TAILIEUCHUNG - Assessing the Frequency and Causes of Out-of-Stock Events Through Store Scanner Data

Many equity investments have a quoted market price in an active market, which is used as fair value. These market prices reflect normal market transactions and are readily avail- able from brokers or in the financial trading is light, recent bid prices are accept- able, although light trading may indicate that estimating fair value is problematic. For exam- ple, a recent price might not be relevant if significant events had taken place after the bid date (CICA ED ). What if there are no recent transactions? The AcSB suggests that fair value can be esti- mated, through judicious use of valuation techniques. These valuation techniques must incorporate. | Assessing the Frequency and Causes of Out-of-Stock Events Through Store Scanner Data Anne-Sophie Bayle-Tourtoulou HEC School of Management 78350 Jouy-en-Josas France tourtoulou@ Gilles Laurent HEC School of Management 78350 Jouy-en-Josas France laurent@ fax 33 1 3967 7087 telephone 33 1 3967 7480 Sandrine Macé ESCP-EAP 79 avenue de la République 75543 Paris Cedex 11 France mace@ The authors thank IRI France for providing the data Pierre Chandon for his comments on a previous version and Ganael Bascoul for his help with the data analysis. 1 Assessing the Frequency and Causes of Out-of-Stock Events Through Store Scanner Data Abstract Both retailers and manufacturers see in-store out-of-stock events OOS as a major problem but there is a lack of research about their frequency the sales losses they generate and their causes. We provide a twofold contribution We describe a new sales-based measure of OOS computed on the basis of store-level scanner data and we identify several of the main determinants of OOS. We also introduce a significant distinction between complete and partial OOS. In both types the observed sales level is significantly below its expected value. Complete OOS occur when there are no sales at all partial OOS takes place when sales though abnormally low are not zero. Our analysis of seven different data sets reveals that complete OOS are far less frequent than partial OOS. In addition complete OOS are more frequent in stores with lower category sales and for stockkeeping units SKUs with lower market shares. In contrast partial OOS are more frequent in stores with higher category sales and for SKUs with higher market shares. With regard to the impact of assortment size in the store we find mixed results. Finally we find that variables related to the segment to which an SKU belongs the manufacturer and the package format all have a significant impact on both partial and complete OOS. Key words Out-of-stock events store-level scanner

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