Chapter 12 MC

For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is Period Demand Forecast January 500 480 February 476 March 503 April a. 489. b. 486. c. 483. d. 480.

A

Given the demand and forecast values shown in the table below: Period Demand Forecast June 495 484 July 515 506 August 519 528 September 496 506 October 557 550 The MAD through the end of October would be a. 9.20 b. -9.20 c. 1.00 d. 7.00

A

Given the demand and forecast values shown in the table below: Period Demand Forecast June 495 484 July 515 506 August 519 528 September 496 506 October 557 550 The exponential smoothing forecast for November using α = 0.35 is a. 552.45. b. 553.50. c. 554.55. d. 557.50.

A

The _______ method uses demand in the first period to forecast demand in the next period. a) naïve b) moving average c) exponential smoothing. d) linear trend

A

The closer the smoothing constant, α, is to 1.0 a. the greater the reaction to the most recent demand. b. the greater the dampening, or smoothing, effect. c. the more accurate the forecast. d. the less accurate the forecast.

A

The weighted moving average forecast for the fifth period with weights of 0.15 for period 1, 0.20 for period 2, 0.25 for period 3, and 0.40 for period 4, using the demand data shown below is Period Demand 1 3500 2 3800 3 3500 4 4000 a. 3760 b. 3700 c. 3650 d. 3325

A

Which of the following can be used to monitor a forecast to see if it is biased high or low? a. a tracking signal b. the mean absolute deviation (MAD) c. the mean absolute percentage deviation (MAPD) d. a linear trend line model

A

A forecasting model has produced the following forecasts: Period Demand Forecast Error January 120 110 February 110 115 March 115 120 April 125 115 May 130 125 The mean absolute deviation (MAD) for the end of May is a. 7.0. b. 7.5. c. 10.0 d. 3.0

A. 7

73. If forecast errors are normally distributed then a. 1 MAD = 1σ b. 1 MAD ≈ 0.8 σ c. 0.8 MAD ≈ 1σ d. 1 MAD ≈ 1.96 σ

B

A company wants to product a weighted moving average forecast for April with the weights 0.40, 0.35, and 0.25 assigned to March, February, and January, respectively. If the company had demands of 5,000 in January, 4,750 in February, and 5,200 in March, then April's forecast is a. 4983.33. b. 4992.50. c. 4962.50. d. 5000.00.

B

A forecast where the current period's demand is used as the next period's forecast is known as a a. moving average forecast. b. naïve forecast. c. weighted moving average forecast. d. Delphi forecast.

B

A forecasting model has produced the following forecasts: Period Demand Forecast Error January 120 110 February 110 115 March 115 120 April 125 115 May 130 125 The mean absolute percentage deviation (MAPD) for the end of May is a. 0.0250. b. 0.0583. c. 0.5830. d. 0.6670.

B

A large positive cumulative error indicates that the forecast is probably a. higher than the actual demand. b. lower than the actual demand. c. unbiased. d. biased.

B

Given the demand and forecast values below, the naïve forecast for September is Period Demand Forecast April 100 97 May 105 103 June 97 98 July 102 105 August 99 102 September a. 100.6. b. 99.0. c. 102.0. d. cannot be determined.

B

Given the demand and forecast values shown in the table below: Period Demand Forecast June 495 484 July 515 506 August 519 528 September 496 506 October 557 550 The forecast error for September is a. 10.00. b. -10.00. c. 1.00. d. 39.00.

B

If the forecast for July was 3300 and the actual demand for July was 3250, then the exponential smoothing forecast for August using α = 0.20 is a. 3300. b. 3290. c. 3275. d. 3250.

B

The _________________ forecast method consists of an exponentially smoothed forecast with a trend adjustment factor added to it. a) Exponentially smoothed b) Adjusted exponentially smoothed c) Time series d) Moving average

B

The exponential smoothing model produces a naïve forecast when the smoothing constant, α, is equal to a. 0.00. b. 1.00. c. 0.50. d. 2.00

B

The sum of the weights in a weighted moving average forecast a. must equal the number of periods being averaged. b. must equal 1.00. c. must be less than 1.00. d. must be greater than 1.00.

