# Forecasting Paper

1450 WordsJan 15, 20066 Pages
Abstract Forecasts are extensively used to support business decisions and direct the work of operations managers. The two major types of forecasts are qualitative and quantitative. Within each of these types are multiple methods and models. Qualitative forecasts are based upon subjective data. Quantitative forecasts are derived from objective data. Both methods are not suitable for all situations and circumstances. Each has inherent strengths and weaknesses. The forecaster must understand the strengths and shortcomings of each method and choose appropriately. One example of forecasting is the United States Marine Corps use of forecasting techniques, both qualitative and quantitative, to predict ammunition requirements.…show more content…
Time Series Analysis Forecasting Time series analysis is a series of observations taken at regular intervals over a specified period of time (Anonymous, n. d.). The following are techniques of time series analysis: simple moving average, weighted moving average and simple exponential smoothing, exponential smoothing with trend, and linear regression (Aquilano, Chase & Jacobs, 2005). Simple Moving Average The simple moving average considers a series of data and uses past performance to predict future performance (Aquilano, Chase & Jacobs, 2005). It is an ongoing exercise. When new data becomes available, the oldest data is dropped from the series and forecasts are recalculated (Aquilano, Chase & Jacobs, 2005). Weighted Moving Average The simple moving average assigns equal weights to all periods considered (Aquilano, Chase & Jacobs, 2005). The weighted moving average allows the forecaster to assigns weights to each period considered (Aquilano, Chase & Jacobs, 2005). The only requirement is that the cumulative weights must equal 1. This method is particularly suitable for businesses with wide seasonal variance. Simple Exponential Smoothing Simple exponential smoothing accounts for the previous period 's forecasting errors in order to more accurately develop the current forecast by applying a smoothing constant or response rate (Anonymous, n. d.). Exponential smoothing also