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Grocery retailing is a highly competitive market (e.g. Keh and Park 1997). European retailers are continuously aiming to improve customer loyalty by offering good service. At the same time, they are struggling to reduce costs in order to stay competitive. The effort to achieve customer service excellence has only been partly successful, as the low average product shelf availability rates of 92–95% (Gruen, Corsten et al. 2002; Roland Berger 2003b) and a sunk store loyalty underline. The major part of retailer costs are personnel costs, and in particular it is the operations in the store that require intensive staff dedication (Broekmeulen, van Donselaar et al. 2004a). The German retailer Globus has calculated that the logistics costs of the last 50 meters in the store, i.e. from the backroom to the shelf, are three times as expensive as the first 250 kilometres from the producer to the store gate (Shalla 2005). A technique that promises to reduce the out-of-stock (OOS) rate by simultaneously reducing the store handling costs are so-called automatic store replenishment (ASR) systems, the main research subject of this thesis.

The outcome of any research is strongly affected by the choice of the research methods and strategies. As Scandura and Williams state (2000, p. 1249) “[a]ny research method chosen will have inherent flaws, and the choice of that method will limit the conclusions.” This means that design choices about instrumentation, data analysis and construct validation may affect the types of conclusions that are drawn (Sackett and Larson 1990). Therefore, this chapter gives an overview of the research methodology chosen for this thesis. First, a research framework narrows the research field down. Second, the qualitative and quantitative research methods are depicted before, finally, the research activities that led to this thesis are presented.

There exists almost no academic source that deals directly with automatic store replenishment systems at retail store level. Yet, even if theory cannot provide direct answers to the research questions, it is fruitful to consider the presented practical problem from different theoretical perspectives in order to obtain new impulses for this research project. Therefore, four theoretical research sources are addressed below in detail to verify, what contribution further theoretical streams can offer. The literature research focuses on sources dealing with inventory management, logistics and operations management, business IT and contingency theory (see Table 2).

The first milestone in this work is the creation of a descriptive model of ASR systems. It provides an answer to the first research question : how can automatic store replenishment systems be classified? This model does not claim to include all possible kinds of replenishment systems, as new, revolutionary, decentralized systems may be developed in the future. Yet it provides a helpful structure to examine the replenishment systems of today’s retailers. As it is created on an abstract level, its core results can be applied to other industries dealing with piece goods replenishment processes as well.

To be able to test the hypotheses formulated in the previous chapter, two different data sets of the company MYFOOD, a major central European grocery retailer, are analysed. One part of the data stems from a physical OOS audit project that the KLOG conducted together with this retailer in summer and autumn 2004. In addition, historical sales and POS data was extracted from the retailer’s ERP system to complement the findings. The quantitative analysis made on this dataset consists of three parts, analogous to the three groups of hypotheses. First, correlations between OOS rate and product characteristics are explored. Second, the influence of store characteristics on the OOS rate is examined. Finally, overall replenishment performance is tested. Table 13 gives an overview of the datasets that are used for the hypothesis testing and which will be presented in this chapter.

As seen in the quantitative analysis, higher ASR systems can significantly improve retailers’ inventory performance, reduce OOS incidents, and show more constant results. Yet it was also found that badly or crudely parameterised systems will not deliver the desired results. As stated by the contingency theory, the context of the company is decisive in determining the success of an automatic replenishment system. Therefore, in order to be able to give recommendations to practitioners it is necessary to examine in detail how retailers successfully introduced ASR systems and in which fields they can still improve their operations. In this chapter, the case studies of four retailers are depicted. For each company, a description of their replenishment processes, the organizational changes and personnel issues linked to the ASR introduction are highlighted as well as the outcome of ASR system’s introduction.

In this final chapter, the contributions for theoretical research and practitioners are summarized, before further research fields are depicted.

The difficulty with the data extracted from MYFOOD’s ERP system was that the system does not record any absolute values of the stock level. This means that it is not possible to determine ex post the quantity of goods there were for a certain product on a specific day. In addition, MYFOOD interviewees stressed the inaccuracy of the inventory records. This statement is supported by physical audits (see Figure 49) and by other researchers (e.g. ). The only available data was relative, i.e. showing how many units were delivered and how many units left the store on a certain day. With this data it is possible to determine the stock level curve, but without knowing at which height on the y-axis the curve is (see Figure 57).