Exam 15: Demand Management and Forecasting

Cyclical influences on demand may come from occurrences such as political elections, war or economic conditions.

A good forecaster is one who develops special skills and experience at one forecasting technique and is capable of applying it to widely diverse situations.

Which of the following forecasting methodologies is considered a causal forecasting technique?

In exponential smoothing, it is desirable to use a higher smoothing constant when forecasting demand for a product experiencing high growth.

Continual review and updating in light of new data is a forecasting technique called second-guessing.

Simple exponential smoothing lags changes in demand.

A company wants to forecast demand using the weighted moving average.If the company uses three prior yearly sales values , and we want to weight year 2010 at 30%, year 2011 at 30% and year 2012 at 40%, which of the following is the weighted moving average forecast for year 2013?

Which of the following forecasting methods is very dependent on selection of the right individuals who will judgmentally be used to actually generate the forecast?

In time series data depicting demand which of the following is not considered a component of demand variation?

Decomposition of a time series means identifying and separating the time series data into its components.

Exponential smoothing forecasts always lag behind the actual occurrence but can be corrected somewhat with a trend adjustment.

Market research is a quantitative method of forecasting.

In most cases, demand for products or services can be broken down into several components.Which of the following is not considered a component of demand?

A tracking signal (TS) can be calculated using the arithmetic sum of forecast deviations divided by the MAD.

Given a prior forecast demand value of 1,100, a related actual demand value of 1,000, and a smoothing constant alpha of 0.3, what is the exponential smoothing forecast value?

It is difficult to identify the trend in time series data.

In causal relationship forecasting leading indicators are used to forecast occurrences.

A central premise of exponential smoothing is that more recent data is less indicative of the future than data from the distant past.

A time series is defined in the text as chronologically ordered data that may contain one or more components of demand variation: trend, seasonal, cyclical, autocorrelation, and random.

In the weighted moving average forecasting model the weights must add up to one times the number of data points.