## Chapter 03: Understanding the Forecasting Process

**Forecasting techniques generally assume an existing causal system that will continue to exist in the future.**

**TRUE**

Forecasts depend on the rules of the game remaining reasonably constant.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-03 Evaluate at least three qualitative forecasting techniques and the advantages and disadvantages of each. Topic Area: Features Common to All Forecasts*

**For new products in a strong growth mode, a low alpha will minimize forecast errors when using exponential smoothing techniques**.

**FALSE**

If growth is strong, alpha should be large so that the model will catch up more quickly.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**Once accepted by managers, forecasts should be held firm regardless of new input since many plans have been made using the original forecast.**

__FALSE__

Flexibility to accommodate major changes is important to good forecasting.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Easy Learning Objective: 03-02 Outline the steps in the forecasting process. Topic Area: Steps in the Forecasting Process*

**Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items don’t include as many influencing factors.**

**FALSE**

Forecasting for an individual item is more difficult than forecasting for a number of items.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-02 Outline the steps in the forecasting process. Topic Area: Features Common to All Forecasts *

**Forecasts help managers plan both the system itself and provide valuable information for using the system**.

**TRUE**

Both planning and use are shaped by forecasts.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-01 List the elements of a good forecast. Topic Area: Introduction*

**Organizations that are capable of responding quickly to changing requirements can use a shorter forecast horizon and therefore benefit from more accurate forecasts.**

**TRUE**

If an organization can react quicker, its forecasts need not be so long term.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-02 Outline the steps in the forecasting process. Topic Area: Elements of a Good Forecast *

**When new products or services are introduced, focus forecasting models are an attractive option**.

**FALSE**

Because focus forecasting models depend on historical data, they’re not so attractive for newly introduced products or services.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The purpose of the forecast should be established first so that the level of detail, amount of resources, and accuracy level can be understood.**

__TRUE__

All of these considerations are shaped by what the forecast will be used for.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-02 Outline the steps in the forecasting process. Topic Area: Steps in the Forecasting Process *

**Forecasts based on time series (historical) data are referred to as associative forecasts**.

**FALSE**

Forecasts based on time series data are referred to as time-series forecasts.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Associative Forecasting Techniques *

**Time series techniques involve identification of explanatory variables that can be used to predict future demand**.

**FALSE**

Associate forecasts involve identifying explanatory variables.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Hard Learning Objective: 03-04 Compare and contrast qualitative and quantitative approaches to forecasting. Topic Area: Forecasts Based on Time-Series Data *

**A consumer survey is an easy and sure way to obtain accurate input from future customers since most people enjoy participating in surveys**.

**FALSE**

Most people do not enjoy participating in surveys.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-03 Evaluate at least three qualitative forecasting techniques and the advantages and disadvantages of each. Topic Area: Qualitative Forecasts *

**The Delphi approach involves the use of a series of questionnaires to achieve a consensus forecast**.

**TRUE**

A consensus among divergent perspectives is developed using questionnaires.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-03 Evaluate at least three qualitative forecasting techniques and the advantages and disadvantages of each. Topic Area: Qualitative Forecasts *

**Exponential smoothing adds a percentage (called alpha) of last period’s forecast to estimate next period’s demand**.

**FALSE**

Exponential smoothing adds a percentage to the last period’s forecast error.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The shorter the forecast period, the more accurately the forecasts tend to track what actually happens**.

**TRUE**

Long-term forecasting is much more difficult to do accurately.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Easy Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast *

**Forecasting techniques that are based on time series data assume that future values of the series will duplicate past values**.

**FALSE**

Time-series forecast assume that future patterns in the series will mimic past patterns in the series.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data*

**Trend adjusted exponential smoothing uses double smoothing to add twice the forecast error to last period’s actual demand**.

**FALSE**

Trend adjusted smoothing smoothes both random and trend-related variation.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**Forecasts based on an average tend to exhibit less variability than the original data**.

