Predictive Policing Is a Trend That Uses

Predictive policing is a trend that uses technology to predict hot crime spots and send police to the area before a crime is committed. By using data mining and crime mapping, police are deployed to areas based on statistical probability and geospatial predictions. This technology is based on the same technology used by businesses to predict sales trends and customer behavior patterns. Now, police departments can use the same technology to predict crime patterns and work to reduce crime in their area.

Predictive policing is putting officers where crimes are more likely to occur. "…it generates projections about which areas and windows of time are at highest risk for future crimes by analyzing and detecting patterns in years of past crime data." (Goode) The data mining generates projections using past crime data to analyze which areas and the time of the day, week, or month, etc. that crime is likely to be committed. The projections are recalibrated daily as new crimes are committed and updated information is added to the data base. It provides information to make decisions in coming up with solutions to better fight crime before it takes place.

The technology program uses mathematical algorithm to predict when and where certain crimes will be committed and puts police at the scene before it happens. It has correctly predicted 40% of the crimes it was designed to monitor. (Shurkin, 2011) If it is proved to be reliable, it could help to utilize resources more efficiently, thus reducing crime with less cost. In a weak economy, predictive policing could help police departments operate more efficiently on reduced budgets. And, it provides for more sound management decisions to cover all areas of the city instead of just the hot spots.

By using the predictive policing technique, police departments are better able to put officers in the areas that are vulnerable to crime, utilizing department manpower. It is more effective than just having the officers randomly patrol the streets. Randomly patrolling the streets, the officers may be in an area of crime or may be in other areas while the crimes are being committed making it hard for officers to keep track of criminal behaviors. By being aware of potential hot spots, officers have a better chance of being in the right spot at the right time. The cost of investigating crime is also reduced because more crimes are caught as they occur, instead of having to investigate after they happen. Prevention of crimes reduces the department costs in short-term and long-term.

"Compstat is a police management program with the basic components of accurate and timely intelligence, rapid deployment of personnel and resources, effective tactics, and relentless follow-up and assessment." (CrimeSolutions.gov) Compstat acts as an information system. Crime data is input with lag time of less than 24 hours, which makes it easier to identify criminal activity quicker. Information gets updated as new crimes are committed and information is added to the database. Analyst process the information to determine criminal behavior based on geographic information system (GIS) mapping. The criminal behavior data can determine the areas and the timeframe that criminal behavior is most likely to occur. Police commanders take this information and discuss solutions to deploy officers to the locations within the predicted time frame. It provides ideas for new strategies to be used or considered. The commanders are then responsible for reporting the results of the solutions discussed. The feedback tells them how well the solutions and the system are working. It provides for a strength and weakness evaluation and is a way to examine problems from a new angle to determine the causes and new solutions to be considered. This information gives ideas for change, holds everyone accountable, and motivates proactive actions with greater team work for efficiency.

Police departments that have used the information system technology programs have more ideas for better management of personnel and budgets, city and neighborhood planning, and offender monitoring. (Uchida) The predictive policing techniques currently being used are data mining, identifying hot spots, crime mapping, statistical probability, geospatial prediction, social network analysis, and deployment of manpower. Using data mining to identify the hot spots and map crime can provide better decisions for efficiency of resources. Statistical probability and geospatial predictions give new information on criminal behavior and help police to be more aware of how criminals think, when and where crime is likely to be committed, and better deployment of manpower and resources. The social network analysis plays a part in offender monitoring and can introduce more criminals to the police. Information obtained from data mining gives management more to work with in making decisions with city and neighborhood planning. It gives information to determine where the vulnerable neighborhoods are and what the signs are that can bring about crime.

A SWOT analysis can help police departments determine if information technology programs can help them reduce crime or what aspects of the programs will be beneficial. "…the greatest benefit to predictive policing is the discovery of new or previously unknown patterns and trends." (Pearsall, 2010) Predictive policing borrows from principles of other policing models and is designed to enable officers to do things better and more efficiently. It brings police strategies under one umbrella with the tremendous infusion of data, which provides for greater problem identification and assessment. The data provided exposes unknown patterns and trends to bring about more awareness and provides greater information and analysis for problem solving. Teamwork is better implemented with the greater awareness of where and when crimes are most likely to be committed and new ideas the criminals are coming up with.

The weaknesses have been privacy, personnel training, enforcing accountability, understanding the available data, and reliability. (Willis) Privacy policies are weak, personnel using the data have not been properly trained to protect privacy, accountability has primarily been with top management, there is weak understanding of all the available data, and reliability has not been proven. In order to strengthen the system, there needs to be more transparency, auditing, and due diligence to develop trust, protect privacy, and produce good outcomes. Personnel need more intensive training to understand the all the data. There also needs to be measures to hold everyone accountable, not just the management.