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Digital twins – how to get there faster – and without friction

Mariia Nalapko
5 Jul 2022

Building digital twins into a frictionless business model enables it to not only respond to the immediate circumstances it is designed to address – but to entire function of which it forms part.

In the first article in this short series, we looked at what’s driving the adoption of digital twins, and at the extent to which value and sustainability goals are being realized. In this, the second and final article, we’ll look at how a digital twin works in an integrated model, and at how the transformation this model delivers can be accelerated.
It doesn’t matter if digital twins are replicating physical processes such as manufacturing or logistics, or whether they replicate other areas of business, such as HR, customer operations, and finance. In every case, a digital twin delivers most value, commercially and also in terms of sustainability, when everything is connected. At Capgemini, we call that model the Frictionless Enterprise.
To accelerate the deployment of a digital twin and to achieve benefits sooner, it’s good to do some groundwork. In a recent report called “Digital Twins: Adding Intelligence to the Real World,” the Capgemini Research Institute (CRI) identified the following areas worthy of investment in order to drive transformation at scale.

Develop a stepwise long-term roadmap

It of course makes sense to start out in developing digital twins by addressing repetitive pain points or strategic issues, because that’s the quickest way to see results. But it makes sense at the same time to put a roadmap in place. This will help the organization identify the gaps in each function of the organization, and the enablers (such as data management and skillsets) that will be needed to plug those gaps. The roadmap can also scope anticipated value and sustainability outcomes.

Set up well-balanced governance

While it’s true that digital twins can and should be designed to address the key issues first, that doesn’t mean the approach should be piecemeal. A well-planned governance structure that covers the management of all the digital twins used by an organization helps to avoid developments descending into chaos, and introduces and sustains a necessary level of consistency.

Strengthen enablers for scaling

The foundations on which the scaling of digital twin deployments should be built are consistent with the principles of the Frictionless Enterprise . They are as follows:

  • Secured connectivity – to ensure continuity of information from edge to cloud, from design to operations and services
  • Data management – digital twins need to mine, model, simulate, predict, and monitor effectively, which necessitates integration with multiple data sources. Scaling makes this harder still, and so organizations must develop a data management strategy to qualify the right data; to understand the data flows across various systems and processes; and to transform the data into actionable insights
  • Capabilities – organizations will also need to strengthen skillsets in areas including design and operations. Given the importance of removing friction from the equation, building collaborative skills all along the value chain, across both internal and external ecosystems, is also a prime requirement
  • User experience and user interface – an intuitive UX/UI is necessary to exploit the full potential of smart, connected systems and processes in the field.

Anticipate and enable end-to-end integration

As we’ve seen in principle, the transformation that digital twins can bring to business processes is predicated on cohesiveness – on removing friction beyond the immediate scope of the twin. In practice, and to anticipate and enable this goal, what’s needed is a single and up-to-date source of truth, federating:

  • Cold data (such as historical information, system specifications and models)
  • Hot data (such as IoT data, operational data, and real-time events)
  • Descriptive data (such as GISs)
  • Transactional data (such as ERP)

Digital twins are an the technology-agnostic concept. The approach to implementing a digital twin should be flexible, and should be able to offer advanced data services such as: modeling and simulation, intuitive visualization, analytics and AI/ML, and event orchestration services to efficiently manage predictive/preventive alerts or real-time incidents.

Enhance data security and privacy

Digital twins replicate real-world systems, and hence are privy to operational and possibly strategic information that may be highly sensitive. Unauthorized access to this information could compromise not only the performance of the twin, but the integrity of business functions. Communication between the twin and its physical counterpart therefore needs to be absolutely secure – which is why almost three-quarters (73%) of respondents to the CRI report said they were making changes to their end-to-end cybersecurity to accommodate digital twins.

Empower the ecosystem

A fully frictionless model encompasses enterprise processes from end to end – but it also extends beyond that, and out into the organization’s ecosystem of suppliers, technology partners, and customers. The greatest value of a digital twin comes from being able to predict or simulate the impact of a particular change on this entire network of partners.

Droughts, famine, plague, floods storms, heat, new diseases are all caused by climate change and all impact business cash flow. Sustainability mitigates against external risks – a company that doesn’t is exposed . This is possible only when data or inputs from or about partners can be fed into the digital twin, which is why it’s a good idea for organizations to include their partners in the process.

The ultimate digital twins?

In summary, then, building a digital twin into a frictionless business model means that it can more accurately reflect real-world scenarios, because it is responding not just to the immediate circumstances it is being designed to address, but to entire function of which it forms part – whether that be HR, customer operations, finance, or processes in the physical world, such as manufacturing or supply chain operations.

In fact, digital twins may in time be able to go even further. The CRI report tells us that work is under way to create a digital twin of the entire planet, to help combat climate change by simulating the atmosphere, the oceans, and also human systems. If that’s possible, then creating a digital twin of an entire global enterprise is surely also only a matter of time.

To learn more about how implementing a digital twin can help your organization to drive improved business operations and transition to the Frictionless Enterprise, contact:  


Mariia Nalapko

Digital Twin Global Process Owner, Capgemini’s Business Services
Mariia Nalapko focuses on digital transformation and enablement, developing Digital Twin & Transformation and Innovation Office (TIO) concepts, ways of working, and delivery.