Demand forecasting to optimize supply chain management

Demand forecasting is generally related to the market demand for goods and services. Failure to predict customer demands of products, intent to purchase, preferences, and needs may lead to potential loss in revenues. The role of demand forecasting in the supply chain is more significant as it must take care of both customer-driven demand and material requirement planning. Therefore, demand forecasting is a crucial tool for the supply chain as it provides information for inbound and outbound logistics, manufacturing, financial planning, risk assessments, and meeting customer demand. The chapter deals with demand forecasting and its role in supply chain management. This is an exploratory study in which we are using secondary data to formulate the objectives of the study. A systematic narration will be done to compare various information regarding demand forecasting in supply chain management. Existing literature, databases, cases, and web pages are explored to drive conclusions for the stated objectives. Demand forecasting is in a state of transition to achieve optimal results in the supply chain. Although traditional methods of demand forecasting still exist, an impetuous has been given by the latest technologies involving advanced analytics, powerful databases, and the use of artificial intelligence (AI) and machine learning. By predictive analysis, the supply chain has increased accuracy, reduced inventory cost, and increased inventory control ( Bam et al. 2017 ). The latest techniques have made the data updating process faster, and it is linked to the forward and reverse logistics helping in accessing demands. Different industries have different demand and supply patterns. Henceforth, each industry type has its way of meeting the demand for the products. It includes both the procurement of raw materials and the prediction of customer demand.