Loose-leaf for Operations Management (The Mcgraw-hill Series in Operations and Decision Sciences)
12th Edition
ISBN: 9781259580093
Author: William J Stevenson
Publisher: McGraw-Hill Education
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Chapter 7.S, Problem 13P
Summary Introduction
To provide: Justification for learning percentage of 82 possessed by person K.
Introduction: Learning curve is referred as the cost curve, experience curve, efficiency curve or productivity curve. The leaving curve gives information about the cost, efficiency, productivity and performance of an organization.
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Scenario
You have been given a task to create a demand forecast for the second year of sales of a premium outdoor grill.
Accurate forecasts are important for many reasons, including for the company to ensure they have the materials
they need to create the products required in a certain period of time. Your objective is to minimize the forecast
error, which will be measured using the Mean Absolute Percentage Error (MAPE) with a goal of being below 25%.
You have historical monthly sales data for the past year and access to software that provides forecasts based on
five different forecasting techniques (Naïve, 3-Month Moving Average, Exponential Smoothing for .2, Exponential
Smooth for .5, and Seasonal) to help determine the best forecast for that particular month. Based on the given
data, you will identify trends and patterns to create a more accurate forecast.
Approach
Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next…
Chapter 7 Solutions
Loose-leaf for Operations Management (The Mcgraw-hill Series in Operations and Decision Sciences)
Ch. 7.S - Prob. 1DRQCh. 7.S - Prob. 2DRQCh. 7.S - Prob. 3DRQCh. 7.S - Prob. 4DRQCh. 7.S - Prob. 5DRQCh. 7.S - Prob. 6DRQCh. 7.S - Prob. 7DRQCh. 7.S - Prob. 8DRQCh. 7.S - Prob. 9DRQCh. 7.S - Prob. 10DRQ
Ch. 7.S - Prob. 1PCh. 7.S - Prob. 2PCh. 7.S - Prob. 3PCh. 7.S - Prob. 4PCh. 7.S - Prob. 5PCh. 7.S - Prob. 6PCh. 7.S - Prob. 7PCh. 7.S - Prob. 8PCh. 7.S - Prob. 9PCh. 7.S - Prob. 10PCh. 7.S - Prob. 11PCh. 7.S - Prob. 12PCh. 7.S - Prob. 13PCh. 7.S - Prob. 14PCh. 7.S - Prob. 15PCh. 7.S - Prob. 16PCh. 7.S - Prob. 17PCh. 7.S - Prob. 18PCh. 7.S - Prob. 19PCh. 7.S - Prob. 1CQCh. 7.S - Prob. 2CQCh. 7.S - Prob. 3CQCh. 7 - Prob. 1DRQCh. 7 - What are some of the main advantage and...Ch. 7 - Prob. 3DRQCh. 7 - Prob. 4DRQCh. 7 - Prob. 5DRQCh. 7 - Prob. 6DRQCh. 7 - Prob. 7DRQCh. 7 - What are motion study principles? How are they...Ch. 7 - Prob. 9DRQCh. 7 - Prob. 10DRQCh. 7 - Prob. 11DRQCh. 7 - Prob. 12DRQCh. 7 - Prob. 13DRQCh. 7 - Prob. 14DRQCh. 7 - Prob. 15DRQCh. 7 - Prob. 16DRQCh. 7 - Prob. 17DRQCh. 7 - Prob. 18DRQCh. 7 - Prob. 19DRQCh. 7 - Prob. 1TSCh. 7 - Prob. 2TSCh. 7 - Prob. 3TSCh. 7 - Prob. 1CTECh. 7 - Prob. 2CTECh. 7 - Prob. 1PCh. 7 - Prob. 2PCh. 7 - Prob. 3PCh. 7 - Given these observed times (in minutes) for four...Ch. 7 - Prob. 5PCh. 7 - Prob. 6PCh. 7 - Prob. 7PCh. 7 - Prob. 8PCh. 7 - Prob. 9PCh. 7 - Prob. 10PCh. 7 - Prob. 11PCh. 7 - Prob. 12PCh. 7 - Prob. 13PCh. 7 - An analyst made the following observations about...Ch. 7 - Prob. 15PCh. 7 - Prob. 16PCh. 7 - Prob. 17PCh. 7 - Prob. 18PCh. 7 - Prob. 19PCh. 7 - Prob. 1CQCh. 7 - Prob. 2CQCh. 7 - Prob. 3CQCh. 7 - Prob. 4CQ
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- Approach Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next month. Remember to select the forecasting technique that produces the forecast error nearest to zero. For example: a. Naïve Forecast is 230 and the Forecast Error is -15. b. 3-Month Moving Forecast is 290 and the Forecast Error is -75. c. Exponential Smoothing Forecast for .2 is 308 and the Forecast Error is -93. d. Exponential Smoothing Forecast for .5 is 279 and the Forecast Error is -64. e. Seasonal Forecast is 297 and the Forecast Error is -82. The forecast for the next month would be 230 as the Naïve Forecast had the Forecast Error closest to zero with a -15. This forecasting technique was the best performing technique for that month. You do not need to do any external analysis-the forecast error for each strategy is already calculated for you in the tables below. Naïve Month Period Actual Demand Naïve Forecast Error 3- Month Moving Forecast 3- Month Moving…arrow_forwardScenario You have been given a task to create a demand forecast for the second year of sales of a premium outdoor grill. Accurate forecasts are important for many reasons, including for the company to ensure they have the materials they need to create the products required in a certain period of time. Your objective is to minimize the forecast error, which will be measured using the Mean Absolute Percentage Error (MAPE) with a goal of being below 25%. You have historical monthly sales data for the past year and access to software that provides forecasts based on five different forecasting techniques (Naïve, 3-Month Moving Average, Exponential Smoothing for .2, Exponential Smooth for .5, and Seasonal) to help determine the best forecast for that particular month. Based on the given data, you will identify trends and patterns to create a more accurate forecast. Approach Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next…arrow_forwardUse the internet to obtain crash safety ratings for passenger vehicles. Then, answer thesequestions:a. Which vehicles received the highest ratings? The lowest ratings?b. How important are crash-safety ratings to new car buyers? Does the degree of importancedepend on the circumstances of the buyer?c. Which types of buyers would you expect to be the most concerned with crash-safety ratings?d. Are there other features of a new car that might sway a buyer from focusing solely on crashsafety? If so, what might they be?arrow_forward
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