Digital twins are becoming big business, says Toby Mills, CEO of entopy. But there’s still a lot of confusion about what they are, what they do — and why they’re important.
A digital twin is a virtual representation of an object or system that spans its entire lifecycle, is updated from real-time data, and uses simulation, machine learning, and reasoning to support decision-making. It acts as a bridge between the physical and digital worlds. Businesses use digital twins in a variety of ways, from product development to improving operational performance. Increasing digitization makes it easier to create accurate digital twins and drive adoption of the technology.
For the logistics industry, digital twins open the door to a new way of tracking goods moving between different organizations and physical locations. Data from multiple supply chain systems can be captured and combined to create a “digital twin” of a shipment – providing a single data product that everyone involved can benefit from sight range you need.
This novel approach was made possible by the latest “Data Mesh” technology based on a distributed architecture for analytical data management. It allows end-users to easily access and query data where it resides—without first transporting it to a data lake or data warehouse. Leveraging data across the supply chain makes it possible to get a much more complete picture at a granular level. And using data from existing systems used in the daily operations of the organizations involved means that the data is of high quality, can be trusted and the systems are well maintained.
The concept of the digital twin is at the heart of the work of supply chain visibility pioneer Entopy – and forms the backbone for the company’s unique intelligent data orchestration technology that is the secret to supply chain success. As in a traditional orchestra, a “conductor” takes center stage and synchronizes all the various data inputs. Each separate system communicates directly and only with the ladder platform – eliminating the need for numerous discrete connections and maintaining data integrity.
Like everyone digital twin is created, proprietary algorithms define and assign policies to ensure only relevant data is collected from each connected system. Data from order management and transportation management systems is combined with real-time data sources from other systems present throughout the supply chain. For example, shipment and inventory data can be combined with timetables and assigned transports.
The telematics system of the associated transport vehicle provides real-time location and status data of the shipment, which in combination with analytics generate detailed records of the shipment’s life cycle and continuously record important events. These events can be communicated throughout the supply chain, improving communication and paving the way to automating processes.
Research suggests that with optimal supply chains, companies can halve inventory levels, reduce supply chain costs by 15% and triple the speed of their cash-to-cash cycle. But the increasing complexity of supply chains makes optimization harder than ever, while the costs of inefficiencies soar. Digital twins and intelligent data orchestration now offer a new way to unlock supply chain value and gain competitive advantage.