“The concept of digital twins,” writes freelance journalist Elizabeth Wallace, “has been a game-changer in digital transformation. They’ve provided a virtual mirror to physical assets, processes, or systems and [enabled] unprecedented levels of analysis, monitoring, and prediction.”[1] The concept certainly hasn’t gone unnoticed. Gartner predicts, “The digital twin market will cross the chasm in 2026 to reach $183 billion in revenue by 2031.” The marriage of artificial intelligence and digital twin technology is truly transformative. As one AI enthusiast notes, “With the rapid rise of artificial intelligence and cognitive computing, a new frontier is emerging — Cognitive Digital Twins (CDTs). These advanced models bring together the power of AI and machine learning to replicate not only the physical attributes of real-world systems but also their decision-making processes, behavior patterns, and cognitive functions.”[2]
Company executives now understand that being able to test scenarios and strategies that can help them successfully navigate today’s volatile supply chain landscape is crucial. Digital twins provide a data-driven view of operations, which allows variables to be tested so that smarter decisions can be made resulting in improved performance. Wallace explains, “Cognitive digital twins can significantly shorten product and service design and development cycles. By simulating real-world conditions and user interactions in a virtual environment, businesses can rapidly prototype, test, and iterate on new ideas without the time and cost associated with physical prototypes. This can lead to faster innovation cycles, allowing companies to stay ahead in competitive markets.”
The Value of Digital Twins
McKinsey & Company analysts posit that if we had a personal digital doppelgänger who could test the consequences of our actions without fear, pain, or embarrassment, we would probably make better decisions in our lives with a lot more certainty of the outcome. The same holds true for businesses. “In business,” they write, “this heightened degree of certainty is extremely valuable — and emerging digital twins may help deliver it. Digital twins are linked to real data sources from the environment, which means that the twin updates in real time to reflect the original version. Digital twins also comprise a layer of behavioral insights and visualizations derived from data. When interconnected within one system, digital twins can create a digital and often immersive environment that replicates and connects every aspect of an organization to optimize simulations, scenario planning, and decision making.”[3] The CIO Review staff agrees that digital twins offer significant value. They also report that there are four myths too many companies believe about digital twins.[4] Those myths are:
● Myth 1: Digital twins are purely 3D models. Digital twin technology uses real-time data collected from connected devices to identify “patterns, trends, anomalies, and correlation” so that better decisions can be made.
● Myth 2: Digital twins are only good for large organizations. Today, cloud-based platforms and cost-effective solutions have made digital twin technology more affordable for smaller organizations.
● Myth 3: Digital twins are only for engineers and technical experts. Digital twin technology can be user-friendly. With the right interfaces, a collaborative digital twin can provide valuable insights to individual across the company.
● Myth 4: Digital twins are expensive. Digital twins can be expensive to build and costly to maintain depending on the level of complexity and detail required. However, not every company needs a digital twin that mirrors the entire organization.
The CIO Review staff recommends clearly defining goals and objectives then concentrating resources on those areas that provide the greatest benefit. McKinsey analysts note there are various types of digital twins to be considered. They explain, “There are a few different types of digital twins. First, there’s a product twin, which is a representation of a product. This digital twin can include products at various stages of the life cycle, from initial concept design and engineering through full functionality — meaning you get live, real-time data on a product as if it’s in service. Another type of digital twin is a data twin. You probably already have a great example of a data twin in your pocket: Google Maps is a digital twin of the Earth’s surface. It links real-time data on traffic to help optimize your commute. Other types of twins include systems twins, which model the interaction between physical and digital processes, including manufacturing processes, end-to-end supply chain management, store operations, and customer journeys. And finally, infrastructure twins represent physical infrastructure such as a highway, a building, or even a stadium.” They add, “Digital twins have the potential to deliver more agile and resilient operations.”
Supercharging Supply Chains
The Economist notes, “Artificial intelligence, in particular, will make it much easier for all sorts of businesses to build virtual replicas and oversee them on a scale managers alone never could. As a result, digital twins will redefine what it means to run a company. … What distinguishes these models from their predecessors is their ability to continuously monitor (and influence) their real-world equivalents.”[5] Nothing is more important to a business than its supply chain. As McKinsey analysts observe, “Maintaining supply chains is a top priority across organizations. McKinsey analysis indicates that supply chain disruptions cost, on average, 45 percent of one year’s cash profit. Organizations are aware of the risk: an estimated 86 percent of companies recently surveyed are investing in supply chain transformation to respond to industry disruptions.” Part of that transformation, they report, is leveraging digital twin technology.
They explain, “Digitally enabled supply chains deploy digital-twin and AI technology to drive optimization and efficiency. They take data captured from all facets of an organization’s operations and model the data to mimic physical assets, people, and processes. Based on insights from a twin, an organization’s leaders can freely experiment, increase their decision-making speed by up to 90 percent, and more. Top-performing companies we surveyed are already aware of the benefits of this technology: among companies investing in supply chain disruption, digital twins rank in the top three investment priorities.”
Concluding Thoughts
Wallace concludes, “The strategic decision-making enabled by cognitive digital twins offers companies a significant competitive advantage, providing deep, actionable insights that support informed and strategic decisions across all organizational levels. This capability for differentiation in crowded markets underscores the transformative potential of cognitive digital twins. They’re not just mirroring physical and digital realities. They’re using anticipation and learning to shape the future of industries. For many organizations, this path is unveiling a new dimension of digital interaction and operational intelligence.” In today’s everchanging world, companies compete against the business environment as much as they compete against other companies. That’s why Enterra Solutions© developed its Enterra Business WarGaming™ capability. Business WarGaming enables organizations to leverage their data to make strategic decisions by anticipating the moves of their competitors and taking direct action to beat the competition, mitigate risk, navigate uncertainty, and maximize market opportunity. Part of Enterra Business WarGaming is the Enterra Global Insights and Decision Superiority System™ (EGIDS™) — powered by the Enterra Autonomous Decision Science™ platform — which can help business leaders rapidly explore a multitude of options and scenarios. The bottom line is that digital twin technology will help future-proof your company and supercharge your supply chain.
Footnotes
[1] Elizabeth Wallace, “Cognitive Digital Twins are a Leap Forward,” CD Insights, 30 March 2024.
[2] AI Pioneer, “Cognitive Digital Twins: The Future of Smart Systems,” Medium, 12 October 2024.
[3] Kayvaun Rowshankish, Rodney W. Zemmel, Tomás Lajous, and Kimberly Borden, “What is digital-twin technology?” McKinsey & Company, 26 August 2024.
[4] Staff, “Digital Twins: Beyond the Hype and Myths,” CIO Review, 15 December 2023.
[5] Staff, “Digital twins are making companies more efficient,” The Economist, 28 August 2024.
