7 Steps to Build Your Digital Supply Chain Twin
We’re pleased to host a guest blog from our partner, Agillitics, who provided their own perspective on how to approach the creation of a digital twin. This was originally published on their blog January 28, 2020.
The digital twin is the virtual representation of physical processes, assets, or systems.
Organizations build and maintain digital supply chain twins to manage their complex and global supply chain networks. Digital twins are utilized to provide horizontal visibility, identify opportunities by discovering patterns, eliminate inefficiencies by determining root causes, create responsive plans for potential disruptions, optimize current processes and available assets, and so much more.
Building and maintaining a digital supply chain twin is not a simple network modeling effort. It requires cross-functional collaboration by operations, finance, IT, and BI teams at the minimum.
The following steps provide you with a proven methodology for supply chain planning by building a digital twin for your supply chain.
Step 1: Map Out Processes and/or Assets
Organizations might prefer to choose to start with creating an end-to-end digital twin of their supply chain. They also might start with a section as a pilot and then scale it after testing. In either case, the teams for each component of the supply chain operations and assets — transportation (fleets), warehousing, inventory, sourcing, etc. — should be the ones who conduct the actual mapping.
Step 2: Determine Data Sources
Traditional network modeling calls for historical data. In some cases, it also requires forecasts and plans. In contrast, digital twins require real-time data that’s steadily fed into the model. Therefore, they are generally linked hand-in-hand to the Internet of Things (IoT). As all relevant operational and financial data is identified during the mapping process, the sources and owners of the data should also be identified.
Step 3: Choose Hosting Technology
There are many critical technological factors when creating and maintaining an IT architecture digital twin. The architecture should allow for connecting to multiple data sources including internal, external, and real-time data and support a wide variety of data formats. It should be scalable to run multiple simulation and optimization scenarios. Security and monitoring should be configured to provide easy access to users with diverse purposes and tasks.
Step 4: Model the Supply Chain Twin
The digital twin should be built keeping the long-term objectives in mind. This process will reflect the creation of supply chain models for optimization and simulation. The structure should allow for simulating and analyzing alternative processes, optimizing asset performances, and predicting occurrences.
Step 5: Connect to Real-Time Data
The two main distinctions of digital twins compared to the optimization of simulation modeling are the use of real-time data and minimal data aggregation to allow for detailed visibility. In other words, the digital twin needs data that is both current and raw. Once the digital twin is built, it is connected to internal as well as external real-time data sources. This might require investment in new technologies such as sensors or RFIDs and collaboration with third parties.
Step 6: Simulate, Optimize, and Analyze
The opportunities for prescriptive, predictive, and advanced analytics using the digital supply chain twin to drive decisions range from strategic to operational. Combined with machine learning when applicable, operations and assets can be simulated or optimized to gain insights, test alternative scenarios, or become responsive to disruptions. The outputs should be shared across the organization to drive organization-wide action plans.
Step 7: Scale and Enhance
As the digital twin of the supply chain is built piece by piece and tested, it is only bound to evolve and expand. It can be scaled across the organization to clone end-to-end supply chains. However, when we think about the supply chain holistically, it can go even beyond the borders of the organization connecting with suppliers and customers. The twin can be enhanced with additional real-time data points from internal sources as well as third parties and industry organizations for optimal scenario planning.
And as always, the whole process needs to be well documented in order to maintain, modify and scale.
Our partner Agillitics covered the seven steps that businesses should consider taking when they get started building a digital twin for their supply chain. With a digital replica of the physical supply chain, this always-on reference model is unlocked with advanced algorithms to visualize all your current state nodes, flows, and policies which can inform operational, strategic, and tactical plans. From mapping processes to modifying architecture based on new information, a digital twin can help an organization's operations with a continuous design model for supply chain resiliency.
The technology behind our digital twin capabilities is something Coupa Supply Chain Design & Planning powered by LLamasoft has perfected over 18 years of doing end-to-end supply chain design and building supply chain models - in thousands of supply chain analytics initiatives for companies with the largest and most complex supply chains in the word.