Digital twin technology, creating virtual models that reflect both online and physical systems, has caught the attention of the retail market. Inventory shortages and supply chain issues have dominated retail headlines since 2022. Now, more and more retail brands are using technology to gain a better grip on inventory management and streamline the design and setup of physical stores.
From a general perspective, a digital twin is a virtual representation of a system throughout its lifecycle. Digital twin technology is generally updated using real-time data and relies on a combination of simulation and machine learning to make decisions. It is used by businesses to detect critical signals, such as customer behavior and expectations, that could influence future needs. The technology can also be set up to provide CIOs with data on market and policy trends, tracking how external factors such as fuel prices and weather events might be affecting demand in the store.
The digital twin technology market is projected to grow 42% annually to $53 billion by 2028. That’s an increase from just $6.5 billion in 2021.
According to Chap Achen, vice president of product strategy and operations at Nextuple, a SaaS and logistics company that uses digital twins to help its retail customers, usage of digital twin technology has surged this year as the holiday shopping season kicked off in earnest. Insights gained from this technology can be used to help retailers create virtual copies of their entire supply chain and create plans based on what-if scenarios – for example what stock levels would be needed at a particular store location , when a unique weather pattern occurs .
“This technology allows retailers to model different demand patterns against their order sourcing rules to see how the impact of certain rule changes affect their ability to serve customers from a cost and speed perspective,” says Achen.
How the technology is deployed in the real world largely depends on the organization using it. Retail brands like Lowe’s and Kroger were reportedly on the cutting edge.
For example, a regional sporting goods retailer could use digital twin technology to track fuel prices and weather patterns in the markets where its stores are located. With this information, the company would be able to model how an increase in fuel prices or an unexpected natural disaster such as a hurricane would affect product flow in its supply chain. The retailer would then be able to develop contingency plans to allow the business to turn around should these unexpected events occur.
While digital twin technology is not new, its use in the retail sector is increasing. To avoid additional inventory problems, more and more retailers are using digital twin technology to plan how much inventory they need to stock at any given time and how their physical stores should be designed. They also use the technology to model merchandising strategies, identify new fulfillment opportunities and optimize business operations.
“As processing complexity increases, so do the rules for managing it,” says Achen. “It’s becoming increasingly difficult for retailers to understand the impact of changes to these rules on demand patterns that they may not have seen before.”
Data drives the results of the digital twin
Achen says the data his company provides helps retailers evaluate complete models before making permanent, real-world changes. It also plays a crucial role for omnichannel retailers this holiday season.
“With the increasing use of branches for fulfillment, but with a tight labor market and concerns about carrier availability, retailers must be concerned about pushing too much demand to certain locations in the network to avoid delays or missing holiday deliveries,” says Achen . “The data can give them insight into where there are capacity gaps and how usage can be adjusted [fulfillment centers] vs stores.”