Decoding business model transformation

"There is nothing permanent except change” – Heraclitus

Businesses like predictability and familiarity. These are qualities that enable effective planning, budgeting, and implementation. 

Unfortunately, predictability is not always a quality of the real world. The real world is often characterized by volatility, unpredictability, complexity and ambiguity (what we call VUCA). This has never been more so than today, where the forces of digitalization and mass connectivity have accelerated the pace of change, ushering in new ways of working, communicating, and collaborating.

This technological transformation is precipitating an upheaval in business infrastructure and behavior no less radical than the industrial revolution. And on top of these fundamental structural changes, there have been more unexpected geopolitical shocks, most recently in the form of a global pandemic and the war in Ukraine. These can have profound consequences for business-as-usual.

“Around 80% of existing business models were already at risk,” says Florence Verzelen, Executive Vice President, Industry, Marketing and Sustainability at Dassault Systèmes. “Across the past three years, we've seen a lot of crises, all of which have impacted manufacturing business models. For example, many businesses ran on low-stock, just-in-time models,” she says. “COVID-19 and the Russian invasion of Ukraine have highlighted the fragility of these approaches.”

So what can businesses do amid such seismic shifts to encourage business resiliency? How can business model innovation be effectively pursued? Well, innovation, from sustainable innovation to commercial innovation, increasingly means making the most of your data.

This starts with collecting, standardizing, and analyzing it in a way that means it can be effectively utilized. From supply chain to sales, design to distribution, manufacturers produce huge amounts of data. Having all this information in the right state enables businesses to make decisions far beyond next quarter’s budget, and allows for successful business model innovation.

“The most logical next step in using data to manage this scale of transformation is the virtual twin,” says Florence Verzelen. “Take your products, for example. If you have a virtual twin of your product, you can optimize it at the design stage, boosting its quality and durability – and help reduce its environmental footprint. But you can also model the whole post-sales life of that product, looking at how it might need to be maintained, how its components could best be recycled when it has reached its end of life, and what its second or third lives could be.

“The value of virtual twins also extends into your operations. If something goes wrong in your supply chain, for instance – say if one of your suppliers comes and says, ‘we’re out of semiconductors’ – you can turn to your virtual twin and experiment with new models, risk-free, and use that information to find new suppliers or logistics arrangements and get your operation back up and running.”

But what is an example of how we can respond to business model transformation?

"What does this approach to business model transformation look like in practice? Let's look at an example,” Florence Verzelen continues. “Consumer electronic goods have many challenges. Having the virtual twin of your computer allows you to create a computer that is sustainable, or circular, by design.” 

“What does that mean? It means that if I'm doing the design of my computer in the virtual world and working on the virtual twin, I'm able to plan for the second, the third, the fourth life of each component of my computer and make sure every part is circular.”

If businesses are going to thrive in a world of metamorphosing physical and commercial realities, they need to be clearsighted about the landscape they are in and about the changes they need to make. Change is inevitable.