How digital twins enable new business models and cooperation among equal partners
What have digital twins got to do with cooperation, collaboration and sustainability? Why is data of limited value without specialists to interpret it? And how much must enterprises invest in order to incorporate digital twins into their processes? TRANSFER explored these questions in an interview with digital transformation expert and academic head of the Ferdinand Steinbeis Institute (FSTI), Professor Dr. habil. Heiner Lasi. The conclusion is clear: every enterprise can benefit from the inexorable trend towards digital twins.
Professor Lasi, everyone’s talking about the importance of cooperation and collaboration. How can digital twins help?
Collaboration sounds easier than it actually is. In practice, you still usually have a client and a contractor – the traditional customer-supplier relationship. At the Ferdinand Steinbeis Institute, we’re firm believers that genuine collaboration can only come about between equal partners. This often requires an impartial moderator, which is where we come in. We like to talk about value creation ecosystems, by which we mean networks of partners where different enterprises bring their own specific strengths to the table in order to add value together.
Digital twins are particularly useful for enabling this type of cooperation between equal partners. Take the example of a pay-per-use model for couple of decades. They’re often seen as visual representations in a virtual reality context, or as simulation models that help to reduce failure rates, for example in predictive maintenance. But that doesn’t create a new business model in itself – or if it does, then only for the software provider. Banks that have attempted to offer pay-per-X models with dynamic financing have faced barriers such as a lack of access to the relevant machine data or a lack of technical know- how. When machine industrial or agricultural machinery –let’s say a combine harvester. There are lots of people who want to use this machine, and a single provider. But rather than just providing the machine itself, they offer a service package that includes insurance, maintenance, bank financing, manufacturer engagement and, if necessary, a repair service. In order for this to work, all the partners need to cooperate at the data level. The insurer needs transparency about the risks, the bank needs transparency about the residual value and the service engineers need transparency about the machine’s maintenance condition. The digital twin provides this crucial transparency, enabling each partner to play their part in the value creation process.
What’s so special about this approach?
Digital twins have been around for a manufacturers offer this type of model, if it’s controlled by the automation technology then it usually just amounts to a new form of leasing.
At the FSTI, we use a definition based on the Digital Twin Consortium definition: a digital twin is a data-driven representation of a real-world object, motivated by concrete potential to add value. Digital twins replicate real-world conditions and make it possible to alter them – they enable control of real-world processes. They thus provide an “abstraction and cooperation layer” that allows multiple partners to jointly control processes and provide services without requiring direct access to the automation technology.
Do digital twins always have to be large, complex projects?
Not necessarily. Projects that use the traditional definition of a digital twin as a complete model of a product, including its geometry, visualization, etc. will tend to be time-consuming and costly. But at the FSTI, we deliberately start small and pragmatic – typically with a specific business case like pay-per-use. We identify the status values that partners really need to deliver their service. This can often be fewer than ten data points, and this type of digital twin can be implemented rapidly and cost-effectively. The fact that many sensors send their data straight to cloud environments anyway means that no major IT investments are necessary – the entry costs are relatively low.
Many enterprises are reluctant to share their data with third parties. How do you address their concerns?
We make sure that the only data shared is the data needed for a particular business model and partner. But owning certain data is less important than being able put the data to good use. If we’re honest, we know that similar datasets exist in the US and China. The advantage we have in Europe is our technical expertise – the people who understand how flow rates or heat transfer coefficients work. They are able to interpret the data and turn it into knowledge. It’s this knowledge that makes the difference – not the data itself. But if we’re too hesitant to share data, we risk falling behind in this important future sector.
How can digital twins support sustainability?
The first way they can help is at the product development stage, by making future products more efficient. They can then enable energy-optimized – or more accurately carbon-optimized – operation when the product is in use. In addition, digital twins can be used to optimize entire systems rather than just individual machines. In a circular economy context, for example, we can track a product’s life history and manage its reuse in a targeted manner.
Does this mean that, in the future, almost everything will have a digital twin?
Undoubtedly. Digital twins are taking off all over the world. The FSTI works closely with the Digital Twin Consortium, and we’re seeing the concept being adopted across more and more sectors, from mechanical engineering and agriculture to critical infrastructure. It’s clear that things are heading in this direction. But we’re still at the point where enterprises can gain a genuine competitive edge from using digital twins.
Contact
Prof. Dr. habil. Heiner Lasi (interviewee)
Academic head of the Ferdinand Steinbeis Institute (Stuttgart/Heilbronn)
www.steinbeis.de/su/2277
www.steinbeis.de/su/2278