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Because increasing product variety in retail conflicts with limited shelf space, managing assortment and shelf quantities is a core decision in this sector. A retailer needs to define the assortment size and then assign shelf space to meet consumer demand. However, the current literature lacks not only information on the comprehensive structure of the decision problem, but also a decision support system that can be directly applied to practice in a straightforward manner. The paper aims to discuss these issues.

The findings were developed and evaluated by means of explorative interviews with grocery retail experts. An optimization model is proposed to solve the problem of assortment planning with limited shelf space for data sets of a size relevant in real retail practice.

The author identifies the underlying planning problems based on a qualitative survey of retailers and relates the problems to each other. This paper develops a pragmatic approach to the capacitated assortment problem with stochastic demand and substitution effects. The numerical examples reveal that substitution demand has a significant impact on total profit and solution structure.

The author shows that the model and solution approach are scalable to problem sizes relevant in practice. Furthermore, the planning architecture structures the related planning questions and forms a foundation for further research on decision support systems.

The planning framework structures the associated decision problems in assortment planning. An efficient solution approach for assortment planning is proposed.

Assortment planning, the determination of the range of choices to be made available at a given time, is a primary merchandising function. Many people with different job titles in both apparel manufacturing and retailing make decisions that impact merchandise assortments. The purpose of this paper is to explain the concept of assortment diversity as measured by volume per stock‐keeping unit for an assortment (VSA), describe the relationship of VSA to per cent gross margin (%GM), and propose topics for further research.

The purpose of this study is to examine the ability of supply chain merchandise replenishment strategies to minimize merchandise plan errors when assortments are diverse.

Sourcing Simulator 2.1, a computer simulation of the merchandising process, was used. Sourcing Simulator generated a total data set of 4,320 and determined financial outcomes of the merchandising processes based on multiple scenario inputs.

The impact of supply chain merchandise replenishment strategies on merchandising performance outcomes significantly differed, depending on assortment diversity and merchandise plan errors. The ability of supply chain merchandise replenishment strategies was limited in minimizing problems inherent in diverse assortments and over‐volume errors.

Sourcing Simulator does not necessarily simulate merchandising processes and performance in real retail stores but principles developed through simulation can be applied in retail stores. Future research based on real information is suggested for additional realistic understanding.

The study suggests that apparel and retail firms should develop both up‐front assortment planning and replenishment strategies, considering the level of assortment diversity.

Based on Behavioral Theory of the Apparel Firm, the study contributes to understanding the importance of merchandising functions in an apparel firm. In addition, the study illuminates assortment diversity as an important factor of merchandise planning, especially when apparel and retail firms plan replenishment strategies to minimize merchandise plan errors.

The purpose of this study was to contribute to merchandising theory development by testing and refining Rupe and Kunz’s Volume per Stock‐keeping unit for an Assortment (VSA) and Assortment Diversity Index(ADI), using multiple merchandising performance measures. Behavioural Theory of the Apparel Firm with a Quick Response construct (BTAF/QR), was used as the theoretical framework for the study. The data were generated by a computer simulation of the merchandising process called Sourcing Simulator. Statistical analyses included Pearson correlation coefficients and regressions. The VSA had significant correlations with all 14 merchandising performance measures (p < 0:001), and the ADI was a consistent indicator of financial productivity considering all 14 merchandising performance measures. The results of the study supported the proposal of additional assumptions as well as propositions and hypotheses related to merchandising responsibility for BTAF/QR.

The purpose of this paper is to explore tactical planning in grocery retailing and propose how process and integration mechanisms from sales and operations planning (S&OP) can enhance retail tactical planning.

This work follows an explorative design with case studies from the grocery retailing industry in Finland, Norway, and the UK.

The tactical planning process focuses on demand management and securing product availability from suppliers in order to reach sales targets. Less attention is directed toward balancing supply and demand or toward providing a single plan to guide company operations. Planning appeared to be functionally oriented with limited coordination between functional plans, but it did include external integration that improved forecast accuracy.

The study involves grocery retailer cases with variable levels of S&OP maturity. The propositions need to be investigated further through action research or additional case studies to confirm their validity.

The study proposes a design of an S&OP process in retailing and propositions for improving tactical planning integration.

The study complements research on retail tactical planning by taking planning process and integration viewpoints. The research suggests that retailers would benefit from a formal and company-wide S&OP process to unify different market-oriented plans to a single set of numbers, thus better balancing supply and demand without sacrificing the emphasis on demand planning.

The purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by task complexity (TC) and market dynamics (MD).

A multi‐variable conceptual model is developed based on the literature and tested among 215 warehouses using a survey.

