See to Decide: Visual Management & Collaboration in S&OP

In an era where agility and accuracy are vital for supply chain resilience, this case study highlights the transformation of a global packaging manufacturer’s demand planning process—from fragmented, manual forecasting methods to a centralized, data-driven and machine learning approach. Faced with inconsistent accuracy, reactive planning, and excess inventory, the company implemented a scalable solution that integrated key data sources and introduced more consistent, forward-looking forecasts. The transformation improved forecast accuracy, streamlined planning cycles, and enabled better alignment across sales, operations, ...