Maybe it is the enduring memory of the pandemic and the enforced isolation from friends and family, but there just does not seem to be much public enthusiasm for the much-hyped virtual reality offered by the Big Tech companies. Never mind that Facebook was so taken with the technology that it renamed itself Meta. Ordinary consumers just did not seem to want to spend much time wearing cumbersome headsets in order to inhabit an alternative world. Instead, it is AI that has captured the imagination — admittedly while creating plenty of anxiety about security, the future of work and indeed society itself.
However, research recently published by the management consultancy Arthur D Little suggests that business would be ill-advised to dismiss the Metaverse out of hand in favour of a focus on AI. In this, it is to some extent echoing the views of some of its rivals, which have for some time been arguing in favour of the opportunities offered by the technology. But the report by the firm’s Blue Shift Institute on the Industrial Metaverse does provide a fairly compelling description of how “a convergence of key technologies” is leading to a step-change in simulation capabilities.
The report summarised in the latest issue of the firm’s Prism magazine under the title “Simulating Strategy — The Real Potential of the Industrial Metaverse” points out that some of “technology blocks” that are part of the “fourth industrial revolution,” or what since 2015 has been known as Industry 4.0, have been around for some time. These include blockchain, virtual workplace, virtual models, simulations, digital twins and, yes, AI. While virtual training — for example, in the airline industry — has become commonplace and digital design tools and other techniques have been around for a while, implementation of Industry 4.0 is still not as widespread as was expected a decade ago, says the report. Among the barriers contributing to the situation are high upfront investment costs, difficulties in co-ordinating the required cross-functional transformation, challenges in data security and management, lack of available skills and problems with legacy IT systems.
This is where the convergence of key technologies identified by Arthur D Little comes in. For example, digital twins, essentially a computer program that uses real-world data to create simulations that can predict how a product or process will perform, has, say the report’s authors, Albert Meige and Rick Eagar, hitherto been mainly been limited to discrete products, components, plants or factories. But developments in complex systems, data visualisation and AI, combined with improvements in connectivity and collaboration technologies, and increasing computer power, are greatly expanding the scope. Instead of being limited to operational improvements and design aids, the digital twin concept is moving towards becoming a key tool for strategic decision making. The report points to how, for instance, the car maker BMW’s iFactory enables a complete production strategy based around the use of digital twins for all production sites.
In fact, Meige and Eagar put digital twins at the heart of their idea of the Industrial Metaverse. Ultimately, they write, it “could represent a complete end-to-end industrial system, including not just physical assets, but also processes, functions, resources and organization.” But for this to happen four key functions are required. They are:
Connect — The digital twin has to be permanently connected to the real world through the Internet of Things for “hot” current data and through ERP systems for “cold” stored data.
Compute — The capability to process very large data volumes from the real system, including analytics, system modelling, pattern recognition and simulation, to enable future scenario planning.
Conceive — Visualizing both physical and non-physical data. This involves interpreting and presenting complex data in different ways, not only to simulate reality but also to facilitate understanding and illustrate scenarios.
Collaborate — Functionality to enable a range of interactions between both internal staff and external customers, partners and the rest.
While the Arthur D Little consultants suggest it could be five years or so before all the required pieces of the puzzle are in place to make the concept fully operational, they do urge business leaders to take it seriously now. There are three key reasons for this — conventional strategic decision making is becoming inadequate to meet “the combined challenges of complexity, acceleration, cognition and sustainability; there are already significant benefits in such areas as training, operation and maintenance and collaboration; and the market could increase rapidly in the coming years. (Arthur D Little says a conservative estimate is it could reach about $400 billion by 2030, although other estimates suggest it could be more than twice that.)
In order to be in a position to capitalize on this, companies should consider four steps, says the report. Executives need to start by having a clear idea of where their organizations’ digitalization journeys are headed because it is not easy to jump to full Industrial Metaverse implementation without a mature digital foundation. Then, in moving forward, they need to assess which applications and uses already in existence are most likely to add the greatest value. As they develop these, they should adopt an agile and responsive “test-and-learn approach” and use relatively small pilot projects with short payback times. Above all, they need to adopt a different mindset and culture that will embrace the idea of sharing more data than is traditionally shared between commercial partners. This is because it is by developing partner ecosystems, where each partner benefits in terms of faster customer responses, smoother customer experiences and reduced working capital, that the real benefits of the Industrial Metaverse appear.
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