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Digital Twins and Phygital Fitness

January 25, 2023


One of the most promising technologies to emerge over the last decade is digital twin technology. Technology writer Aminu Abdullahi explains, “A digital twin is essentially an avatar of a physical object in the virtual world, allowing people to operate it remotely, manage it, and monitor its performance by collecting data from embedded sensors. Digital twins technology is a core element of digital transformation.”[1] Cybersecurity journalist Charlie Osborne agrees that digital twin technology has an important role to play in digital transformation. “When corporations wish to revamp their supply chains and gain more visibility into the everyday workings of their business,” she writes, “Digital twin technologies can provide the solution.”[2] The most successful companies in the Digital Age will be those that demonstrate the best “phygital” fitness (i.e., companies that leverage digital processes to optimize real-world outcomes).


Digital Twin Basics


Abdullahi reports, “The concept of digital twins can be traced back to NASA’s efforts with its space exploration project in the 1960s. This technology took a step further in 2002 when Michael Grieves publicly introduced the concept and model of the digital twin at a Society of Manufacturing Engineers conference in Troy, Michigan. In 2010, NASA’s John Vickers introduced a new use of the term digital twin that was not confined to manufacturing industries but applied across all sectors.” Osborne notes that the emergence of practical digital twin technology had to wait until foundational technologies, like the Internet of Things (IoT), sensors, artificial intelligence (AI), edge computing, and wireless technologies, matured. Stefan Weisenberger, a Global Vice President at SAP, asserts that digital twin technology provides both companies and their clients with a “more reliable ‘phygital’ experience.”[3]


Weisenberger observes that having greater phygital fitness is “especially relevant in the area of supply chain dynamics, where companies that have historically focused on manufacturing excellence are shifting their efforts to improving the customer experience through greater flexibility, more real-time information sharing and tighter collaboration.” Manufacturers were among the first enterprises to appreciate the potential of digital twins — especially in the area of preventive maintenance. Elizabeth Hackenson, Chief Information Officer and Senior Vice President at Schneider Electric, insists, “[Digital twin technology is] going to be a competitive advantage [as organization’s begin] to understand how [their] assets are performing not only from a maintenance perspective but also profitability.”[4] She predicts, “In 10 years, digital replicas of industrial equipment in industries ranging from food and beverage to manufacturing and health care will be widespread.”


Deloitte analysts agree that digital twin usage will continue to grow as the technology becomes more sophisticated. They write, “Digital twins are multiplying as their capabilities and sophistication grow. But realizing their full potential may require integrating systems and data across entire ecosystems.”[5] Looking forward, they write, “Imagine you had a perfect digital copy of the physical world: a digital twin that can virtually replicate physical products and processes. This twin would enable your organization to collaborate virtually, intake sensor data and simulate conditions quickly, understand what-if scenarios clearly, predict results more accurately, and output instructions to manipulate the physical world.”


The Way Ahead


Deloitte analysts note, “Today, many companies are using digital twin capabilities in a variety of ways. Digital twins can simulate any aspect of a physical object or process. They can represent a new product’s engineering drawings and dimensions or all the subcomponents and corresponding lineage in the broader supply chain, from the design table all the way to the consumer.” As they mentioned earlier, digital twins can also be used to understand what-if scenarios. That is one of activities the Enterra Global Insights and Decision Superiority System™ (EGIDS™) can help organizations with today. Powered by Enterra’s artificial intelligence engine — the Enterra® Autonomous Decision Science™ (ADS®) platform — it can help business leaders rapidly explore a multitude of options and scenarios.


How important is this capability? Alex Koshulko, Co-founder and CEO at Streamline, explains, “Advanced supply chain players strive for real-time supply chain execution. In fact, a Gartner study shows that 60% of chief supply chain officers are expected to make quicker, more informed and accurate real-time decisions. Meanwhile, real-time decision making requires two things: knowing exactly what’s happening in the supply chain at any given moment and seeing into a variety of future scenarios.”[6] He adds, “In times of uncertainty and non-stop disruption, the digital twin technology can be a way to achieve both by improving the supply chain visibility, performance and more. The technology can help companies boost revenue by up to 10%, improve time to market by as much as 50% and upgrade product quality by up to 25%, according to McKinsey.”


Today’s business world moves at computer speed — and that presents a decision-making challenge. It also helps explain why digital twin technology is gaining more attention. Jeff Harris, a Vice President at Keysight Technologies, writes, “Artificial intelligence, machine learning, and digital twins — why are we hearing so much about them and why do they suddenly seem critical? The simplest explanation is this: When something is too complex for a human to easily process or there is too little time for a human to make a critical decision, the only choice is to remove the human. That requires the ability to replicate the thought process a human might go through, which requires a lot of data and a deep understanding of the decision environment.”[7]


Deloitte analysts predict, “Digital twins [will be] deployed broadly across industries for multiple use cases. For logistics, manufacturing, and supply chains, digital twins combined with machine learning and advanced network connectivity such as 5G will increasingly track, monitor, route, and optimize the flow of goods throughout factories and around the world. Real-time visibility into locations and conditions (temperature, humidity, etc.) will be taken for granted. And without human intervention, the ‘control towers’ will be able to take corrective actions by directing inventory transfers, adjusting process steps on an assembly line, or rerouting containers.”


Concluding Thoughts


Harris concludes, “The shift to AI-driven development and digital twins has become necessary due to the amount of functionality and autonomous decision-making expected in new products. … The need for AI and digital twins is real.” In today’s digital environment, finding the right data to drive a digital twin is not as difficult as one might think. Journalists from The WHIR note, “You can leverage information, data sciences, and powerful systems to enable digital twins of supply chain management, entire factory processes, and even inventory management.”[8] Digital twin technology will continue to help companies perform “what if” scenario analysis and, when prudent, make autonomous decisions to optimize processes as they improve their phygital fitness.


[1] Aminu Abdullahi, “What Are Digital Twins?” eWeek, 14 November 2022.
[2] Charlie Osborne, “The rise of the Digital Twin: Why the enterprise needs to take notice,” ZDNet, 3 May 2018.
[3] Stefan Weisenberger, “‘Phygital’ Fitness: Melding Physical and Digital to Improve Supply Chain Outcomes,” SupplyChainBrain, 19 August 2021.
[4] Sara Castellanos, “Digital Twins Concept Gains Traction Among Enterprises,” The Wall Street Journal, 12 September 2018.
[5] Adam Mussomeli, Aaron Parrott, Brian Umbenhauer, and Lane Warshaw, “Digital Twins: Bridging the Physical and Digital,” The Wall Street Journal, 23 June 2020.
[6] Alex Koshulko, “How Digital Twins Can Help Supply Chains Survive Disruption,” Forbes, 21 June 2022.
[7] Jeff Harris, “The Genesis of Artificial Intelligence and Digital Twins,” InformationWeek, 2 May 2022.
[8] The WHIR, “Understanding Digital Twins as a Key Part of Digital Transformation,” Channel Futures, 23 September 2017.

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