Digital twins are set for rapid adoption in 2023

JUN 30, 2023

Digital twins are set for rapid adoption in 2023

Like artificial intelligence a few years ago, digital twin technology has tipped from highly specific applications into becoming a widespread management best practice.

Digital twins are replacing historical data-driven models used for business strategy.

In life sciences, digital twins are being used to research human organs, enabling new approaches to medical research and care.

The idea of digital twins — digital representations of physical systems, products or processes that serve as indistinguishable counterparts for purposes such as simulations, testing, monitoring and maintenance — has been around for some time. But indications are the concept’s time has come for wider adoption to support business applications.

“With the rapid adoption of digital twins, we’re seeing two categories of practical applications arise: use-cases by industry that solve a very specific challenge, and industry-agnostic use-cases which aid in broader strategy and decision making,” said Frank Diana, principal futurist at Tata Consultancy Services.

Like artificial intelligence a few years ago, digital twin technology has tipped from highly specific applications into becoming a widespread management best practice, Diana said.

“With the deeper and more contextualized insights digital twins provide, we gain a better understanding of our products, processes, and systems and more confidence in our models,” said Matt Barrington, emerging technologies leader at consulting firm EY Americas.

“For example, this enables more organizations to have the confidence to experiment with access-based service models for complex products or new data-based services” such as twin-based insurance policies for smart buildings, Barrington said. “Moving forward in a more dynamic, ecosystem-oriented marketplace, we expect all companies to enable and become dependent [on] digital twins to intelligently operate most aspects of their business,” he said.

Coming to life with real-time data

Companies are using virtual product development twins to accelerate design and development cycles more effectively, Barrington said. “Digital twins take the models we already have for today’s products, processes and systems and bring them to life in real-time with real-world data,” he said.

One practical application of digital twins within TCS has been in guiding the firm’s return to office strategy during the late stages of the pandemic, Diana said. “To re-open effectively, we needed to know answers to questions like how many [workers] might get infected? Who should we test, and when? What should the capacity of our quarantining facility be?” he said.

To answer these questions, TCS created a digital twin environment with a novel machine-processable “model of locality,” with the principal objective of predicting and controlling the spread of Covid. “The digital twin serves as a quantitative aid to explain the current state of the environment and assist in decision-making, enabling a safe and effective return to office for our associates,” Diana said.

Digital twins are also replacing historical data-driven models used for business strategy, Diana said. “These legacy strategic platforms lack the ability to account for deviations and disruptions, which have become increasingly common in the post-Covid world,” he said.

Along with AI, organizations are using digital twins to help envision, experiment with, and execute business decisions through simulators that represent key business entities, interrelationships, and external forces such as competitors or natural disasters, Diana said.

In life sciences, digital twins are being used to create twins of human organs, enabling new approaches to medical research and care, Diana said. Pharmaceutical and cosmetics companies can use twins to test how to deliver new drugs or products on human skin in cyberspace instead of relying on animal testing, he said. Researchers can use digital hearts to find new surgical techniques or treatments for heart disease.

Smarter cities

Digital twins are also being used for smart city initiatives, Diana said. For example, Los Angeles is employing digital twin technology that will model transportation movement and activity, such as ride sharing and autonomous drones, to better plan its mobility infrastructure.

Another possible application is in environmental, social and governance initiatives. The technology “leverages huge data sets of historical weather, travel, and physical infrastructure data to create a digital twin of any physical location,” said Dan Versace, research analyst ESG business services at research firm International Data Corp. By using artificial intelligence and machine learning, digital twinning can perform in-depth analysis to provide users with elaborate, scenario-based assessments of environmental conditions, Versace said.

“This technology, when appropriately applied, can produce insights into the physical risks that come hand-in-hand with the increasing instances of climate-related natural disasters,” Versace said. “In the coming year this technology stands to only grow in capabilities, with some organizations claiming that they will be able to account for not only direct risks faced by organizations due to climate change, but also the impact these disasters will have to their clientele and value chain.”

This will allow companies to develop resiliency planning and mediation strategies long before they are needed, without having to be exposed to any material risk, Versace said.

“We are going to see digital twins adopted rapidly in 2023, in many different industries,” Diana said. “The volatility and uncertainty that’s on the horizon for this year will serve as a catalyst to drive companies into a mode of rehearsing uncertain futures. Digital twins will be a critical tool for that rehearsal.”

Digital twins are gaining momentum in adoption and sophistication as more organizations see positive outcomes from the early adopters, Barrington said. As digital twins become mainstream, EY predicts two major trends. One is hyper-personalization, using twins to better tailor products, services, and experiences with the goal of improving customer loyalty and value.

The other is dynamic supply chains. “As more twins of critical assets and processes come online, leaders will leverage digital twins to not only model and simulate their supply chain, but to optimize and automate a dynamic and intelligent supply chain model — all orchestrated by digital twins,” Barrington said. “Many leaders learned from the recent pandemic that static linear supply chains will not suffice moving forward and digital twins are one of the best ways to remove risk.”

Bob Violino

Guillermo Gutierrez Carrascal | LightRocket | Getty Images

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