Answered: Find forecasting error from the…

Find forecasting error from the following table by using Tracking Signal. Period Actual Demand Forecasted Demand 1 8 10 2 10 10 3 7 10 4 13 10 5 9 10 6 12 10

Contemporary Marketing

18th Edition

ISBN:9780357033777

Author:Louis E. Boone, David L. Kurtz

Publisher:Louis E. Boone, David L. Kurtz

Chapter14: Pricing Strategies

Section14.2: Forecasting Demand

Problem 1LO

See similar textbooks

Related questions

Q: The Pro Apparel company manufactures baseball-stylecaps with various team logos. The caps come in an…

A: Forecasting is a tool to recognize problems and opportunities in the business and turning it into…

Q: Given the following data, use exponential smoothing(a = 0.2) to develop a demand forecast. Assume…

A: Given data Exponential smoothing (a) or α= 0.2 Initial time period (F1) = 5 To develop the demand…

Q: I Using a numerical example, demonstrate to Mr. Ferdinand how he can use a three- week and a…

A: Forecasting the future demand/sales can be done by various methods like moving average, weighted…

Q: a. Using a simple three-month moving average, make a forecast for this month. (Round your answer to…

A: Forecasting is the process of predicting the future demand according to past data and demand.

Q: Explain linear trend forecast?

A: Forecasting is the technique of accurately estimating future demand for the goal of planning future…

Q: Given the following history, use a three-quarter moving average to forecast the demand for the third…

A: Solution Moving average considers the average of the past data. The average can be of three periods…

Q: Tracy is the the Director of Supply Chain at Circuits Inc. An accurate forecast at Circuits Inc. is…

A: Error = Actual demand - Forecast Absolute Error = Positive Value of Error MAD = Average of Absolute…

Q: The number of internal disk drives (in million) made at a plant in Taiwan during the past 5 years…

A: a. Forecast using simple linear regression: Year (X) Disks (Y) X×Y X2 1 142 142 1 2 156 312…

Q: Period Actual 1 12 2 15 16 4 16 Given the information in the following table, Use exponential…

A: Note: - Since the actual data for period 5 is not given, the trend-adjusted forecast can be made by…

Q: Given the following history, use a three-quarter moving average to forecast the demand for the third…

A: Given data is

Q: Employing a 4 period moving average, forecast periods 5-8 and determine the forecast error (round 2…

A: 4 Period Moving Average forecast = sum of the actual demand of last 4 periods / 4…

Q: Zeus Computer Chips, Inc., used to have major contracts to produce the Centrino-type chips. The…

A: Two years ago Units Last Year Unit This Year Units I 4805 I 3505 I 3195 II 3505 II 2705 II…

Q: Short term forecast can be used for the following operation.

A: Short term forecastUp to 1 year, usually less than 3 monthsPurchasing, job planning, staff levels,…

Q: The following table shows the actual demand observed over the last 11 years: Year 1 2 4 7 8 10 11…

A: Given - Table for demand seen in past years- Year Actual Demand 1 6 2 9 3 4 4 9 5 13…

Q: Given the following history, use a three-quarter moving average to forecast the demandfor the third…

A: Given information:

Q: Describe the exponential smoothing forecast?

A: In exponential smoothing forecasting, all the values of past demand are taken into consideration by…

Q: c) What is this year's forecast using exponential smoothing with alpha = 0.4, if year 2017's…

A: The concept of Operation Management: Operation management is the management that applies to a…

Q: 1 demand of cotton(intones) by Westham textile S.C are shown below 1 2 3 4 7 8 year Actual 10 11 13…

A: Note: Since you have posted multiple parts in the same questions, we will be answering the first…

Q: Determine the Forecast Error for the data below using the Mean Absolute Percentage Error (MAPE)…

A: Error = Demand - Forecast Absolute Error = Positive value of Error Percent Error = (Absolute error…

Q: Hint: Exponential Smoothing: The company has accumulated the demand data, shown below, for its…

A: Exponential smoothing- F(t+1) = αAt + (1-α)Ft α = 0.5

Q: Given the following history, use a three-quarter moving average to forecast the demand for the third…

A: 3 -period moving average forecast = At-1+At-2+At-33 Where, At-1= Actual data of previous period t…

Q: Storrs Cycles has just started selling the new Cyclone mountain bike, with monthly sales as shown in…

A: Since you have posted a question with multiple sub-parts, we will solve the first three subparts for…

Q: 1. Which of the following is indicative of the season of heaviest demand when seasonality is…

A: The seasonal index of 1.25 indicates the season of heaviest demand because this is 125% that shows…

Q: 1. The Southern Pizza Parlor is a small restaurant. One of the customers' favorites is Southern…

A: Forecasting helps to know the sales of the product in advance so that appropriate stock levels are…

Q: b. Given the forecast demand and actual demand for a fishing boat, compute the tracking signal and…

Q: 5. Compute a three-period moving average forecast and five-period moving average forecast given…

A: Moving average forecast method is a simple average method in which forecast for next period is…

Q: Dave's Bar-B-Q operated a moble kitchen that serviced construction sites, office buildings, and…

A: From the given data, Let F3 = forecast value for third week of june Y2= 6 F2=4.7…

Q: Using exponential smoothing method, forecast the demand for the fourth period. The historical demand…

A: Exponential smoothing is a time series method for forecasting to know the demand for the next…

Q: A firm uses simple exponential smoothing with trend adjustment to forecast demand, "a = 0.6" and…

A: Given, TAF for first month TAF1 = 434 units Actual demand for first period A1= 488 units Trend T1 =…

Q: Weekly demand for an item averaged 100 units over the past year. Actual demand forthe next eight…

Q: Can you either overestimate or underestimate the actual sales number for a poor forecast?

