Virtual twin of territories: what does it take? Data, data, data

I was delighted to take part in the Brit_twin event organised by techUK on 22 January in London to discuss how to develop a digital twin of the nation. The discussions triggered a few key thoughts that I would like to share. I hope that this will give way to further exchanges, to ensure we can continue discussing the benefits of digital twins for urban planners and infrastructure managers, but also national and local government decision-makers and ultimately citizens living in UK cities & territories.

A Digital Twin can be interpreted in many different ways. At the Brit_Twin event, it was referred to as:

  • One unique Referential
  • Holistic planification environment
  • Simulation mock-up
  • Real Time Data hyper vision system
  • Predictive analysis 

In many ways, digital twins are a combination of all of these, but behind these different concepts, one pervasive and universal element is pivotal: data. For manufacturers and service providers as well as for public entities today, this element is key to support the complexity of the products they are designing and the services they are deploying/offering to the public. The challenging conditions of the markets, in which they operate, make these data more and more complex.

I recall that one of Dassault Systemes’ customers once challenged one of our solutions and the CEO asked their teams: “We have been making our products for the last 90 years, we digitalized all our processes over the last 30 years, and I see no big change with our delivery times …so audit the software solution, and tell me if it is the right one for us”. Three months later the team came back to their leader and explained: It is fair to say that so far we haven’t improved our performance in terms of delivery times, but without this digital solution:

1) we wouldn’t be able to manage the complexity of the design and production of our products,

2) we wouldn’t be able to be competitive on the market today”. 

3) we wouldn’t have reach this level of value and experience for our customers”. 

This point helps to illustrate that, - and of course there are a variety of solutions in many domains- digitalisation is key to manage the complexity of the world we are living in today. It is the same for a territory or a city, which has to deliver services to its citizens, while those services are becoming more and more complex. This complexity is coming from the amount and diversity of information we have to understand, integrate & digest. This is why a blueprint has to be put in place to manage this information. To build it, we have to start with the basics: the use cases we want to address (Mobility, Resilience, Demography,…). Different methods can be used to build them, such as Design Thinking or “Experience Thinking” that a company like Dassault Systèmes provides through our Design Studio consulting services. It helps illustrate and describe precisely the experience these organisations ultimately aspire to provide to their final customers.

When these use cases are defined, we can use digital twins to set all the services needed to operate them and bring together all the stakeholders that are needed to make things happen. And it’s only once these two phases have been rolled out, that you can evaluate the data you will need to produce and deliver your experiences.

Nowadays, all information has to be digital. However, it is not always the case. Private companies and public entities will need a certain level of agility to transform this information into real digital data, step by step.

We can generate data with the following methods:

  • Scanning of 2D or 3D documents/information
  • On-line B to C services
  • Native internal documents (XLS, Word, PDF, IFC, CityGML,…)
  • IoT and real time data
  • The most important of all, the digitalization of the processes

If we speak about data and digital twins, it is also imperative to establish a robust framework to guarantee a rigorous data governance. Efficiency and security rhyme with data governance.

To set a powerful governance model, the following pillars are necessary:

  • Sovereignty : Data sovereignty is key to ensure data protection and long-term investment
  • Third party trusted partner : confidence between all the stakeholders can only happen if the repository where data will be shared is hosted by a trusted player. This is where public entities have their role to play.
  • Regulation & Laws
  • Management of the data life cycle
  • A platform to make it happen (Collaboration, Security, Referential)

To conclude, three key elements are needed to establish a digital twin: 1) use cases, 2) data, 3) governance. 

Another one will be value (the value of data, but also of what digital twins bring to different stakeholders, etc.) and I will delighted to dwell on the concept of value in more depth in another blog post.

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