There is a latest trend gaining traction in the supply chain industry – and that is digital twin technology. With supply chains becoming more dynamic, complex and interdependent as a result of globalization and digitalization, digital twins have emerged as a potential solution to manage the growing intricacies of the supply chain.
Wait…what is a digital twin in the context of a supply chain?
A digital twin in supply chain is a virtual image or software representation of an organization's actual supply chain - consisting of assets, processes, logistics and inventory positions. Using AI, the digital twin simulates the performance of the physical supply chain to plan, predict and optimize operations. The connection with the physical twin and the corresponding virtual twin is established by generating real-time data using sensors.
The growing need for twin technology
Without digital twin technology, organisations rely on mathematical models to understand and program supply chain systems. However, according a report by STIQ, there is only so much that can be achieved with mathematical models. Many of the new automation solutions integrated into supply chains are dynamic systems which require simulation for managers to understand how they work. For example, managing replenishment, inventory depth, product promotion are complex issues that are difficult to understand from just observation and performing some calculations.
As written in the 2019 Gartner report, at least 50% of large global companies will be using AI, advanced analytics and IoT in supply chain operations by 2023. Digital twins is an example of one such technology that has the potential to transform the efficacy and resiliency of the supply chain.
How can digital twins benefit supply chains?
Enter the digital twin. With digital twin technology, there are 3 key benefits they may bring to an organization’s supply chain.
1. Enable long term planning through dynamic optimization
Digital twin software allows organizations to create realistic and verifiable replicas of their supply chains. The practice of data mining techniques and real-time inputs from Internet of Things (IoT) sensors allow organisations to feed the latest data into models. The digital twin will then continuously track performance and deduce the most suitable corrective action.
Unlike mathematical models, digital twin models are not static and offer organisations the ability to continuously optimize supply chain performance. In the long term, digital twin simulations allow organisations to understand where the most significant system constraints and bottlenecks are and plan for future transformation.
2. Manage uncertainty in a volatile climate
The COVID-19 pandemic has revealed the vulnerability of supply chains to unexpected disruptions. As organisations pick themselves back up from the crises, there has been greater emphasis placed on how businesses can better manage and prepare for future disruptions.
One way is through the application of digital twins - organizations can use digital twins to derive the predicted impacts and trade-offs of decisions through performing ‘what-if’ analyses. The data-driven systems can be easily tweaked and redesigned, allowing businesses to test how different aspects of the supply chain impact one another. This enables well-informed decisions to be made for their supply chain operations with minimal risk involved – effectively future-proofing supply chains and building greater resiliency.
3. Drive innovation
Digital twins work to bridge the gap between the physical and digital world. Intelligent sensors integrated into physical elements allow for the capture and transmission of massive amounts of data. When such operational data is juxtaposed with relevant business data, organizations can expect to uncover surprising opportunities that may otherwise have gone undetected.
The ability to understand at depth how various elements of the supply chain are interconnected is necessary for managers to drive transformation and growth at scale.