A stockout, or out-of-stock (OOS) event is an event that causes inventory to be exhausted. While out-of-stocks can occur along the entire supply chain, the most visible kind are retail out-of-stocks in the fast moving consumer goods industry (e.g., sweets, diapers, fruits). Stockouts are the opposite of overstocks, where too much inventory is retained.
The global average of retail out-of-stocks is 8.3%. This means that shoppers will have a 42% chance of fulfilling a ten-item shopping list without encountering a stockout. Despite the initiatives designed to improve the collaboration of retailers and their suppliers, such as Efficient Consumer Response (ECR), and despite the increasing use of new technologies such as radio-frequency identification (RFID) and point-of-sales data analytics, this situation has improved little over the past decades.
Recent surveys on retail out-of-stocks suggests that instore operations are fundamental to reducing retail out-of-stocks. Around 70-90% of stockouts are caused by defective shelf replenishment practices, as opposed to the 10-30% resulting from the upstream supply chain, such as a shortage of supply from a supplier.  This broad knowledge offers retailers the opportunity to improve on-shelf availability through internal measures. However, it requires a detailed understanding of the causes for out-of-stocks.
Stockouts frustrate shoppers and force them to take a number of corrective actions that are beyond the retailer’s control. Understanding how consumers respond to stockouts is therefore the starting point for retailers who wish to improve on-shelf availability. When shoppers are unable to find an item that they had intended to purchase, they might switch stores, purchase substitute items (brand switch, size switch, category switch), postpone their purchase or decide not to buy the item at all.  Although these responses differ in severity, each entails negative consequences for retailers. Stockouts cause lost sales, dissatisfy shoppers, diminish store loyalty, jeopardize marketing efforts, and obstruct sales planning, because substitution disguises true demand. Moreover, shopper surveys reveal stockouts to currently be the most prevalent annoyance to shoppers. Shoppers spend a considerable amount of time looking for and asking for out-of-stock items.  Shopper response to stockouts has been investigated by researchers with respect to cognitive response (e.g. perceived availability), affective response (e.g. store satisfaction), behavioural response (e.g. brand switching) and aggregated response in terms of category sales effects.  Studies find shopper response to out-of stocks depends on brand-related antecedents (e.g. brand equity), product and category-related antecedents (hedonic level), store-related antecedents (e.g. service or price-oriented), shopper-related antecedents (e.g. shopper age) and situational antecedents (e.g. purchase urgency). 
Depending on the shopper response to an out-of-stock, manufacturer and retailer incur various losses. Both manufacturer and retailer face a direct loss of the potential sale when a consumer faces an out-of-stock because the shopper purchases the item at another store or does not purchase it at all. Additionally, when a substitution is made, the retailer also loses an additional portion of the potential sale because the shopper tends to switch to smaller and/or cheaper substitutes. In addition to the direct losses, both the retailer and the manufacturer incur additional indirect losses due to decreased customer satisfaction that results in less overall reliance on the particular retailers and brands. When an out-of-stock leads to purchase at another store, this provides the consumer an opportunity to try a different store. Consumer behavior theory argues that trial precedes adoption, and, thus, an out-of-stock sets the stage for possible permanent store switching. When an out-of-stock leads to purchase of a competing brand, the consumer trial can lead to possible permanent brand switching as well. Research findings show that a typical retailer loses about 4 percent of sales due to having items out-of-stock. A loss of sales of 4 percent translates into a earnings per share loss of about $0.012 (1.2 cents) for the average firm in the grocery retailing sector, where the average earnings per share, already is about $0.25 (25 cents) per year.
Identifying and reducing retail out-of-stocks
Identification of stock levels can reduce out-of-stocks. The traditional method is to perform a manual audit of the store and manually look for “gaps” on the shelves. Due to differing sales velocities and replenishment schedules, the effectiveness of manual stockout audits depends heavily on their frequency and timing, and on avoiding human counting errors. A second method makes use of point-of-sale data or, more specifically, scanner data. Based upon historical sales data, the latency period between sales is taken as a gauge of whether an item is on the shelf. It is a preferred method for investigating fast-selling retail items, such as soda cans. Out-of-stocks may also be identified by using inventory data, depending on its accuracy. Finally, various types of technology, such as radio-frequency identification, shelf stoppers and weight or light sensors, can be used. However, these technologies are so far not equipped to monitor the condition of the retail items (e.g. undamaged labels).
- Gruen, Thomas W. and Daniel Corsten (2008), A Comprehensive Guide to Retail Out-of-Stock Reduction in the Fast-Moving Consumer Goods Industry, Grocery Manufacturers of America, Washington, DC, ISBN 978-3-905613-04-9. http://itsoutofstock.com/wp-content/uploads/2013/04/OOS-Guide-2008-Revision.pdf
- Aastrup, J. and Kotzab, H. (2010), "Forty years of out-of-stock research – and shelves are still empty", International Review of Retail, Distribution & Consumer Research, Vol. 20 No. 1, pp. 147-64.
- Gruen, Thomas W., Daniel Corsten and Sundar Bharadwaj (2002). Retail Out of Stocks: A Worldwide Examination of Causes, Rates, and Consumer Responses. Washington, D.C.: Grocery Manufacturers of America. http://itsoutofstock.com/wp-content/uploads/2013/04/GMA_2002_-Worldwide_OOS_Study.pdf
- McKinnon, A.C., Mendes, D. and Nabateh, M. (2007), "In-store logistics: an analysis of on-shelf availability and stockout response for three product groups", International Journal of Logistics: Research and Applications, Vol. 10 No. 3, pp. 251-68.
- Rajaram, K. and Tang, C.S. (2001), "The impact of product substitution on retail merchandising", European Journal of Operational Research, Vol. 135 No. 3, pp. 582-601.
- Campo, K., Gijsbrechts, E. and Nisol, P. (2003), "The impact of retailer stockouts on whether, how much, and what to buy", International Journal of Research in Marketing, Vol. 20 No. 3, pp. 273-86.
- EMFI (2008), Consumer Trends, Leusden, The Netherlands.
- Zinn, W. and Liu, P.C. (2008), "A comparison of actual and intended consumer behavior in response to retail stockouts", Journal of Business Logistics, Vol. 29 No. 2, pp. 141-59.
- Sloot, L.M., Verhoef, P.C. and Franses, P.H. (2005), "The impact of brand equity and the hedonic level of products on consumer stock-out reactions", Journal of Retailing, Vol. 81 No. 1, pp. 15-34.
- Ehrenthal, J.C.F., Gruen, T. W., & Hofstetter, J. S. (2012). Value-attenuation in distribution networks: Insights from a service dominant-logic perspective on retail out-of-stocks. Presented at 2012 AMA Winter Marketing Educator’s Conference, St.Petersburg, FL, USA. http://itsoutofstock.com/wp-content/uploads/2012/02/WE_AMA2012_Vale-attenuation_EhrenthalGruenHofstetter.pdf
- Ehrenthal, J.C.F., & Stölzle, W. (2011). Improving On-Shelf Availability Through Store-Level Root Cause Analysis: LOG-HSG.
- Papakiriakopoulos, D., Pramatari, K. and Doukidis, G. (2009), "A decision support system for detecting products missing from the shelf based on heuristic rules", Decision Support Systems, Vol. 46, pp. 685-94.
- Raman, A., DeHoratius, N. and Ton, Z. (2001), "Execution: the missing link in retail operations", California Management Review, Vol. 43 No. 3, pp. 136-52.