Organized Retail Crime: Understanding and Mitigating the Risks with Geospatial Analytics

With more than a million apprehensions worth over $159 million annually, shoplifting is a significant problem affecting the retail industry (Jack Hayes International, Inc., 2015). While the numbers are staggering, there are other more hidden costs as well. Specifically, research suggests the retail industry loses an estimated $11 billion annually due to shoplifting (Hollinger & Adams, 2011). Shoplifting not only affects retail establishments but also affects law enforcement with 1.2 million reports/responses annually (Federal Bureau of Investigation, 2015). Yet, while shoplifting is a significant and costly challenge, it is dwarfed in terms of scale and severity by another more pervasive form of criminal activity: organized retail crime.

While similar in practice, organized retail crime or ORC is distinguished from shoplifting by intent. For example, ORC is primarily committed to convert the stolen or fraudulently obtained goods into financial gain while a shoplifter steals primarily for personal use. In addition to intent, ORC is further distinguished through the methods of operation and quantity or value of the targeted goods. For instance, ORC typically involves the theft of large quantities of products by a group of criminals in a coordinated effort while shoplifting is typically committed by a single person taking a small amount of product (National Retail Federation, 2013).

Though there are many ways to convert stolen wares into financial gain, working through a fence is one of the most common. Fences are stolen goods dealers who operate behind the guise of a legitimate business. Fences are central figures in ORC schemes by recruiting thieves and providing “shopping lists” of the types of items they want for their stores. Though some inexperienced thieves attempt to act as their own fence by selling stolen items out of the back of a car or on a street corner, professional ORC groups often operate through an eCommerce or physical storefront “fence.”

Secondary market research indicates fences are classified into one of three levels. In a Level 1 scenario, a thief sells stolen product to a storeowner or second level broker (i.e. pawn shop, flea market, or corner store). The storeowner then sells the goods within the business to unsuspecting consumers or to another fence. In contrast, a Level 2 Wholesale fence buys goods from a Level 1 fence and repackages the goods to make them appear as if they came from the original manufacturer. While the first two are subversive, a Level 3 fence is particularly insidious because not only do they receive goods from a Level 2 Wholesale fence but they sell the goods back to legitimate merchants which can result in a retailer unknowingly buying back the same goods that were originally stolen from their own stores (Sutton, 2010).

Though difficult to quantify, estimates suggest ORC is pervasive and prevalent with financial impacts to retail ranging from $30 to $37 billion in annual losses (Federal Bureau of Investigation, 2007), or about three times that of shoplifting. Though the direct financial impact to retailers is substantial, the true cost of ORC extends beyond the walls of a store. Reduced inventory resulting from products that are no longer on the shelf because of theft means consumer demand cannot be met. The inability to meet economic demands has a trickle-down affect across the economy.

For example, the lack of available product at a legitimate business means a taxable sale was not made. The non-sale affects not only profits but it also impacts tax coffers. Estimates suggest government taxing authorities fail to collect approximately $1.6 billion annually because of sales lost due to ORC (Coalition Against Organized Retail Crime, 2007). On a more granular level, consumers are negatively impacted through higher costs, approximately $400 annually for an average household, because retailers are forced to raise prices to compensate for the lack of sales on popular ORC items (Checkpoint Systems, 2013). Across the long term, depressed inventory levels and inflated prices are detrimental to the overall health of the economy.

While ORC’s financial implications are substantial, other risks are also present. For example, ORC products often end up back in the marketplace via a fence. Repackaging or improper handling of ORC items (i.e. over-the-counter medications or other perishable items) during the fencing process means unsuspecting consumers can potentially be exposed to expired or hazardous goods during a resale. Exposure to unsafe products can lead to illness or other personal injury (National Retail Federation, 2013). The risk of exposure to unsafe merchandise through the resale of stolen items is of particular concern to retailers and product manufacturers who are focused on maintaining the integrity of their brand.

