IoT-Based Dynamic Demand Forecasting Measures

Abstract: Markets continue to change, and the speed of such change is becoming faster than ever. In order to adapt to the changing markets, corporations have placed a greater emphasis on supply chain management (SCM). Demand forecasting, being the cause of all factors that constitute SCM, is the most crucial factor. Therefore, it is essential to have a dynamic demand measuring method, so that companies could to adapt to the continuous market changes, and carry out market and demand predictions. Predicting the future based on a vast amount of information on diverse areas is one of the unique means for forecasting. Moreover, it has been proven that the forecasts are more accurate when there is more information with greater diversity. The advent of the IoT (Internet of Things) technology and the era of big data have provided humans with more information on diverse areas. This research aims to utilize the IoT technology and big data for an accurate forecast of the intermittent demand, which has been a difficult area for prediction until now. Moreover, the paper presents a platform that can contribute to effective inventory management and production planning through intermittent demand forecasting.