Measuring the Quality of Intermittent-Demand Forecasts: ItÕs Worse than WeÕve Thought!

Steve Morlidge

Foresight: The International Journal of Applied Forecasting, 2015, issue 37, 37-42

Abstract: In this eye-opening article, Steve Morlidge shows that when our demand histories are intermittent, we should rethink the use of our most common accuracy metrics for selecting a best forecast method. The problem is acute because many software applications use these metrics for performance evaluation and method selection; in doing so, they potentially provide us with poor feedback and inferior models, resulting in harmful consequences for inventory management. Copyright International Institute of Forecasters, 2015

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2015:i:37:p:37-42

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