Forecasting methods Sample Clauses

Forecasting methods. Accurate forecasting may affect decisions and activities of different sectors such as accounting, finance, production, marketing, human resources. All planning processes require forecasting in order to avoid unexpected expense and cope with uncertainty in the future. Forecasting methods allow us to predict and estimate future based on the past data, experience. Forecasting can be performed for (Xxxx and Xxxxxxx, 1989): 1) Long-term decisions: they are used mainly to support strategic decisions such as capacity decision for example. 2) Short-term decisions: they are useful for operational planning in order to meet day-to- day demand. Forecasting can be carried out monthly, yearly or quarterly. We need to remember those: 1) accuracy of forecasting depends on both time horizon and techniques for performing forecasting 2) the longer the forecast time horizon, the less accurate forecasting will be 3) aggregate forecasting is more accurate Companies that implement forecasting approach have the following benefits: 1) ready to meet in advance demand occurring 2) the ability to identify the trend of activities 3) planning capacity and production 4) the ability to reduce cost 5) the ability to increase efficiency As we have already written that forecasting is used to predict what will occur in the future. That’s why forecast accuracy is playing a significant role whether the forecasting will be implemented or not. Forecast accuracy is measured by Mean Average Deviation (MAD) or the Mean Squared Error (MSE) or Mean Absolute Percentage Error (MAPE). We will calculate all of them but will give decisions based on MAPE since it doesn’t depend on the magnitude of the values of demand. MSE is similar to the variance of a random sample. MAD is often used for measuring the forecast error because it doesn’t require squaring. (Xxxxxxx, 1993) We will benefit from the following formulas: Mean Absolute Deviation: MAD = 1 n e ∑ n i =1 i Mean Squared Error: MSE = ∑ ei  1 n e  Mean Absolute Percentage Error: MAPE =  ∑ i  *100  n i=1 Di  Where ei = Fi − Di is the forecast error in period i, D- is the actual value in period i, F- is the forecasted value in period i. n- number of time periods There are many different approaches for conducting a forecast. First of all, forecasting technique is divided into two types: quantitative methods and qualitative methods. Qualitative is based on insights, experiences, opinions and judgments. They do not involve any mathematical computations...