Application Of Classic Demand Forecasting Methods And Fuzzy Time Series Methods In Large-Scale Building Sector

Demand forecasting continues to be up to date as it is used in many stages of supply chain management. Since the demand forecasting directly affects the costs and profitability of the enterprises, scientific researches are carried out from the past to the present. Although there are many demand forecasting methods, it is necessary to determine the best of these methods according to the operating conditions. The aim of this study is; It is the study of determining which demand estimation method or methods would be more appropriate in the inventory management of a large-scale enterprise operating in the building sector. By taking the past recorded data of the business; Demand forecasting analysis has been done using trend analysis, simple exponential correction, double exponential correction, multiplicative winters and additive winters methods and also fuzzy time series method. Error analysis has been made in order to reach the correct result of the calculation. When the results are compared, the most appropriate demand estimation method for the enterprise is the Additive Holt-Winters method, which has the lowest average absolute percentage error value (3.6%).