You are observing the sales department staff using exponential smoothing to fore- cast monthly sales. Their forecast for January's sales was 12,000 units. January's actual sales figure became available yesterday: 10,000 units. Today, the sales depart- ment announced their sales forecast of 11,300 units for February. What alpha are they using to forecast sales?

You are observing the sales department staff using exponential smoothing to fore- cast monthly sales. Their forecast for January's sales was 12,000 units. January's actual sales figure became available yesterday: 10,000 units. Today, the sales depart- ment announced their sales forecast of 11,300 units for February. What alpha are they using to forecast sales?

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

See similar textbooks

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 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_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?
We have a new chief sales officer who is proposing that we should forecast in dollars, not in units/cases. I have never heard of anyone forecasting in dollars. It is true that dollarized forecasts can help sales in knowing precisely what sales target they should be hitting. But, is it the best practice?
Consider the monthly sales data of a company for last year as well as first six-month data for current year. Use a three- quarter weighted moving average, Forecast the sales of company for 3rd Quarter of current year. Use Weights of 4/7, 2/7 and 1/7, giving more weight to more recent data. Note, the 1ist quarter is Jan, Feb and March, 2nd quarter is Apr, May, June, 3rd quarter is July, Aug and Sept, and 4th quarter is Oct, Nov and Dec. Month Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec Last Yr 100 125 135 175 185 200 150 140 130 200 225 250 Current Yr 125 135 135 190 200 190
b) Use exponential smoothing with a smoothing constant of 0.30 to forecast the sales. Assume that last period’s forecast for month 1 is equal to actual to begin the procedure. b. Which method do you think is best? Is this an improvement over the weighted average- use MAD only ?
Explain the trade-off between responsiveness and stability in a forecasting system that uses time-series data. Who needs to be involved in preparing forecasts? 3. How has technology had an impact on forecasting? What capability would an organization have to have to not need forecasts? Give three examples of unethical conduct involving forecasting and the ethical principle each violates
A reputable FMCG company is holding its Annual Sales Conference on January 30th 2021 for its New Year sales plan. The company is interested in launching new product beside its existing product lines. The new product will be novel in the history of the company. 1. Discuss the techniques of forecasting that will be used by the company for its existing and new products.2. Explain specific type and reason for using those techniques. Also identify the limitations of these techniques. Answer should be explaining about new product of FMCG company in details (do not expalin genral it should be specific)
How much does the forecasting process at Deckers correspond with the “typical forecasting process” described at the end of this chapter?
How do you evaluate a forecasting model please use a hypothetical example?Why would you use mean absolute deviation as opposed to the mean average?3. Describe a specific scenario of how you would use a pro forma financial statement?4. List and describe three time series models, and explain when would you use it? (be specific)
Tools View Week 3 Bonus Activity- DEMAND FORECASTING CASE STUDY After reviewing the forecasting demonstration and looking over the slides, complete the following case activity and transfer your answers to the appropriate questions in the Canvas activity quiz. You have been hired as a demand planning intern for Hawaiian Island Creations (HIC). They want you to de- velop a forecast for their HIC Papanui style of sun- glasses. The goal is to determine how many pair they will produce to meet retailer demand in July 2021. During your first meeting, you were handed some data to work with and the product team talked about the company's upcoming promotional blitz to support Summer Break '21 in major vacation destinations. Month Forecast Demand January 2021 4.000 3,300 February 2021 4,200 3,900 March 2021 4,500 4,300 April 2021 4.800 4,200 May 2021 5 000 5.400 of 4 P Type here to search 立

Sara manages one of the Albireds shoe lines, and is working to improve the group's forecasting capabilities so that production will more closely match actual demand (that's the goal, at least!). Work our the exponential smoothing with a smoothing constant equal to 0.2, (seed the model with a January forecast = 16,000). A weighted moving average using 0.6(t-1), 0.3(t-2) and 0.1(t-3)