OMIS Chapter 5

If a tracking signal is positive, which one of the following is true? a. Actual value is higher than forecast b. Actual value is less than forecast c. Actual value is equal to forecast d. Unable to draw any conclusion

A

Inaccurate forecasts can result in negative outcomes like: a. Stockouts and poor responsiveness to market dynamics b. High inventory costs of inventory and increased profits c. Material shortages and decreased costs of obsolescence d. Low inventory costs of inventory and stockouts.

A

One common Cause-and-Effect Model used is: a. Regression analysis b. Linear Trend Forecast c. Moving Average Forecast d. Mean Absolute Deviation

A

Period = Sales Volume 1 = 10000 2 = 12400 3 = 14250 4 = 15750 5 = 20500 6 = 18500 7 = 15750 8 = 20500 9 = 21500 10 = 22550 Using Data Set E1, what would be the forecast for period 6 using a five period weighted moving average? The weights for each period are 0.05, 0.10, 0.20, 0.30, and 0.35 from the oldest period to the most recent period, respectively. (Choose the closest answer.) a. 16500 b. 17825 c. 14575 d. 16275

A

The impact of poor communication and inaccurate forecasts resonates along the supply chain and results in the: a. Bullwhip effect b. Delphi method c. CPFR effect d. Mean deviation

A

Using the actual demand shown in the table below, what is the forecast for May (accurate to 1 decimal) using a 4-month weighted moving average and the weights 0.1, 0.2, 0.3, 0.4 (with the heaviest weight applied to the most recent period)? Nov. 39 Dec. 36 Jan. 40 Feb. 38 Mar. 48 Apr. 46 a. 44.4 b. 43.0 c. 42.5 d. 41.6

A

In the Delphi forecasting method, a group of internal and external experts are surveyed during several rounds in terms of future events and long-term forecasts of demand but the group members do not physically meet. T/F

True

One of the goals of an effective CPFR system is to minimize the negative impacts of the bullwhip effect on supply chains. T/F

True

Some of the benefits of CPFR include strengthening partner relationships, providing an analysis of sales and order forecasts both upstream and downstream, and allowing collaboration on future requirements and planning. T/F

True

Some of the important steps involved in implementation of a CPRF process model include developing a collaborative arrangement, creating a sales forecast, creating an order forecast, and generating those orders. T/F

True

Some of the leading suppliers of CPFR solutions mentioned in the textbook are JDA Software Group, i2 Technologies, and Oracle. T/F

True

The difference between a simple regression forecast and a multiple regression forecast is that simple regression is used when there is only one explanatory (or independent) variable, while multiple regression is used when there are numerous explanatory variables. T/F

True

Which of the following indices provided by the Institute for Supply Management (ISM) is considered the most important by economists because it is a composite of five weighted, seasonally adjusted indices? a. Purchasing Managers Index b. Export Orders Index c. Production and Inventory Index d. New Orders Index

A

The goal of a good forecasting technique is to minimize the deviation between actual demand and the forecast. T/F

True

According to the textbook, which of the following is NOT a way to closely match supply and demand? a. Holding high amounts of inventory b. Maintaining a rigid pricing system c. Utilizing overtime d. Hiring temporary workers

B

Month-Actual-Forecast 1-10-11 2-8-10 3-9-8 4-6-6 5-7-8 Based on the information in Data Set E2, what is the mean squared error (accurate to 2 decimals)? a. 7.00 b. 1.40 c. 1.00 d. 0.80

B

The following are all common qualitative forecasting models EXCEPT: a. Jury of Executive Opinion b. Trend Variation c. Delphi Method d. Sales Force Composite

B

What does the acronym CPFR represent? a. Coordinated planning and forecasting relationships b. Collaborative planning, forecasting, and replenishment c. Centralized purchasing and forecasting relationships d. Collaborative purchasing, forecasting, and receivables

B

Your company is conducting forecasting that revolves around the current recession and expansion of the U.S. economy. This type of forecasting can be referred to as what component of a time series? a. Trend Variations b. Cyclical Variations c. Seasonal Variations d. Random Variations

B

According to textbook, the top three challenges for CPFR implementation include all of the following except: a. Making organizational and procedural changes b. Trust between supply chain partners c. Cost d. Supplier lead times

D

According to textbook, which of the following companies is a leading forecasting software provider? a. Just Enough b. SAS c. Business Forecast Systems, Inc. d. All of these

D

According to textbook, which of the following companies is recognized as a leader in CPFR software solutions? a. Autonomy b. Cloud software c. JDA software d. Transperion

D

Given the following information, calculate the forecast (accurate to 2 decimals) for period three using exponential smoothing and α = 0.3. Period-Demand-Forecast 1-64-59 2-70 a. 36.90 b. 57.50 c. 61.50 d. 63.35

