Asked by Demia Kelly on May 21, 2024
Verified
Describe the basic characteristics of forecasts that managers should be aware of.
Forecasts Characteristics
Features or attributes of predictions about future events, such as demand or market trends, including accuracy, reliability, and timeliness.
- Gain insight into the idea and mathematical calculation of Mean Squared Error (MSE) in projection tasks.
- Gain insight into the elementary metrics for forecasting inaccuracies: MSE, MAD, and MAPE.
- Absorb and put into practice Holt's method for forecasting.
Verified Answer
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Cassie CampiottiMay 22, 2024
Final Answer :
Companies and supply chain managers should be aware of the following characteristics of forecasts:
Forecasts are always wrong and should thus include both the expected value of the forecast and a measure of forecast error.Thus,the forecast error (or demand uncertainty)must be a key input into most supply chain decisions.An estimation of demand uncertainty is unfortunately often missing from forecasts,resulting in estimates that vary widely among different stages of a supply chain that is not forecasting collaboratively.
Long-term forecasts are usually less accurate than short-term forecasts;that is,long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
Aggregate forecasts are usually more accurate than disaggregate forecasts,as they tend to have a smaller standard deviation of error relative to the mean.The greater the degree of aggregation,the more accurate the forecast.
In general,the further up the supply chain a company is (or the further they are from the consumer),the greater the distortion of information they receive.One classic example of this is the bullwhip effect,where order variation is amplified as orders move further from the end customer.As a result,the further up the supply chain an enterprise exists,the higher the forecast error.Collaborative forecasting based on sales to the end customer can help enterprises further up the supply chain reduce forecast error.
Forecasts are always wrong and should thus include both the expected value of the forecast and a measure of forecast error.Thus,the forecast error (or demand uncertainty)must be a key input into most supply chain decisions.An estimation of demand uncertainty is unfortunately often missing from forecasts,resulting in estimates that vary widely among different stages of a supply chain that is not forecasting collaboratively.
Long-term forecasts are usually less accurate than short-term forecasts;that is,long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
Aggregate forecasts are usually more accurate than disaggregate forecasts,as they tend to have a smaller standard deviation of error relative to the mean.The greater the degree of aggregation,the more accurate the forecast.
In general,the further up the supply chain a company is (or the further they are from the consumer),the greater the distortion of information they receive.One classic example of this is the bullwhip effect,where order variation is amplified as orders move further from the end customer.As a result,the further up the supply chain an enterprise exists,the higher the forecast error.Collaborative forecasting based on sales to the end customer can help enterprises further up the supply chain reduce forecast error.
Learning Objectives
- Gain insight into the idea and mathematical calculation of Mean Squared Error (MSE) in projection tasks.
- Gain insight into the elementary metrics for forecasting inaccuracies: MSE, MAD, and MAPE.
- Absorb and put into practice Holt's method for forecasting.
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