Supply Chain Optimization

Supply chains are complex. Fluctuation in demand, transportation costs, and many other factors, such as bad weather, can adversely affect supply chain network performance. Managers require insights to inform decisions in the face of such uncertainties and mitigate risks such as delays and excess stock. Without tools to provide these insights, planning is extremely challenging and optimization becomes impossible.

A digital twin is a digital representation of a real world physical product, system or process1. When applied to supply chain optimization, it is possible to model the entire network and run different what-if scenarios to ascertain how the network will react to different input behaviors (time delays, varying costs etc.).

Using the anyLogistix software, ITC Infotech, a global business solutions & technology services leader, was able to build a digital twin for a fast moving consumer packaged goods (FMCPG) company2. Using input from ERP systems, event information and daily demand forecasts, the digital twin was utilized to fully replicate the supply chain’s behavior and output a 15 day forecast for the network.

AI-powered root cause analysis algorithms were then applied to the forecast in order to identify potential underperformance and suggest remediation actions ahead of time.