On the bias of intermittent demand estimates

By A. Syntetos, John E. Boylan. 2001

383 citations recorded by the source corpus.

Forecasting and inventory control for intermittent demand items has been a major problem in the manufacturing and supply environment. Croston (Operational Research Quarterly 23 (1972) 289), proposed a method according to which intermittent demand estimates can be built from constituent events. Croston's method has been reported to be a robust method but has shown more modest benefits in forecasting accuracy than expected. In this research, one of the causes of this unexpected performance has been identified, as a first step towards improving Croston's method. Certain limitations are identified in Croston's approach and a correction in his derivation of the expected estimate of demand per time period is presented. In addition, a modification to his method that gives approximately unbiased demand per period estimates is introduced. All the conclusions are confirmed by means of an extended simulation experiment where Croston's and Revised Croston's methods are compared. The forecasting accuracy comparison corresponds to a situation of an inventory control system employing a re-order interval or product group review.

Subfields: Discrete Mathematics and Combinatorics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7e1f4e8aad9e1dc8f609bdf130ba692d98221523

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Citations in the corpus

Stochastic models underlying Croston ’ s method for intermittent demand forecasting 2 February 2005 (2005, methodology): “Other authors, including Johnston & Boylan (1996) and Syntetos & Boylan (2001), have suggested a few modifications to Croston’s method that can provide improved forecast accuracy.”
Demand Forecasting in the Fashion Industry: A Review (2013, neutral): “ Slow‐moving: demand is usually defined as having infrequent demands, which occur in very few units [30].”
The accuracy of intermittent demand estimates (2005, methodology): “This data set is not part of the set of 17,000 series described earlier by Syntetos and Boylan (2001) .”
Forecasting and operational research: a review (2008, methodology): “(Standard accuracy measures such asMAPE are inadequate in this context because of the zero denominator, Syntetos and Boylan, 2001.)”
Intermittent demand forecasts with neural networks (2013, methodology): “Therefore, as Hyndman and Shenstone (2005) find, Croston’s method is inconsistent with the properties of intermittent demand, but of practical usefulness as it has been shown empirically to outperform conventional methods (Willemain et al., 1994; Syntetos and Boylan, 2001).”
Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping ☆ (2015, background): “Although Croston claims that hismethod is unbiased, Syntetos and Boylan (2001) show that the opposite is true and present an improved method that corrects for bias (Syntetos & Boylan, 2005).”
EXPONENTIAL SMOOTHING: THE STATE OF THE ART, PART II (2006, positive): “Shenstone and Hyndman also found that there is no underlying stochastic model for Croston’s method or the two variants proposed by Syntetos and Boylan (2001, 2005).”
'Horses for Courses' in demand forecasting (2014, methodology): “For a selected level of number of observations (l) and level of IDI, we generate a vector which specifies the occurrence of non-zero demands as a Bernoulli distribution (Croston, 1972; Syntetos and Boylan, 2001), where p=1/IDI.”
Retail forecasting: Research and practice (2019, methodology): “Techniques designed specifically for intermittent demand include Croston’s method (Croston, 1972), the Syntetos and Boylan method (Syntetos and Boylan, 2001), Levén and”