Cost Optimization and on Time Delivery Performance Decisions- Made Stronger Through Digital Twins

There is an optimum balance of network on-time performance, customizable delivery options and cost in the supply chain, but to achieve it you need the insight to make the right decisions. A recent Molex blog outlined how network modeling and optimization provides the insight to understand how different changes will impact network performance. But what are the foundational underpinnings of this process?

One of the keys of accurate network modeling and optimization is the digital model of the Molex supply chain footprint and product flows called a digital twin. The digital twin is “a virtual representation of real-world entities and processes, synchronized at a specified frequency and fidelity.” The definition centers around three primary values: 

• Transform business by accelerating holistic understanding, optimal decision-making, and effective action. 

• Use real-time and historical data to represent the past and present and simulate predicted futures. 

• Motivate digital twins by outcomes, tailor them to use cases, power them by integration, build them on data, guide them by domain knowledge, and implement them in information technology (IT) and operational technology (OT) systems.  

Through a digital twin, you can gain a decision support capability that enables you to test optionality by creating different scenarios on a baseline model and selecting the optimal supply network configuration. The design can be tuned for cost reduction, improved on-time delivery performance, and better customer experiences. It also uniquely allows for the evaluation of trade-offs between delivery cost and speed, agility, and potentially long-term strategic investment/divestment decisions.

Digital twins integrate software analytics with spatial network graphs to create a living digital model of ecosystems, such as supply networks that update and change dynamically as their physical counterpart changes. As an example of how a digital twin can be utilized in the world of supply, let’s look at how the Molex Global Logistics Team empowers better visibility and decision-making capability into Molex’s supply chain HUB network. In this case, a digital twin was developed to map the network and define how product was moving from manufacturing all the way to the customer. The goal was to address challenges faced around a supply network disruption, and to enable quick decision making around those challenges by providing information such as flow mapping and cost incurred – all at the click of a button. The digital twin enables quick extraction of this information for access by key resources in Molex divisions so that they can ensure on-time deliveries and communicate with customers quickly and effectively. 

Through baseline modelling, historical data on all products at a particular manufacturing plant can be identified and products can be tracked as they move through hubs or direct to the customer. The historical flow of product is replicated by extracting information from the data lake. By utilizing shipment data, including the mode of shipment, an automated workflow can be developed to build the twin.  

If there is a disruption at a plant, the insights provided by the digital twin can highlight which products are impacted, including how some of those products may impact a finished product at a later stage and anticipate any disruptions to customer planned shipments. This visibility can help evaluate the availability of raw materials and the capability and capacity of other plants to determine other options available in the network to move past the disruption and ensure on-time performance.  

Cost and revenue generated can also be included in a digital twin model to measure the performance of specific decisions compared to the baseline, particularly where freight spend is high. As an example, our team members can drill deeper into products with a high logistics spend and might discover that those particular products are being shipped by air. They can then examine the root cause of the decision process behind that optionality. Were there constraints on supply driving the decision? Could the product be shipped by sea rather than air? The allows for mapping the impact of each of those decisions before they are made.

Network optimization also benefits from a digital twin by enabling examination of the footprint of a particular product, product family or series and optimizing the footprint by testing different scenarios against the baseline. Let’s say a product was going to be manufactured at a different location. Our team members leverage the digital twin to determine the savings impact of that decision, but also define how the footprint change would impact the network as a whole including customer delivery sensitivity. Will the network impact ultimately make the costs benefit untenable? The digital twin reveals these and other answers. 

Once Molex builds its digital twin to examine a part of a network, it can be expanded to consider additional connections and contingencies. If the initial effort centered on examining options from manufacturers to the customers, it can also be expanded to consider raw materials. Additional sourcing and hubs can be considered, as well as additional risks and cost benefits as part of the scenario planning. We can examine every component of the network and “war game” different decisions and how they might alter the operational whole. Global risks can be inserted into the model to support contingency planning, and proposed cost efficiency changes can be evaluated to truly understand their worth. The fact that a digital twin is simply a digital copy of the network enables a wide range of scenarios to be played out while avoiding the negative real-world consequences.  

In a world where on-time delivery performance must be achieved in the most cost-effective manner possible, global supply chains need the ability to predict the future. A digital twin is just that predictor, enabling us to see the consequences of network changes before we actually put those changes into place. This is why Molex has invested in the technology and expertise to support digital twin capabilities. These digital twin models are all part of the network optimization process, ultimately driving better on-time delivery performance over time.  Digital twins serve as powerful tools across a wide range of industries to ensure businesses like Molex can be ready for supply network challenges that might lie just over the horizon.