Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More
Digital twin implementations are already demonstrating a 76% cost reduction and a 68% increase in customer engagement. And digital twin adoption is predicted to increase by 36% in the next five years. However, only 13% of organizations have developed full-scaled digital twin strategies.
These are the findings of a recent Capgemini survey on digital twin adoption. The systems’ integration consultancy launched the survey to tease apart why so many companies struggled with the technology, despite the tremendous gains of early adopters.
The top challenges for bridging this gap include developing a long-term roadmap, cultivating the right skills and building the appropriate partnerships. The payoff for doing these right is immense. Leading firms are seeing a 15% increase in sales, turnaround time and operational efficiency and a 25% improvement in system performance.
Why digital twins?
Capgemini had a previous focus on AI, edge computing, IoT and analytics, which are all crucial for digital transformation. Brian Bronson, president of Americas and APAC at Capgemini Engineering, told VentureBeat they realized that digital twins are also central to intelligent industry trends, such as changing customer preferences, growing regulatory pressures and increased concerns around carbon emissions.
Join us in San Francisco on July 11-12, where top executives will share how they have integrated and optimized AI investments for success and avoided common pitfalls.
One big driver is increasing concerns about sustainability. Capgemini found that digital twin leaders realized an average of 16% improvement in sustainability due to digital twins. Bronson said digital twins enhance scalability and promote the integration of products and services.
Sustainability benefits range from process efficiencies, reducing emissions and the ability to test the viability of new, sustainable materials.
“We are seeing many applications across industries such as urban planning, infrastructure, energy and utilities, auto, aviation, consumer products and healthcare,” Bronson said.
Bridging the gap
Despite the tremendous promise, many organizations struggle to get digital twin projects off the ground.
“We found that although 55% of organizations consider digital twins strategic in digital transformation, 42% lack vision on how to deploy them,” Bronson said.
A mismatch between long-term vision and operational governance creates various delays. For example, inefficient program management and lack of governance can derail the launch of a digital twin.
New skills required
Digital twins are built across multiple interconnected disciplines, which requires a unique set of skills that are not yet common. Jiani Zhang the chief software officer at Capgemini Engineering, told VentureBeat that enterprises need to engage or cultivate experts in data analysis, IoT, design and industry.
“Industry specialists must be comfortable with reinventing how people will interact with digital versions of what they know well,” Zhang said.
Designers need to understand and then express the value in the data that is collected, in addition to knowing the user and tasks intimately. IoT architects should consider the future needs and growth of the systems they build and advocate these requirements to the customer in the form of business models. Data scientists need to experiment, strategize and collaborate with business experts, designers and engineers.
“While we can certainly attract folks with the potential to do this work, it is very challenging to grow the kind of talent that can be both hyper-focused on their areas and broad enough to work well under the requirements of digital twin applications,” Zhang said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.