Retailers of all sizes are victimized by ORC (National Retail Federation, 2013). Walmart, the world’s largest retailer with more than 11,500 stores operating under 65 banners in 28 countries, offers a unique operational environment (Wal- Mart Stores, Inc., 2016). Due to its scale, Walmart is at particular risk of being impacted by ORC. In response to the threat, Global Investigations was formed to proactively identify and mitigate the most significant risks through conducting investigations and leveraging analytics. One of the primary tools utilized by Global Investigations in the fight against ORC is geospatial analytics. Through geospatial analytics Global Investigations is able to identify areas at risk, assess the impact of a fence, and disrupt serial offenders.

Identifying the Risks

To identify ORC, it is imperative to understand which items area at risk. Research suggests the most commonly stolen goods are Concealable, Removable, Available, Valuable, Enjoyable, and Disposable or CRAVED (Gill, 2004). Using the CRAVED model, items at risk for ORC activity can be identified. Understanding consumer demand for popular products also helps identify ORC items. While new products always come to market, certain items remain a staple of ORC. Cigarettes, energy drinks, infant formula, over-the-counter medicine, diabetic testing strips, razors, and electronics are commonly impacted by ORC due to their high resale value and demand (National Retail Federation, 2013).

Once potential ORC items have been identified, Global Investigations can conduct research to determine negatively affected areas. Using transactional databases to search inventory and product sales, discrepancies can be identified and scored accordingly. Geospatial analytics allows the analyst to visually identify emerging patterns that may indicate ORC activity is occurring. Moreover, third-party data (i.e. crime or demographics) can be overlaid to further enrich the analytical product.

Figure 1 illustrates how low inventory levels (elevated points) of a popular ORC item can be combined with third-party data (high retail density areas) to highlight stores at risk. By using geospatial analytics in conjunction with inventory data, an analyst can focus on the highest risk locations.

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Assessing a Fence

As discussed, a fence is a central piece of the ORC equation. Through directed thefts of CRAVED items, a fence can significantly impact stores in the area. Leveraging various investigative techniques (i.e. open source intelligence, field surveillance, and offender interviews), Global Investigations is able to develop leads into suspected fencing locations. However, simply identifying a possible fence is only the first step and determining the potential impact of that fence and documenting losses becomes imperative.

One way Global Investigations assesses the impact of a fence is by leveraging geospatial analytics in conjunction with statistical tests. By integrating intelligence about the fence and the types of stolen products, Global Investigations can research inventory levels and/or sales of those items. Geospatial analytics allows the analyst to identify stores within a given range of the fence and compare inventory levels of the items in question to stores outside of the range of the fence. Statistics can then be leveraged to determine if there is a significant difference between inventory levels of the items at stores near the fence in comparison to stores out of range. While not conclusive in terms of causality, this technique does establish a possible correlation between the fence and corresponding inventory levels at nearby stores. Figure 2 illustrates store inventory levels on a popular ORC item (elevated points) in relation to suspected fences (green circles).

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Disrupting Serial Offenders

Wolfgang et al. (1972) found that a relatively small number of offenders were responsible for a majority of crime. Building upon this assertion, Global Investigations has developed strategies to identify and disrupt serial offenders in an effort to make the most significant impact against organized retail crime. By leveraging the fundamentals of tactical crime analysis (i.e. temporal analysis, hotspot analysis, sequential movements, etc.), Global Investigations is able to mitigate the impact of serial offenders by directing resources to the most at-risk locations at the appropriate times to either deter activity or facilitate an apprehension when applicable.

Once a serial offender or an organized group working in conjunction with one another has been identified, Global Investigations analysts utilize tactical crime analysis techniques to analyze affected locations and identify patterns. Additionally, a forecast for possible future targets can often be formulated based upon previous activity in the series. Local resources can then be directed toward at-risk facilities in an attempt to mitigate the problem through deterrence, apprehension, or intelligence gathering. Figure 3 is an example of how Global Investigations analyzes the movements of a serial offender and formulates projections for where the next event in the series may occur.

