Question 1

Minimizing the negative impacts of the bullwhip effect on supply chains is one of the goals of an effective CPFR system.

Accepted Answer

CPFR (Collaborative Planning, Forecasting, and Replenishment) is a strategy that aims to reduce the bullwhip effect by facilitating collaboration and data sharing among all members of a supply chain network. By working together, trading partners can gain visibility into each other's inventory levels, demand forecasts, and production schedules, which enables them to make more informed decisions and minimize the risk of over- or under-production. Therefore, minimizing the negative impacts of the bullwhip effect is indeed one of the goals of an effective CPFR system.

Question 2

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.

Accepted Answer

The true value of CPFR comes from both the exchange of forecasting information and the use of sophisticated forecasting algorithms, which work together to provide companies with highly accurate forecasts.

Question 3

The Naïve forecast, Mean Profit Leverage, and Mean Square Error are examples of forecasting accuracy measures.

Accepted Answer

The Naïve forecast is a forecasting method, while Mean Profit Leverage and Mean Square Error are measures of forecasting accuracy.

Question 4

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.

Accepted Answer

Tighter control limits for the tracking signal mean that smaller deviations from the average demand will trigger an exception. This increases the likelihood of finding exceptions that require no action, but it also means that any significant changes in demand will be detected earlier, allowing for prompt action to be taken.

Question 5

Random variations represent either increasing or decreasing movements over many years due to factors such as population growth, population shifts, cultural changes and income shifts.

Accepted Answer

Random variations are unpredictable fluctuations that do not follow a consistent pattern or trend, unlike systematic changes caused by factors like population growth or cultural shifts.

Question 6

Individual biases could negatively impact the effectiveness of the Sales Force Composite forecasting approach, due to the proximity of the sales personnel to the consumers.

Accepted Answer

Due to their proximity to customers, sales personnel may have personal biases and may overestimate or underestimate sales figures, which can negatively impact the accuracy of the Sales Force Composite forecasting approach.

Question 7

One of the benefits of CPFR include integration of planning, forecasting, and logistics activities.

Accepted Answer

CPFR (Collaborative Planning, Forecasting, and Replenishment) is a supply chain management strategy that enables collaboration among trading partners in planning and executing demand forecasting, inventory replenishment, and logistics activities. Its major benefit is the integration of these activities which leads to increased efficiency, reduced inventory costs, and improved customer service.

Question 8

Cyclical variations are longer than a year and are influenced by macroeconomic and political factors.

Accepted Answer

Cyclical variations refer to fluctuations in economic activity that occur over a period of time longer than a year, typically driven by macroeconomic factors such as changes in interest rates, government spending, and international trade. These changes can also be influenced by political factors, such as changes in regulations, policies, and political stability.

Question 9

Regression analysis is commonly used in the cause-and-effect forecasting model.

Accepted Answer

Regression analysis is a statistical technique that helps in understanding the relationship between variables. It can be used in the cause-and-effect forecasting model to identify the factors that impact the outcome and predict the future values of the outcome variable based on the input variables. Therefore, the statement is true.

Question 10

Toymaker Spin Master, did not properly forecast demands for their new product, Hatchimals, in 2016.This caused stockouts for their distributors.

Accepted Answer

Spin Master reported shortages and stockouts of Hatchimals during the 2016 holiday season due to higher than anticipated demand.

Question 11

It is possible to expect 100 percent forecast accuracy most of the time.

Accepted Answer

It is impossible to achieve 100 percent forecast accuracy most of the time. Forecasting involves estimating future events and there are always factors that can impact the accuracy of the forecast. However, it is possible to improve forecast accuracy through using more advanced methods and continually refining the forecasting process.

Question 12

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

Accepted Answer

The ultimate aim of a good forecasting technique is to predict the actual demand with minimal error, which is achieved by minimizing the deviation or the difference between actual demand and the forecast.

Question 13

Trend variations are wavelike movements that are shorter than a year.

Accepted Answer

Trend variations refer to long-term movements in data, typically lasting longer than a year, while wavelike movements shorter than a year are usually considered seasonal variations.

Question 14

Without supply chain trading partners collaborating and exchanging information, the supply chain will always be suboptimal and contain excess inventories, resulting in less-than-maximum supply chain profits.

Accepted Answer

Collaboration and exchange of information between supply chain trading partners can help to optimize inventory levels, reduce costs, and improve overall efficiency, resulting in higher profits for the supply chain as a whole. Therefore, the statement is true.

Question 15

Given the following information, the forecast for period two using exponential smoothing an  = 0.3 is 60.5.

Accepted Answer

The question states that the forecast for period two using exponential smoothing with alpha (the smoothing constant) equals 0.3 is 60.5.

Question 16

Forecast error is the actual quantity minus the forecast.

Accepted Answer

Forecast error is calculated by subtracting the actual quantity from the forecasted quantity, so it is the actual quantity minus the forecast. Therefore, the statement "Forecast error is the actual quantity minus the forecast" is true.

Question 17

The calculated forecast for May is 46, using the actual demand shown in the table below, and a 3-month weighted moving average with weights 0.1, 0.4, 0.5 (the heaviest weight applied to the most recent period).

Accepted Answer

The answer of The calculated forecast for May is 46,...

Question 18

The Delphi forecasting approach is applicable for high-risk technology forecasting; large, expensive projects; or major new product introductions

Accepted Answer

The Delphi forecasting approach is particularly useful for complex and high-risk projects or new product introductions where there is significant uncertainty or where the consequences of incorrect forecasting are high. It involves gathering input from a panel of experts, who provide anonymous feedback through a series of rounds until a consensus is reached. This approach can be particularly useful for large, expensive projects where accurate forecasting is essential.

Question 19

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.

Accepted Answer

The statement is incorrect. In order to emphasize recent demand trends, a conventional weighted moving average would be more appropriate as it gives more weight to recent periods. Simple moving averages give equal weight to all periods.

Question 20

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

Accepted Answer

The statement is reversed. Quantitative forecasting methods use mathematical models and relevant historical data, while qualitative forecasting methods are based on opinions and intuition.

Quiz 5: Demand Forecasting