Teaching police recruits the basic value of data and the operational utility of crime analysis will prove to be public money spent for the public good.
Policy-makers, please take note: Teaching police recruits the basic value of data and the operational utility of crime analysis will prove to be public money spent for the public good.
Billions of public dollars are spent on real estate, buildings and technologies to collect, manage, analyze and communicate the many, many, petabytes of data that police agencies generate. Fusion centers, real-time crime centers, CCTV and surveillance centers, mobile data terminals, or automatic vehicle location systems, are just a few of the capital assets. Each of these cost millions of dollars to build or setup, plus more to maintain and staff. Added to these appropriations are the costs of computer-aided dispatch, records management systems, and predictive policing software, to name a few of the digital resources, which comprise a multi-billion dollar industry in the United States, alone.
Elected officials clearly value data because they invest heavily in producing and preserving its related infrastructure. But there is an obvious void: investments in the human elements that make data actionable.
Far removed from the new buildings with walls of integrated flat screen TVs, in roll-call rooms and on police patrol routes throughout America, exists evidence that data analysis is undervalued by line-level police officers, and even some commanders. Or, maybe the value of data is just overlooked and, therefore, underappreciated. Police of all ranks have a symbiotic relationship with data and analytical products. Every day data informs strategies, tactics and resource deployments. It aids criminal investigations, and is discoverable in courts of law. Data analysis informs command decisions and patrol activities that can directly affect officer safety, public safety, and police-community relations. Skilled analysts in police departments throughout the country turn ‘big data’ into ‘smart data’ and, when used wisely, these products offer insights to prevent crime and reduce risks. Many stakeholders use police administrative data to measure various aspects of success or failure.
Police officers are both the generators of original data and the end users of crime analyses. Yet, they are rarely, if ever, formally trained to preserve the integrity of data measures, to see value in datasets, or to fully harness the utility of analytical products. Largely missing from public spending is deliberate investments to teach police recruits the basic value of data and the operational utility of crime analysis for their personal and departmental interests.
Basic law enforcement training programs in the United States last an average of 840 hours, or 21 weeks, according to the Bureau of Justice Statistics’ (BJS) survey of state and local academies. Major training areas include operations (an average of 213 hours per recruit); firearms, self-defense, and use of force (168 hours); self-improvement (89 hours); and legal education (86 hours). “Data utility” is not mentioned. Adding an hour long module to basic training would account for less than half of 1% of training time, but could yield a huge return on investment.
Police are the front line brokers of crime analysis results to operational practice. Yet their brokering skills and training are often un-nurtured and ad hoc. Recently, 79% of survey respondents agreed that a basic introduction to data and crime analysis should be a required part of police academy training. Expert academy instructors can come from a variety of places, including from within a local police department’s crime analysis unit, as the City of Chesapeake already institutionalized.
Policy-makers responsible for police academy curriculums should add learning objectives to teach recruits why data is important, how it relates to their job, how it can be reliably collected, how it should inform their decision-making, how it can be used to develop crime and risk reduction strategies, and how it can justly identify places for resource deployments. Recruits should graduate with clear expectations of how they’ll produce and use data on the job. Police officers deserve to understand why commanders might have told them to do what they’re doing, and where to do it. They deserve the transparency of knowing that data probably played a role in the orders they were given; that the reliability and validity of data analyses can be affected by the discretionary decisions they make and the actions they take every shift; and that directly or indirectly, this feedback loop affects their future work duties and related liabilities.
The petabytes of data available to police only becomes actionable when people interpret it in meaningful ways. This takes training and practice; but it starts with an honest introduction. It requires a similar level of dedicated training that is already given to shooting accurately, driving emergency vehicles safety, or handcuffing quickly.
Elected officials and many other stakeholders will realize huge long-term benefits when police learn that data has value, and how to harness it. They will witness a more effective, responsive and transparent police department when police officers are trained to balance empirical evidence with professional experience. Learning to value data should be taught early to new recruits and not forgotten or dismissed during field training. The mindset and operational practice of evidence-based policing requires that new generations of recruits learn to value data and empirical evidence, along with a healthy balance of critical professional insights and intuition. Police academies are the places to start to nurture this trend.