In an ideal world, demand and supply would be steady and predictable, resulting in optimal capacity utilization and no back orders or missed customer orders. However, in the actual supply chain world variations in actual sales vs. projected sales result in lower forecast accuracy, and either overstocking or stock out situations.
Over the past few months, we’ve been running simulation tests on different demand forecasting methods: Winter’s additive & multiplicative, seasonal and robust seasonal. Then, we used MAPE to determine the forecast accuracy for each method. Here’s what we found.
“It is said that the present is pregnant with the future” – Voltaire Forecasting, therefore, is an attempt to deduce the future from the present. It is both, art and science. We will explore the practice of forecasting demand in the short to medium term. Within the constraints of economic and technology trends, demand forecasting drives the planning process in most businesses.