Digital twin offers immense opportunities. McKinsey estimates that digital twin technologies can increase revenue by 10%, accelerate time to market by 50%, and improve product quality by 25%.
The use of digital twin has “applications in virtually every aspect of industry,” according to Kevin Baker, an analyst focusing on Industry 4.0 in Orange Silicon Valley’s Business Group. From automotive and healthcare to insurance and construction, “any meaningful data products can be represented and…leveraged to gather insights, drive efficiencies and provide a more precise view of business operations.”
Baker was speaking as part of a panel on digital twin and its role as a foundation for Industry 4.0. He pointed out that digital twin doesn’t just cover physical objects but can also apply to processes. As Baker puts it, the deciding factor is the presence of data. “Any real-world entity could be virtually represented as long as there is data to represent.”
Digital twin challenges
But despite the benefits, challenges have slowed widespread adoption of the digital twin technology. The panelists summarized these as: initial investment, the lack of a clear business case and organizational silos.
It is important to remember that digital twin is a concept, not a technology. Many potential tools are used to deliver digital twin, from Internet of Things sensors and platforms to edge computing and artificial intelligence. For panelist Sameer Kher, Senior Director, Product Development at engineering simulation software company Ansys, this creates an early stumbling block. “You do need to sensorize your equipment, you do need to have the infrastructure for communication protocol…you need compute infrastructure, storage infrastructure.”
For many, that represents a significant start-up investment that won’t necessarily deliver a direct return, with any benefit coming through the eventual use of digital twin. This can be a hard sell to budget holders and other decision makers. Dan Isaacs, Chief Technology Officer at the Digital Twin Consortium, said, “some of the typical questions that we’re seeing…is where do I start and what is the ROI? How long is this going to take?”
This caution comes from what Isaacs identified as “a lack of real value-based use cases and understanding.” Added to this are the misconceptions about digital twins. More than one of the consortium’s members say customers have ten different definitions within their organizations.
That leads to organizational silos. Any digital twin deployment must fit into existing workflows and the general operation of the business. “Where does digital twin fit in that journey is the question being asked now by executive teams, IT leadership teams and certainly by lines of business,” said the fourth panelist Ken Carpenter, Vice President and Head of Partnerships at ParkourSC.
Digital twin not only needs to fit into existing ways of working, it also needs to span the entire organization. Kher said, “There is the engineering group that has domain knowledge, there is the operations group that’s going to benefit or the sales group that’s going to benefit, so spanning those sometimes can be challenging just because of the organizational boundaries and different platforms.”
Identifying use cases to scale success
To tackle these challenges, the panelists agreed that businesses must first identify their most pressing problems and work backward. Once they have a clear use case, they can, in the words of Carpenter, “figure out what kind of skills or technology sets they lack in order to go in and deploy digital twin.”
It’s a case of identifying “the job that you’re hiring a digital twin for, and then look at it, not in terms of the data or an architecture or an implementation…[but] what are the capabilities that are needed to fulfill that,” said Isaacs. This then highlights the technology needed to provide the data the company is looking for.
This creates an opportunity to secure quick wins, which can then be scaled out. For example, a business may only wish to monitor the condition of one piece of equipment to understand why there was unplanned downtime. Once the digital twin is in place and the company is clear on the problem, it could use the digital twin to anticipate when the issue might reoccur.
This is a route to realizing a return on investment quickly. It also creates an opportunity to unify understanding across the organization of what a digital twin is.
Building an ecosystem of digital twin partners
Of course, identifying what you need is one thing; acquiring it is another. As previously highlighted, digital twin deployments already require significant technology, much of which is relatively new. As such, a business may not have the requisite knowledge within its team nor the right relationships with appropriate vendors. Finding partners, therefore, can help anyone considering digital twin to take their first steps, as Kher noted. “This is going to definitely require partnerships and ecosystems…once you’ve identified the business problem, I think there’s quite a few different sorts of players that can help you.”
This need for partnership led international equipment manufacturer LACROIX Group to work with Orange Business on its state-of-the-art factory. Orange created an indoor 5G network that allows the Group to experiment with new applications and tap into the potential of innovations such as digital twin.
Listen to the full Orange Silicon Valley panel “Digital Twins – A Foundation for the Fourth Industrial Revolution,” or take a look at other digital twin resources from the Orange Group.
I am a technology writer with a decade of experience in business, technology and logistics. From starting off my career writing questions for a TV quiz show, I’m now spending my time looking at how the world of business is going digital and transforming a variety of sectors and industries.