When managers and leaders want to know what is common or what is average when thinking about a particular problem, they refer to statistics to reach some type of conclusion. The conclusions reached in a statistical analysis can be represented visually by seven common charts. These charts are: (1) Pareto diagram or bar graph; (2) pie chart or circle graph; (3) histogram; (4) stem-and-leaf plot; (5) dot plot; (6) scatterplots; and (7) time-series graphs. Using the correct graph or chart when presenting a course of action or requesting funding can make the difference between a “yes” and a “no” answer and people understanding what you are saying and your point getting lost.
I have attended community meetings, briefings by senior executives and meetings by city and county councils and am always struck by the lack of statistics and PowerPoint presentations with the proper statistical graph or chart by the presenter. In most cases, the presenter is asking for funding for more personnel or equipment and then becomes disappointed when their request is denied. Whether at the executive level or the mid-management level, the importance of using statistics cannot be stressed enough and seems to be downplayed by leaders.
When used correctly, statistics can help an organization become more proactive by identifying trends in crime and criminal activity.
When I retired from the U.S. Army Military Police Corps and started working at the sheriff’s department, I was immediately curious at how patrol assignments were planned for the patrol deputies. Police departments seldom have a statistician and would have to rely on the statistician used by the city or county to obtain a statistical analysis if they wanted one. Obtaining an analysis can also be time-consuming since there is most likely a line of people waiting on their statistical analyses. When I first started out in the sheriff’s department, information was passed down from shift to shift via a log book the patrol supervisor would write in. Unfortunately, information wasn’t always passed down or was specific. Deputies basically reported for work and then went out to patrol their assigned district. Working in this fashion always assures an organization of working in a reactive posture because criminal activity has to be reported by a witness or victim. When used correctly, statistics can help an organization become more proactive by identifying trends in crime and criminal activity.
Soon after I began working patrol, a rash of burglaries in a particular section of a patrol district occurred and the assigned deputy was simply told to stay observant and patrol the area of reported burglaries of his district more often, despite the fact his patrol area was the size of a small city. Because of the number of burglaries, and because I felt deputies would be like flies wandering the desert hoping they would just happen to get lucky to catch someone, I took the initiative and found a clerk typist willing to learn something new and do an analysis for me. I asked the typist to review each burglary report in that patrol district for a particular period of time and to write down the time period in which the burglary was reported to have occurred and to write down the address of each burglary. I then asked the typist to have the computer generate the median and mean time for the burglaries and to use a cluster chart to map the locations. The result of the data gave me the most likely times for the burglaries (between 2:30–3:30 a.m. and 4–5:30 a.m.) so I knew at what time I should be in that neck of the woods, and the cluster chart showed me where the highest density was on a map so I knew what neck of the woods I needed to be in.
I had a similar problem in 1985 while working as a Military Police investigator. I was new and had worked on this post for four months before being assigned as a supervisor to the Investigations Section. My first task by the provost marshal after reporting to duty was to investigate and stop a rash of car burglaries, which I learned had occurred for the previous five years in one particular large parking lot and would ebb and wane. While speaking to the executive secretary, I mentioned the task and wondered if a statistical analysis could be done. The secretary told me that she could compile statistics and we planned for the analysis. As mentioned above, I obtained the most likely time of day and night, on what days of the week they most often occurred and during what months they occurred most often. I assigned investigators and participated in the surveillance using the statistical analysis. According to the analysis, we were lucky and were in the time frame for the burglaries, so we began our surveillance on the parking lot. We surveilled the area for five days, when, after the first hour on the early morning of the sixth day, we made several apprehensions (Military Police does not arrest). The result of our investigation was we identified and stopped a burglary ring operating out of a nearby city, identified and stopped several soldiers acting on opportunity and identified and stopped a prostitution ring no one knew about.
We repeated our procedure in several other areas on post with smaller results, but our efforts resulted in car burglaries in the targeted parking lot ceasing for about five months, and car burglaries on post falling by approximately 73%. Statistics allows me to go further, and if I had wanted to, I could have identified a particular make, model and color of vehicle most likely to be stolen or burglarized. I could have also identified the type of soldier most likely to commit a car burglary simply by using the information of those apprehended for the offense (age, race, rank, job specialty, time of service and time assigned to the post). The reality is, when an officer or their leadership uses their imagination, statistics can astound you with the results.
Whether at the executive level or the mid-management level, the importance of using statistics cannot be stressed enough.
CompStat is analytical software developed by the NYPD to take the guesswork out of the equation, and its use is beginning to become more common as law enforcement agencies become aware of it. Research has shown that there are limitations and pros and cons to CompStat, and that not everyone is pleased with it, but it is a tool nonetheless to be considered. The bottom line is, whether an organization uses CompStat or other software or a statistician, law enforcement can become more proactive than reactive when patrolling the streets, conducting an investigation or asking for more funding.
As mentioned above, statistics can aid in predicting the type of vehicle most likely to be stolen or burglarized. It doesn’t hurt an organization to periodically select an area, say an airport, and see how many stolen vehicle reports have been taken over a selected period of time because they may identify a problem. Statistics could then help determine the type of vehicle most likely to be stolen, what month(s), time(s) of month, what day(s) of the week and time(s) of day(s) the crime is most likely to be committed. Statistics can also indicate if the criminals have adjusted to the enforcement.
We can further the logic in burglaries. An organization can categorize burglaries as home, commercial property, vehicle and RV and have every report input into the program. Over a period of time, clustering becomes more definitive so the patrol areas become more precise. The type of home or commercial property becomes more defined and can be targeted by LEOs for patrolling and crime-prevention techniques, such as courtesy home or commercial crime prevention inspections. In time, these courtesy inspections will become more popular and more important to the owner since these inspections help mark valuable property upon request and create a list of valuable property for identification in case they are stolen.
The predictive value of statistics when used to predict criminal trends can also be valuable. I recommend coordinating and working in conjunction with a knowledgeable statistician because they have the experience and educational background to aid leaders in delving deeper into the construct and getting full use of what statistics can do to maximize the results. When used correctly, statistics can help identify when and which type of scams may become prevalent and identify what type of scam a scam may mutate into.
In essence, statistics can be a valuable and powerful tool for law enforcement, and though statistics does have limitations, the true limitation is the level of creative thinking by the user.