Choosing an Early Intervention System for Your Department

Most EIS platforms still run on trigger-based logic designed in the 1970s. That’s not surprising — the category was built to record incidents, and recording incidents is what it still does. It was never designed to answer the question agencies are actually asking now: is anything changing? 

That’s the question that matters: not what the system records, but whether outcomes improve, such as fewer officer injuries, fewer citizen complaints, or fewer future investigations. Answering it requires an Early Intervention System, ideally one that is part of an officer management system (OMS), the platform an agency uses to turn personnel data into measurable agency performance. Benchmark Analytics® defined this as The Outcomes Standard for Agency Performance, and it’s the lens this guide uses to weigh your options. 

Non-Disciplinary by Design

Early intervention systems were never meant to be disciplinary. From the earliest programs, the intent was support: identify officers showing signs of strain and connect them with help before a career-damaging incident. Most police executives would still agree that helping officers is preferable to punishing them. 

But trigger-based systems couldn’t keep that promise, because nothing in how they were built supported it. The inputs were disciplinary data: complaints, use-of-force reports, internal affairs cases. And the way it worked looked exactly like discipline: cross a set threshold, get a formal review. The flag itself offered no context, no insight into what the officer needed, and no next step. The result was a tool that was non-disciplinary in intent but punitive in experience, used in hindsight if it was used at all. 

The data confirms what officers already sensed. A peer-reviewed study from our research partners at the University of Chicago found that most trigger-based systems produce a 78% false positive rate and a 90% false negative rate. The officers flagged mostly didn’t need intervention, and the officers who needed it mostly weren’t flagged. 

An EIS built to keep the original promise works differently. It analyzes indicators in context, including cumulative exposure to stressful events and patterns that merit recognition, not just concern. Under the Outcomes Standard, the measure isn’t how many officers a system identifies, but whether they get the right support early enough to change the outcome. And it works through your frontline supervisors, informing the judgment of the people who know their officers best. 

How Do Early Intervention Systems Work?

A trigger-based EIS doesn’t analyze anything. It counts events against predetermined thresholds and flags when a number is crossed. That single design choice explains most of what’s wrong with legacy systems, and most of what a research-based EIS does differently. 

Here’s how the counting works: an agency selects a set of indicators, defines a limit for each, and the system flags any officer who crosses one. Three use-of-force incidents in a month, for example, generates a supervisor alert. The indicators are chosen by intuition, and the counts carry no context about assignment, shift, or the situations behind the numbers. 

That’s the root of the false positive and false negative problem covered above. A raw count can’t distinguish a justifiably active officer on a high-volume beat from one who is genuinely off track, so supervisor attention gets pulled in the wrong direction while officers who need support go unnoticed. 

A research-based EIS works from a different foundation. Instead of intuition-picked indicators, it draws on longitudinal analysis of officer data across many agencies to identify which patterns actually precede adverse events. Instead of raw counts, it evaluates behavior in context: what happened, when, where, and under what conditions. The result reaches supervisors earlier and with far greater accuracy, which is what makes preventative action possible rather than aspirational. 

For a closer look at the research-based approach, check out First Sign® Early Intervention. 

Why would your agency want an EIS?

The case for an EIS comes down to outcomes, and they show up in three places: your officers, your accreditation posture, and your standing with the community. 

Protect Your Officers (and Their Careers)

Law enforcement officers regularly adapt to high-stress, complex, and often unfamiliar situations, and they document nearly all of it, from use-of-force reports to vehicle pursuits. The profession generates enormous amounts of data about its people, yet historically very little of it has been used to help them. 

A research-based EIS puts that data to work for the officer. Analyzed properly, it reveals when someone is accumulating stress exposure, drifting off track, or carrying a workload that puts their health and career at risk, early enough for a supervisor to step in with support rather than a sanction. Every career-damaging incident prevented is an officer retained, a family protected, and a liability that never materializes. 

Accreditation Compliance

EIS guidance is table stakes for CALEA accreditation. Agencies operating an EIS are required to maintain a written directive covering behavioral indicators, review of identified employees, and remedial action. In CALEA’s words, failure to develop a comprehensive system “can lead to the erosion of public confidence in the agency’s ability to investigate itself,” while putting both the public and agency employees at greater risk. An EIS with structured review workflows built in makes that directive something your agency lives, not just files. 

