The overall objective of this challenge is to develop a proof of value (PoV) which uses real-time data including variabilities in supply and demand to predict the likelihood of shortages and optimise inventory levels over time to improve performance in today’s volatile supply chains.
This should include:
- Capturing multiple real-time demand signals to improve the overall demand forecast accuracy
- Sensing tools should capture the impact of external variables such as economic conditions, weather forecast, market shifts, oil price or similar causal factors
- Real-time data analytics to provide visibility into potential supply shortfalls during specific periods
- Predict and provide early warning related to service and inventory risks based on the state of the demand and supply conditions
- Applying the demand and supply sensing to specific end-to-end supply chain dataset, demonstrating how this will provide a better solution than is currently available for manufacturing supply chains
- Ensuring the solution is suitable for the SME market