The results suggest that TC and MD are the main drivers of warehouse management, measured by planning extensiveness (PE), decision rules complexity, and control sophistication. Differences between production and distribution warehouses are found with respect to the relationship between assortment changes and PE. Furthermore, TC appears to be a main driver of the specificity of the warehouse management (information) system (WMS).

This paper is based on 215 warehouses in The Netherlands and Flanders (Belgium); future research may test the model on a different sample. More research should be conducted to further validate the measures of the core dimensions of warehouse management.

Different levels of TC and MD characterize warehouses. Such a characterization is a first step in determining generic warehouse functionalities and helping managers to decide on the best software for their warehouse operations.

The paper defines the core dimensions of warehouse management, makes them measurable, tests them and assesses how these drivers impact specificity of WMS. The paper shows that PE in production warehouses is driven by different variables than in distribution centers.

This paper aims to describe the cross-channel challenges experienced by a leading US fashion retailer and illustrates the adaptation to consumer needs as led by a female divisional head and female executive.

The teaching objectives include to understand the assortment planning complexities experienced by merchandise managers; address critical issues surrounding channel strategies; identify the data needs for assortment improvement and cross-channel management; investigate responsive solutions for customer-focused assortment diversification; and explore the challenges associated with continual retail channel adaptation.

The fashion retailer Spirit & Free (S&F) (pseudonym) is a Fortune 500 retailer. As a multi-channel retailer, S&F is proud of the consistency of the brand’s identity across channels. However, recently, S&F has noticed a difference between their mobile (m-commerce, social commerce) and in-store/e-commerce customers. Through this case study, students will follow the Women’s Apparel Divisional Merchandise Manager and explore how the business will maintain a consistent brand identity and capture both sets of customers through assortment planning. Resources will be provided for assortment planning analysis, and students will be asked to consider assortment opportunities regarding category mix and pricing strategy.

The case would be relevant to upper-level undergraduate courses or introductory master's level course in retail, management, fashion merchandising and omni-channel retail.

Teaching notes are available for educators only.

CCS 8: Marketing

Suggests that gaps exist between the product ranges or lines offered by manufacturers and the assortments selected and stocked by retailers. Looks at the extent to which differing levels of “product volatility” affect retailers’ selectivity in stocking items from a manufacturer’s line. Provides a limited test of several hypotheses about how the degree of product volatility of the category within which a manufacturer’s line belongs might affect the number of items in the line that will be stocked by a retailer. Analysis of stock‐planning data for two retailers in each of two product categories offers some support for the hypotheses. Interprets these results in light of theories of distribution channel co‐ordination and retailer expertise. They may reflect an alternative explanation for widely observed increases in retailer power.

The challenge faced by supplier companies in the grocery supply chain for implementing collaborative planning, forecasting and replenishment (CPFR) is how to get the retailer to forecast, especially when it has not been necessary before. In this paper a solution that would allow collaboration on a wide scale is presented. The forecasting approach is called “rank and share” and uses input from the retailer’s existing planning process – the category management process. The benefit of using category management as the basis is that the retailer can scale up collaboration with a large number of suppliers without increasing planning resources. For the supplier the benefit is point of sales forecasts at the time of the assortment decision. To support this collaborative forecasting process there is a need for more robust replenishment solutions, new measures to illustrate benefits, and for a distributed planning architecture and software. Potential solutions for these are also discussed in the paper.

The purpose of this paper is to develop a holistic operations planning framework for grocery retailing. The authors aim to identify, describe and structure coherent demand and supply chain (SC) planning problems in a comprehensive architecture.

The authors reviewed key literature on retail SC management and sales planning. This built a foundation for the development of an integrated operations planning framework. The findings were evaluated through discussions with retailers and communications with retail planners, including personal interviews with 28 leading European grocery retailers and with people in related positions from the consumer goods industry and consultancies.

The core of this paper is the development of a coherent demand and SC planning matrix. It demonstrates planning interdependencies and defines a framework for retail operations. The grocery planning framework integrates retail specifics, as well as hierarchical and sequential aspects of decision making. That is why this planning architecture also forms the foundation for research and development of advanced decision support systems.

Planning tasks are identified in interrelated planning modules permitting coordinated and decentralised decision making, which is necessary for operational and complexity reasons. The planning framework assists retail planners in understanding their decision problem from a comprehensive perspective. Better coordination of different modules and further development of retail‐tailored analytical models will improve planning quality.

This is the first paper that structures retail demand and SC planning questions coherently in one framework, matching demand and supply from a long‐ to short‐term perspective and from supplier to customer.