D

Period = Sales Volume 1 = 10000 2 = 12400 3 = 14250 4 = 15750 5 = 20500 6 = 18500 7 = 15750 8 = 20500 9 = 21500 10 = 22550 Using Data Set E1, what would be the forecast for period 7 using a four period moving average: (Choose the closest answer.) a. 17625 b. 15225 c. 15300 d. 17250

D

Which of the following statements is FALSE: a. Time Series forecasting is based on the assumption that the future is an extension of the past b. Cause-and-Effect forecasting assumes that one or more factors are related to demand and, therefore, can be used to predict future demand c. All quantitative methods become less accurate as the forecast's time horizon increases d. It is generally not recommended to use a combination of both quantitative and qualitative methods

D

Which one of the following is not a type of qualitative forecasting? a. Sales force composite b. Consumer survey c. Jury of executive opinion d. Naïve method

D

If you felt that recent demand trends were more significant, and thus should be emphasized more in formulating a forecast, then in forecasting demand for the upcoming demand period, you would probably favor using a simple moving average over the conventional weighted moving average. T/F

False

If you were calculating a forecast using an exponential smoothing model, a calculation using α = 0.2 would be putting a greater emphasis on recent data, while a calculation using α = 0.8 would be putting a greater emphasis on past data. Thus a lower α is more responsive to changes in demand in the most recent periods. T/F

False

Quantitative forecasting methods are based on opinions and intuition, whereas qualitative forecasting methods use mathematical models and relevant historical data to generate forecasts. T/F

False

The Institute of Supply Management (ISM) surveys more than 300 purchasing and supply executives in the United States using a questionnaire seeking information on "changes in production, new orders, new export orders, imports, employment, inventories, prices, lead-times, and the timeliness of supplier deliveries in their companies comparing the current month to the previous month." The ISM Report on Business focuses only on the manufacturing sector. T/F

False

The goal of a good forecasting technique is to achieve 98.7% accuracy between the forecast and actual demand. T/F

False

The modern day business environment must deal with a more homogenous consumer base, which has caused the evolution of a more "push" oriented environment where suppliers must focus on manufacturing high volumes of standardized goods. T/F

False

According to the text, the ultimate goal of any forecasting endeavor is to have an accurate and unbiased forecast. T/F

True

As tighter control limits are instituted for the tracking signal, there is a greater probability of finding exceptions that require no action, but it also means catching changes in demand earlier. T/F

True

Cause-and-Effect Models can have multiple independent variables. T/F

True

Examples of forecasting accuracy measures are Mean Absolute Deviation, Mean Absolute Percentage Error, and Mean Square Error. T/F

True

Month-Actual-Forecast 1-10-11 2-8-10 3-9-8 4-6-6 5-7-8 A forecasting method has produced the following data over the past 5 months shown in Data Set E2. What is the mean absolute deviation (accurate to 2 decimals)? a. −0.60 b. −1.20 c. 1.00 d. 1.25

C

Period = Sales Volume 1 = 10000 2 = 12400 3 = 14250 4 = 15750 5 = 20500 6 = 18500 7 = 15750 8 = 20500 9 = 21500 10 = 22550 Using Data Set E1, what would be the forecast for period 6 using the exponential smoothing method? Assume the forecast for period 5 is 14000. Use a smoothing constant of α = 0.4 (Choose the closest answer.) a. 14575 b. 26100 c. 16600 d. 19700

C

Some measures of forecasting accuracy include mean absolute deviation, mean absolute percentage error, and mean squared error. The formula for each is dependent on the forecast error, which is calculated by using the equation: a. Actual demand for period t divided by the forecasted demand for period t b. Actual demand for period t plus the forecasted demand for period t c. Actual demand for period t minus the forecasted demand for period t d. The average of Actual demand for period t and forecasted demand for period t

C

The equation for a simple linear regression that saw sales averaging $225,000 over the last ten periods, and advertising budgets averaging $3,000 over the last 10 periods is: Y = 3250 + 120x This indicates that a $1 increase in advertising will increase sales by: a. $3370 b. $250 c. $120 d. $1875

C

The exponential smoothing forecast has the same value as the naïve forecast when α in the exponential smoothing model is equal to: a. 0 b. 0.5 c. 1 d. Insufficient information provided to determine answer

C

The following time-series approach to forecasting uses historical data to generate a forecast and works well when demand is fairly stable over time: a. Naïve Forecast b. Weighted Moving Average c. Simple Moving Average d. Exponential Smoothing

C

Associative forecasting methods are based on opinions and intuition. T/F

False

The objective of CPFR is to optimize the supply chain by improving demand forecast accuracy, delivering the right product at the right time to the right location, reducing inventories across the supply chain, avoiding stock-outs, and improving customer service. As a result of the many benefits attributed to CPFR, this business practice has been widely adopted. T/F

False

The true value of CPFR comes from the sophisticated forecasting algorithms that provide companies with highly accurate forecasts, not from the exchange of forecasting information. T/F

False