Situación financiera 34

Location characteristics were found to affect how store managers managed OOS and OS occurrences in their stores. Findings revealed that not all store managers adopted HQ’s list of products to be offered. The newer stores adopted a higher percentage of products listed by HQ and the reason given was the short length of operation and the fact that the stores were still gathering insights on customer buying preferences. The older, more established stores only adopted 60 (and at most 80) per cent of products listed by HQ and the remaining product assortment was provided to suit their customers’ buying preference. For example, stores with a high proportion of customers from low income groups, tended to stock cheaper brands of groceries and wet market fresh produce. While this strategy sustained store patronage, the wide variations in product assortments adopted by the older stores posed a challenge for HQ to manage. Not only did they have to manage the supply chain of

166 prescribed products but also of those unique to the different stores. With increased product proliferation and high inventory levels, order-picking operations at HQ warehouses faced complexity and higher chance of mistakes (Skinner 1974). Such mistakes could flow into the stores and cause OOS and OS occurrences. In contrast, findings from this study have revealed that stores with higher SKUs had a lower extent of OOS occurrences when compared with stores with lower SKUs, which experienced higher extent of OOS occurrences (see Table 4-23).

Table 4-23 Comparisons of SKUs and extent of OOS occurrences in low-, medium- and high-OOS stores.

Low-OOS Stores Medium-OOS Stores High-OOS Stores

SKU (Average) ± 15,000 ± 17,000 ± 10,000 % of OOS (Average) 0.98% 2.70% 7.56%

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Conclusion

4.7

Within-group analysis revealed that some in-store processes experienced higher frequency of errors (e.g. receiving and checkout stations) compared to other in-store processes. Errors were caused by staff (e.g. under-scans at checkout stations, error scans due to similarity in packaging) and physical store factors (e.g. error scans at makeshift and unsheltered receiving stations to prevent congestion at the stations, longer replenishment times due to lack of back rooms). A system of mobile storage equipment (e.g. roller cages, mobile racks and shelves) was adopted to manage OS of products caused by internal factors (e.g. when HQ pushed excess stock onto stores) and external factors (e.g. unsuccessful product promotions). The time taken to detect and resolve in-store process errors by store managers also affected the integrity of stock level information in the stores’ systems.

Store managers paid special attention to relationship management with HQ and suppliers, so as to enable quick resolution of errors in inventory information and prompt correction of inaccurate deliveries. Some of the initiatives taken by store managers to maintain good relations with HQ and suppliers included personal calls to HQ and supplier, assisting suppliers with replenishment when customer traffic was low and the store managers’ keenness to improve product knowledge from suppliers. Store managers also adopted customer-centric strategies (e.g. being attentive to customers’ need for assistance, replacing shelf-tags of OOS items with yellow OOS labels while stackers retrieved replenishment stock and frequent walkabouts by store staff to check stock levels of display shelves) to ensure the minimisation of customer reactions to OOS.

Finally, the adoption of micro-marketing strategy on offering localised product assortment caused HQ to experience challenges in managing their extensive product assortment ranges. HQ not only had to manage the ‘chain-wide’ list of products, but also had to manage product assortment specifically offered by stores to meet local customers’ demands. This increase in

168 product complexity had resulted in a higher occurrence of mistakes made with orders and deliveries.

The next chapter will examine the above issues in further depth, together with a comparative analysis of OOS and OS management approaches employed by stores in the three groups.

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Chapter 5 Discussions

The within-group analysis revealed different levels of efforts expended by managers of low-, medium- and high-OOS stores in managing OOS and OS occurrences. Most store managers of low-OOS stores displayed high levels of diligence in the detection and resolution of errors. These managers also made their staff responsible for achieving and maintaining OSA by including incidence of mistakes made that had a direct, or perceivable indirect, impact on inventory record as an employee performance indicator. The exception was E-3-B, which took little proactive action to increase GSOP effectiveness, though it adhered closely to GSOP. On the other hand, most high-OOS store managers (except those of W-6-B and W-7-B, which adhered to GSOP) displayed tolerance and acceptance of mediocre outputs from staff, HQ and suppliers. To understand the effects of contrasting attitudes towards causes of OOS and OS occurrences in stores, this chapter cross- examines the findings of the within-group analysis to identify similarities and differences between OOS and OS management approaches used by store managers in the three groups.

The chapter is organised into three main sections, starting with Section 5.1, which presents the key findings of the cross-group analysis, including a discussion of the main similarities and differences in the management of OOS and OS causes common across the three groups. Section 5.2 discusses the management of OOS and OS occurrences in stores in each of the three groups. The discussion includes a list of propositions that provide insights on how FS’s stores managed OOS and OS occurrences. Section 5.3 concludes the chapter with a summary discussion that highlights key considerations in the management of OOS and OS occurrences in the stores of supermarket chains.

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Cross-Group Analysis