Virtual twins drive innovation and democratize knowledge

Combining the experience economy, where experiences matter more than products, with the circular economy, focused on reducing, reusing, and recycling, leads to a generative economy. This shift is vital to meet global needs while preserving the planet. To succeed, enterprises must evolve beyond current digital transformations.

The generative economy model creates continuous value through innovation, while also being a powerful means to address social and environmental challenges. Given that knowledge and innovation are important foundations in this model, it’s no surprise that thriving in a generative economy will require enterprises to leverage data to make better decisions.

This requires providing every team member with access to comprehensive data and knowledge to power innovation, within a collaborative environment that enables people to share results and act across the enterprise. This democratization of knowledge-driven decision-making will empower people and accelerate innovation, fostering more agile organizations and freeing up time to focus on the company’s largest, mission-critical challenges.

At Dassault Systèmes, we believe the virtual world will extend and improve the real world – and we anticipate experiences powered by virtual twins will be at the heart of this transformation.

Beyond the digital twin

Many companies – across all sectors, but led by those in aviation, automotive, and general manufacturing – are familiar with digital twins.

There’s no question digital twins have proven their worth. As the Capgemini Research Institute noted in its 2021 report Reflecting reality, organizations using digital twins enjoyed, on average, a 15% growth in key sales and operational metrics, an improvement in system performance of more than 25%, and a 16% boost to sustainability.

That said, digital twins rely on data generated in the past, even as they’re used to predict the future. Virtual twins are extending the possibilities. Virtual models powered by generative AI allow us to contextualize and elevate data into a unified, normalized representation of complex objects, systems, or factories.

In addition to providing a common referential for understanding, learning, and predicting, this approach unleashes the power of simulation to enable “What if” scenario modeling.

Data, decisions, and operations

Virtual twins are a blend of three important components:

• The digital model – an advanced representation of the product, the factory, or the enterprise. This model can be a 3D representation, a system model, or an ontology.
• Real-world data from across the enterprise’s ecosystem and beyond, fully contextualized, projected on the virtual twin, and available anytime, anywhere, via any device.
• People and processes, through powerful built-in collaboration methods and tools.

This ability to reduce the gap between data, decisions, and operations is the key that will enable companies to imagine, build, and deploy innovative new products and services.

Virtual twins are already transforming innovation at companies in many industrial sectors. Here are a couple of examples drawn from clients who are using the NETVIBES solution.

Superior supply management: In the manufacturing sector standards, regulations, and competition are raising expectations for automotive manufacturers. Every design decision is weighed against large sets of critical KPIs, and designers must balance price, weight, CO2 emissions, safety, and other vital criteria. With MOD/SIM/DATA and AI, designers can easily understand the impact of their decisions on all criteria. They can leverage knowledge, supplier value chain content and catalogues, procurement, logistics, best practices, new material specifications and other data to select the most relevant combination to create a better product. AI-enabled virtual twins help navigate this complexity and provide a new level of synthesis to guide decisions. Dassault Systèmes provides a major global automaker with a unique combination of artificial intelligence, machine learning, collaborative business processes, and an enriched single 3D data model of each vehicle. This helps the client better manage the business impacts of market volatility. The automaker can aggregate equipment designs, configurations, historical data, and forecasts to test different design scenarios in a virtual twin. The company can understand, anticipate, quantify, and optimize vehicle price and cost, and improve equipment-purchasing negotiations by sharing these insights with other stakeholders.

Better project oversight: In the infrastructure & cities sector – encompassing nuclear, oil and gas, and renewable energy – we use virtual twin experiences to help clients elevate data, from engineering and construction to operation and maintenance. Virtual twins are a game changer, providing science-based models for interpreting, understanding, and contextualizing real-world data from sensors. AI is accelerating this by helping customers learn from the past to navigate the future through predictive models, such as anticipating deviation risks in construction phases. An example of this is our work with India-based L&T Hydrocarbon.

“Virtual models powered by generative AI allow us to contextualize and elevate data into a unified, normalized representation of complex objects, systems, or factories.”

Maximizing the virtualization of knowledge

The virtual twin experience is the enabler to transform implicit information and know-how into explicit and actionable knowledge. At Dassault Systèmes, we provide our customers with virtual twin experiences that help them think and operate in a generative way and create new, net positive business models. Our virtual twin solutions build on our AI-augmented Industry Solution Experiences by leveraging the current acceleration of AI to maximize an enterprise’s ability to virtualize knowledge. This provides clients with fresh opportunities to leverage their employee know-how and other corporate assets to drive innovation.

The generative economy will extend the experience economy with sustainability and other imperatives. This will have a major impact on the way organizations work and will require connections between silos of people who don’t share the same backgrounds and expertise. The virtual twin experience will not only trigger this transformation, it will enable it to succeed – and organizations must start implementing such solutions now to ensure they’re prepared for future growth.

Innovation takeaways

The innovation imperative

Sustainability is making innovation even more important – and is just one factor disrupting current economic models. Companies must embrace solutions like virtual twins powered by AI to succeed in this rapidly evolving environment.

Turn data into a corporate asset

Companies must provide all employees – not just leaders and experts – with the ability to make informed, knowledge-driven decisions. Virtual twins leverage data and AI to enable a common understanding, shared learning, and coordinated, effective action.

Enterprises don’t exist in a bubble

True innovation and competitive advantages will increasingly require companies to understand information in context, then deploy solutions specifically designed to help leverage the insights derived from this contextualized data.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 8 features contribution from leading experts from Capgemini and esteemed partners like Dassault Systèmes, Neo4j, and The Open Group. Delve into a myriad of topics on the concept of virtual twins, climate tech, and a compelling update from our ‘Gen Garage’ Labs, highlighting how data fosters sustainability, diversity, and inclusivity. Embark on a voyage of innovation today. Find all previous Waves here.