This Forecasting in Business Strategy Quiz assesses knowledge on demand characteristics, forecasting techniques, and the importance of error estimation and forecast monitoring. It's designed to enhance strategic decision-making skills in business environments.
Only A
A, B, and C
D and E
B, C, D, and E
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Forecasts are more accurate for individual items than for groups of items
Forecasts are more accurate for distant periods of time
Every forecast should include an estimate of error
Forecasts are usually accurate
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The past is a valid indicator of the future
Demand trend is seldom linear
Seasonal variations are small
Random variations are small
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Trend time average
Moving average
Demand smoothing
Qualitative analysis
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To compare the actual sales with the forecast
To improve our forecasting methods
To utilize actual sales data
To satisfy marketing's need to know
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Demand fluctuations that depend on the time of the year, week, or day are called trend
The season index is an estimate of how much the demand during the season will be above or below the average demand
Seasonality always occurs in summer, winter, spring, and fall
Random variation is constant from period to period
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Random variation from average demand
Errors in monitoring the forecast
Differences in lead times
Differences between sales and demand
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Independent demand items should be forecast
A forecast for sales next year will not be as accurate as a forecast for a year from now
Forecasts for families of products should be built up from individual product forecasts
Forecasts are almost always accurate
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If we wish to forecast demand, past sales must be used for the forecast
Forecasts made in dollars for total sales should be used by manufacturing
Forecasts should be made for individual items in a group
The circumstances relating to demand data should be recorded
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