Naïve Methods Naïve Forecast – uses a single previous value of a time series as the basis of a forecast. Techniques for Averaging • What is the purpose of averaging? • Common Averaging Techniques o Moving Averages o Exponential smoothing Moving Average Exponential Smoothing Techniques for Trend Linear Trend Equation Curvilinear Trend Equation Techniques for Seasonality • What is seasonality? • What are seasonal
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FORECASTING FUNDAMENTALS Forecast: A prediction‚ projection‚ or estimate of some future activity‚ event‚ or occurrence. Types of Forecasts * Economic forecasts * Predict a variety of economic indicators‚ like money supply‚ inflation rates‚ interest rates‚ etc. * Technological forecasts * Predict rates of technological progress and innovation. * Demand forecasts *
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implementing an effective supplier certification program include all or the following EXCEPT: a. Building long-term relationships b. Reducing time spent on incoming inspections c. Increasing supplier base d. Recognizing excellence 4. A company using a weighted-criteria evaluation system has established these 5 categories and the appropriate weight in parentheses: Quality (0.30) Responsiveness (0.20) Delivery (0.20) Cost (0.20) Technology (0.10) Company X received the following ratings in each of the five
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phone is required to be off during the test. A basic calculator is allowed. 1. Use a 3-period simple moving average to develop a forecast for year 6. Year 2 3 4 5 6 a. b. c. d. e. $415 $445 $525 $605 $625 Sales $450 $495 $518 $563 $584 Forecast 2. Data collected on the annual demand for 50-pound bags of fertilizer at Pikes Garden Supply is shown below. Use a 3-year weighted moving average to forecast sales for year 6‚ where the weights are 0.5‚ 0.3‚ and 0.2‚ respectively (where 0.5 is the weight
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quarters. Based on data analysis the best method for forecasting Highline Financial Services for the upcoming year would be the Moving Average (McNamara‚ 2012). The Moving Average offers the lowest Mean Absolute Deviation ( MAD)‚ lowest means squared error (MSE)‚ and the lowest mean absolute percent error (MAPE) of the two choices selected to forecast. The weighted moving average was not utilized due to the amount of data provide. The ability to
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Part 3 : Acquisition & Production Support. Ch.3 Demand Forecasting. Edited by Dr. Seung Hyun Lee (Ph.D.‚ CPL) IEMS Research Center‚ E-mail : lkangsan@iems.co.kr Demand Forecasting. [Other Resource] Definition. ․ An estimate of future demand. ․ A forecast can be determined by mathematical means using historical‚ it can be created subjectively by using estimates from informal sources‚ or it can represent a combination of both techniques. - 2 - Demand Forecasting. [Other
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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 customers or potential customers regarding
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.......................... 7 4 STATIONARY TIME SERIES.......................................................................................................... 8 4.1 MOVING AVERAGE:............................................................................................................................. 8 4.2 WEIGHTED AVERAGE: ......................................................................................................................... 9 4.3 EXP. SMOOTHING: .....................
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Case study: Forecasting at Hard Rock Café 1. Hard Rock uses a 3- year weighted moving average to evaluate to evaluate managers and set bonuses and determine the café sales. A moving average is also used in which they applied 20% to sales 2 years ago. Using multiple regression‚ managers can compute the impact on demand of other menu items if the price of one item is changed. The three other areas which we think Hard Rock could use forecasting models are: • Computerized Scheduling
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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) b. Calculate the weighted 3-month moving average using weights of 0.50‚ 0.30‚ and 0.20 for periods 4-6. (5 points) c. Calculate the exponential smoothing forecast for periods 2-6 using an initial forecast (F1) 62‚ and an of 0.30. (10 points) d.
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