Retail Loss Prevention

Topics: Regression analysis, Retailing, Data mining Pages: 12 (2550 words) Published: October 12, 2010

Retail Loss Prevention: Doing more with Analytics

February 2009 DRAFT


he retail industry is in the middle of an unprecedented economic crisis. All retailers are trying to figure out how to cut costs, retain customers, conserve cash and more importantly stay in business. Recently, the National Retail Federation (NRF) polled readers of its SmartBrief asking them what was on top of their mind. Loss Prevention (LP) came in second only to the overall economy! It is no surprise given that every dollar saved from retail shrink is a dollar added directly to the bottom-line. Looking back in history, we have seen tough times like these are conducive for higher shrink numbers. This is mainly due to retailers cutting down loss prevention staffing and store personnel, slowdown in technology investments, and increase in theft owing from people who cannot handle the economic pressure. LP organizations are at different stages of evolution when we look at their capability to harness the power of analytics – From basic reporting on shrink to understanding the key drivers with high correlation to shrink and managing by exception with the help of predictive models. There is a need to utilize available data assets effectively by building capabilities to report, analyze and predict shrink accurately. This article reviews the trends in retail shrink, its sources and how analytical techniques can help attack shrink in a cost effective manner.

Retail Shrink Trends
Global retail shrinkage, inventory losses from crime or waste, cost retailers approximately $104.5 Billion last year, or 1.34% of sales1. In North America, shrink totaled $42.3 billion, or 1.48% of sales, with the US accounting for a significant portion of this figure. North American retailers spent $12.3 Billion, or 0.43% of sales, last year to fight shrink. Majority of the loss prevention budget goes towards payroll (LP corporate and field personnel) and systems like CCTV, Electronic Article Surveillance (EAS) & Point of Sale (POS) software to detect fraud.

Figure 1: 2008 Global Shrink by Region: $104.5 billion
[pic] 1. Source: 2008 Global Retail Theft Barometer Figure 2: Sources of Shrink As Reported By U.S. Retailers
2. Source: 2007 National Retail Security Survey

The reported sources of retail shrink have been consistent over the past several years2. Loss Prevention (LP) executives in the US believe employees account for 44% of the shrink dollars followed by shoplifters at 34%. Retail shrink has been declining in recent years compared to the early 90s. Although this is self-reported survey data3, we still can directionally infer that shrink rate has been declining. The total dollar loss; however, has been rising due to industry growth. Although the latest shrink rate is at an all time low at 1.44%, several LP executives fear that this trend may reverse due to factors like rising unemployment, budget cuts in LP and pressure to drive top-line sales.

Figure 3: U.S. Retail Shrink Trend

3. Source: 2007 National Retail Security Survey

Common Loss Prevention Programs

Retailers use a variety of LP programs to combat shrink. These programs include screening employees before hiring, LP awareness programs, code of conduct training, asset control policies, standard operating procedures and several system implementations. The framework in Figure 4 outlines the overall objectives of loss prevention teams and how analytics fits in. The LP programs are implemented to meet three main objectives of any LP organization.

1. Deter: Objective here is to prevent the loss from happening in the first place. Given employees account for the largest portion of shrink dollars, it makes sense to put programs in place to screen candidates for integrity before hiring them, train them on asset control policies and make the employees aware of LP programs. Theft deterrents like alarms, signs and live...
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