Feasibility principles for Downstream Demand Inference in supply chains

Many companies are adopting strategies that enable Demand Information Sharing (DIS) between the supply chain links. Recently, a steady stream of research has identified mathematical relationships between demands and orders at any link in the supply chain. Based on these relationships and strict model assumptions, it has been suggested that the upstream member can infer the demand at the downstream member from their orders. If this is so, DIS will be of no value. In this paper, we argue that real-world modelling requires less restrictive assumptions. We present Feasibility Principles to show that it is not possible for an upstream member to accurately infer consumer demand under more realistic model assumptions. Thus, we conclude that DIS has value in supply chains. We then move our focus to the supply chain model assumptions in the papers arguing that there is value in sharing demand information. Using a simulation experiment, we show that the value of sharing demand information in terms of inventory reductions will increase under more realistic supply chain model assumptions.     

Demand forecasting adjustments for service-level achievement

John E. Boylan School of Business and Management, Buckinghamshire New University, Bucks, UK Email: a.syntetos{at}salford.ac.uk Received on 25 January 2007. Accepted on 3 October 2007. Demand forecasting and stock control are traditionally examinedas independent of each other. Even though this weakness hasbeen highlighted in the academic literature, little empiricalwork has been conducted on forecasting adjustments addressingthe interaction between forecasting and stock control. In thispaper, the relevant literature is critically reviewed. Subsequently,the empirical performance of some modifications and adjustments,on slow-moving items, is examined in detail. The data set consistsof the individual demand histories of 753 intermittent lineitems from the Royal Air Force (UK). Overall, the results indicatethat there is a scope for improving the performance of parametricstock control systems, and adjustments are indeed required inorder to account for the interaction between forecasting andstock control.     

Book Review: Encyplopedia of Pharmaceutical Technology

James Swarbrick:Pharmaceutech, Inc., Pinehurst, North Carolina and aaiPharma Inc., Wilmington, North Carolina, U.S.A.; James J. Boylan: Pharmaceutical Consultant, Gurnee, Illinois, U.S.A.; This revised version was published online in August 2006 with corrections to the Cover Date.     

Forecasting for Items with Intermittent Demand

In a service environment, a stockist usually has many slow moving items whose infrequency of demand can give rise to forecasting problems. Moreover, when a demand occurs, the request is sometimes for more than a single unit, which results in so-called lumpy demand. In this paper, the standard method for dealing with such intermittent demand is reassessed. Some general results are presented that enable variance estimates to be made, and these are particularly straightforward when the demand occasions can be represented as a Poisson process. Some experimental evidence is advanced to support this model in the specific situation under study. Since EWMA forecasts are central to many commercial systems, a simulation analysis was conducted to determine under what conditions intermittent demand requires its own model, rather than an unadjusted EWMA. Superior performance is demonstrated for items that have an average inter-order interval greater than 1.25 forecast review periods, and the magnitude of the improvement increases as the average interval lengthens.     

Characterizing the frequency of orders received by a stockist

John E. Boylan Applied Social Sciences and Humanities, Buckinghamshire Chilterns University College, Buckinghamshire HP11 2JZ, UK F. R. Johnston Kerridge Computer Company, Charnham Park, Hungerford RG17 0YU, UK Email: estelle.shale{at}warwick.ac.uk Received on 26 January 2007. Accepted on 19 November 2007. It is regularly asserted that the frequency of orders receivedby a stockist can be represented as a Poisson process, but verylittle corroborative evidence has been published. This paperpresents some results supporting the assumption. An adaptationto the standard testing methodology is presented which overcomesthe complications arising from the necessity of sampling fromtime series data. The new approach is applied to a large rangeof stock-keeping units. Except for the extreme tail of the distribution,which is of little interest for most inventory applications,it is found that the frequency of orders is well representedby a Poisson process.     

Speciation of mercury in soil and sediment by selective solvent and acid extraction

In order to characterize the mercury hazard in soil, a sequential extraction scheme has been developed to classify mercury species based on their environmental mobility and/or toxicity for either routine lab analysis or on-site screening purposes. The alkyl mercury species and soluble inorganic species that contribute to the major portion of potential mercury toxicity in the soil are extracted by an acidic ethanol solution (2% HCl+10% ethanol solution) from soil matrices as "mobile and toxic" species. A High-Performance Liquid Chromatography (HPLC) system coupled with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) detection has been developed to further resolve the species information into soluble inorganic species (Hg(2+)), methylmercury(II) (MeHg(+)) and ethylmercury(II) (EtHg(+)) species. Alternatively, these species can be separated into "soluble inorganic mercury" and "alkyl mercury" sub-categories by Solid-Phase Extraction (SPE). A custom Sulfydryl Cotton Fiber (SCF) material is used as the solid phase medium. Optimization of the SCF SPE technique is discussed. Combined with a direct mercury analyzer (DMA-80), the SCF SPE technique is a promising candidate for on-site screening purposes. Following the ethanol extraction, the inorganic mercury species remaining in soil are further divided into "semi-mobile" and "non-mobile" sub-categories by sequential acid extractions. The "semi-mobile" mercury species include mainly elemental mercury (Hg) and mercury-metal amalgams. The non-mobile mercury species mainly include mercuric sulfide (HgS) and mercurous chloride (Hg(2)Cl(2)).     

Relationships between Service Level Measures for Inventory Systems

The service level provided by an inventory system can be measured in various ways. If different measures are used at a number of stock-holding depots, difficulties may arise in comparing performance or assessing the impact of depot centralization or decentralization. If the same measures are used at all depots but the inventory system changes from being based on one measure to another, similar problems arise. In this paper, relationships between six of the most frequently used service measures are presented, enabling each to be converted to a common measure. Data requirements for using the relationships are considered and, where appropriate, alternative relationships are presented which depend on data which may be more readily available in practice.     

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

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.