Retail Loss Prevention
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Retail Loss Prevention: Doing more with Analytics
February 2009 DRAFT
Abstract
T
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
Retail Loss Prevention: Doing more with Analytics
February 2009 DRAFT
Abstract
T
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