B

Which of the following is not a type of predictable demand behavior? a. trend b. random variation c. cycle d. seasonal pattern

B

A forecasting model has produced the following forecasts: Period Demand Forecast Error January 120 110 February 110 115 March 115 120 April 125 115 May 130 125 At the end of May the average error would be a. 7. b. 5. c. 3. d. 1.

C

A long-range forecast would normally not be used to a. design the supply chain. b. implement strategic programs. c. determine production schedules. d. plan new products for changing markets

C

A qualitative procedure used to develop a consensus forecast is known as a. exponential smoothing. b. regression methods. c. the Delphi technique. d. naïve forecasting.

C

For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is Period Demand Forecast January 1250 1200 February 1225 March a. 1200. b. 1220. c. 1222. d. 1225.

C

Given the demand and forecast values shown in the table below: Period Demand Forecast June 495 484 July 515 506 August 519 528 September 496 506 October 557 550 The three-period moving average forecast for November is a. 516. b. 528. c. 524. d. 515.

C

The per period average of cumulative error is called a) cumulative forecast variation. b) absolute error. c) average error. d) noise.

C

The smoothing constant, α, in the exponential smoothing forecast a. must always be a value greater than 1.0. b. must always be a value less than 0.10. c. must be a value between 0.0 and 1.0. d. should be equal to the time frame for the forecast.

C

Given the following demand data for the past five months, the three period moving average forecast for June is Period Demand January 120 February 90 March 100 April 75 May 110 a. 103.33. b. 99.00. c. 95.00. d. 92.50

C. 95.00

The mean absolute percentage deviation (MAPD) measures the absolute error as a percentage of a. all errors. b. per period demand. c. total demand. d. the average error.

C. total demand

A ___________ is an up-and-down movement in demand that repeats itself over a lengthy time period of more than a year. a. trend b. seasonal pattern c. random variation d. cycle

D

A tracking signal is computed by a. multiplying the cumulative error by MAD b. multiplying the absolute error by MAD c. dividing MAD by the cumulative absolute error d. dividing the cumulative error by MAD

D

An exponential smoothing forecasting technique requires all of the following except a. the forecast for the current period. b. the actual demand for the current period. c. a smoothing constant. d. large amounts of historical demand data.

D

Correlation is a measure of the strength of the a. nonlinear relationship between two dependent variables. b. nonlinear relationship between a dependent and independent variable. c. linear relationship between two dependent variables. d. linear relationship between a dependent and independent variable.

D

Selecting the type of forecasting method to use depends on a. the time frame of the forecast. b. the behavior of demand and demand patterns. c. the causes of demand behavior. d. all of the above.

D

Which of the following statements concerning average error is true? a. a positive value indicates high bias, and a negative value indicates low bias b. a positive value indicates zero bias, and a negative value indicates low bias c. a negative value indicates zero bias, and a negative value indicates high bias d. a positive value indicates low bias, and a negative value indicates high bias

D

Given the following demand data for the past five months, the four period moving average forecast for June is Period Demand January 120 February 90 March 100 April 75 May 110 a. 96.25. b. 99.00. c. 110.00. d. 93.75.

D 93.75

A forecasting model has produced the following forecasts: Period Demand Forecast Error January 120 110 February 110 115 March 115 120 April 125 115 May 130 125 At the end of May the tracking signal would be a. 0.000. b. 0.667. c. 1.333. d. 2.143.

D. 2.143

Which of the following is a reason why a forecast can go "out of control?" a. a change in trend b. an irregular variation such as unseasonable weather c. a promotional campaign d. all of the above

D. all

Regression forecasting methods relate _________to other factors that cause demand behavior. a) Supply b) Demand c) Time d) Money e) Efficiency

b

Forecast methods based on judgment, opinion, past experiences, or best guesses are known as ___________ methods. a. quantitative b. qualitative c. time series d. regression

b. qualitative

A mathematical technique for forecasting that relates the dependent variable to an independent variable is a. correlation analysis. b. exponential smoothing. c. linear regression. d. weighted moving average.

c

A forecasting model has produced the following forecasts: Period Demand Forecast Error January 120 110 February 110 115 March 115 120 April 125 115 May 130 125 The forecast error for February is a. 10. b. -10. c. -15. d. -5

d