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The bigger and more complicated the engineering problem, the more likely it is to have a digital twin. Firms that build rockets, planes and ships, for example, have been creating digital twins since the early 2000s, seeing significant operational efficiencies and cost-savings as a result. To date, however, few firms have been able to realise the full potential of this technology by using it to develop new value- added services for their customers. We have developed a framework designed to help scale the value of digital twins beyond operational efficiency towards new revenue streams. In spite of the hype surrounding digital twins, there is little guidance for executives to help them make sense of the business opportunities the technology presents, beyond cost savings and operational efficiencies. Many businesses are keen to get a greater return on their digital twins’ investment by capitalising on the innovation – and revenue generating - opportunities that may arise from a deeper understanding of how customers use their products. However, because very few firms are making significant progress in this regard, there is no blueprint to follow. New business models are evolving but the business opportunities for suppliers, technology partners and end-users is yet to be fully documented. Most businesses will be familiar with the business model canvas as a tool to identify current and future business model opportunities. Our ‘Four Values’ (4Vs) framework for digital twins is a more concise version of the tool, developed to help executives better understand potential new business models. It was designed from a literature review and validated and modified through industry interviews. The 4Vs framework covers: the value proposition for the product or service being offered, the value architecture or the infrastructure that the firm creates and maintains in order to generate sustainable revenues; the value network representing the firm’s infrastructure and network of partners needed to create value and to maintain good customer relationships; and value finance such as cost and revenue structures. Value proposition The value proposition describes how an organisation creates value for itself, its customers and other stakeholders such as supply chain partners. It defines the products and services offered, customer value (both for customers and other businesses) as well as the ownership structure. Examples of digital twin-based services include condition monitoring, visualization, analytics, data selling, training, data aggregation and lifespan extension. Examples of customer value in this context might include: decision support, personalisation, process optimisation and transparency, customer/operator experience and training. Value architecture The value architecture describes how the business model is structured. It has 5 elements: 1. Value control is the approach an organisation takes to control value in the ecosystem. For example, does it exist solely within its own ecosystem of digital twin services or does it intersect with other ecosystems? 2. Value delivery describes how the digital twins are delivered, are they centralised, decentralised or hybrid? It also seeks to understand any barriers that may prevent the delivery of digital twins to customers. 3. Interactions refers to the method of customer interaction with the digital twin. Common examples of interaction include desktop or mobile app, virtual reality and augmented reality interactions. 4. Data collection underlies the digital twin value proposition and can be a combination of the following: sensor based and/or supplied/purchased data. 5. Boundary resources are the resources made available to enhance network effects and scale of digital twin services. This typically comprises of the following: APIs, hackathons, software development toolkits and forums. Value network The value network is the understanding of interorganisational connections and collaborations between a network of parties, organisations and stakeholders. In the context of digital twin services, this is a given as the delivery mechanism relies on multiple organisations, technological infrastructure and stakeholders. Value finance This defines how organisations approach costing, pricing methods and revenue structure for digital twins. Digital twin revenue model most commonly refers to outcomes-based revenue streams and data-driven revenue models. Digital twin pricing models include, for example, freemium and premium, subscription models, value-based pricing and outcome-based pricing models. Four types of digital twin business models were identified from extensive interviews with middle and top management on services offered by digital twins, we identified four different types of business models and applied our 4Vs approach to understand how those models are configured and how they generate value. Brokers These were all found in information, data and system services industries. Their value proposition is to provide a data marketplace that orchestrates the different players in the ecosystem and provides anonymised performance data from, for example, vehicle engines or heating systems for buildings. Value Finance consists of recurring monthly revenues levied through a platform which itself takes a fee and allocates the rest according to the partnership arrangements. Maintenance-optimisers This business model is prevalent in the world of complex assets, such as chemical processing plants and buildings. Its value proposition lies in providing additional insights to the customer on the maintenance of their assets to provide just-in-time services. What-if analysis and scenario planning are used to augment the services provided with the physical asset that is sold. Its Value Architecture is both open and closed, as these firms play in ecosystems but also create their own. They control the supply chain, how they design the asset, how they test it and deliver it. Its Value Network consists of strategic partners in process modelling, 3D visualisation, CAD, infrastructure and telecommunications. Value Finance includes software and services which provide a good margin within a subscription model. Clients are more likely to take add-on services that show significant cost savings. Uptime assurers This business model tends to be found in the transport sector, where it’s important to maximise the uptime of the aircraft, train or vehicle. The value proposition centres on keeping these vehicles operational, either through predictive maintenance for