drone- and vehicle based scanning and to create a register of its assets using an asset-tagging system. “We are aiming for this pilot to demonstrate the impact of digital modelling and analysis of infrastructure performance and use on organisational productivity. On a wider scale, we also want the twin to provide the foundation for integrating city-scale data to optimise city services such as power, waste, transport and understand the impact on wider social and economic outcomes.”

ISSUE 11 | P31

Dr Ajith Parlikad

Figure 2: Monitoring the asset condition of heating, ventilation and air conditioning systems

The pilot comprises three interconnected phases: 1

Mapping the IfM

The West Cambridge project is different from other examples of infrastructure-level digital twins in that it is based on existing buildings and infrastructure rather than plans or purpose-built assets. This presents some interesting challenges for the team. As Ajith says: “The IfM building is now just over ten years old and we never had a good or as-built drawing or model of the building. So we had to develop a representation of the structure of the building and the components within it.” This work is being carried out through a joint effort between researchers at the IfM, Bentley Systems, who provided expertise and the technologies for 3D Building Information Modelling (BIM) of the IfM building, GeoSLAM, who provided the detailed context capture scan, Topcon, who generated a low-level-detailed 3D geometry and photogrammetry of the West Cambridge Site using drone and vehicle-based scanning and camera devices, and Internet of Things (IoT) software company Redbite. Ajith adds: “The team has also deployed and tested additional IoT sensors and devices throughout the IfM building that will help us to monitor and control the condition and operation of critical assets and the environment in the IfM.” An asset register has been developed, along with asset identification tags for critical equipment across the IfM. Over 200 assets have been tagged within the building. 2D barcodes are placed on the physical objects and the associated asset data is stored in Redbite’s asset management solution ‘itemit’. “What these 2D barcode tags allow us to do is not only identify these assets

P32 | ISSUE 11

uniquely but if you scan the tag, the app will show us an asset profile which provides all sorts of descriptions about what the asset is, but more importantly asset management data as well,” explains Ajith. “So, you can see information about when it was last inspected, what the inspection record was, when it is due for inspection next, when the next maintenance is due and so forth. It’s a rich collection of data that you can store on those asset profiles using these tags.” 2

Harvesting, integrating and analysing the data in real time

Close to 60 environmental sensors have been deployed in the building so far, including temperature sensors, humidity sensors, and ones that can monitor whether windows are open or closed. “We are going to deploy CO2 sensors and also occupancy monitors as well, within the building,” says Ajith. “On top of that there are some condition monitoring sensors that allow us to capture data that is not currently captured through the building management system. So, for instance, we have these vibration sensors that are put on the pumps on the heating, ventilation and air conditioning systems in our plant room.” Data from various sources needs to be integrated from the pilot to enable effective data analytics for decision making. To achieve this, the team is using Building Information Modelling (BIM) which is an intelligent 3D modelbased process used by construction professionals, with open standards such as Industry Foundation Classes (IFC). Ajith adds: “Using open standards is an important aspect of this project for two reasons. As well as helping to make sure that the digital twin development is vendor-

agnostic, it is also a useful way of revealing any gaps and weaknesses in the current open source schema.” To create a central repository for the sensor data and building management system data, everything is being pushed to a cloud database on Amazon Web Services (AWS). This is partly because the University’s local data infrastructure is locked down, but more importantly because the project gives an opportunity to explore how emerging cloud-based solutions can be used within the digital twin context. 3

Extending the project to future potential

The West Cambridge project is beginning to extend its reach beyond the IfM building. It will expand geographically, aiming to look at how a city level digital twin could deliver benefits to the community and local government and planning authorities. Ajith will be working with Dr Richard Mortier and Dr Ian Lewis from the Department of Computer Science and Technology over the next two years to add sensors for things like traffic monitoring, air quality, parking and visionbased condition monitoring of the road surface. The project is also exploring potential applications for the IfM’s digital twin. These include: a Better asset maintenance using predictive data analytics. a Better asset tracking. a More efficient use and management of equipment. a Finding ways to reduce energy consumption. a Using augmented reality to help with maintenance and inspection.