**TRUE**

Averaging is a way of smoothing out random variability.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The naive approach to forecasting requires a linear trend line**.

**FALSE**

The naïve approach is useful in a wider variety of settings.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The naive forecast is limited in its application to series that reflect no trend or seasonality**.

**FALSE**

When a trend or seasonality is present, the naïve forecast is more limited in its application.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The naive forecast can serve as a quick and easy standard of comparison against which to judge the cost and accuracy of other techniques**.

**TRUE**

Often the naïve forecast performs reasonably well when compared to more complex techniques.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data*

**A moving average forecast tends to be more responsive to changes in the data series when more data points are included in the average**.

**FALSE**

More data points reduce a moving average forecast’s responsiveness.

Bloom’s: Understand

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**In order to update a moving average forecast, the values of each data point in the average must be known**.

**TRUE**

The moving average cannot be updated until the most recent value is known.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Hard Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**Forecasts of future demand are used by operations people to plan capacity**.

**TRUE**

Capacity decisions are made for the future and therefore depend on forecasts.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-01 List the elements of a good forecast. Topic Area: Introduction *

**An advantage of a weighted moving average is that recent actual results can be given more importance than what occurred a while ago**.

**TRUE**

Weighted moving averages can be adjusted to make more recent data more important in setting the forecast.

Bloom’s: Understand

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**Exponential smoothing is a form of weighted averaging**.

**TRUE**

The most recent period is given the most weight, but prior periods also factor in.

Bloom’s: Understand

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a smoothing constant value of .3**.

**FALSE**

Smaller smoothing constants result in less reactive forecast models.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Hard Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**The T in the model TAF = S+T represents the time dimension (which is usually expressed in weeks or months)**.

**FALSE**

The T represents the trend dimension.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**Trend adjusted exponential smoothing requires selection of two smoothing constants.**

**TRUE**

One is for the trend and one is for the random error.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**An advantage of “trend adjusted exponential smoothing” over the “linear trend equation” is its ability to adjust over time to changes in the trend**.

**TRUE**

A linear trend equation assumes a constant trend; trend adjusted smoothing allows for changes in the underlying trend.

Bloom’s: Remember

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**A seasonal relative (or seasonal indexes) is expressed as a percentage of average or trend.**

**TRUE**

Seasonal relatives are used when the seasonal effect is multiplicative rather than additive.

Bloom’s: Remember

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**In order to compute seasonal relatives, the trend of past data must be computed or known which means that for brand new products this approach can’t be used**.

**TRUE**

Computing seasonal relatives depends on past data being available.

Bloom’s: Understand

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**Removing the seasonal component from a data series (de-seasonalizing) can be accomplished by dividing each data point by its appropriate seasonal relativ**e.

**TRUE**

Deseasonalized data points have been adjusted for seasonal influences.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Hard Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Forecasts Based on Time-Series Data *

**If a pattern appears when a dependent variable is plotted against time, one should use time series analysis instead of regression analysis**.

**TRUE**

Patterns reflect influences such as trends or seasonality that go against regression analysis assumptions.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Hard Learning Objective: 03-08 Assess the major factors and trade-offs to consider when choosing a forecasting technique. Topic Area: Associative Forecasting Techniques*

**Curvilinear and multiple regression procedures permit us to extend associative models to relationships that are non-linear or involve more than one predictor variable.**

**TRUE**

Regression analysis can be used in a variety of settings.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-08 Assess the major factors and trade-offs to consider when choosing a forecasting technique. Topic Area: Associative Forecasting Techniques *

.**The sample standard deviation of forecast error is equal to the square root of MSE**

**TRUE**

The MSE is equal to the sample variance of the forecast error.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Forecast Accuracy *

**Correlation measures the strength and direction of a relationship between variables.**

**TRUE**

The association between two variations is summarized in the correlation coefficient.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Associative Forecasting Techniques *

.**MAD is equal to the square root of MSE which is why we calculate the easier MSE and then calculate the more difficult MAD**

**FALSE**

MAD is the mean absolute deviation.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-06 Explain three measures of forecast accuracy. Topic Area: Forecast Accuracy *

**In exponential smoothing, an alpha of 1.0 will generate the same forecast that a naïve forecast would yield**.

**TRUE**

With alpha equal to 1 we are using a naïve forecasting method.