vehicle/ aircraft fleet management and, in the case of HGVs, route optimisation. Its Value Architecture is transitioning from closed to open ecosystems. There are fewer lock- in solutions as customers increasingly want an ecosystems approach. Typically, it is distributors, head offices and workshops that interact with the digital twin rather than the end-customer. The Value Network is open at the design and assembly lifecycle stages but becomes closed during sustainment phases. For direct customers digital twins are built in-house and are therefore less reliant on third-party solutions. Its Value Finance is focused on customers paying a fee to maximise the uptime of the vehicle or aircraft, guaranteeing, for example, access five days a week between certain hours. Mission assurers This business model focuses on delivering the necessary outcome to the customers. It tends to be found with government clients in the defense and aerospace sector. Value propositions are centered around improving efficacy of support and maintenance/ operator insight and guaranteeing mission success or completion. These business models suffer from a complex landscape of ownership for integrators of systems as much of the data does not make it to sustainment stages. Its Value Architecture is designed to deliver a series of digital threads in a decentralised manner. Immersive technologies are used for training purposes or improved operator experience. Its Value Network is more closed than open as these industries focus on critical missions of highly secure assets. Therefore, service providers are more security minded and careful of relying on third-party platforms for digital twin services. Semi-open architecture is used to connect to different hierarchies of digital twins/digital threads. Value Finance revealed that existing pricing models, contracts and commercial models are not yet necessarily mature enough to transition into platform-based revenue models. Insights as a service is a future direction but challenging at the moment, with the market not yet mature for outcome-based pricing. For B2B service-providers who are looking to generate new revenue from their digital twins, it is important to consider how the business model should be configured and identify major barriers to their success. Our research found that the barriers most often cited were cost, cybersecurity, cultural acceptance of the technology, commercial or market needs and, perhaps most significantly, a lack of buy-in from business leaders. Our 4Vs framework has been designed to help those leaders arrive at a better understanding of the business opportunities digital twin services can provide. We hope this will drive innovation and help digital twins realise their full business potential. Now for a small request to the reader that has reached this far, we are looking to scale these research findings in our mass survey across industry on the business models of digital twins. If your organisation is planning to implement or has already started its journey of transformation with digital twins please help support our study by participating in our survey. Survey remains fully anonymised and all our findings will be shared with the DTHub community in an executive summary by the end of the year. Link to participate in the survey study https://cambridge.eu.qualtrics.com/jfe/form/SV_0PXRkrDsXwtCnXg

PRESS RELEASE With the announcement that the Digital Twin Hub will transition to an Industry/Catapult partnership housed at the Connected Places Catapult (CPC), we are pleased to add that the next phase of the National Digital Twin programme’s Climate Resilience Demonstrator (CReDo) will also move to CPC. This next phase will build on the excellent efforts of the interdisciplinary and cross-sectoral team who worked on CReDo so far. This work is being shared openly to contribute to a culture of secure data sharing for the purposes of resilience and adaptation to climate change. The first phase of CReDo, showing the benefits of connected digital twins across infrastructure networks on adaptation and resilience, is coming to a close at the end of March. This phase of the project, funded by UK Research and Innovation, the University of Cambridge and CPC, wrapped up with a public webinar on 2nd March 2022, which was attended by over 240 participants and featured insights from the technical development team, funders and asset owners. So far, CReDo has demonstrated how collaboration through connected digital twins is key to tackling climate change. The project is marking the move into its next phase at CPC with a series of outputs that will share key findings, benefits, lessons learned and the technical approach to this first-of-its-kind collaboration. These are all openly available on the Digital Twin Hub from today. Discussing the urgency for collaboration through connected digital twins, Sarah Hayes, Head of the CReDo project, said: “The risks arising from failing to adapt to climate change are huge. CReDo seeks to mitigate these risks by increasing our understanding of infrastructure interdependencies and the future impact of interventions to increase resilience. The CReDo team have worked incredibly hard to lay the foundations for increasing infrastructure system resilience. It is the skills of our people, supported by new technologies, which will take forward our capability to tackle climate change through connected digital twins.” Pointing to the potential for this work to have a positive impact, Mark Enzer, Head of the National Digital Twin programme, said: “In a wonderfully tangible and relevant way, CReDo has shown the value of enabling secure information flow across sector boundaries. But this should be just the beginning. The idea of connecting digital twins must be extended to other sectors and other use cases – not only in addressing climate change, but wherever we need to understand systems better and intervene more effectively. I believe in CReDo!” Looking forward to the next phase of the project, Yalena Coleman, Director of Applied Data & Technology at CPC, said, “Integrated infrastructure is a key strategic focus area for Connected Places Catapult, and we will be investing in further phases of CReDo, working together with partners to take forward the key learnings from this phase. We will ensure the learnings are shared with the wider community and across other relevant initiatives like the Digital Connectivity Infrastructure Accelerator, National Underground Asset Register and others; and link up industry, academia and government thinking in this area.”

