OM Chapter 3 – Flashcards

Forecasts based on judgment and opinion don't include A. executive opinion B. salesperson opinion C. second opinions D. customer surveys E. Delphi methods

In business, forecasts are the basis for: A. capacity planning B. budgeting C. sales planning D. production planning E. all of the above

Which of the following features would not generally be considered common to all forecasts? A. Assumption of a stable underlying causal system. B. Actual results will differ somewhat from predicted values. C. Historical data is available on which to base the forecast. D. Forecasts for groups of items tend to be more accurate than forecasts for individual items. E. Accuracy decreases as the time horizon increases.

Which of the following is not a step in the forecasting process? A. determine the purpose and level of detail required B. eliminate all assumptions C. establish a time horizon D. select a forecasting model E. monitor the forecast

Minimizing the sum of the squared deviations around the line is called: A. mean squared error technique B. mean absolute deviation C. double smoothing D. least squares estimation E. predictor regression

The two general approaches to forecasting are: A. mathematical and statistical B. qualitative and quantitative C. judgmental and qualitative D. historical and associative E. precise and approximation

Which of the following is not a type of judgmental forecasting? A. executive opinions B. sales force opinions C. consumer surveys D. the Delphi method E. time series analysis

Accuracy in forecasting can be measured by: A. MSE B. MRP C. MAPE D. MTM E. A & C

Which of the following would be an advantage of using a sales force composite to develop a demand forecast? A. The sales staff is least affected by changing customer needs. B. The sales force can easily distinguish between customer desires and probable actions. C. The sales staff is often aware of customers' future plans. D. Salespeople are least likely to be influenced by recent events. E. Salespeople are least likely to be biased by sales quotas.

Which phrase most closely describes the Delphi technique? A. associative forecast B. consumer survey C. series of questionnaires D. developed in India E. historical data

The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is: A. sales force opinions B. consumer surveys C. the Delphi method D. time series analysis E. executive opinions

One reason for using the Delphi method in forecasting is to: A. avoid premature consensus (bandwagon effect) B. achieve a high degree of accuracy C. maintain accountability and responsibility D. be able to replicate results E. prevent hurt feelings

Detecting non-randomness in errors can be done using: A. MSEs B. MAPs C. Control Charts D. Correlation Coefficients E. Strategies

Gradual, long-term movement in time series data is called: A. seasonal variation B. cycles C. irregular variation D. trend E. random variation

The primary difference between seasonality and cycles is: A. the duration of the repeating patterns B. the magnitude of the variation C. the ability to attribute the pattern to a cause D. the direction of the movement E. there are only 4 seasons but 30 cycles

Averaging techniques are useful for: A. distinguishing between random and non-random variations B. smoothing out fluctuations in time series C. eliminating historical data D. providing accuracy in forecasts E. average people

Putting forecast errors into perspective is best done using A. Exponential smoothing B. MAPE C. Linear decision rules D. MAD E. Hindsight

Using the latest observation in a sequence of data to forecast the next period is: A. a moving average forecast B. a naive forecast C. an exponentially smoothed forecast D. an associative forecast E. regression analysis

Moving average forecasting techniques do the following: A. immediately reflect changing patterns in the data B. lead changes in the data C. smooth variations in the data D. operate independently of recent data E. assist when organizations are relocating

Which is not a characteristic of simple moving averages applied to time series data? A. smoothes random variations in the data B. weights each historical value equally C. lags changes in the data D. requires only last period's forecast and actual data E. smoothes real variations in the data

In order to increase the responsiveness of a forecast made using the moving average technique, the number of data points in the average should be: A. decreased B. increased C. multiplied by a larger alpha D. multiplied by a smaller alpha E. eliminated if the MAD is greater than the MSE

A forecast based on the previous forecast plus a percentage of the forecast error is: A. a naive forecast B. a simple moving average forecast C. a centered moving average forecast D. an exponentially smoothed forecast E. an associative forecast

Which is not a characteristic of exponential smoothing? A. smoothes random variations in the data B. weights each historical value equally C. has an easily altered weighting scheme D. has minimal data storage requirements E. smoothes real variations in the data

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast? A. 0 B. .01 C. .1 D. .5 E. 1.0

Simple exponential smoothing is being used to forecast demand. The previous forecast of 66 turned out to be four units less than actual demand. The next forecast is 66.6, implying a smoothing constant, alpha, equal to: A. .01 B. .10 C. .15 D. .20 E. .60

