OM300 Chapter 4

Operations managers most commonly deal with which type of​ forecast? A. Demand B. Environmental C. Technological D. Economic

A. Demand

Which one of the following statements is NOT true about the forecasting in the service​ sector? A. Detailed forecasts of demand are not needed. B. Demand patterns are often different from those in​ non-service sectors. C. Hourly demand forecasts may be necessary. D. Forecasting in the service sector presents some unusual challenges.

A. Detailed forecasts of demand are not needed.

A forecast that projects a​ company's sales is A. a demand forecast. B. an environmental forecast. C. an economic forecast. D. a technological forecast.

A. a demand forecast

Which of the following is a quantitative forecasting​ method? A. exponential smoothing B. market survey C. jury of executive opinion D. sales force composite

A. exponential smoothing

What is a data pattern that repeats itself after a period of​ days, weeks,​ months, or​ quarters? A. seasonality B. cycle C. trend D. random variation

A. seasonality

Which of the following is the FIRST step in a forecasting​ system? A.Determine the time horizon of the forecast. B. Determine the use of the forecast. C. Select the forecast​ model(s). D. Select the items to be forecasted.

B. Determine the use of the forecast.

Which of the following is NOT a​ time-series model? A. exponential smoothing B. multiple regression C. moving averages D. naive approach

B. multiple regression

The forecasting time horizon that would typically be easiest to predict for would be the A. long range. B. intermediate range. C. short range. D. medium range.

C. Short Range

CPFR is A. complete, partner,​ forecasting, and replenishment. B. complete, planning,​ forecasting, and replenishment. C. collaborative, planning,​ forecasting, and replenishment. D. collaborative, partner,​ forecasting, and replenishment.

C. collaborative, planning,​ forecasting, and replenishment.

Café Michigan's​ manager, Gary​ Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical​ observations, Gary has gathered the following​ data, which show the numbers of these coffees sold over six different price​ values: Price, Number Sold ​$2.50, 770 ​$3.50, 505 ​$1.90, 975 ​$4.20, 240 ​$3.20, 320 ​$4.05, 490 Using simple linear regression and given that the price per cup is ​$1.75​, the forecasted demand for mocha latte coffees will be (?) cups ​(enter your response rounded to one decimal​ place).

SEE EXCEL SHEET

The following table shows the actual demand observed over the last 4​ years: Year: 1, 2, 3, 4 Demand: 8, 9, 6, 9 Using exponential smoothing with α=0.40 and a forecast for year 1 of 7.0​, provide the forecast from periods 2 through 5 ​(round your responses to one decimal​ place). a) Year: 1, 2, 3, 4, 5 Forecast​ (ES): 7.0, (?), (?), (?), (?) b) Provide the forecast from periods 2 through 5 using the naive approach ​(enter your responses as whole​ numbers). Year: 2, 3, 4, 5 Forecast​ (NA): (?), (?), (?), (?)

a) 0.4 x 8 + 0.6 x 7= 7.4 0.4 x 9 + 0.6 x 7.4= 8 0.4 x 6 + 0.6 x 8= 7.2 0.4 x 9 + 0.6 x 7.2= 7.9 b) 8, 9, 6, 9

Lenovo uses the​ ZX-81 chip in some of its laptop computers. The prices for the chip during the last 4 months were as​ follows: Month, Price Per Chip January, $1.80 February, $1.68 March, $1.64 April, $1.93 This exercise contains only parts​ a, b, and c. ​a) Using a​ 2-month moving​ average, calculate the forecast for March and April ​(round your responses to two decimal ​places). Month: Mar, Apr Forecast: (?), (?) b) Using a​ 3-month moving​ average, calculate the forecast for April. The forecast for April is $​(?) c) Calculate the mean absolute deviation based on a​ 2-month average. The mean absolute deviation based on​ 2-month moving average of March through April is ​$(?) ​(round your response to three decimal ​places).

a) 1.74, 1.66 (1.8+1.68)/2= 1.74 (1.64+1.93)/2= 1.66 b) 1.71 (1.8+1.68+1.64)/3= c) .185 d) .223 e) .185 .223>.185

The monthly sales for Yazici​ Batteries, Inc., were as​ follows: Month: Sept, Oct, Nov, Dec Sales: 20, 21, 23, 24 This exercise contains only parts b and c. ​b) Forecast January sales using each of the following methods. ​i) Compute the January sales forecast using naive method. The January sales forecast using the naive method= (?) sales. ​(Enter your response as a whole​ number.)

a) 24 DEC=JAN b)= 22.67 21+23+24=68/3= c)

