Traditionally, fashion products have incurred high losses due to stockouts and inventory obsolence because long lead times coupled with a concentrated selling season force all or at least most production to be committed before demand information is available. Under a Quick Response system, lead times are shortened sufficiently to allow a greater portion of production to be scheduled in response to initial demand. We model and analyze the decisions required under Quick Response and give a method for estimating the demand probability distributions needed in our model. We applied these procedures with a major fashion skiwear firm and found that cost relative to the current informal response system was reduced by enough to increase profits by 60%. Relative to the cost that would have been incurred if no response were used, optimized response reduces cost by enough to roughly quadruple profits.
Inventory turnover varies widely across retailers and over time. This variation undermines the usefulness of inventory turnover in performance analysis, benchmarking, and working capital management. We develop an empirical model using financial data for 311 publicly listed retail firms for the years 1987--2000 to investigate the correlation of inventory turnover with gross margin, capital intensity, and sales surprise (the ratio of actual sales to expected sales for the year). The model explains 66.7% of the within-firm variation and 97.2% of the total variation (across and within firms) in inventory turnover. It yields an alternative metric of inventory productivity, adjusted inventory turnover, which empirically adjusts inventory turnover for changes in gross margin, capital intensity, and sales surprise, and can be applied in performance analysis and managerial decision making. We also compute time trends in inventory turnover and adjusted inventory turnover, and find that both have declined in retailing during the 1987--2000 period.benchmarking, inventory turnover, retail operations, performance measures
Traditional inventory models, with a few exceptions, do not account for the existence of inventory record inaccuracy (IRI), and those that do treat IRI as random. This study explores IRI observed both within and across product categories and retail stores. Examining nearly 370,000 inventory records from 37 stores of one retailer, we find 65% to be inaccurate. We characterize the distribution of IRI and show, using hierarchical linear modeling (HLM), that 26.4% of the total variance in IRI lies between product categories and that 2.7% lies between stores. We identify several factors that mitigate record inaccuracy, such as inventory auditing practices, and several factors that exacerbate record inaccuracy, such as the complexity of the store environment and the distribution structure. Collectively, these covariates explain 67.6% and 69.0% of the variance in IRI across stores and product categories, respectively. Our findings underscore the need to design processes to reduce the occurrence of IRI and highlight factors that can be incorporated into inventory planning tools developed to account for its presence.execution, information technology, inventory control, record inaccuracy, retail, supply chains
Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved “open consent” process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain—we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.
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