Building an accurate and efficient demand forecast is essential to successful supply chain management. This white paper focuses on how an efficient use of data can lead to a high-performance forecast. Demand forecasts have common characteristics that a business can use to identify appropriate methodologies. Predicting future demand is difficult because of natural variation, underlying growth trends, and seasonality. Demand is manifested from aggregated human behavior, which is based on a subjective decision-making process. This paper advocates for collaborative forecasting and using classical methods as a baseline for more complex models.
A statistical understanding of how demand forecasts work can pave the way to success for all supply chain partners. To evaluate performance, it is also important to keep a record of forecast errors. Businesses can accomplish their supply chain objectives and make better decisions with great forecasts. Not all businesses are building demand forecasts to their full potential, and the ones that do are able to retain their competitive edge.
