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Stock-keeping Units (stock-keeping + unit)

Distribution by Scientific Domains

Mathematics and Statistics	50%

Selected Abstracts

Warehouse sizing to minimize inventory and storage costs

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 4 2001
Mark Goh
Abstract This paper considers a warehouse sizing problem whose objective is to minimize the total cost of ordering, holding, and warehousing of inventory. Unlike typical economic lot sizing models, the warehousing cost structure examined here is not the simple unit rate type, but rather a more realistic step function of the warehouse space to be acquired. In the cases when only one type of stock-keeping unit (SKU) is warehoused, or when multiple SKUs are warehoused, but, with separable inventory costs, closed form solutions are obtained for the optimal warehouse size. For the case of multi-SKUs with joint inventory replenishment cost, a heuristic with a provable performance bound of 94% is provided. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 299,312, 2001 [source]

The Effect of Buyer-Imposed Bidding Requirements and Bundle Structure on Purchase Performance

JOURNAL OF SUPPLY CHAIN MANAGEMENT, Issue 1 2007
Tobias Schoenherr
SUMMARY Many requests for quotation (RFQs) consist of a group of different stock-keeping units (SKUs), bundled together in a single order lot. How this lot is structured and whether suppliers are required to adhere strictly to its composition (i.e., quote on all items in the bundle versus a subset) may significantly impact the competitiveness of the bidding and the buyer's perceived performance of the purchase. To better understand bundling practices and experiences, a survey of purchasers that aggregate several SKUs into a single bundled RFQ was undertaken. Within this context, respondent replies are categorized by buyer-imposed bidding requirements according to whether suppliers are required to submit bids on all items in the bundle, merely encouraged, or free to bid on any item combination in the bundle. The resulting bundle structure is examined and its impact on purchase (bundle) performance, as perceived by the buying company, is explored. Results are discussed, with managerial insights provided for purchasing professionals. [source]

THE VALUE OF SKU RATIONALIZATION IN PRACTICE (THE POOLING EFFECT UNDER SUBOPTIMAL INVENTORY POLICIES AND NONNORMAL DEMAND)

PRODUCTION AND OPERATIONS MANAGEMENT, Issue 1 2003
JOSÉ A. ALFARO
Several approaches to the widely recognized challenge of managing product variety rely on the pooling effect. Pooling can be accomplished through the reduction of the number of products or stock-keeping units (SKUs), through postponement of differentiation, or in other ways. These approaches are well known and becoming widely applied in practice. However, theoretical analyses of the pooling effect assume an optimal inventory policy before pooling and after pooling, and, in most cases, that demand is normally distributed. In this article, we address the effect of nonoptimal inventory policies and the effect of nonnormally distributed demand on the value of pooling. First, we show that there is always a range of current inventory levels within which pooling is better and beyond which optimizing inventory policy is better. We also find that the value of pooling may be negative when the inventory policy in use is suboptimal. Second, we use extensive Monte Carlo simulation to examine the value of pooling for nonnormal demand distributions. We find that the value of pooling varies relatively little across the distributions we used, but that it varies considerably with the concentration of uncertainty. We also find that the ranges within which pooling is preferred over optimizing inventory policy generally are quite wide but vary considerably across distributions. Together, this indicates that the value of pooling under an optimal inventory policy is robust across distributions, but that its sensitivity to suboptimal policies is not. Third, we use a set of real (and highly erratic) demand data to analyze the benefits of pooling under optimal and suboptimal policies and nonnormal demand with a high number of SKUs. With our specific but highly nonnormal demand data, we find that pooling is beneficial and robust to suboptimal policies. Altogether, this study provides deeper theoretical, numerical, and empirical understanding of the value of pooling. [source]

The diffusion of marketing science in the practitioners' community: opening the black box

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4-5 2005
Albert C. Bemmaor
Abstract This editorial discusses an illustration of the potential hindrances to the diffusion of modern methodologies in the practitioners' (i.e. the buyers of research, not the consultants) community. Taking the example of classical regression analysis based on store-level scanner data, the authors discuss the potential limitations of the classical regression model, with the example of the occurrence of ,wrong' signs and of coefficients with unexpected magnitudes. In an interview with one of the authors, a (randomly picked) Senior Marketing Research Manager at a leading firm of packaged goods reports his/her experience with econometric models. To him/her, econometric models are presented as a ,black box' (his/her written words). In his/her experience, they provided results that were ,quite good' in a ,much focused' context only. There were experimental data obtained with a Latin square design and the analysis included a single brand with only four stock-keeping units (SKUs). The company ,dropped' the more ,ambitious' studies, which analysed the effect of the retail promotions run by all the actors in a market because of a lack of predictive accuracy (his/her written words are in quotes). The authors suggest that Bayesian methodology can help open the black box and obtain more acceptable results than those obtained at present. Copyright © 2005 John Wiley & Sons, Ltd. [source]