John’s key points are these. • Organizations should consider which service level measure aligns most closely to their corporate objectives. Cost of Forecast Error (CFE) calculations should be based on this measure. • Assessment of service level targets at higher levels of aggregation elevates an operational task to a strategic issue and facilitates consideration of external factors. • Alternative approaches which do not depend on Cost of Forecast Error estimates, such as tradeoff curves, should be considered. Copyright International Institute of Forecasters, 200
Little attention has been devoted to explaining the failure to predict the turning points at the beg...
Economists are often puzzled as to why profit-maximizing firms buy professional forecasts when stati...
This paper contributes to the growing literature in macroeconomics and finance on expectation format...
Our study evaluates the impact of forecast errors on organizational cost by simulating a labor-inten...
Foresight’s Summer 2010 issue contained a letter to the editor from David Hawitt, suggesting that fo...
Forecast adjustment commonly occurs when organizational forecasters adjust a statistical forecast of...
The paper shows that due to the features of SKU (stock-keeping unit) demand data wellknown error mea...
Successful demand planning relies on accurate demand forecasts. Existing demand planning software ty...
John and Aris distinguish between forecase-accuracy metrics, which measure the errors resulting from...
Rather than automatically proceeding to forecast with data at the same level of aggregation as that...
Misforecasting demand will cost profits and threaten reputations, market share, and even the busines...
The signs of forecast errors can be predicted using the difference between individuals' forecasts an...
Judgmental adjustments to statistically generated forecasts have become a standard practice in deman...
Understanding the economic value of weather and climate forecasts is of tremendous practical importa...
The Online Forecast Error Package is used to identify and track the type, frequency and magnitude of...
Little attention has been devoted to explaining the failure to predict the turning points at the beg...
Economists are often puzzled as to why profit-maximizing firms buy professional forecasts when stati...
This paper contributes to the growing literature in macroeconomics and finance on expectation format...
Our study evaluates the impact of forecast errors on organizational cost by simulating a labor-inten...
Foresight’s Summer 2010 issue contained a letter to the editor from David Hawitt, suggesting that fo...
Forecast adjustment commonly occurs when organizational forecasters adjust a statistical forecast of...
The paper shows that due to the features of SKU (stock-keeping unit) demand data wellknown error mea...
Successful demand planning relies on accurate demand forecasts. Existing demand planning software ty...
John and Aris distinguish between forecase-accuracy metrics, which measure the errors resulting from...
Rather than automatically proceeding to forecast with data at the same level of aggregation as that...
Misforecasting demand will cost profits and threaten reputations, market share, and even the busines...
The signs of forecast errors can be predicted using the difference between individuals' forecasts an...
Judgmental adjustments to statistically generated forecasts have become a standard practice in deman...
Understanding the economic value of weather and climate forecasts is of tremendous practical importa...
The Online Forecast Error Package is used to identify and track the type, frequency and magnitude of...
Little attention has been devoted to explaining the failure to predict the turning points at the beg...
Economists are often puzzled as to why profit-maximizing firms buy professional forecasts when stati...
This paper contributes to the growing literature in macroeconomics and finance on expectation format...