Whatâ&#x20AC;&#x2122;s coming next?

Innovating business models to target value from the second wave of digital disruption. Dr Chander Velu, head of the IfMâ&#x20AC;&#x2122;s Business Model Innovation research group, has been collaborating with digital strategy consultants at IBM to consider how the next wave of digital technologies will impact on firm-level business operations, and to create a framework for companies to target the full value potential including the implications for business models. We interview Chander to find out more about the researchâ&#x20AC;Ś

ISSUE 11 | P33

Mobile

Networ k Va lue Cloud

Analytics Value Proposition

Value Creation

Business Models

Value Capture Blockchain

IoT

AI Source: Velu, C; Coopetition and Business Models, Routledge ( 2018 )

Figure 1: Business model components – 4Vs

Your research identifies a ‘second wave’ of digital disruption. What is meant by the second wave? Over the past few years we’ve seen widespread disruption driven by new technologies which have revolutionised the way companies can interact, including within their organisations, with their supply chain partners, and with their customers. This disruption has included e-commerce, and has been centred on internet-enabled platforms. As part of this first wave, advancements in mobile, cloud and analytics have resulted in the rapid expansion of digital platforms and more personalisation of offers. The platform companies that emerged from this shift captured significant value by monetising direct access to the customer. Many have also created new value through external networks, often by acting as intermediaries within ecosystems. So what’s changing to indicate a ‘second wave’? Well, the maturity of cloud, analytics and mobile is now matched with the progress in Internet of Things (IoT), artificial intelligence (AI) and blockchain technologies. New digital technologies are creating intelligent engines that enable augmented human intelligence, autonomous decision making, more efficient machine-to-human interactions, and optimisation of any system in real time. Collectively, these newly emerged technologies are changing the economics of industry value chains from end-to-end and are impacting every component of business models – the value proposition, value

P34 | ISSUE 11

creation, value capture, and value network (see Figure 1). These technologies can enable new value propositions, capabilities, and optimisation opportunities in end-to-end supply chains, operations and distribution. Yet at the same time they are causing significant changes in how organisations position themselves, as well as dislocation and disintermediation of players in the value chain through the emergence of new business models.

Can you share some examples from industry? There are some great examples showing how digital technologies are resulting in innovative business models through extended value networks, and how these can render some business models and players in the value chain irrelevant. The Food Trust blockchain is an example of an industry partnership that improves transparency and efficiency across the entire food supply chain. This ecosystem includes retailers (including Walmart, Kroger, Dole, Nestle, Tyson Foods and Unilever) growers, distributors and more, who collaborate to improve food safety by pinpointing contamination sources. Walmart is now able to trace food-based products back to the original source within 2.2 seconds. Each new supplier or distributor entering the Food Trust creates more value for all members; suppliers get access to a broader network of consistent demand and distributors get access to a larger variety of supplies with diminishing costs. Such industry partnerships and coopetition business models, whereby competing

firms cooperate, are emerging across more and more industries. The rationale for coopetition-based business models could be to increase the size of the current market, to create new markets, or to increase efficiency in resource utilisation in order to help improve the firms’ competitive position. Another example shows the cost of being left behind with a business model that has been superseded: American Tire Distributors, the largest distributor of tyres in the US, filed for bankruptcy in 2018. Their position in the value chain was disintermediated after the two of the largest tyre manufacturers in the US (Goodyear and Bridgestone) decided to go directly to consumers through their own networks, and Sears Holdings Corp. agreed a partnership to install tyres bought on Amazon.com.

What are the challenges of estimating and measuring the value of digital initiatives? And what is the ‘productivity paradox’? Assessing the value and impact from digital technology investments remains a challenge for most enterprises. For businesses, improved profitability and productivity are often used to measure the impact of digital initiatives. Digital technologies can increase profitability by reducing a wide range of costs across the value chain. These technologies are streamlining supply chain activities through integration, automation, tracking and better forecasting. They are also driving significant operational efficiencies through more efficient use of equipment, increased labour productivity, and enhanced monitoring and management. In distribution, they help remove steps and activities between customers and how they use goods and services. Productivity, however, presents a conundrum. In spite of the prevalence of digital technologies, in aggregate there seems to be a persistent slowdown in productivity that has plagued modern economies for the past 10 years. This is widely known as the ‘productivity paradox’ and there are many possible reasons that explain it. These include the impact of the financial crisis, the lack of diffusion of the benefits of digital technologies among small and medium sized enterprises, mismeasurement of the digital economy, and more. However, our view is that siloed approaches, too much focus on operational efficiencies, and the lack of business model innovation following the adoption of digital technologies, could also be major contributors to the productivity paradox.

