AI Use Case
Optimise supply chain
Use historic data to model supply chains to identify and predict the way potentially complex and opaque demand patterns ripple through the system under different scenarios (e.g. weather changes). This can be used to predict potential pricing.
Operational - Enables Just in Time approach,Operational Support - Performance tracking,Cost - Reduced inventory costs,Cost - Reduced waiting times
Lennox ~Lennox improves service levels by 16% and increases inventory turns by 25% with machine learning powered demand predictions,Granarolo~Granarolo reduces inventory levels by more than 50% and cuts capital and lead time in half using machine learning ,Infinera~Infinera will optimise its supply chain management to make better predictions about delivery dates using machine learning,Global Transport Provider ~A global transport provider gains a significant competitive advantage by implementing AI for supply chain visibility,University of Pittsburgh Medical Center (UPMC)~University of Pittsburgh Medical Center (UPMC) improves hospital supply chain performance to achieve 92% on-time payments with AI,Kiabi~Kiabi increases in-store product availability by 7% by optimising supply chain management with machine learning,Shell~Shell saves over a million dollars annually by doing inventory analysis 32 times faster using machine learning,Alliance Boots ~Alliance Boots achieves inventory savings and improved service levels with machine learning optimisation algorithm,Unnamed global manufacturer~Unnamed global manufacturer reduces inventory costs by 25-35% and frees up working capital using machine learning,Leroy-Merlin~Leroy-Merlin forecasts sales and suggests orders to department managers to optimise supply chain with machine learning,Schneider Electric ~Schneider Electric saves €8 million by optimising its supply chain using machine learning,"Gousto~Gousto, a British meal kit retailer, grows customer base by 700% by using machine learning to forecast demand and personalise recommendations",Instacart~Instacart predicts availability of 200 million grocery items every 30 minutes using machine learning
Structured / Semi-structured,Time series
Machine Learning (ML),ML Task - Prediction - Regression,Traditional AI,ML Task - Action Selection - Reinforcement Learning ,Model Architecture - Deep Neural Networks,Model Architecture - Recurrent Neural Network (RNN)
ToolsGroup,ToolsGroup,Gravity Supply Chain,Infor,Databricks,C3 IoT,VEKIA,LLamasoft