Crime Analysis for Problem Solvers in 60 Small Steps

A very important principle of crime prevention is that crime is highly concentrated on particular people, places, and things. This suggests that focusing resources where crime is concentrated will yield the greatest preventive benefits. These concentrations (dealt with in more detail in later steps) have attracted labels that are becoming well known to most crime analysts:

• Repeat Offenders In Wolfgang's famous Philadelphia cohort, about 5 percent of all offenders in the study were responsible for more than 50 percent of the crimes.
• Repeat Victims According to the British Crime Survey, repeat victims (just over 4 percent of all victims) endure 40 percent of the crimes reported in the survey (see Step 29).
• Hot Spots In the landmark paper that put this concept on the map, so to speak, Lawrence Sherman and colleagues found that 6 percent of the addresses in Minneapolis accounted for 60 percent of the calls for police service.
• Hot products Annual data produced by the Highway Loss Data Institute show that theft claims for some automobile models are as much as 30 times greater than for other cars (see Step 31).
• Risky Facilities In Danvers, Massachusetts, 3 out of 78 stores (5 percent) accounted for 55 percent of shoplifting incidents reported to the police (see Step 28).

This kind of concentration is not peculiar to crime and disorder, but is almost a universal law. A small portion of the earth's surface holds the majority of life on earth. Only a small proportion of earthquakes cause most of the earthquake damage. A small portion of the population holds most of the wealth. A small proportion of police officers produce most of the arrests.

This phenomenon is commonly called the 80-20 rule, where in theory 20 percent of some things are responsible for 80 percent of the outcomes. In practice, it is seldom exactly 80-20, but it is always a small percentage of something or some group involved in a large percentage of some result. The table shows this rule in practice. It reports an analysis made by Stacy Belledin of construction site thefts and burglaries for 55 homebuilders in Jacksonville, Florida. Eleven of the builders (20 percent of the group) experienced between them 85 percent of all the thefts and burglaries at construction sites reported to the Jacksonville Sheriff's Department during January-September 2004.

In investigating any problem, you should therefore always ask if the 80-20 rule applies. A simple six-stage procedure shows how to answer this:

1. Make a list of the people, places, or products, with a count of the number of events associated with each of these.
2. Rank order them according to the number of eventsassociated with each - most to least.
3. Calculate the percentages of the events each person, place, or product contributes. In the table, there are 386 incidents of theft and burglary. Sixty of these incidents (15.5 percent) occurred at construction sites owned by Builder 1.
4. Cumulate the percentages of incidents starting with the most involved person, place or product (or in this example, home builders).
5. Cumulate the percentages of the people, places, or products (in our example, the cumulative percentage of home builders in column 5).
6. Compare the cumulative percentages of people, places, or products (column 5) to the cumulative percentage of outcomes (column 4). This shows how much the most involved people or places contribute to the problem.

These kinds of calculations can be very helpful at the scanning stage in directing preventive effort. Thus, in the Jacksonville example, just five builders experienced more than 50 percent of the incidents. In theory, focusing preventive action on these five builders, rather than on the total group of 55, could be a very efficient strategy for reducing the city's overall problem of theft and burglaries in construction sites.

At the analysis stage, these kinds of tables can help in determining if there are important differences among people, places, or products at the top and those at the bottom of the list. In our example, Stacy Belledin found that an approximate measure of the numbers of homes built correlated fairly well with the numbers of thefts and burglaries experienced by each builder, but it did not explain all the differences in risk. Other possibly important sources of these differences could be the neighborhoods where builders were operating, their police reporting practices and their standard security precautions.