An aggregate-disaggregate intermittent demand approach (ADIDA) to forecasting: An empirical proposition and analysis

Nikolopoulos, K; Syntetos, AA; Boylan, JE; Petropoulos, F; Assimakopoulos, V

dc.contributor.author	Nikolopoulos, K	en
dc.contributor.author	Syntetos, AA	en
dc.contributor.author	Boylan, JE	en
dc.contributor.author	Petropoulos, F	en
dc.contributor.author	Assimakopoulos, V	en
dc.date.accessioned	2014-03-01T01:35:05Z
dc.date.available	2014-03-01T01:35:05Z
dc.date.issued	2011	en
dc.identifier.issn	0160-5682	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20967
dc.subject	aggregation	en
dc.subject	demand forecasting	en
dc.subject	empirical investigation	en
dc.subject	intermittent demand	en
dc.subject	inventory management	en
dc.subject.classification	Management	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	aggregation	en
dc.subject.other	demand forecasting	en
dc.subject.other	empirical investigation	en
dc.subject.other	Intermittent demand	en
dc.subject.other	inventory management	en
dc.subject.other	Forecasting	en
dc.subject.other	Industrial applications	en
dc.subject.other	Military applications	en
dc.subject.other	Inventory control	en
dc.title	An aggregate-disaggregate intermittent demand approach (ADIDA) to forecasting: An empirical proposition and analysis	en
heal.type	journalArticle	en
heal.identifier.primary	10.1057/jors.2010.32	en
heal.identifier.secondary	http://dx.doi.org/10.1057/jors.2010.32	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	Intermittent demand patterns are characterised by infrequent demand arrivals coupled with variable demand sizes. Such patterns prevail in many industrial applications, including IT, automotive, aerospace and military. An intuitively appealing strategy to deal with such patterns from a forecasting perspective is to aggregate demand in lower-frequency 'time buckets' thereby reducing the presence of zero observations. However, such aggregation may result in losing useful information, as the frequency of observations is reduced. In this paper, we explore the effects of aggregation by investigating 5000 stock keeping units from the Royal Air Force (UK). We are also concerned with the empirical determination of an optimum aggregation level as well as the effects of aggregating demand in time buckets that equal the lead-time length (plus review period). This part of the analysis is of direct relevance to a (periodic) inventory management setting where such cumulative lead-time demand estimates are required. Our study allows insights to be gained into the value of aggregation in an intermittent demand context. The paper concludes with an agenda for further research. Journal of the Operational Research Society (2011) 62, 544-554. doi:10.1057/jors.2010.32 Published online 28 April 2010	en
heal.publisher	PALGRAVE MACMILLAN LTD	en
heal.journalName	Journal of the Operational Research Society	en
dc.identifier.doi	10.1057/jors.2010.32	en
dc.identifier.isi	ISI:000287309500013	en
dc.identifier.volume	62	en
dc.identifier.issue	3	en
dc.identifier.spage	544	en
dc.identifier.epage	554	en