Across sectors, CPG companies today face daunting strategic and operational challenges. An efficient shipments model is imperative to provide a cutting edge cost-optimized logistics chain to drive growth.

In its effort to optimize its supply chains, the consumer industry has evolved in a way to measures its delivery performance, by adopting  “On-Time In-Full” (OTIF) delivery metric.

Identifying late, incomplete deliveries & reasons for the same and then taking timely corrective action to ensure meeting the OTIF (On-Time-In-Full) targets is mission critical for CPG industries, as the fines/penalties imposed by Retailers are quite hefty and negatively impact the margins. 

Key Solution Features

• Infosys Solution uses Machine Learning to generate insights into historical trends and predicts OTIF scores for upcoming weeks. This solution can work as an extension of existing planning systems (e.g. IBP)
• At the time of Order creation - Solution predicts whether the order will be fulfilled In full.
• At the time of Shipment creation – Solution predicts if the shipment will be On-time

• The model learns with every new data point provided to it and prediction accuracy keeps on improving over time. 

• Insights dashboard is created, which provide clear over all picture of ON-TIME and IN-FULL shipments and a comparison of Predicted vs Actual Results to verify accuracy of Solution
  

Business Benefits

• Solution is capable of predicting On -Time vs Late/Early and  In-Full vs Partial  deliveries with 75% accuracy.
• Help CPG Clients to avoid financial Penalties due to late / early and ‘not In-full’ deliveries.
• Though 100% OTIF score may not be possible, the real time supply chain visibility helps move towards it .