Impact level (costs reduction) Disruptive

2.5 – 6%

Substantial

1 – 2.5%

Moderate

0 – 1%

Retail

Auto

Hospitality

Healthcare

Electric Utility

Oil Refining

Moderate

Disruptive

Substantial

Disruptive

Substantial

Cloud/Analytics

Substantial

Disruptive

Substantial

IoT

Disruptive

Substantial

Disruptive

Substantial

Cognitive/AI

Disruptive

Substantial

Disruptive

Moderate

Blockchain

Disruptive

Substantial

Moderate

Mobile

What strategic approaches can be used to target the potential value of digital transformation? From our research on digital business model innovation, and drawing on experiences of managing digital transformation efforts, we have developed practical recommendations for how to increase the likelihood that digital transformation efforts are successful in targeting the full value potential. These focus on four courses of action (shown in Figure 3):

Figure 2: Estimated technology impact potential by industry sector Source: IBM and Cambridge research and analysis

How can firms capitalise on the opportunities opening up from this second wave of disruption?

How have you estimated the potential value of emerging technologies in your research?

Firms are approaching digital initiatives in one of two ways. The first is a primary focus on incremental product improvements and operational efficiencies. Most digital initiatives fall into this first category. This is likely because firms can see the results of such initiatives faster and can use wellestablished cost take-out KPIs to set targets and measure success. The impact from these cost savings and productivity gains will be significant. We estimate that in the US alone this will amount to an average of USD 1.8 trillion per year over the next 10 years. However, these efficiency gains represent only a portion of the value potential and will not be evenly distributed across sectors.

To estimate the potential impacts of five core digital technologies (mobile, cloud/analytics, IoT, cognitive/AI, blockchain), we developed a value chain-based model. We estimated total impacts by cataloguing how each technology could transform individual parts of each sector’s value chain. We assessed current and planned uses of emerging technologies for leading firms in each sector. We then mapped where in the value chain these technologies were being applied, and how they would create value, and documented any publicly disclosed estimates of the potential or already delivered value. The full encyclopedia of unique use cases documents over 200 distinct applications.

Indeed, the second category of digital initiative offers much more extensive potential value, and the development of new value propositions could contribute to significant growth and innovation through the design of new business models. The combination of IoT, AI and blockchain, in particular, could enable strong network effects, whereby an established leader can drive a virtual circle of adoption resulting in improved capabilities and economics. As such, it is imperative for organisations to assess value creation and capture opportunities through expanded value networks.

While emerging technologies will impact all sectors, the value they create will not be evenly distributed. The amount of impact depends on a variety of factors including, but not limited to, which parts of the value chain are affected, which technologies dominate, and the speed with which different industries drive successful adoption of digital technologies. We have done a ‘bottom-up’ estimate on several sectors in order to see how different the impact could actually be (see Figure 2).

Objective

Confirm your ambition

Reimagine your value chain and your ecosystem to define a north star

2 Shape a value roadmap

Define initiatives in 3–5 prioritised business areas, and make deliberate choices to prioritise them into a roadmap

3 Build the supporting capability roadmap

Conduct a Digital Capability Gap Assessment and develop a capability roadmap in support of your value roadmap

Confirm your organisational ambition by mapping and reimagining your ecosystem and your value chain.

Identify opportunities and define initiatives across every component of the business model and make deliberate choices in prioritising them into a value roadmap.

Conduct a digital capability assessment to develop a capability roadmap in support of the value roadmap.

Align and engage the organisation behind the ambition and the value roadmap; shape a programme with strong governance.

