Data-Driven Answers to Law Enforcement Staffing Considerations
Whether your goal is to maximize community and officer safety, justify your current staffing level, or explain the need for increased staffing, the task requires thought, data, precision, and transparency. Efficient and effective police officer staffing and scheduling should avoid speculation and assumptions about critical issues like personnel deployment. It should be based on data and stated organizational goals and objectives. We should not expect our policing experience and intuition to provide all the answers. This will be critical in the future as police agencies are increasingly asked to justify budgetary requests and there is community pressure to not over or under police the people the police are sworn to protect.
Just a few of the typical questions about policing staffing issues police leaders are likely to face now, and certainly in the future, include:
What will happen to your response times if the county or city gives you funding for more officers?
Where would you put them?
What shift should they work to be the most effective, and does the current scheduling ensure that your supply of officers/deputies meets community expectations for policing service?
Do you schedule your officers on 5/8, 3/12, 4/10, 9/80, or a combination thereof?
How is unallocated officer time currently used and how will it be used in the future if you are allocated more officers/deputies?
Does understaffing lead to longer response times?
What day of week or time do we see this as the most significant threat?
If we are facing the possibility that we do not have an available officer to send to a call, can we shift the schedule to avoid this?
If your agency budget is reduced, and the number of officers/deputies is reduced, what is the impact on service levels and response times?
Can you do this and maintain officer safety?
These were just some of the questions my agency was seeking answers to. We turned to a data-driven approach to assist.
Answering these questions became my task, and a custom application called Schedule Optimizer was the solution. Since the early 90’s, my Agency worked with GeoSpatial Technologies (GST), a company based in Tustin, California, to solve many law enforcement analytical needs. GST built our GIS mapping system, an interface with Parole Leads, scripts to cleanse our data, and a geocoding protocol that cut the time analysts spent fixing addresses that failed to map automatically. We also took advantage of their state-of-the-art Intelligence Database System called IntelNexis. Given all of the support GST had provided in the past, this new project was not an odd request. Working closely together over the following months, the application Schedule Optimizer became the tool that filled the gaps in our knowledge and allowed us to articulate our staffing needs in an easy-to-understand manner.
Like the process of creating anything, lessons are learned along the way. It is crucial to comprehend the data that your Agency gathers and, if necessary, be open to making the required changes in data collection to ensure the accuracy of your findings.
The following are a few upfront considerations we worked through, and you should too, when you consider implementing such a system:
With the board of supervisors or the city council's preferred endorsement, the Agency sets and hopefully mutually agrees upon minimum staffing safety requirements, definitions, and concepts.
Access to specific data points is vital to the most complex analysis. These data points include access to an in- house scheduling database, spreadsheet, or third-party application. Agency Web handled our scheduling needs, and GST built a link to access the most up-to-date information needed for each query. The application tapped into every data source we had, including CAD, Call History, and RMS data. Schedule Optimizer reflected the actual workload of our officers by not only calculating the time committed of an assigned officer but also looking at the time commitment of the backup officers. To do this, time stamps for Call Received, Call Pending, Call Dispatched, Arrival Time, and Cleared Times for every officer on a call become vital to the final answers. Call History data plays a crucial role in understanding historical trends and fills in the blanks of the missing information needed.
You will need to be able to explain outliers and how to deal with them. Outliers can include "on sight activity," calls that changed priority in the middle of the call, and justifiable calls that pended for long periods.
Determine the types of reports/queries you will need, how they will look, and whether you can quickly change parameters on the fly to answer specific questions based on the priority of the call or other factors.
Some of the critical reports applications like Schedule Optimizer should include are:
Response Time Report: This report shows the average response time to the total number of officers on duty during the selected time range. It calculates the average time duration between the incident received and arrival times and estimates how much a given increase in officer count will decrease the average time duration. Data is shown according to the selected priority level.
Available Time Report: The average time an officer is not on a call per day of the week. This is calculated as the time between the closure of a call and the next assigned call.
Travel Time Report: This depicts the average travel time from dispatch to arrival. It estimates how much a given increase in officers would decrease the average travel time. This assumes the more officers you have, the greater the likelihood you will be able to respond to calls faster, thereby decreasing travel time.
Unavailability Report: This shows the average percentage of calls by priority and by day of the week when there is no available unit to respond. It also shows the time duration between the incident being received and dispatched and the percentage of time the call went beyond the selected time frame.
Workload Report: This report shows the average number of calls received by hour, weekday, month, or pay period according to the selected priority level.
Uncommitted Time Report: This report shows the average uncommitted time per day of the week for each officer on duty during the selected time range by calculating the average time between the last incident closed and the next incident dispatched. The maximum consecutive uncommitted time selection allows the user to choose the maximum duration between the last incident closed and the next incident dispatch time to avoid calculating between shifts or across multiple days for a particular officer.
Below is a screenshot that is a typical report generated by Schedule Optimizer. This one displays the delay from the time calls are received by dispatcher personnel and when they were dispatched to officers/deputies. It provides a visual reference for the power of the application.
Schedule Optimizer may be a consideration if your Agency needs to better understand, and answer questions about, staffing, shift scheduling, improving response times, the benefits of additional officers, or the effects of eliminating positions. If you want to know more about this application, contact Dr. Hong Chou at GeoSpatial Technologies at (714) 871-7033.
Note: The FPI received no compensation from GeoSpatial Technologies for this article.
About the author: FPI Fellow Brian Gray has more than 30 years experience in the world of crime and intelligence analysis and is retired from the Riverside County Sheriff’s Department (CA). He is the president of the Association of Law Enforcement Intelligence Units Foundation and is the Training Advisor to the executive Board of the Association of Law Enforcement Intelligence Units (LEIU). To read his full bio click here.