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In conclusion, organized retail crime is a significant risk affecting not only Walmart, but the retail industry as a whole. Left unchecked, ORC has the potential to significantly impact retailers in ways beyond a line on a profit and loss sheet by injecting doubt and risk into the minds of consumers who trust the safety and quality of the products they are buying. Walmart has recognized these risks and the Global Investigations team actively works to mitigate them. Geospatial analytics is a powerful tool and allows Global Investigations to mitigate the loss of company assets and reduce reputational harm as a result of ORC.

References

Checkpoint Systems. (2013). Global Retail Theft Barometer finds shrink cost retailers $112 billion, averaging 1.4 percent of sales. Retrieved January 31, 2016, from http://www.checkpointsystems.com/ en/About/press-releases/2013/GRTB_2013_US.aspx

Coalition Against Organized Retail Crime. (2007). Hearing of organized retail theft prevention: Fostering a comprehensive public-private response. Retrieved from Food Marketing Institute website: https://www.fmi.org/docs/testimonies/ orctestimony.pdf?sfvrsn=0

Federal Bureau of Investigation. (2007). Fighting organized retail theft: New initiative to tackle the problem. Retrieved January 31, 2016, from http:// www.fbi.gov/news/stories/2007/april/retail040607

Federal Bureau of Investigation. (2015). Crime in the United States, 2014. Retrieved February 1, 2016, from https://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2014/crime-in-the-u.s.-2014/cius-home.

Gill, M. (2004). The illicit market in stolen fast-moving consumer goods: A global impact study. Perpetuity Research and Consultancy International.

Hollinger, R., & Adams, A. (2011). National retail security survey: Final report. Retrieved from University of Florida website: http://www.clas.ufl. edu/users/rhollin/srp/srp.html.

Jack Hayes International, Inc. (2015). 27th Annual retail theft survey. Retrieved from http://hayesinternational.com/wp-content/ uploads/2012/01/27th-Annual-Retail-Theft-Survey- Jack-L.-Hayes-Intl-1.pdf

National Retail Federation (2013). Organized retail crime survey. Retrieved from

https://nrf.com/resources/retail-library/2013-organized-retail-crime-survey.

Sutton, M. (2010). Stolen Goods Markets. Washington, DC: U.S. Department of Justice, Office of Community Oriented Policing Services.

Wal-Mart Stores, Inc. (2016). Our Story. Retrieved January 31, 2016, from http://corporate.walmart. com/our-story

Wolfgang, M., Figlio, R., & Sellin, T. (1972). Delinquency in a birth cohort. Chicago, IL: University of Chicago Press.

Scott Peacock

Scott Peacock has over 14 years of crime analysis and investigative experience in diverse areas to include both the public and private sector. Scott is currently a Senior Intelligence Analyst with Walmart Global Investigations and is based out of Bentonville, Arkansas. Scott provides advanced analytical support to mitigate loss and risk associated with organized retail crime and fraud across Walmart business units to include eCommerce, Health & Wellness, International, and over 5,000 Walmart stores and Sam’s Clubs throughout the United States. Prior to beginning his career with Walmart, Scott served as a crime analyst with the Scottsdale, AZ, Police Department and worked on a variety of projects, including tactical analysis of serial offenders, intelligence analysis, strategic planning, administrative reporting, citizen outreach, and crime prevention. Scott also had the privilege of serving on the Board of the Arizona Association of Crime Analysts as the Vice-President, where he worked to provide professional development opportunities for association members. Scott is a member of numerous industry associations to include the International Association of Crime Analysts, and is a three time winner of the association’s annual Crime Mapping Award. Scott holds a Master’s in Education from the University of Georgia along with a Master’s in Public Administration, a Bachelors of Science in Administration of Justice, and a Bachelors of Arts in Integrative Studies from Arizona State University.

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