Manufacturing is the next $180 billion metaverse opportunity

The not-so-little secret of the metaverse is that manufacturing can and should be one of its earliest and most lucrative adopters. Accenture is backing that belief by investing in “reality capture” and digital-twinning-tech firm Cintoo to help realize what it sees as a $180 billion opportunity. But to fully realize the value will demand the widespread adoption of the HFS OneEcosystem mindset.

Accenture Technology Europe Lead Yves Bernaert told visitors to the Lisbon Web Summit that he believes manufacturing will find valuable use cases faster than other sectors. The metaverse is an exceptional new way to visualize data, which is critical to understanding its value for manufacturing. Teams who can observe 3D digital twins of manufacturing processes in the metaverse can quickly see where problems occur, test new solutions virtually, and see the outcome of applying them before making any physical changes, saving time and costs.

Think of the metaverse as our best-yet 3D data visualization tool that unlocks a (real and virtual) world of new use cases. It follows the model of the HFS OneOffice Data Cycle in Exhibit 1, in which delivering data to the right people at the right time—and in the best possible format for decision making—is crucial.

Exhibit 1: The metaverse is our best-yet data visualization tool, opening a world of productivity enhancements in manufacturing.

Source: HFS Research, 2022

Five stages to manufacturing metaverse heaven

Yves laid out the following five stages of the adoption of the metaverse in manufacturing. To move beyond stage two depends on an ecosystem approach – sharing and connecting metaverse data across the supply chain to create new value outcomes.

Stage One: The journey for manufacturers starts with scanning in your current static state by acquiring a digital 3D image of one key part of your process. Digital twinning companies such as Cintoo do this using laser scanning technologies.

Stage Two: Add the live telemetry and other data acquisition technologies required to make your static digital twin a real-time replica of an element of your process. Building from the experience of your first steps, extend this to the whole production line to model its behavior over time for trend analysis. Subject matter experts (SMEs) in those specific processes, with broad experience of best practices across multiple industries, are essential here, such as the kind of capabilities global service providers like Accenture offer.

Stage Three: Connect your digital twins with other enterprise systems downstream and upstream, including those of your partner ecosystem, to establish a digital twin of your supply chain.

Stage Four: Add human interaction to the digital twin—mapping the impact of human interventions throughout, bringing human assets into the modeling process and scenario planning.

Stage Five: Move to autonomous manufacturing. With the application of artificial intelligence (AI), Yves identifies the ultimate state as one in which digital twins continuously learn, improving alignment with the data received while self-monitoring and resolving issues. It’s “the art of the possible,” where synchronizing all the components from the first four stages allows you to combine the digital and the physical.

The Bottom Line: The manufacturing opportunity is real—the five-stage case studies to date, less so.

Case studies for stages one and two of Accenture’s five are abundant. Cintoo uses “mesh” technology of the kind found in video games to render realistic 3D digital twins. Customers say these enable them to reduce the delays and costs of site visits, accelerating staff training while improving sustainability, for example.

While the technology required for stages three to five is within our grasp, the human desire and imagination to make the leap depend not only on an HFS OneEcosystem mindset but also on more experience and acceptance of the metaverse. Accenture sees the metaverse as a continuum from the real to the virtual and back, from 2D to 3D, and from the cloud and artificial intelligence to extended reality, digital twins, edge technologies, and beyond. Ultimately (from stage three onward), this will demand interoperability between each instance of the metaverse deployed by your ecosystem partners. That connection between metaverse instances has yet to emerge.