Wouldn't it be nice if a technology was developed that could identify shoplifters as they enter a store instead of as they leave? Then store personnel could spot the "bad guys" before any merchandise is stolen. Impossible, you say? Probably.

But, a growing number of retailers are apprehending shoplifters and keeping detailed records on who they are, and on what, where and when they are most likely to steal. The idea is to establish some basic profile and trend information that can be used to pinpoint theft occurrences and either confirm or debunk the notion that "everyone is a potential thief."

According to the National Retail Security Survey, U.S. retailers have lost an average of about $8 billion per year to dishonest customers. This amount would be far higher if it weren't for anti-theft systems such as EAS and CCTV. Each year, well over 1 million shoplifting incidences are reported to the local law enforcement. It is estimated that less than half of all known incidences are reported.

Most retail loss prevention experts believe that the number of successful thefts dwarfs those that are reported! When a typical shoplifting apprehension occurs, the loss prevention agent completes a case document which includes some standardized information on the thief, such as gender, age and race. Additionally, the month, day of the week and hour of the incident are recorded, as are the type and amount of merchandise recovered.

This basic information can be fed into a computer and sorted. If the data set is large enough, an informal "profile" of a typical theft occurrence can be formulated. A retail chain can use its own case data to provide assistance in its loss prevention efforts. Suppose the data collected for a department store suggests that 25% of all cases involves a Caucasian female in her twenties, who steals blouses from the Juniors' Department on Fridays between 4 and 6 PM? It makes sense to deploy extra security personnel, sales associates or other anti-theft measures that place at that time, doesn't it?

National Data Within the past couple of years, a large national database for shoplifting incidence reports has been established by Read Hayes, the noted loss prevention consultant. It is the largest known collection, containing 171,141 reports from 171 different retail chains and over 21,000 branch stores. A wide variety of retail vertical markets are included. The most data comes from the Groceries/Supermarkets category, with 49 companies in the sample. The Drug Stores category is next, with 16 reporting companies. Following those segments, are Home Centers/Hardware stores, with 15 reporting companies; Fashion Merchandise, with 13 companies; and Department Stores and Discount Stores with 12 companies each.

Even though this may be an impressive amount of raw data, the study is intended to provide guideline information rather than ironclad statistical facts. There are a few of "caveats" that should be described. First, since many shoplifters are successful, the data is incomplete. Successful shoplifting incidences usually cannot be reported in detail. Second, retailers generally schedule loss prevention people for specific hours. It makes sense that most apprehensions would occur during the hours when floor detectives are scheduled. Who knows how many successful thefts occur at other times? And third, the data is skewed toward the retail segments that supplied the most information. So, the database is imperfect, but as Read Hayes noted "our contention remains that some data is better than no data. At least it provides a place from which to begin."

Who Steals?

Normally, the type and style of merchandise sold by a retailer "dictates" the gender of most customers. Men are the typical customers in auto parts stores, and women frequent supermarkets more regularly. The study indicates that 55% of apprehended shoplifters were men, 44% were women, and about 1% of the cases supplied no gender.

It is noteworthy that the study also suggests that female thieves steal more per incident than men do. A little over 60% of all apprehended shoplifters were adults (18 years old or over). About 75% of the entire U.S. population are adults. Of the adult thieves, about 52% are between 18 and 30 years old; 45% are between 31 and 65 years old, and 3% are over 65.

The juvenile statistics are very interesting. Almost 1/3 of all apprehended shoplifters were between the ages of 13-17. This age group represents only about 7% of the U.S. population. Teenagers tend to steal things that they either can't afford or are prohibited from buying, such as recorded music, cosmetics, stylish apparel, tobacco products and consumer electronics.

Most shoplifters (about 41%) were recorded as Caucasian, while African Americans accounted for about 29%, Hispanics about 44% and Asian Americans about 1%.

What is Stolen?

Nationally, the most frequently stolen items (at least those confiscated from shoplifters) are tobacco products, athletic shoes, brand name apparel, designer jeans and intimate apparel, health & beauty aids, videos & compact discs.

It is well documented that shoplifters target merchandise either for their own consumption or for a quick conversion to cash, so the items most frequently stolen tend to be expensive and in high demand. The study indicates that the average amount of theft per incident was $56.67, but the statistics probably have more relevancy when examined by retail vertical market.

For example, the average theft in a drug store was $3.68, but in a consumer electronics/computer store the number jumped to $412.97!

Where and When?

When viewed on a monthly basis, and compared to sales by month, shoplifting is a "year around" activity. The national statistics showed that March and December experienced the highest amount of apprehensions—about 10% each. In contrast, the months of January and September experienced the lowest number of apprehensions—about 7% of the total. The other eight months were consistently in the 8% range.

Almost 18% of all apprehensions took place on Saturday. About 15.4% occurred on Friday, and the other five days ranged between 13 and 13.6%. This indicates that thefts take place anytime, with "amateur hour" occurring on the weekends.

The data on hourly activity is probably skewed a bit because most stores are not open around the clock. It is no surprise that less than 1% of the apprehensions occurred between midnight and 6 AM. Only 9% occurred between 6 AM and noon. About 55% of the theft apprehensions took place between 2 PM and 8 PM, with about 32.5% occurring between 2-6 PM.

Conclusions According to the experts who analyzed this data, it remains clear that shoplifting continues to be a year-round activity, perpetrated by almost anyone at any hour of the day and night. The data indicates that, "pound for pound", juveniles (ages 13-17) engage in an alarming amount of thievery compared to their proportion of the general population.

Our society is data-driven. Studies of this nature can be instrumental in both isolating shoplifting problems and calling attention to the need for more effective solutions—sociological as well as technological. Judging by these statistics, we all have work to do before the shoplifting problem is solved.