A digital twin is a digital representation of something that exists in the physical world (be it a building, a factory, a power plant, or a city) and, in addition, can be dynamically linked to the real thing through the use of sensors that collect real-time data. This dynamic link to the real thing differentiates digital twins from the digital models created by BIM software—enhancing those models with live operational data. Since a digital twin is a dynamic digital reflection of its physical self, it possesses operational and behavioral awareness. This enables the digital twin to be used in countless ways, such as tracking construction progress, monitoring operations, diagnosing problems, simulating performance, and optimizing processes. Structured data requirements from the investor are crucial for the development of a digital twin. Currently project teams spend a lot of time putting data into files that unfortunately isn’t useful during the project development or ultimately to the owner; sometimes it is wrong, at other times too little, or in other cases an overload of unnecessary data. At the handover phase, unstructured data can leave owner/operators with siloed data and systems, inaccurate information, and poor insight into the performance of a facility. Data standards such as ISO 19650 directly target this problem that at a simple level require an appreciation of the asset data lifecycle that starts with defining the need in order to allow for correct data preparation. Implementing a project CDE helps ensure that the prepared data and information is managed and flows easily between various teams and project phases, through to completion and handover. An integrated connected data environment can subsequently leverage this approved project data alongside other asset information sources to deliver the foundation of a valuable useable digital twin. To develop this connected digital twin, investors and their supply chains can appear to be presented with two choices: an off-the-shelf proprietary solution tied to one vendor or the prospect of building a one-off solution with risk of long term support and maintenance challenges. However, this binary perspective is not the case if industry platforms and readily available existing integrations are leveraged to create a flexible custom digital twin. Autodesk has provided its customer base with the solutions to develop custom data integrations over many years, commencing with a reliable common data environment solution. Many of these project CDEs have subsequently migrated to become functional and beneficial digital twins because of a structured data foundation. Using industry standards, open APIs and a plethora of partner integrations, Autodesk’s Forge Platform, Construction Cloud and recently Tandem enable customers to build the digital twin they need without fear of near term obsolescence or over commitment to one technology approach. Furthermore partnerships with key technology providers such as ESRI and Archibus extend solution options as well as enhancing long term confidence in any developed digital twin. The promises of digital twins are certainly alluring. Data-rich digital twins have the potential to transform asset management and operations, providing owners new insights to inform their decision-making and planning. Although digital twin technologies and industry practice are still in their youth, it is clear that the ultimate success of digital twins relies on connected, common, and structured data sources based on current information management standards, coupled with adoption of flexible technology platforms that permit modification, enhancement or component exchange as the digital twin evolves, instead of committing up front to one data standard or solution strategy.

