Changes in today’s business world are occurring so fast they are creating challenges former generations of supply chain leaders never faced. As analysts from John Galt note, “Companies across industries have recently found themselves operating with supply chains designed for a world that no longer exists. Today’s growing complexity and volatility means that companies need to evolve their supply chains to deliver transformational outcomes that help them become more resilient, agile and intelligent to stay ahead of disruption and seize new opportunities.”[1] They believe one of the ways supply chain professionals can cope with a rapidly changing world is to leverage the power of digital twins. They explain, “Supply chain management can be like navigating a labyrinth filled with unexpected twists and turns, and major disruptions like enemies threatening to upset the balance of operations across the ecosystem. But the good news is that there’s a hero in the digital realm ready to come to the rescue — and that hero is the digital supply chain twin.”[2]
What is a Digital Twin?
Justin Honaman, Head of the worldwide Consumer Packaged Goods (CPG) Food & Beverage organization for Amazon Web Services, reports that the term “digital twin” may be newly coined, but the concept has been around for years. He explains, “For the last few years, the term Digital Twin has been at the top of the buzzword list for manufacturers and industrial companies, often meaning different things in different production environments. Most of these organizations have developed Digital Twins to improve operations and product offerings and deliver more business value to their end customers. The concept of digital twins is not new and dates back to the early days of the space program. The Apollo 13 mission in the 1960s is an early use case of using twins to model the state of the damaged spacecraft and bring the astronaut crew safely back to Earth.”[3] IBM defines the term this way: “A digital twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.”[4]
Siemens analysts add, “Digital twin technology has been used in industries such as manufacturing to provide virtual simulation capabilities that can test planned decisions. This has provided managers with a powerful tool to successfully anticipate outcomes — both positive and negative.”[5] Of course, the biggest difference now and when NASA used the digital twin approach to rescue Apollo 13 astronauts is the availability of greater computing power. Siemens analysts note, “With the development of greater computing speed and power, digital twin capabilities have advanced. Now they are able to grapple with the greater complexities of supply chain management. In this particular environment, which presents many more variables than in manufacturing, the cause and effect of supply chain events can be anticipated with a new level of precision. Benefits for supply chain managers include reductions in operating expenditures, more accurate pairing of logistic budgets with planned sales increases, and an overall greater business resiliency.”
Digital Twins in the Supply Chain
According to Honaman, there are four key elements of a digital twin. They are: (1) the physical system, (2) the digital representation, (3) the connectivity between the two, and (4) the business outcome. I would add a fifth element that is only implied in his framework: analysis and decision-making which must take place before business outcomes can be realized. Let’s discuss each of those elements:
(1) The physical system. Honaman explains that the entire supply doesn’t require a digital twin to produce beneficial outcomes. He writes, “The physical system itself can be an individual physical entity, an assembly of physical entities, a physical process, or even a person. It doesn’t necessarily have to be an industrial system but can be a biological, chemical, ecological, or any other system.”
(2) The digital representation. Honaman explains that the digital representation is a model and requires data. He writes, “This is not just a collection of data, such as a data model that represents the structure of the physical system, or an IoT data dashboard that represents the current state of the physical system. A Digital Twin is a model that emulates or simulates the behavior of the physical system, such that when you give it an input, the model returns a response or output. This leads to the third element, connectivity.” In other words, to be useful, the model must produce insights that reflect real-world results.
(3) Connectivity. According to Honaman, “A true Digital Twin must be regularly updated with data from the physical system (often using IoT sensors). A validated model provides a snapshot of the behavior of the physical system at a moment in time, and a Digital Twin extends the model to where the physical system’s behavior changes significantly from the original.”
(4) Analysis and decision-making. The links between the model and business outcomes are the decisions that are made as a result of analysis. Ronald G. Ross, cofounder and Principal at Business Rule Solutions, and an expert in enterprise decision management (EDM), explains, “Operational decisions provide the actual value-add for the business — not the rules used to make those decisions per se. In other words, rules are simply the means to some important business end, some operational decision(s) to be made. So if you want to make the business and its processes smarter (and who doesn’t!?), you must enable better decisions.”[6] This is the area where Enterra Solutions® is focusing much of its attention. Enterra® automates a new way of problem-solving and decision-making, going beyond advanced analytics to understand data, perform analytics, generate insights, answer queries, and make decisions at the speed of the market. This powerful capability uniquely enables end-to-end value chain optimization and decision-making at scale and allows clients to uncover and understand the interrelationships that lead to innovative new product development and innovation, heightened consumer understanding and targeted marketing, revenue growth tactics, and intelligent demand and supply-chain planning. Driven by Enterra’s artificial intelligence engine — the Enterra Autonomous Decision Science™ (ADS®) platform — it can help business leaders rapidly explore a multitude of options and scenarios.
(5) Business outcomes. As Honaman makes clear, “A Digital Twin must drive a specific outcome related to some kind of economic or business value. And thus, drive business decisions on the managed process.”
Concluding Thoughts
John Galt analysts note, “One of the key advantages of a digital supply chain twin is its ability to simulate and optimize decision-making processes. By leveraging real-time data and advanced algorithms, you can run scenarios, assess the impact of different strategies, and make informed decisions. Whether it’s adjusting production schedules, optimizing inventory allocation, or reallocating resources, the digital twin provides an innovative environment to experiment and ensure that actions are executed in the right place at the right time. This allows you to enhance operational efficiency, reduce costs, and minimize risks.” Siemens analysts add, “Digital twin technology will prove to be a game changer for supply chain management. The way is wide open for supply chain planning that more accurately foresees and/or reacts to service or cost impacts before they can cause significant issues.” The benefits of digital twin technology in the supply chain are just beginning to be tapped.
Footnotes
[1] Staff, “Digital Supply Chain Twin: Is it the Foundation of a Well-Designed Digitalization Initiative?,” John Galt Blog, 1 February 2023.
[2] Staff, “5 Ways a Digital Supply Chain Twin Supercharges Performance,” John Galt Blog, 19 June 2023.
[3] Justin Honaman, “Digital Twins & CPG Manufacturing Transformation,” Consumer Goods Technology, 1 March 2023.
[4] Staff, “What is a digital twin?” IBM.
[5] Siemens, “Successfully Delivering Digital Twins for Supply Chain Management,” SupplyChainBrain, 20 June 2023.
[6] Ronald G. Ross, “The Decision Center ~ A Center of Excellence for Coordinating Business Rules and Other Process ‘Smarts’,” Business Rules Journal, Vol. 8, No. 12, December 2007.
