Council Post: Advanced Demand Forecasting using ML – My Experiments

It has become imperative for large organizations to invest in advanced forecasting. While statistical forecasting has been around for decades, this area of time series forecasting is evolving at a breakneck speed.
The post-COVID supply chain world has become significantly more unpredictable and complex. Predicting customer demand is as important as ever, and a precise demand forecasting model is worth its weight in gold. Improving forecast accuracy aids in inventory optimization, warehouse resource/labor planning, supply & logistics planning, financial planning, and enhancing customer service levels. It has become imperative for large organizations to invest in advanced forecasting. While statistical forecasting has been around for decades, this area of time series forecasting is evolving at a breakneck speed. Due to this speed of innovation, traditional supply chain planning platforms are sometimes not able to catch up with the latest technology and AI innovations. As a result, many enterpri
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Picture of Pritam Debnath
Pritam Debnath
Pritam Debnath, Director - Inbound Supply Chain Technology & Supply Chain Innovation at Sysco. He has extensive techno-functional experience in leading diverse cross-functional agile teams through digital transformation, legacy system modernization, AWS cloud migration, and large-scale data migration using Scrum, Kanban, and Scrumban methodologies and is passionate about Digital Transformation, Domain Driven Design, Design Thinking, and Innovation
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