The Demand Forecasting module uses a combination of classical statistical forecasting techniques together with modern ML/AI algorithms to generate accurate long-term, medium-term and short- term forecasts. The Auto modeling functionality and Hyper Parameter optimization ensures that the system offers you a ‘best-fit’ forecasting model for a given product, location, and planning level combination, empowering citizen demand planners to create accurate demand plans. This is suitable even in lean manufacturing environments, it supports Kanban, a progressive Operations Planning technique that optimizes inventory levels while reducing inventory costs.
The long-term forecast generated by Demand Forecasting is next refined for higher accuracy over the immediate short-term future horizon using various internal & external variables that have a significant impact on sales demand. Historical data on sales, forecast, and other internal/external variables, such as promotions, price, Point-of-Sales, supply factors, weather events, strikes, lockdowns etc.are used to train an AI / ML model to analyze all events and highlight events that may have a significant impact on sales demand. The trained AI/ML models are then used to predict sales demand accurately over the near-immediate future horizon on a real-time basis.
Successful implementation of demand sensing needs the right mix of data, technology, people & skills. It’s vital to start on a small but sound base and gradually iterate to expand to more variables and application areas across product categories. The key steps to successful implementation are broadly defined below:
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