Given an actual demand of 59, a previous forecast of 64, and an alpha of .3, what would the forecast for the next period be using simple exponential smoothing? A. 36.9 B. 57.5 C. 60.5 D. 62.5 E. 65.5

Given an actual demand of 105, a forecasted value of 97, and an alpha of .4, the simple exponential smoothing forecast for the next period would be: A. 80.8 B. 93.8 C. 100.2 D. 101.8 E. 108.2

Which of the following possible values of alpha would cause exponential smoothing to respond the most quickly to forecast errors? A. 0 B. .01 C. .05 D. .10 E. .15

A manager uses the following equation to predict monthly receipts: Yt = 40,000 + 150t. What is the forecast for July if t = 0 in April of this year? A. 40,450 B. 40,600 C. 42,100 D. 42,250 E. 42,400

In trend-adjusted exponential smoothing, the trend adjusted forecast (TAF) consists of: A. an exponentially smoothed forecast and a smoothed trend factor B. an exponentially smoothed forecast and an estimated trend value C. the old forecast adjusted by a trend factor D. the old forecast and a smoothed trend factor E. a moving average and a trend factor

In the "additive" model for seasonality, seasonality is expressed as a ______________ adjustment to the average; in the multiplicative model, seasonality is expressed as a __________ adjustment to the average. A. quantity, percentage B. percentage, quantity C. quantity, quantity D. percentage, percentage E. qualitative, quantitative

Which technique is used in computing seasonal relatives? A. double smoothing B. Delphi C. Mean Squared Error (MSE) D. centered moving average E. exponential smoothing

A persistent tendency for forecasts to be greater than or less than the actual values is called: A. bias B. tracking C. control charting D. positive correlation E. linear regression

Which of the following might be used to indicate the cyclical component of a forecast? A. leading variable B. Mean Squared Error (MSE) C. Delphi technique D. exponential smoothing E. Mean Absolute Deviation (MAD)

The primary method for associative forecasting is: A. sensitivity analysis B. regression analysis C. simple moving averages D. centered moving averages E. exponential smoothing

Which term most closely relates to associative forecasting techniques? A. time series data B. expert opinions C. Delphi technique D. consumer survey E. predictor variables

Which of the following corresponds to the predictor variable in simple linear regression? A. regression coefficient B. dependent variable C. independent variable D. predicted variable E. demand coefficient

The mean absolute deviation (MAD) is used to: A. estimate the trend line B. eliminate forecast errors C. measure forecast accuracy D. seasonally adjust the forecast E. all of the above

Given forecast errors of 4, 8, and - 3, what is the mean absolute deviation? A. 4 B. 3 C. 5 D. 6 E. 12

Given forecast errors of 5, 0, - 4, and 3, what is the mean absolute deviation? A. 4 B. 3 C. 2.5 D. 2 E. 1

Given forecast errors of 5, 0, - 4, and 3, what is the bias? A. - 4 B. 4 C. 5 D. 12 E. 6

Which of the following is used for constructing a control chart? A. mean absolute deviation (MAD) B. mean squared error (MSE) C. tracking signal (TS) D. bias E. none of the above

The two most important factors in choosing a forecasting technique are: A. cost and time horizon B. accuracy and time horizon C. cost and accuracy D. quantity and quality E. objective and subjective components

The degree of management involvement in short range forecasts is: A. none B. low C. moderate D. high E. total

Which of the following is not necessarily an element of a good forecast? A. estimate of accuracy B. timeliness C. meaningful units D. low cost E. written

Current information on _________ can have a significant impact on forecast accuracy: A. prices B. promotion C. inventory D. competition E. all of the above

A managerial approach toward forecasting which seeks to actively influence demand is: A. reactive B. proactive C. influential D. protracted E. retroactive

Customer service levels can be improved by better: A. mission statements B. control charting C. short term forecast accuracy D. exponential smoothing E. customer selection

Use of simple linear regression analysis assumes that: A. Variations around the line are random. B. Deviations around the line are normally distributed. C. Predictions are to be made only within the range of observed values of the predictor variable. D. all of the above E. none of the above

Given forecast errors of - 5, - 10, and +15, the MAD is: A. 0 B. 10 C. 30 D. 175 E. none of these