The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as​ follows: Year: 1, 2, 3, 4, 5 Mileage: 3,050, 4,000, 3,500, 3,750, 3,750 ​a) Using a​ 2-year moving​ average, the forecast for year 6​ = (?) miles ​(round your response to the nearest whole​ number). ​b) If a​ 2-year moving average is used to make the​ forecast, the MAD based on this​ = (?) miles ​(round your response to one decimal​ place). ​ (Hint: You will have only 3 years of matched​ data.) c) The forecast for year 6 using a weighted​ 2-year moving average with weights of 0.40 and 0.60 (the weight of 0.60 is for the most recent​ period) = (?) miles ​(round your response to the nearest whole​ number). ​d) Using exponential smoothing with α= 0.20 and the forecast for year 1 being 3,050​, the forecast for year 6​ = (?) miles ​(round your response to the nearest whole​ number).

a) 3750 (3750+3750)/2 b) ((3050+4000)/2)=3525 ((4000+3500)/2)=3750 ((3500+3750)/2)=3625 3525-3500=25 3750-3750=0 3750-3625=125 ((125+25+0)/3)=50 c) 3750, 90 (0.4×3050+0.6×4000)/1=3620 (0.4×4000+0.6×3500)/1=3700 (0.4×3500+0.6×3750)/1=3650 ∣3500-3620∣=120 ∣3750-3700∣=50 ∣3750-3650∣=100 270/3 d) 3457 3050+0.2*(3050-3050)=3050 3050+0.2*(3050-3050)=3050 3050+0.2*(4000-3050)=3240 3240+0.2*(3500-3240)=3292 3292+0.2*(3750-3292)=3383.6 3383.6+0.2*(3750-3383.6)=3456.88

The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as​ follows: Year: 1, 2, 3, 4, 5 Mileage: 3,050, 4,050, 3,450, 3,750, 3,750 ​a) Using a​ 2-year moving​ average, the forecast for year 6​ = (?) miles ​(round your response to the nearest whole​ number). b) Compute the January sales forecast using a​ 3-month moving average. The January sales forecast using a​ 3-month moving average approach= (?) sales. c) Compute the January sales forecast using a​ 3-month weighted average with weights of 0.10​, 0.30​, and 0.60 with the heaviest weights applied to the most recent months. The January sales forecast using a​ 3-month weighted average=(?) sales

a) 3750 (3750+3750)/2 b) ((3050+4050)/2)=3550 ((4050+3450)/2)=3750 ((3450+3750)/2)=3600 3550-3450=100 3750-3750=0 3750-3600=150 ((100+150+0)/3=83.3 *****c) 3750, *90 (0.4×3050+0.6×4050)/1=3650 (0.4×4050+0.6×3450)/1=3960 (0.4×3450+0.6×3750)/1=3630 ∣3450-3650∣=200 ∣3960-3750∣=210 ∣3750-3630∣= 120 270/3 d) 3569 3050=3050+0.3*(3050-3050) 3050=3050+0.3*(3050-3050) 3350=3050+0.3*(4050-3050) 3380=3350+0.3*(3450-3350) 3491=3380+0.3*(3750-3380) 3568.7=3491+0.3*(3750-3491)

Daily high temperatures in St. Louis for the last week were as​ follows: 93​, 92​, 93​, 94​, 95​, 86​, 95 ​(yesterday). ​a) The high temperature for today using a​ 3-day moving average ​= (?) degrees ​(round your response to one decimal​ place). ​b) The high temperature for today using a​ 2-day moving average ​= (?) degrees ​(round your response to one decimal​ place). ​c) The mean absolute deviation based on a​ 2-day moving average​ = (?) degrees ​(round your response to one decimal​ place).

a) 92 95+86+95=286/3= b) 90.5 86+95=181/2= c)

The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6​ weeks: Week Of, Pints Used August 31, 360 September 7, 372 September 14, 408 September 21, 383 September 28, 371 October 5, 371 ​a) The forecasted demand for the week of October 12 using a​ 3-week moving average​= (?) pints ​(round your response to two decimal ​b) Using a​ 3-week weighted moving​ average, with weights of 0.15​, 0.35​, and 0.50​, using 0.50 for the most recent​ week, the forecasted demand for the week of October 12​ = (?) pints ​(round your response to two decimal places and remember to use the weights in appropriate order — the largest weight applies to most recent period and smallest weight applies to oldest period.​) ​c) If the forecasted demand for the week of August 31 is 360 and α ​= 0.20​, using exponential​ smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 ​(round your responses to two decimal​ places). Week Of, Pints Used, Forecast for this Date August 31, 360, 360 September 7, 372, 360.00 September 14, 408, 362.40 September 21, 383, (?)

​a) 375 (383+371+371)/3 b) 372.8 (383*.15+371*.35+371*.50)