Retailers Bet on Digital Twin Technology
Digital twin technology creates virtual models designed to reflect both online and physical systems, and it has captured the attention of the retail market. Inventory shortages and supply chain woes have been dominating retail headlines for much of 2022. Now, a growing number of retail brands are using the technology to get a better handle on inventory management and optimize the design and setup of physical stores.
From a high-level view, a digital twin is a virtual representation of a system spanning its lifecycle. Digital twin technology generally updates using real-time data, and it relies on a combination of simulation and machine learning for decision making. It’s used by businesses to spot critical signals, like customer behaviors and expectations, that could influence future needs. The technology can also be set up to provide CIOs with data on market and policy-related trends, and track how external forces like fuel prices and weather events could impact in-store demands.
The market for digital twin technology is expected to grow 42% annually to $53 billion by 2028. That’s up 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, the use of digital twin technology ramped up this year as the holiday shopping season began in earnest. The insights gleaned from this technology can be used to help retailers create virtual copies of their entire supply chain and build plans based on what-if scenarios — for example, what inventory levels would be needed at a certain store location if a unique weather pattern emerged.
“This technology allows retailers to model different demand patterns against their order sourcing rules to see how the impact of certain rule changes impacts their ability to serve customers from a cost and speed perspective,” Achen says.
How the technology is used in the real world depends largely on the organization using it. Retail brands like Lowe’s and Kroger have reportedly been on the cutting edge.
A regional sporting goods retailer, for example, might use digital twin technology to track fuel prices and weather patterns in the markets where its stores are located. With that information, the company would be able to model how a fuel pricing increase or an unexpected natural disaster, like a hurricane, would impact the flow of products across its supply chain. The retailer would then be able to develop contingency plans so that if those unexpected events were to occur, the business would be able to pivot.
While digital twin technology is not new, its use within the retail sector is on the rise. In an effort to avoid additional inventory issues, more retailers are now using digital twin technology to plan for how much inventory they need to have on hand at any given time, and how their physical stores should be designed. They’re also using the technology to model merchandising strategies, identify new fulfillment opportunities, and optimize business operations.
“As fulfillment complexity increases, so do the rules to manage it,” Achen says. “It’s becoming harder for retailers to understand the impact of tweaks to these rules against demand patterns they may not have seen before.”
Data Drives Digital Twin Outcomes
Achen says the data his company provides helps retailers evaluate complete models before they make lasting, real-world changes. It’s also playing a critical role for omnichannel retailers this holiday season.
“With increasing use of stores for fulfillment but with a tightening labor market, and concerns on carrier availability, retailers need to be concerned with pushing too much demand to certain locations in the network to avoid slowdowns or missing holiday deliveries,” Achen says. “The data can tell them where gaps exist in capacity and how to adjust the usage of [fulfillment centers] vs. stores.”
