Operations Management
17th Edition
ISBN: 9781259142208
Author: CACHON, Gérard, Terwiesch, Christian
Publisher: Mcgraw-hill Education,
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 15, Problem 1CQ
When creating a time series–based forecast for the amount of soda to be sold in the cafeteria next week, which data sources can you include in your
- a. The opinion of the principal
- b. Old demand data
- c. Data about upcoming sports events
- d. The age of the cafeteria worker
Expert Solution & Answer
Summary Introduction
To determine: The data source to be included in time series-based forecast for the quantity of soda to be sold in cafeteria for next week.
Answer to Problem 1CQ
b. Old demand data.
Explanation of Solution
Data to be included in time series-based forecasting:
Option B which is old demand data is correct. Time series based forecasting method utilizes the data from the past to forecast the future demand. So, the past demand data must be included in time series forecasting methods.
Want to see more full solutions like this?
Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!
Students have asked these similar questions
Which of the following is not true of qualitative forecasting methods?
a. They generally work best when combined with a quantitative approach
b. They are more objective than quantitative methods
c. They are largely non-mathematical
d. They are not restricted to only the quantifiable data
e. They come with the danger of biasing the forecast due to subjectivity
Explain both true and false options briefly
You have a data set that includes time period and past sales data, and you want to use a time series forecasting technique.
Which of the following forecasting methodologies is considered a time series forecasting technique?
a.Group of answer choices
b.Delphi method
c.Simple movement smoothing
d.Weighted moving average
e.Simulation
f.Exponential averaging
Walmart’s Human Resource Planning
Forecasting. Walmart’s human resource management forecasts its workforce needs to ensure capacity to address changes in consumer demand. While other forecasting methods and techniques are also used, these three are the most notable at Walmart:
Chapter 15 Solutions
Operations Management
Ch. 15 - When creating a time seriesbased forecast for the...Ch. 15 - Prob. 2CQCh. 15 - Prob. 3CQCh. 15 - Prob. 4CQCh. 15 - Prob. 5CQCh. 15 - Prob. 6CQCh. 15 - Prob. 7CQCh. 15 - Prob. 8CQCh. 15 - Using the moving average forecast, is it possible...Ch. 15 - Prob. 10CQ
Ch. 15 - Prob. 11CQCh. 15 - Prob. 12CQCh. 15 - Prob. 13CQCh. 15 - Deseasonalizing old demand data is the process of...Ch. 15 - Prob. 15CQCh. 15 - Prob. 1PACh. 15 - Prob. 2PACh. 15 - Prob. 3PACh. 15 - A police station had to deploy police officers for...Ch. 15 - MyApp is a small but growing startup that sees...Ch. 15 - Prob. 6PACh. 15 - Prob. 7PACh. 15 - Prob. 1CCh. 15 - CASE INTERNATIONAL ARRIVALS The U.S. Department of...Ch. 15 - Prob. 3C
Additional Business Textbook Solutions
Find more solutions based on key concepts
1-1. Define marketing and outline the steps in the marketing process. (AASCB: Communication)
Marketing: An Introduction (13th Edition)
Real options and its types. Introduction: The net present value is the variation between present cash inflows v...
Gitman: Principl Manageri Finance_15 (15th Edition) (What's New in Finance)
The flowchart for the process at the local car wash. Introduction: Flowchart: A flowchart is a visualrepresenta...
Principles of Operations Management: Sustainability and Supply Chain Management (10th Edition)
How would the decision to dispose of a segment of operations using a split-off rather than a spin-off impact th...
Advanced Financial Accounting
Mary Williams, owner of Williams Products, is evaluating whether to introduce a new product line. After thinkin...
Operations Management: Processes and Supply Chains (12th Edition) (What's New in Operations Management)
How is activity-based costing useful for pricing decisions?
Horngren's Cost Accounting: A Managerial Emphasis (16th Edition)
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.Similar questions
- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?arrow_forwardThe file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.arrow_forward
- The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?arrow_forwardThe file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?arrow_forwardThe file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?arrow_forward
- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?arrow_forwardThe file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?arrow_forwardThe file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?arrow_forward
- When creating a time series–based forecast for the amount of soda to be sold in thecafeteria next week, which data sources can you include in your forecasting process?a. The opinion of the principalb. Old demand datac. Data about upcoming sports eventsd. The age of the cafeteria workerarrow_forwardAn analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is F; = 124 + 2.1t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.) t Units Sold 11 144 12 146 13 152 14 142 15 152 16 149 17 152 18 154 19 157 20 164 Click here for the Excel Data File MAD (Naive) 5.11 MAD (Linear) 5.49 MSE (Naive) MSE (Linear)arrow_forwardYou manager gave you February 2021 actual sales and sales forecast. This is the only raw data you have access to. Which of the following is the most appropriate technique for forecasting March 2021's sales? a.Simple moving average b.Exponential smoothing c.Causal relationship forecasting d.Simple linear regression e.Weighted moving averagearrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,
Contemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage Learning
MarketingMarketingISBN:9780357033791Author:Pride, William MPublisher:South Western Educational Publishing
Practical Management Science
Operations Management
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:Cengage,
Contemporary Marketing
Marketing
ISBN:9780357033777
Author:Louis E. Boone, David L. Kurtz
Publisher:Cengage Learning
Marketing
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Single Exponential Smoothing & Weighted Moving Average Time Series Forecasting; Author: Matt Macarty;https://www.youtube.com/watch?v=IjETktmL4Kg;License: Standard YouTube License, CC-BY
Introduction to Forecasting - with Examples; Author: Dr. Bharatendra Rai;https://www.youtube.com/watch?v=98K7AG32qv8;License: Standard Youtube License