to determine what forecasting method to use. Based upon the following historical data‚ calculate the following forecasts for each given forecasting method and then choose the best one to do the forecasts for the future. Actual Month Demand 1 62 2 65 3 68 4 70 5 72 6 74 a. Calculate the simple 3-month moving average forecast for periods 4-6. (5 points)
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Quantitative Methods ADMS 3330 3 0 3330.3.0 Forecasting QMB Chapter 6 © M.Rochon 2013 Quantitative Approaches to Forecasting Are based on analysis of historical data concerning one or more time series. Time series - a set of observations measured at successive points in time‚ or over successive periods of time. If the historical data: • are restricted to past values of the series we are trying to forecast‚ it is a time series method. 1 Components of a Time Series 1)
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account data trend‚ cyclical effects‚ or seasonality. For this reason‚ naive models seem to work better with data that are reported on a daily or weekly basis or in situations that show no trend or seasonality. The simplest of the naive forecasting methods is the model in which the forecast for a given time period is the value for the previous time period. Ft = x t-1 Where‚
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Delphi method 1.moving averages 1.regression analysis 2.Opinion poll 2.exponential smoothing 2.multiple regression 3.Historical Analogy 3.econometric models 4.Field Surveys 5.Business barometers 6.Extrapolation Technique 7.Input-Out put Analysis 8.Lead Lag Analysis 9.Sales force composites 10.Consumer Market survey Simple Average Method The historical data is used for extrapolating and forecasting. Either simple averages or moving averages could
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June Demand 89 57 144 221 177 280 Month July August September October November December Demand 223 286 212 275 188 312 a. Determine the one-step-ahead forecasts for the demand for January 2000 using 3-‚ 6-‚ and 12-month moving averages. b. Using a four-month moving average‚ determine the one-step-ahead forecasts for July through December 1999. c. Compute MAD‚ MSE‚ MAPE for the forecasts obtained in b. Solution: a. MA (3) forecast: 258.33 MA (6) forecast: 249.33 MA (12) forecast: 205.33 b. Month
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Managers are always trying to reduce uncertainty and make better estimates of what will happen in the future n This is the main purpose of forecasting n Some firms use subjective methods n Seat-of-the pants methods‚ intuition‚ experience n There are also several quantitative techniques n Moving averages‚ exponential smoothing‚ trend projections‚ least squares regression analysis` © 2009 Prentice-Hall‚ Inc. 5–2 1 9/5/14 Introduction n Eight steps to forecasting : 1. Determine
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Co-owner Barbara wants to use a three-period moving average. 1. Is there a strong lineal trend in sales over time? 2. Fill in the table with what Amit and Barbara each forecast for May and the earlier months‚ as relevant. 3. Assume that May’s actual sales figure turns out to be 405. Complete the table’s columns and then calculate the mean absolute deviation for both Amit’s and Barbara’s methods. 4. Based an these calculations‚ which method seems more accurate? 1. Naive forecast:
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superior forecasting method to exponential smoothing. 3. T F The 3 categories of forecasting models are time series‚ quantitative‚ and qualitative. 4. T F Time-series models attempt to predict the future by using historical data. 5. T F A moving average forecasting method is a causal forecasting method. 6. T F An exponential forecasting method is a time-series forecasting method. 7. T F The Delphi method solicits input from
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forecasting General steps in the forecasting process Qualitative techniques in forecasting Time series methods The Naive Methods Simple Moving Average Method Weighted Moving Average Exponential Smoothing Evaluating the forecast accuracy Trend Projections Linear Regression Analysis Least Squares Method for Linear Regression Decomposition of the time series Selecting A Suitable Forecasting Method More on Forecast Errors Review Exercise CHAPTER 6 FORECASTING TECHNIQUES 6.1 Introduction: Every manager
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| (a) Forecast the demand for pizza for Week 4‚ 5‚ and 6 using a naïve method. (b) Forecast the demand for pizza for Week 4‚ 5‚ and 6 using the simple moving average method with n = 3. (c) Repeat the forecast for Week 4‚ 5‚ and 6 by using the weighted moving average method with n = 3 and weights of 0.50‚ 0.30‚ and 0.20 with 0.50 applying to the most recent demand. (d) Calculate the MAD and MSE for each method. Q-2. The monthly demand for units manufactured by the Ace Rocket Company
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