A: A forecast is a foresight of whatever will occur. While usually practiced in the circumstances of…

Q: Plot the demand data. What do you observe? Forecast XR-42S demand for month 7, using a weighted…

A: Given data - Month Number of lenses sold 1 12 2 17 3 15 4 20 5 18 6 23

Q: Consider the following yearly demand values for a particular product. Year Demand 1 360 2 389 410 4…

A: The technical analysis methods used to smooth the data price by creating a regular updated average…

Q: A restaurant manager with analyzing records of the last 6 weeks summarizes the daily demand figures…

A: Forecasting can help in predicting the demand for the product in the future. There are various time…

Q: a) Calculate the three-period moving-average forecast for periods 7 through 10. Three-period Period…

A: Given data is

Q: Given the following history, use a three-quarter moving average to forecast the demand for the third…

A: The solution for the above is mentioned in the below excel spreadsheet as follows.

Q: Apply collaborative techniques to forecast demand.

A: Collaborative forecasting is the process for collecting and reuniting the information from different…

Q: A restaurant manager with analyzing records of the last 6 weeks summarizes the daily demand figures…

A: Forecasting is critical for any business since it helps the organization to make informed business…

Q: A manager uses this equation to predict demand for landscaping services: Ft= 10 + 5t. Over the past…

Q: Compute the forecast sale using α = 0.20 and α = 0.35 respectively. (Note: express all answers…

A: Forecasting is the process of estimation in which the future demand is determined based on previous…

Q: The following data shows sales forecast of Axis Dealer for motorbikes. Month Demand 1 650 2 700 810…

A: Given data:

Q: b. Compute all possible forecasts using a five-period moving average. (Round your answers to 1…

A: Forecasting is the technique that is used to predict future trends on the basis of historical data.…

Q: Week Of Pints Used August 31 September 7 September 14 September 21 September 28 October 5 345 370…

A: c) Exponential smoothing is also the forecasting technique. In this method of forecasting, alpha is…

Q: The manager of XYZ carpet cleaning company needs a weekly forecast of the number of customers…

A: Find the Given details below: Given Details: Demand Year 1 Year 2 Year 3 Week 1 102 114…

Q: b. If 275 units were actually demanded this month, what would your forecast be for next month, again…

Q: You have the data on the application during the 8 consecutive year period below Wanted / Find the…

A: Given that: Year Demand 2000 24 2001 48 2002 50 2003 68 2004 60 2005 66 2006 70…

Q: While monitoring the forecast values in last 5 months, the tracking signals are consistently coming…

A: The tracking signal is given the ratio of accumulated forecast error to average error, with 0 being…

Q: Year 1 Demand Year 2 Demand Year 3 Demand 1 12 1 16 1 14 45 25 32 3 76 52 3 71 84 4 4 62 4 47 a.…

A: Since we only answer up to 3 sub-parts, we’ll answer the first 3. Please resubmit the question and…

Q: Given the following demand data, compute a simple exponential smoothing forecast for alpha values of…

A: Given data is

Concept explainers

Forecasting in Business

Forecasting is the process of predicting the future based on the past and the present data and circumstances. In other words, forecasting is the act of making a detailed analysis of future events based on the decisions made in the past as well as the present. Forecasting plays a very important role in operational management as it helps in planning and decision-making. It is not only important for the success of a business but also contributes to individual growth and success. Many business organizations or companies have failed due to the shortcomings of their forecasting.

Question

Find forecasting error from the following table by using Tracking Signal.

Period	Actual Demand	Forecasted Demand
1	8	10
2	10	10
3	7	10
4	13	10
5	9	10
6	12	10

Leveraging special tenchniques in analyzing historical data to predict future trends. Forecasting covers the methods and types of forecasting and their application to case studies.

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Forecasting Error:

VIEW

Computation of Forecasting error by using Tracking Signal.

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 2 steps with 1 images

SEE SOLUTION Check out a sample Q&A here

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

The 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.
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?
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?
The 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?
The 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?
The 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?
The 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?
The 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?
Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.
The following represents the actual demand and two different sets of forecasts using different methods. Compute the MAD for each forecasting method and determine the best method for this set of data. Year-Qtr Actual demand Forecast methos 1 MAD1 (A-F) Forecast Method 2 MAD2 (A-F) 2020-3 98 97 89 2020-4 108 110 106 2021-1 83 68 70 2021-2 100 101 102 2021-3 95 86 87 2021-4 90 94 92 2022-1 71 68 72 2022-2 104 105 106 2022-3 84 91 88 2022-4 80 93 91 2023-1 78 68 70 2023-2 120 118 122
Given the following data for demand at the XYZ Company, calculate the monthly forecast for 2003 using a 3-month moving average. Calculate the Forecast, Error, MAD (mean absolute percentage error), Bias and the TS (tracking signal) . Period Demand Forecast Error MAD Bias TS 2-Oct 2012 800 　　　　　 2-Nov 2012 1000 　　　　　 2-Dec 2012 950 　　　　　 2-Jan 2013 1100 2-Feb 2013 930 2-Mar 2013 1020 2-Apr 2013 870
Consider the following information: Year Quarter Actual Sales (000) 2018 1 20 2 15 3 22 4 35 2019 1 24 2 18 3 25 4 45 2020 1 15 2 05 3 28 4 40 Forecast demand using trend projection method taking into consideration seasonality for the year 2021.