Demand forecasting is the process of leveraging historical data and other analytical information to build models that help predict future estimates of customer demand for specific products over a specific period. It helps shape product road map, inventory production and inventory allocation, among other things.
According to McKinsey, a 10% to 20% improvement in supply chain forecasting accuracy is likely to produce a 5% reduction in inventory costs and a 2% to 3% increase in revenues. In a world where margins are increasingly narrow and critical, this percentage can be make or break. But traditional supply chain forecasting tools have failed to deliver the desired results, limiting success of retailers and manufacturers.
https://www.youtube.com/watch?v=eJukecrmzoI
https://www.databricks.com/solutions/accelerators/demand-forecasting
Demand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data. Retailers are facing a trillion-dollar problem due to unavailable products at the time consumers demand them. Poor demand forecasting is causing companies to put the wrong product on the shelf, or an even bigger issue, to have in-store stock outages
https://www.databricks.com/glossary/demand-forecasting
https://www.databricks.com/notebooks/fine-grained-demand-forecasting.html
https://www.databricks.com/wp-content/uploads/notebooks/fine-grained-demand-forecasting-spark-3.html
https://github.com/databricks-industry-solutions/parts-demand-forecasting
https://github.com/databricks-industry-solutions/fine-grained-demand-forecasting
https://www.youtube.com/watch?v=VWD1PJpYYUQ
https://www.databricks.com/company/partners/consulting-and-si/partner-solutions/ey-demand-forecasting-for-manufacturing
https://vimeo.com/706361508
https://www.youtube.com/watch?v=N1N0fmJDlfc
https://www.youtube.com/watch?v=TkcpjnLh690