How Does Technology Drive ILP?
Many law enforcement agencies are now experiencing depleted resources and an incoming generation whose desired job criteria do not match typical policing requirements (77% of millennials say flexible schedules would make them more productive, an unrealistic ask in the field). Consequently, allocating resources to community engagement is a luxury that many departments cannot afford. Therefore, unless we find a solution that’s less reliant on extra bodies, gaps in policing will continue to grow.
ILP technology is designed to drive efficiency, enabling officers to focus on preventing crime, revitalizing troubled neighborhoods and ultimately reducing department workload. Even if a precinct is operating with 60 to 70% of officer positions filled, ILP-focused technology can help the force operate as if 100% of spots were filled.
Many ILP-driven police departments use the data they’re already collecting, such as criminal records, to determine the best neighborhoods for patrol. However, software solutions designed with ILP and machine-learning capabilities can make more strategic decisions by analyzing crime data and recommending hour-by-hour patrol areas, enabling departments to effectively allocate officers among these areas.
As more police departments turn to ILP, police chiefs will need to obtain complete officer buy-in to ensure the program’s ongoing success. A common approach is offering incentives to move officers to areas recommended by the software. By tracking a police vehicle’s GPS, the department knows whether the officer is in the recommended neighborhood and can evaluate their efforts over time to determine their effectiveness. The commanding officer can then design a strategic performance forecast and track how well officers are implementing tactics toward meeting the forecast. Departments could also choose to make the data available internally, encouraging officers to challenge themselves and meet or exceed their co-worker’s efforts.