Relationship with Community

Community support for early intervention is broad and crosses demographic lines. In a National Policing Institute survey of nearly 2,000 metro-area residents, 75% of white respondents and 80% of Black and Hispanic respondents favored early intervention systems as an accountability mechanism within police agencies. As communities ask for more transparency into how agencies identify and address off-track behavior, an EIS signals that your agency is investing in the wellbeing of its officers and the community at the same time. Under the Outcomes Standard, those aren’t separate goals; fewer adverse incidents means both. 

6 Baseline Functions to Look for in an EIS

Whether you’re reevaluating your existing early intervention system or purchasing your first one, these are the baseline functions to look for, and the standard to hold each one to is the same: does it help change outcomes? 

Beyond Trigger or Threshold Mechanisms

Though research indicates these mechanisms are no longer enough (and can often mislead supervisors), they still provide some insight into the frequency of certain events. But research shows counts alone mislead supervisors more often than they inform them. A system that stops at triggers isn’t a baseline anymore, it’s a liability. Look for a platform that treats thresholds as one input among many, not the mechanism itself. 

A Research Base

There’s only so much you can learn comparing your agency against itself. An EIS built on a longitudinal research base helps you understand your officers in the context of policing across many departments, so the patterns it surfaces reflect what actually precedes adverse events, not one agency’s intuition. The strongest research base is both large and independent. Benchmark operates the largest officer performance database in policing, more than 80 million officer performance records, and its predictive model was developed and validated in partnership with the University of Chicago and the Joyce Foundation. 

Advanced Analytics

Data without analytics isn’t very useful. If your EIS doesn’t include them, your team is left to crunch the numbers themselves, and at the rate a law enforcement agency produces data, no individual can derive meaningful insight unaided. The difference is measurable: a research-based model weighs 91 model variables per officer to reach 85% model precision, compared with roughly 30% for threshold-based systems. 

Situational Evaluation

Your EIS should interpret information in situational context. This is what separates accuracy from noise: a system that can’t process the circumstances behind an event won’t differentiate a justifiably active officer from an off-track one. 

Temporal Evaluation

When something occurred matters as much as what occurred. Whether a series of events happened on third watch, over a weekend, or during a large public event should factor into which officers are flagged, if any. 

Command Channel Review Support

Every agency has a review process, and no two are alike. Your EIS should be flexible enough to align with your command channel review rather than forcing your agency to conform to the software. A flag is the start of a conversation, not a verdict, so the system should support a documented, trackable intervention that follows your chain of command rather than working around it. 

Choosing an EIS is one of the more consequential decisions an agency makes about its people. Look for a partner who understands the complexities of policing, brings the research to prove what works, and measures success the way you do: in outcomes. 

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 and measured by The Outcomes Standard for Agency Performance. 

How do you choose an early intervention system? Start with outcomes, not features. Look for six baseline functions: context-aware handling of triggers and thresholds, a longitudinal research base, advanced analytics, situational evaluation, temporal evaluation, and command-channel review support. Then ask the deciding question of any vendor: in agencies like yours, did anything actually change after deployment? 

Why do threshold-based early intervention systems fail? Threshold-based systems flag officers only after they cross a fixed count of incidents, which yields roughly 30% precision and a high volume of false flags. They send supervisors after officers doing their jobs while missing those who are struggling. A research-based model reaches about 85% precision by weighing predictive patterns instead. 

Does an early intervention system replace supervisor judgment? No. A research-based early intervention system is non-punitive and amplifies frontline supervisors rather than replacing them. A flag is the start of a supportive conversation, not a disciplinary verdict, and structured follow-up turns that insight into a documented, trackable plan within your command channel. 

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. 

Stephen James, Lois James, and L. Dotson, “Evaluating the effectiveness of a police department’s early intervention system,” Journal of Experimental Criminology 17 (2021): 457–471. 

Jennifer Helsby et al., “Early Intervention Systems: Predicting Adverse Interactions Between Police and the Public,” Criminal Justice Policy Review 29, no. 2 (2018): 190–209. 

 

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