Leading from the front, the New York Police Department has begun exploring mechanisms to incorporate sentiment analysis — data about public perceptions — as a component of its flagship performance management system.
They are on to something important. The NYPD knows that it matters how members of the public feel about police services.
Police are dependent upon the support and cooperation of the public to be effective, and communities are likewise dependent upon the police to help create safe communities.
If you ask most police officers, they will tell you their role is simply to respond to police calls for service, fight crime, and arrest violators of the law as the intake process for the criminal justice system.
In this worldview, success is typically defined by numbers of arrests, citations, special initiatives. If crime rates are going down, and we are making a lot of contacts, citations, and arrests, we must be doing a great job.
However, ask most members of the public, and they will paint a very different picture.
They will invariably tell you they want to feel safe in their neighborhoods; they want police to be responsive to concerns they have about crime and other issues that negatively impact their quality of life. They want prompt and timely police services when they have been impacted by crime, and they want police to help them avoid becoming victims in the future. Anytime they come in contact with police, they want to be treated with dignity and respect.
Sentiment analysis refers to the process of gathering and analyzing available data so decision-makers have a well-informed understanding of each community’s critical issues.
The very best kind of “data” is, of course, the understanding and insights that are the by-product of trust-based relationships with as diverse a spectrum of the public as possible.
Community surveys and feedback from community outreach efforts are the next best type of sentiment data. These methods provide insights into concerns from members of the public who may be less engaged, satisfied, or trustful of police.
By learning concerns from those less engaged, officials can carefully examine police activities to see if there are opportunities to improve outcomes and enhance trust. Knowledge about community frustrations is vital. Frustration, especially when it arises from perceived injustices and unfulfilled needs, are common precursors of unrest and disorder.
The truth is, however, that there is a level of trust involved in someone simply completing a survey. Those who distrust government, distrust police, and feel alienated from the larger community, often will not participate at all.
Through the analysis of publicly available sources of data, such as social media postings, it is often possible to begin to identify those issues of greatest concern to those less engaged through other means. There is great opportunity to be gained by learning to understand community concerns and becoming responsive to them, and great peril in ignoring those concerns.
Sentiment analysis is about far more than measuring whether or not people like the police. Sentiment analysis is about understanding the underlying community narratives. We seek to identify the unfulfilled needs, underlying fears, and resultant frustrations most impacting on how people feel about their neighborhoods, and the police officials who are paid to serve them.
By understanding those narratives, officials can earn trust by seeking to help fulfill those needs. Having gleaned insights into those issues of greatest concern, and by being responsive to those concerns, officials can demonstrate caring and responsiveness, and earn a measure of trust in the process.
As we consider the broad range of services police provide, and our role in creating safe and just communities, we should explore performance metrics to measure the broader array of services: Are police effective in creating public spaces where people feel safe? How successful are we at identifying and responding to emerging public order trends? Are we successfully engaging with other community stakeholders to ensure issues impacting on neighborhood quality of life problems are addressed?
Public trust and confidence are earned when police are both effective and act with integrity. Measuring performance outcomes accomplishes both. By holding ourselves accountable for the outcomes of our policing efforts, taking the time to measure those outcomes, and adapting police activities to improve future outcomes, police earn vital trust and confidence.
When attempting to measure the outcomes of policing efforts, there are three areas of concern regarding public sentiment.
Quality of Life: Community members are concerned about crime and disorder, as well as a host of other non-criminal conditions that impact their sense of safety, security, and well-being in their neighborhoods and public spaces.
Quality of Service: Measuring the outcomes of police efforts also includes obtaining feedback on how people feel about the quality of the services they receive. Do members of the public believe their police to be effective at their jobs? Do they feel their police are responsive to their needs?
Perceptions of Procedural Justice: Do people feel the police treat them with dignity and respect, in a fair and unbiased manner, and the police are judicious in their use of coercive authority? Are they restrained in their use of force?
Policing has already used data to become more effective at fighting crime. Police performance management systems and our use of data to direct policing efforts have created huge advances in policing as a profession. Many believe programs like CompStat, Evidenced-based and Intelligence-Led Policing have permitted us to dramatically improve our effectiveness in reducing crime.
By incorporating sentiment analysis, it is possible for police officials to further measure the outcomes of our work – have we been successful from the perspective of those impacted?
By measuring the outcomes of our policing efforts, and creating a feedback loop, and by using this feedback to refine our work to improve our outcomes, we can improve both our effectiveness at creating safe communities and responsiveness to public concerns, while helping us earn public trust and confidence in the process.
Retired Chief Cameron S. McLay, formerly chief of police for the city of Pittsburgh (PA) Bureau of Police, is principle of TPL Public Safety Consulting and serves as senior adviser for PricewaterhouseCoopers Safe Cities Initiative — an initiative to enable police use of enhanced data analytics and monitoring of social risk and sentiment to improve their performance outcomes and to build public trust and confidence.
McLay has a master of science from Colorado State in organizational leadership, and a bachelor of arts in forensic studies from Indiana University. McLay served for more than 29 years with the city of Madison (WI) Police Department, where he retired with the rank of captain. He went on to teach leadership in police organizations for the IACP before serving as Pittsburgh’s chief.