/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q21OQ The following table shows predic... [FREE SOLUTION] | 91影视

91影视

Log out

Learning Materials

Features

Discover

Chapter 4: Q21OQ (page 480)

The following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred:

Forecast

Actual

1500

1550

1400

1500

1700

1600

1750

1650

1800

1700

a. Compute the tracking signal using the mean absolute deviation and running sum of forecast errors.

b. Discuss whether your forecasting method is giving good predictions.

Short Answer

Expert verified

Forecasting is the method of creating predictions supported by past and current data. Later these may be compared against what happens.

Step by step solution

01

(a) Tracking signal (mean absolute deviation & running sum of forecast)

The mean absolute deviationis defined as the average distance between each data point and therefore the mean. It gives us a plan for the variability in an exceeding data set. The MAD calculation of forecast errors is done in the (8) column of the table as shown below:

A tracking signal(TS) can be calculated using the arithmetic sum of forecast deviations divided by the mean absolute deviation. The calculation of the tracking signal is done in the (9) column of the table as shown below:

TS = RSFE/MAD

TS = -150/90 = -1.67

For month 5, the MAD(mean absolute deviation)is 90.0

For month 5, the TS (tracking signal) is -1.67

02

(b)Comment on the forecasting method

Looking solely at the value of the TS(tracking signal), the model seems acceptable since the tracking signal is only 1.67 of the mean.

However, the MAD (mean absolute deviation) has been increasing since the first period, and the downward trend over the last several periods in the graph is cause for concern that there may be some bias in the model.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Demand for stereo headphones and MP3 players for joggers has caused Nina Industries to grow almost 50 percent over the past year. The number of joggers continues to expand, so Nina expects demand for headsets to also expand, because, as yet, no safety laws have been passed to prevent joggers from wearing them. Demand for the players for last year was as follows:

Month

Demand (units)

January

4200

February

4300

March

4000

April

4400

May

5000

June

4700

July

5300

August

4900

September

5400

October

5700

November

6300

December

6000

  1. Using linear regression analysis, what would you estimate demand to be for each month next year? Using a spreadsheet, follow the general format in Exhibit 18.8. Compare your results to those obtained by using the forecast spreadsheet function.
  2. To be reasonably confident of meeting demand, Nina decides to use three standard errors of estimate for safety. How many additional units should be held to meet this level of confidence?

Plan production for a four-month period: February through May. For February and March, you should produce to exact demand forecast. For April and May, you should use overtime and inventory with a stable workforce; stable means that the number of workers needed for March will be held constant through May. However, government constraints put a maximum of 5,000 hours of overtime labor per month in April and May (zero overtime in February and March). If demand exceeds supply, then backorders occur. There are 100 workers on January 31. You are given the following demand forecast: February, 80,000; March, 64,000; April, 100,000; May, 40,000. Productivity is four units per worker hour, eight hours per day, and 20 days per month. Assume zero inventory on February 1. Costs are hiring, \(50 per new worker; layoff, \)70 per worker laid off; inventory holding, \(10 per unit-month; straight-time labor, \)10 per hour; over time, \(15 per hour; backorder, \)20 per unit. Find the total cost of this plan.

Your manager is trying to determine what forecasting method to use. Based upon the following historical data, calculate the following forecast and specify what procedure you would utilize.

Month

Actual demand

1

62

2

65

3

67

4

68

5

71

6

73

7

76

8

78

9

78

10

80

11

84

12

85

a. Calculate the simple three-month moving average forecast for periods 4鈥�12.

b. Calculate the weighted three-month moving average using weights of 0.50, 0.30, and 0.20 for periods 4鈥�12.

c. Calculate the single exponential smoothing forecast for periods 2鈥�12 using an initial (F1) of 61 and an伪of 0.30.

d. Calculate the exponential smoothing with trend component forecast for periods 2鈥� 12 using an initial trend forecast (T1) of 1.8, an initial exponential smoothing forecast (F1) of 60, and 伪of 0.30 and未of 0.30.

e. Calculate the mean absolute deviation (MAD) for the forecasts made by each technique in periods 4鈥�12. Which forecasting method do you prefer?

Question: The following tabulations are actual sales of units for six months and a starting forecast in January.


 ACTUAL
 FORECAST
January
 100
 80
February
 94

March
 106

April
 80

May
 68

June
 94

a. Calculate forecasts for the remaining five months using simple exponential smoothing with 伪= 0.2.

b. Calculate MAD for the forecasts.

SY Manufacturers (SYM) is producing T-shirts in three colors: red, blue, and white. The monthly demand for each color is 3,000 units. Each shirt requires 0.5 pounds of raw cotton that is imported from Luft-Geshfet-Textile (LGT) Company in Brazil. The purchasing price per pound is \(2.50 (paid only when the cotton arrives at SYM鈥檚 facilities) and the transportation cost by sea is \)0.20 per pound. The traveling time from LGT鈥檚 facility in Brazil to the SYM facility in the United States is two weeks. The cost of placing a cotton order, by SYM, is $100 and the annual interest rate that SYM is facing is 20 percent.

a. What is the optimal order quantity of cotton?

b. How frequently should the company order cotton?

c. Assuming that the first order is needed on April 1, when should SYM place the order?

d. How many orders will SYM place during the next year?

e. What is the resulting annual holding cost?

f. What does the resulting annual ordering cost?

g. If the annual interest cost is only 5 percent, how will it affect the annual number of orders, the optimal batch size, and the average inventory? (You are not expected to provide a numerical answer to this question. Just describe the direction of the change and explain your answer.)
See all solutions

Recommended explanations on Business Studies Textbooks

Business Operations

Read Explanation

Public Relations Business Studies

Read Explanation

Introduction to Business

Read Explanation

Intermediate Accounting

Read Explanation

Organizational Communication

Read Explanation

Organizational Behavior

Read Explanation
View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.