“Digital Twin” in the Supply Chain

In Miebach’s definition, a Supply Chain Digital Twin is a virtual representation of a company’s supply chain supported by real data. There are several key criteria for it:

• It connects different Supply Chain functions and/or organizations.
• It is up-to-date supported by frequently updated data, if not real-time.
• It establishes the logical relationships between different supply chain segments and/or organizations to understand impacts and allow scenario planning.
• It analyzes impacts and plans scenarios using heuristics, optimizations and simulations

From raw material sourcing all the way delivery to consumers, the supply chain's complex nature is due to the coordination requirements from the various parties and functions engaged. Risks or disruptions in any one of the steps or locations in the chain can have significant impact to the others, known as the bullwhip effect. With today's volatility, the cause-and-effect relationships can become convoluted quickly and it is a common challenge to de-tangle and understand the impacts from different activities in the complete and dynamic supply chain.

A supply chain Digital Twin not only reports what happened historically, but also helps to analyze locate the potential root cause to a situation, as well as potential impacts from an event using advanced analytics (machine learning and simulation). Furthermore, with its analytical capabilities, the digital twin helps predict future impacts and suggests optimal reaction plans through robust optimization algorithms and what-if analysis.

Coupa's Supply Chain Design and Planning tool is the industry leader in digital design and decision-making and provides the one-stop-shop for all capabilities required to establish a digital twin from scratch.

Miebach, as a global alliance partner of Coupa, provides best-in-class consultants, modelers, and app developers to help clients develop their supply chain Digital Twin in the platform. Our success stories include: 

• Manufacturing digital twin for tactical capacity planning
• Distribution network digital twin for flow routing and optimization
• Materials planning and Inventory planning in multi-echelon networks
• Cross-dock and transportation asset management

• Data studio to store, sort, and organize customer’s supply chain data from different sources and different formats
• Connection to various systems for data updates and refreshes
• Model studio to establish the logical relationships along the supply chain for optimization, and simulation
• Enabling Parallel solutions for multiple scenarios to allow a robust what-if analysis
• App studio to enable democratization of the models and direct business user access