Officer Management in the Digital Age: The Impact of Predictive Early Intervention Systems

An early intervention system (EIS) can be an instrumental tool for law enforcement agencies looking to track and address at-risk patterns in officer behavior. The ideal EIS is proactive, enabling leadership to identify off-track behavior before it becomes a real problem, and works seamlessly within the agency’s unique organizational needs and culture. An EIS should also identify positive patterns of behavior in officers exhibiting exemplary performance. Used well, an early intervention system is one piece of a larger officer management system (OMS), the platform an agency uses to turn personnel data into measurable agency performance. The real test is not what the software records but whether anything actually changes: fewer officer injuries, fewer citizen complaints, fewer future investigations. Benchmark Analytics® calls this The Outcomes Standard for Agency Performance. 

Benchmark examined this subject in a webinar as part of our ongoing Data Dialogue series. Panelists included Ron Huberman, CEO of Benchmark Analytics and Nick Montgomery, Chief Research Officer at Benchmark. The dialogue centered around four principal areas concerning EIS: its evolution, data significance, agency adoption, and perceptions towards its daily use by agencies and officers.

How Have Early Intervention Systems Evolved?

Huberman, who rose through the ranks of the Chicago Police Department to serve as Assistant Deputy Superintendent, shed light on the progression of EIS within law enforcement agencies, tracing its origins from the 1970s up to the recent advancements of today. Initially, departments utilized rudimentary “trigger-based” systems. However, these systems often produced “false positives” and “false negatives.” 

“The University of Chicago published a lot of compelling research that showed trigger-based systems typically had a 70% false positive problem, which means 70% of the time it was flagging officers that were doing their job as they should. Furthermore, they had about a 40% false negative problem, meaning they were actually missing officers who were really struggling out there.” 

While policing continued to evolve around more data-centric solutions, early intervention systems failed to keep up until the introduction of First Sign® by Benchmark. First Sign offers a research-based early intervention system that uses various data sources, including arrest records and use-of-force reports, with machine learning to identify predictive patterns. The digital transformation of agency records and advanced algorithms provide a level of accuracy that trigger-based systems lacked at the time and still do to this day. The U.S. Department of Justice’s Office of Community Oriented Policing Services (COPS Office) made this case early: its 2003 planning guide, authored by police-accountability scholar Samuel Walker, framed early intervention as a non-punitive management tool built on officer performance data, while cautioning that any such system is only as good as the data and thresholds behind it. 

Why Do Integrated Datasets Matter?

Benchmark’s Chief Research Officer Nick Montgomery emphasized the power of converging various agency datasets. A combination of data, including over twenty event markers, can lead to 91 model variables for each officer. This integrated approach greatly enhances the understanding of officer behavior compared to analyzing singular incidents. As he stated, “…a research-based early warning system takes all of the data inside a police department looking back over five, ten, fifteen years and uses those various patterns of behavior to create a system that is far more predictive and can accurately identify officers likely to have an adverse event based on past events.” Independent research points in the same direction. A 2026 study in the Journal of the American Statistical Association, by University of Pennsylvania criminologist Greg Ridgeway, compared officers with their peers at the same use-of-force scenes and found that context-aware measurement surfaces consistent escalators that raw incident counts miss, while clearing high-count officers whose force matched the situation. 

How Does Early Intervention Prevent Harm?

Early intervention systems can offer valuable insights by identifying officers exhibiting at-risk behavior, allowing for prompt intervention through training or counseling before problems escalate. Research conducted with the University of Chicago demonstrates that traditional EIS platforms using threshold-based triggers deliver roughly 30% precision when flagging at-risk officers, meaning most flags are wrong. First Sign reaches 85% model precision. Furthermore, approximately 5% of officers identified at risk are responsible for 66% of injuries. This concentration is not new. The Independent Commission on the Los Angeles Police Department, known as the Christopher Commission, reported in 1991 that of roughly 1,800 officers with an excessive-force allegation, just 44 accounted for six or more, a small group responsible for a disproportionate share of incidents. 

Addressing the challenges with this specific group can significantly enhance community trust. Constructive, non-punitive supervision remains crucial for the efficacy of early intervention systems. In Huberman’s words, a modern research-based system like First Sign enables supervisors to say, “Hey, Officer Smith – I know you’re a good guy – and a good officer – but you were flagged in the system, so it’s important I intervene. Let’s talk about next steps to correct your at-risk behavior and how you’re engaging the public.” 

What Outcomes Do Agencies See?

Agencies that implement research-based early intervention see measurable, published results. Post-implementation research shows a 13% reduction in use of force, a 33% reduction in use of force severity, and a 48% reduction in citizen complaints, while essential enforcement activities remain largely unaffected. These outcomes are validated through a standardized national model developed in partnership with the University of Chicago. 

What Does the Future of Officer Management Look Like?

Police reform has historically been broad by necessity: de-escalation training for the entire force, new policy for every officer. Research now supports a more precise approach. A small group of officers drives a disproportionate share of adverse events, officer behavior drifts over time rather than failing all at once, and early intervention works best as a system, not a standalone alert. 

That is where officer management is headed. The future is not more dashboards or more alerts; it is a system accountable for what actually changes — fewer adverse events, fewer citizen complaints, stronger community trust. First Sign® Early Intervention identifies the officers who need support, C.A.R.E. structures the intervention, and the agency measures the result. That is the Outcomes Standard in practice. 

As Huberman puts it in the Data Dialogue , “There’s a tremendous opportunity before all of us in this profession – who view it as a noble calling and care deeply about policing – to say, ‘Let’s make a difference. Let’s turn this corner now because we have the tools to do so.’ I truly believe this is the moment we’re at.” 

Frequently Asked Questions

What is an officer management system? An officer management system (OMS) is the platform an agency uses to manage the full officer lifecycle, from training and performance to early intervention and wellness, and to turn that personnel data into measurable agency performance. Benchmark is the officer management system for law enforcement, built on a research foundation rather than a workflow checklist. 

How does predictive early intervention work? Predictive early intervention analyzes years of department data across multiple sources, weighing 91 model variables per officer to surface patterns that precede an adverse event. Rather than waiting for a fixed count of incidents, it identifies who may need support early, so supervisors can step in before harm occurs. 

Why do threshold-based early intervention systems fail? Threshold-based systems flag officers only after they cross a fixed count of incidents, which produces roughly 30% precision and a high volume of false flags. First Sign reaches about 85% model precision by weighing predictive patterns against a national model built on more than 80 million officer performance records. 

Does early intervention replace supervisor judgment? No. Early intervention is non-punitive and supports supervisor judgment rather than replacing it. A flag is the start of a conversation, not a verdict, and structured follow-up turns that insight into a documented, trackable plan. 

Sources

Samuel Walker, “Early Intervention Systems for Law Enforcement Agencies: A Planning and Management Guide,” U.S. Department of Justice, Office of Community Oriented Policing Services (COPS Office), 2003. 

Independent Commission on the Los Angeles Police Department (Christopher Commission), Report of the Independent Commission on the Los Angeles Police Department, 1991. 

Greg Ridgeway, “A Conditional Ordinal Stereotype Model to Estimate Police Officers’ Propensity to Escalate Force,” Journal of the American Statistical Association, 2026. 

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