It has been many decades since a circuit is designed digitally and its performance tested using a digital twin, an architect constructed the building and laid out its HVAC and plumbing on the building’s digital twin, a company invested in a new distribution center only after significant number of simulations and animations on the digital twin, a dentist scanned a mouth and planned for the treatment on the digital twin and pilots learned how to fight an enemy or transport passengers safely on flight simulators – the ultimate digital twin. The supply chain world is just discovering the digital twin concept and we are nowhere close to the level of detail and sophistication of these decades-old examples.
I will readily accept the following argument: most successful digital twin examples use hard sciences on physical constructs, whereas a supply chain is a complex and dynamic human-machine system where hard and soft sciences mix. However, I also believe that the old-fashioned digital representation of a supply chain with nodes and arcs is like drawing a stick figure. Contemporary technology with massive computational power and virtually seamless integration to cloud allows a much more refined representation of a supply chain and creates a useful digital twin. Therefore, I reject the idea that you can consider any computer model a digital twin.
1. A true digital twin is alive!
The fundamental basis and the necessary condition to be able to build a digital twin: to represent the supply chain at the highest resolution and the ability to keep the representation current as the world changes. After all, a living digital twin is useful for decision support, not a copy that is frozen in time.
2. Needs a comprehensive platform to remain alive!
From a technical point of view, there is a need for a scalable digital platform that has a comprehensive and internally consistent data model for the entire value chain, including suppliers and customers. This platform should allow data exchange with multiple transaction systems – both enterprise and external – in order to keep the digital twin alive and healthy. If you are a typical retailer or manufacturer, then it is quite likely that your world is changing fast, and your digital twin needs to match the reality of the physical infrastructure and the changing business drivers.
3. Allows future what-if scenarios
Furthermore, the digital twin should be able to represent and maintain not only the as-is state of the supply chain but also its future. A digital twin should enable a thorough evaluation of strategic and tactical options for a supply chain, e.g., network design, strategic sourcing through bids, transportation purchasing, seasonal build-ahead options, seasonal assortment options, etc.
4. Enables representation of operational processes
The digital twin should enable the maintenance of business rules and the parameters for operational decisions, e.g., target service levels, forecast accuracy, replenishment/build frequencies, fulfillment priorities, etc.
5. Enables horizontal alignment of decisions
A viable digital twin should enable horizontal alignment of decisions across demand, inventory, supply, procurement, manufacturing, fulfillment, and transportation tied together with a financial representation of the value they collectively generate, e.g., Total Cost to Serve, Total Landed Cost, Total Profit, etc. How else will you be able to assess the effect of a demand change on the material requirements for your factory next week or the transportation capacity you will need?
6. Supports vertical alignment across multiple timeframes
Last but not least, a digital twin should support strategic and tactical choices to influence the operational decision-making in an enterprise, maintaining the vertical alignment across multiple timeframes. The digital twin should reflect an infrastructure change – immediate or planned – on the ways you revise your tactics and execute your plans.
So, are there true digital twins out there?
By way of example, an ideal digital twin should enable you to design/redesign your global production-distribution network using hundreds of scenarios, rationalize your logistics spend annually, optimize your flow paths from your vendors to your points of sale seasonally, revisit your inventory investment targets periodically and replenish the network daily, while keeping all supply chain decisions synchronized across strategic, tactical and operational dimensions.
I would love to hear your views and experience on digital twins. Meanwhile, we continue to improve the fidelity of a digital twin for a global company, having already processed 100M transactions from 400K unique active SKUs, 16K+ demand locations, 6K+ supply locations, and 200+ DCs and cross-docks. The digital twin remains alive and healthy with its lifeline connected to the source data from multiple systems. The horizontal alignment of decisions across a Total Cost to Serve objective already paid for itself many times just after one year, with significant recurring annual savings to come.
For our clients, the future is here! We look forward to maintaining both the thought and the practical leadership on supply chain digital twins and will continue to share our experiences.
If you would like to chat about digital twins or if you are curious about hearing how Solvoyo enables true digital twins, you can book a 15-minute discussion with me using this link.