Ultimately, the firms best placed to reap the opportunities presented by the second wave of digital disruption will be those who can identify value opportunities, and create and capture the value from them based on the ability to adapt and configure their own capabilities and their strategic partnerships. This will rely on adopting a structured approach to business strategy, developing the skills and capabilities required, and building technological solutions which deliver customer needs more effectively than competitors. A company’s willingness to innovate and change its business model will be fundamental. To find out more about support available from the Business Model Innovation research group, contact Dr Chander Velu on cv236@cam.ac.uk. The full report can be downloaded at: bit.ly/2oxJkWV

4 Align and engage the organisation

Align the organisation behind the ambition and the value roadmap, and establish strong governance

Dr Chander Velu Figure 3: Four courses of action to target potential value

ISSUE 11 | P35

different possibilities, with a huge volume of data generated, but had to narrow these down. We learned how to ask really good, focused questions to help us define the scope more tightly and refine down to the most valuable solution. We also needed to navigate resistance from floor managers and work with them to find solutions they were happy to work with.”

Student insights Training the manufacturing leaders of the future IfM’s approach to education has a strong emphasis on practical experience, providing students with opportunities to apply their theoretical learning to real-world contexts in manufacturing. A key ingredient in this approach is the industrial projects: A series of twoweek and four-week projects are core to both the undergraduate (Manufacturing Engineering Tripos years three and four) and one-year taught postgraduate (Industrial Systems, Manufacture and Management (ISMM) MPhil) courses. We asked some of our students and host companies to share their thoughts on how this practical emphasis is helping to train the manufacturing leaders of the future. Future industrial leaders will need the ability to adapt to constantly changing circumstances and new technologies, with an innovative, problem-solving mindset. They also need to develop excellent interpersonal skills, with the ability to motivate their

P36 | ISSUE 11

workforce and keep people on board. This poses interesting challenges for how we best educate and prepare these future leaders. IfM’s educational philosophy has always been based on the belief that students need to be exposed to real industrial situations, learning how to apply theory in practice, and understanding the complexity of dealing with a variety of people and navigating company cultures. Two-week and four-week industry projects, undertaken by students in pairs within a host company, have proven successful as a means to develop these wider capabilities. Student industry projects involve ‘live’ issues for the host company, with the benefit that everyone is invested in the outcome, and that the projects often produce genuinely valuable results for the company. Work is supervised by the host company and the students are treated as if they are company employees. Rob Stocker, who graduated this year from the IfM’s postgraduate ISMM course, reflects on a two-week project with bathroom specialist Kohler Mira, at the company’s Mira Showers plant in Cheltenham: “We had two weeks to design a new subassembly layout,” he explains. “Personally the biggest thing I learned was how to focus quickly on the best route to take. We explored the problem and identified lots of

Fellow student Kiril Krastev worked on a twoweek project at NSG Pilkington. He says: “We had to learn how to plan our interactions with different people. For example we realised the value of seeking different viewpoints and inputs to cross-check what we were doing, so that what we presented was more reliable and not just one person’s opinion. We often had very limited time with particular specialists, so we had to make sure we were not afraid to ask all the questions we needed answering; this required planning and also confidence.” Anastasia Ilina had a two-week project with tea manufacturer Twinings. She explains: “We were working on a quality control issue – we had to identify the root cause of a problem, replicate it and work on improving the algorithms for the machinery. We had to collect data from different sources, including different people and machines, as well as contacting suppliers, then make a plan for how to address it. We managed to get agreement on proposed changes and implement a pilot new process within our two-week project, with results to show that what we’d done was correct.” Joe McNamara from Jaguar Land Rover has hosted several groups of IfM’s undergraduate students on placements. He comments: “I’m always impressed by the way the students arrive and get stuck in straight away. They already have good interpersonal skills, but they get a chance to hone those and work out the best way to approach different types of people to get the best response. They also have to realise that in the real world the information they need isn’t quite at their fingertips. Real industrial situations are more complicated than the way they might be presented in a classroom – it can be hard to identify the ‘best’ solution when you have to deal with timescales, differing opinions, budgets and other constraints.” “There is a learning opportunity for our people as well as for the students,” says McNamara. “I see light bulbs going off for our people when students bring new ideas into the room. All the departments are very ready and willing to host students again because they really gain value from it.” Find out more about IfM’s manufacturing education programmes at www.ifm.eng.cam.ac.uk/education

STIM Consortium The Strategic Technology & Innovation Management (STIM) Consortium is a practice-oriented research and networking collaboration between industrial member companies and the Centre for Technology Management.

