FORECASTING FORECASTING The Role of the Manager Planning Organizing Staffing Leading Controlling Future ? Data Information • Short-range • Medium-range • Long-range Features Common to All Forecasts Forecasting techniques generally assume that same underlying causal system that existed in the past will continue to exist in the future. Forecasts are rarely perfect. Forecasts for groups of items tend to be more accurate than forecasts for individual items. Forecast
Premium Regression analysis Forecasting Time series
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
Free Exponential smoothing Moving average Time series analysis
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 *
Free Exponential smoothing Moving average Forecasting
Excel Chapter 8 Test 1) Match each term with the correct definition (15 points) A sequence of averages computed from parts of a data series that smoothes fluctuations in data to show a trend more clearly. Moving average In a moving average‚ the number of cells to include in the average. Interval Expenses that remain the same each month. Fixed expenses A point at which an entity covers its costs and starts to make a profit. Break-even A what-if
Premium Spreadsheet Mathematics Average
For example‚ raw materials for the leather jackets need to be ordered 8 months ahead. And‚ in the short term‚ food and labor for daily operations should be forecasted. Hard Rock uses many of the forecasting techniques as: moving averages‚ weighted moving averages‚ exponential smoothing‚ and regression analysis. They start forecasting at the unit level every month‚ then take it to the quarter‚ and then to a year. All this data is compared to previous years and to the budget expectation to make
Premium Forecasting Regression analysis Arithmetic mean
Sales Volume 10000 12400 14250 15750 20500 18500 15750 20500 21500 22550 6. Using Data Set E1‚ what would be the forecast for period 7 using a four period moving average: (Choose the closest answer.) a. 17625 b. 15225 c. 15300 d. 17250 7. Using Data Set E1‚ what would be the forecast for period 6 using a five period weighted moving average? The weights for each period are 0.05‚ 0.10‚ 0.20‚ 0.30‚ and 0.35 from the oldest period to the most recent period‚ respectively. (Choose the
Free Exponential smoothing Moving average Average
ActualForecastErrorError1011-11810-22108 2266 0098 11 FCT 3 What is the forecast for May based on a weighted moving average applied to the following past demand data and using the weights .5‚ .3‚ .2 (largest weight is for most recent data) Nov.Dec.Jan.Feb.Mar.April373640424743 FCT 4 Weekly sales of ten-grain bread at the local Whole Foods Market are in the table below. Based on this data‚ forecast week 9 using a three-week moving average. Week Sales 1 415 2 389 3 420 4 382 5 410 6 432 7 380 8 410 FCT 4 Most forecasting
Premium Inventory Forecasting Moving average
output‚ t = -.412 and p = .689. A stationary model seems appropriate since the linear term‚ Period‚ is not significant. 7.1 c. Forecast for January -- 19‚ for upcoming year – 12*19 = 228 7.1 d. Forecast for January -- 20.4 e. 4 month moving average. MAD is 1.72 7.2 See files Ch7.2a.xls and Ch7.2b.xls a. Forecast for January -- 18.86 7.2 b. See file Ch7.2b.xls Forecast for January -- 20.28 c. = .6 gives the lower MSE 7.3 See file Ch7.3.xls a. b. Coefficients
Premium Regression analysis Linear regression Moving average
WACC: Weighted average cost of capital =WACC= SS+B×Rs+BS+B×RB×1-tC note: Rs ‚ cost of equity; RB ‚ cost of debt; tC ‚ corporate tax rate. For cost of equity‚ Rs‚ we calculate it by using the SML‚ according to CAPM model. Rs=RF+β×[RM-RF] As we can see in the chart behind the case‚ beta of Worldwide Paper Company is 1.10; the Market risk premium (RM-RF) is 6.0%. Because this on-site longwood woodyard project has six year life and the investment spend over two years‚ the total long of this program
Premium Weighted average cost of capital Finance Debt
OPERATIONS MANAGEMENT 1. Supplier Us Customer Raw materials Transforming Work in progress inventory Transformation Finished goods inventory Customer Codex 25000D1‚ 18 dollars (Notes and Problems). Assignment 1‚ 2 make for 15%. Midterm make for 35% and the Assignment 3 for 10%. Finals make up for 40%. Assignments handed in at the beginning of sessions 5‚ 7 and 12. Value added: Inputs Transformation process Outputs. How do we increase value to the product. A lot of things
Premium Value added Output Forecasting