The Future of Retail Operations

Retailing consists of all the activities associated with the selling of goods to the final consumer. In this article, we review the research on retail operations published in Manufacturing & Service Operations Research (M&SOM) since 1999. We then discuss the current retail landscape and the new research directions it offers, in which M&SOM can play a prominent role

The Nuisance of Slow Moving Products in Electronic Commerce

Article presents the important problem of products with low turnover in environment of electronic commerce. The key factors leading to the increasing number of slow moving stock keeping units (SKUs) in the context of online store are described. These issues are divided into two sets: general (not connected with online environment) and these which concern mainly online stores. The difficulty with identification of such SKUs is presented and proposition of inventory control shelf warmers indicator is shown. Afterwards the three-stage procedure for dealing with the occurrence of shelf warmers is described. The last part of the paper present the short conclusions

The Top-Dog Index: A New Measurement for the Demand Consistency of the Size Distribution in Pre-Pack Orders for a Fashion Discounter with Many Small Branches

We propose the new Top-Dog-Index, a measure for the branch-dependent historic deviation of the supply data of apparel sizes from the sales data of a fashion discounter. A common approach is to estimate demand for sizes directly from the sales data. This approach may yield information for the demand for sizes if aggregated over all branches and products. However, as we will show in a real-world business case, this direct approach is in general not capable to provide information about each branch's individual demand for sizes: the supply per branch is so small that either the number of sales is statistically too small for a good estimate (early measurement) or there will be too much unsatisfied demand neglected in the sales data (late measurement). Moreover, in our real-world data we could not verify any of the demand distribution assumptions suggested in the literature. Our approach cannot estimate the demand for sizes directly. It can, however, individually measure for each branch the scarcest and the amplest sizes, aggregated over all products. This measurement can iteratively be used to adapt the size distributions in the pre-pack orders for the future. A real-world blind study shows the potential of this distribution free heuristic optimization approach: The gross yield measured in percent of gross value was almost one percentage point higher in the test-group branches than in the control-group branches.Comment: 22 pages, 15 figure

Assortment optimization under the multi-choice rank list model : practical application at CurveCatch

In today’s highly competitive market, retailers are under significant pressure to determine which products will most effectively satisfy the needs and preferences of their customers to maximize profits given strategical and operational limitations. Most of the assortment planning approaches proposed to help businesses understand customer behaviour are based on discrete choice models. However, many choice models assume that a customer can only purchase at most one product, which in some cases is not an accurate reflection of the real-world purchasing behaviour. In this paper I quantify the benefit of accounting for multi-choice behaviour in rank based choice models and measure the impact that business requirements have on the optimal assortment. Based on the numerical experiment using secondary data provided by CurveCatch, an e-commerce lingerie retailer, I demonstrate that multi-choice modelling significantly improves the revenue generated by the assortment. Furthermore, I provide insight into the implementation of strategic and operational constraints and their impact on the optimal assortment.Num mundo atual extremamente competitivo, os retalhistas estão sob uma pressão significativa para selecionar os produtos que vão satisfazer as necessidades e as preferências dos seus consumidores da forma mais eficaz de forma a maximizar os lucros dadas as limitações estratégicas e operacionais do seu negócio. Grande parte das abordagens propostas para ajudar as empresas a compreender o comportamento dos seus clientes baseia-se em modelos de escolha discreta. No entanto, a maior parte dos modelos de escolha parte do pressuposto que cada cliente pode apenas comprar no máximo um produto, o que em alguns casos não reflete de forma realística os comportamentos dos consumidores no mundo real. Nesta tese, eu quantifico o benefício associado em permitir que um cliente compre mais que um produto em modelos de escolha baseados em rankings e para além disso, meço o impacto que as limitações de negócio têm sobre a receita associada à gama de produtos ótima. Através da simulação numérica com base em dados fornecidos pela CurveCatch, uma empresa retalhista de roupa interior focada no comércio eletrónico, eu demonstro que permitir que um cliente compre mais que um produto melhora significativamente a receita gerada pela gama de produtos. Paralelamente, demonstro o impacto que a imposição dos requisitos estratégicos e operacionais pode ter na gama de produtos ótima

Inventory Management under Product Mis-identification/Shipment Errors

“Wrong-product” delivery - the delivery of a product different from that desired - is a significant, but as yet unexplored problem in supply-chain management research. There are basically two reasons for wrong-product delivery: either the wrong product is mistakenly ordered or the right product is ordered but the wrong product is picked/shipped. This paper defines and analyzes the “wrong-product delivery” problem using a 2-product newsvendor model. Two non-substitutable products may be ordered at the beginning of each time period. However, whenever product i is ordered, then with known probability i, product j is delivered; i, j = 1, 2(i 6= j). First, we analyze the “no-recourse scenario”, where management correctly stores whatever was received, but takes no other action. We establish the form of the optimal policy and conduct sensitivity analysis. Although our modeling framework is simple, our results are unexpected and non-intuitive. For example, it is well known that in the single-product newsvendor model, increasing the uncertainty of demand or supply will yield an increase in the corresponding target basestocks and safety stocks. However, increasing the risk of a wrong-product error yields a decrease in the corresponding basestocks and safety stocks. Further, although target basestocks in the single-product newsvendor model are invariant to increases in on-hand inventory, we show that the target basestock for either product is non-decreasing as its inventory increases. We also demonstrate that the cost impact of wrong-product uncertainty is comparable, if not larger than, the cost impact of demand uncertainty. Next, we analyze the “recourse scenario” where management is able to correct errors but only by incurring a fixed cost of $K. We show that it is optimal to take recourse when the wrong-product uncertainty is sufficiently small, but not take recourse when the wrong-product uncertainty is high. In strategic terms, our analysis provides insight into the cost impact of wrong-product errors, and, hence, the importance of reducing them.Supply chain management, Inventory management, Shipment errors, Ordering errors, Yield management, Unreliable supply