Members of the Consortium benefit from:

We are launching the next yearâ&#x20AC;&#x2122;s annual programme on 21st November 2019. If you are interested in attending this event, or finding out more about joining the STIM Consortium, please contact Dr Robert Phaal rp108@cam.ac.uk or visit www.ifm.eng.cam.ac.uk/research/ctm/stim.

a The opportunity to influence the direction of research and development, with the associated early benefits gained through participation in case studies and application pilots.

a Access to a network of firms from a range of industry sectors to share experience through a regular series of meetings and engagement in individual research projects.

a Transfer and application of methods developed, enabled by guidance notes and training packages.

Uncertainty. Complexity. Disruption. With change comes challenges â&#x20AC;&#x201C; and opportunity. IfM Education and Consultancy Services provides consultancy, based on the latest IfM research, to help organisations navigate change, seize opportunities and manage risk. We work with some of the worldâ&#x20AC;&#x2122;s leading companies to help them: a Turn R&D into successful products and services a Make sure their technology strategy supports their business strategy a Optimise their production and supply networks a Grow their service business a Develop their talented leaders and managers into people who can see the big picture and make things happen We work with governments to: a Understand the manufacturing landscape a Develop roadmaps for key sectors and technologies

To find out more about how we can work with your organisation, please contact David Lott: T: +44 (0) 1223 338174 E: dl362@cam.ac.uk

a Reconfigure sector supply chains a Provide policy advice and consultancy

ISSUE 6 | P37

IfM COURSES & EVENTS IfM short courses introduce participants to IfM tools and techniques, showing them how they can be put into practice in highly interactive, hands-on courses.

a Making The Shift To Services 26–27 November 2019, IfM, Cambridge Drawing on the latest work from the Cambridge Service Alliance, this thought-provoking and practical two-day workshop considers how to design the shift to services. a Digitalisation Of End-To-End Supply Chains 25 February 2020, IfM, Cambridge This course helps attendees develop a strategic approach to identifying, integrating and developing supply chains, through supply network configuration and digitalisation. a Strategic Roadmapping 17–18 March, 9-10 June & 13-14 October 2020, IfM, Cambridge A thorough introduction to strategic roadmapping, guiding participants through each step of the roadmapping process. a Technology & Innovation Management 24–26 March 2020, Møller Centre, Cambridge This intensive three-day course will help managers to understand and to use the key tools and techniques needed to manage and exploit technological investments and opportunities. a Making The Right Things In The Right Places 13–14 May 2020 , IfM, Cambridge This two-day course will help attendees to reconfigure their company’s international footprint of manufacturing activities to deliver real business impact. a CIM Symposium 2020 17–18 September 2020, Møller Centre, Cambridge This annual conference provides the chance to hear from world-leading business figures and thinkers on the challenges facing modern manufacturing, across global networks and supply chains. To find out more about these events and to book, please go to www.ifm.eng.cam.ac.uk/events/ or contact ifm-events@eng.cam.ac.uk.

IfM BRIEFINGS A new series of short, thought-provoking seminars that tackle real challenges with insights from world-leading manufacturing researchers and practitioners. Each event is tailored to a defined audience, focusing on a specific topic, bringing together expertise in that topic to address common challenges in manufacturing. For upcoming Briefings please visit: www.ifm.eng.cam.ac.uk/events/ifm-briefings

Institute for Manufacturing, 17 Charles Babbage Road, Cambridge, CB3 0FS, UK +44 (0)1223 766141 | ifm-enquiries@eng.cam.ac.uk | www.ifm.eng.cam.ac.uk | Twitter @IfMCambridge | youtube.com/ifmcambridge