The Cyber-Physical Infrastructure Vision was launched on the 11th February 2022 on the DT Hub. Watch the webinar and read the vision. Humanity faces pressing planetary scale challenges including the climate emergency, resilience to unexpected shocks, consumption, security, healthcare, food, and many others. The UK punches above its weight but we are competing with other countries with more data, more resources, more money and sometimes political advantages too. So as a nation we need to find new ways to create leverage and defensible competitive advantage. To respond to these challenges and opportunities, we need to reframe the concept of infrastructure. This is not just buildings, roads, railways and fibre broadband to rural communities, it is also the enabling cyber-physical infrastructure that is often overlooked. Big vertical initiatives and missions lack the time, budget, capabilities and often the vision to build this infrastructure for themselves, let alone to support other initiatives. Companies like Ocado, Rolls-Royce, Arup and Mott MacDonald are successful demonstrators of the transformative power of this cyber-physical infrastructure but they are the exceptions that we now need to make the norm. So a growing coalition of the willing, led by the Robotics Growth Partnership have been engaging with the government and other stakeholders on a vision for a national Cyber-Physical Infrastructure. Harnessing the power of technologies such as data, Internet of Things, synthetic environments, digital twins, smart machines and living labs, in combination with the tools, infrastructure and recipes that will enable us to work smarter, faster, with less risk and at lower cost. The vision for this Cyber-Physical Infrastructure was published on 11 February 2022 and is available on the gov.uk website via the following link.

Ali Nicholl and Sophie Peachey (IOTICS) present a Feature Focus on Cooperative Ecosystems - Evolution of Trust

Digital twins can help organisations achieve various goals. In some cases, the end goal is for buildings and infrastructure to last longer, use less energy, and be safer. In others, it is enhancing the lives of people who interact with the built environment and its services. As highlighted by the Gemini Principles, these are not mutually exclusive aims, so wherever you are on your digital twin journey, it is important to consider other perspectives on the hybrid digital and physical systems you create. How will your digital twin fit into a wider ecosystem that provides services to all kinds of people? How will your asset’s performance impact the wider built environment and those who need to navigate it? Whose lives will be better if you share data securely and purposefully. In the first output from the Digital Twin Journeys series, the team working on the Smart Hospital of the Future research project, enabled by the Construction Innovation Hub, shared case studies from two smart hospitals and reflect on the innovations they saw during the COVID-19 pandemic. In this two video mini-series, the research team shares insights about how existing digital maturity enabled these hospitals to respond to the pandemic in agile ways, transforming to a hybrid physical and digital model of care distributed across multiple sites. They also explored how individual asset digital twins fit into a wider landscape of ecosystem services, guiding how we approach interoperability to achieve better outcomes. These insights inform the way we think about the role of digital twins in the smart built environments of the future. Dr Nirit Pilosof reflects that, ‘Digital twin as a concept can promote the design of the new system, the design process of the built environment and the technologies, but also really help operate… the hybrid models looking at the physical and virtual environments together.’ If health care is enabled by connected digital twins, how could the design of hospitals – and whole cities – change? In the videos, the team also discusses the limitations and ethics of services enabled by digital data and the use of digital technologies to improve staff safety, from isolated COVID wards to telemedicine. They frame service innovation as an iterative and collaborative process, informed by the needs of digital twin users, whether those are the asset owners and operators, or the people benefitting from the services they provide. According to project co-lead Dr Michael Barrett, ‘The people who need to drive the change are the people who are providing the service.' After the COVID crisis, we can better recognise what we have learned from implementing digital services at scale, as more people than ever have relied on them. The team reflect that having the right people in the right roles enabled the smart hospitals in these cases to transform their services rapidly in response to the need. The same human and organisational infrastructure that is creating the smart hospital of the future is also needed to create the flexible, responsive built environments of the future. Digital Twin Journeys can start from the perspective of available technology, from a problem-solving perspective, or from the perspective of users experiencing a service ecosystem. The smart hospitals project demonstrates the value of the latter two approaches. Hospital staff were instrumental in shaping the digitally-enabled service innovation to keep them safe and offer better services on and offsite, but project co-lead Dr Karl Prince points out how people accessing those services have to navigate a variety of different services in the built environment to get there. As we begin to connect digital twins together, we need to consider not just our own needs but the needs of others that digital twins can address. For more on this project, including links to their publications, see the team’s research profile on the CDBB website. Keep up with the Digital Twin Journeys series on the CDBB website or here on the Digital Twin Hub blog.