Bloom’s: Understand

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

**A forecast method is generally deemed to perform adequately when the errors exhibit an identifiable pattern**.

**FALSE**

Forecast methods are generally considered to be performing adequately when the errors appear to be randomly distributed.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Forecast Accuracy*

**A control chart involves setting action limits for cumulative forecast error.**

**FALSE**

Control charts set action limits for the tracking signal.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast *

**A tracking signal focuses on the ratio of cumulative forecast error to the corresponding value of MAD**.

**TRUE**

Large absolute values of the tracking signal suggest a fundamental change in the forecast model’s performance.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast *

- T
**he use of a control chart assumes that errors are normally distributed about a mean of zero.**

**TRUE**

Over time, a forecast model’s tracking signal should fluctuate randomly about a mean of zero.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Hard Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast*

**Bias exists when forecasts tend to be greater or less than the actual values of time series.**

**TRUE**

A tendency in one direction is defined as bias.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Easy Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast *

**Bias is measured by the cumulative sum of forecast errors.**

__TRUE__

Bias would result in the cumulative sum of forecast errors being large in absolute value.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Monitoring the Forecast*

*Chapter 03: Understanding the Forecasting Process *

**Seasonal relatives can be used to de-seasonalize data or incorporate seasonality in a forecast**.

**TRUE**

Seasonal relatives are used to de-seasonalize data to forecast future values of the underlying trend, and they are also used to re-seasonalize de-seasonalized forecasts.

Bloom’s: Remember

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

*Chapter 03: Understanding the Forecasting Process *

**The best forecast is not necessarily the most accurate.**

**TRUE**

More accuracy often comes at too high a cost to be worthwhile.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-08 Assess the major factors and trade-offs to consider when choosing a forecasting technique. Topic Area: Elements of a Good Forecast*

*Chapter 03: Understanding the Forecasting Process *

**A proactive approach to forecasting views forecasts as probable descriptions of future demand, and requires action to be taken to meet that demand**.

**FALSE**

Proactive approaches involve taking action to influence demand.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Hard Learning Objective: 03-02 Outline the steps in the forecasting process. Topic Area: Using Forecast Information*

*Chapter 03: Understanding the Forecasting Process *

**Simple linear regression applies to linear relationships with no more than three independent variables**.

**FALSE**

Simple linear regression involves only one independent variable.

*AACSB: Reflective Thinking Bloom’s: Remember Difficulty: Medium Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems. Topic Area: Associative Forecasting Techniques*

*Chapter 03: Understanding the Forecasting Process*

**An important goal of forecasting is to minimize the average forecast error.**

**FALSE**

Regardless of the model chosen, so long as there is no fundamental bias average forecast error will be zero.

*AACSB: Reflective Thinking Bloom’s: Understand Difficulty: Medium Learning Objective: 03-07 Compare two ways of evaluating and controlling forecasts. Topic Area: Forecast Accuracy*

*Chapter 03: Understanding the Forecasting Process *

**Forecasting techniques such as moving averages, exponential smoothing, and the naive approach all represent smoothed (averaged) values of time series data**.

**FALSE**

The naïve approach involves no smoothing.

Bloom’s: Remember

Difficulty: Medium

Learning Objective: 03-05 Describe averaging techniques; trend and seasonal techniques; and regression analysis; and solve typical problems.

Topic Area: Forecasts Based on Time-Series Data

*Chapter 03: Understanding the Forecasting Process*