JUSTICE POLICY CENTER

The Milwaukee Police Department’s
Body-Worn Camera Program
Evaluation Findings and Key Takeaways
Bryce E. Peterson, Lilly Yu, and Nancy La Vigne
URBAN INSTITUTE

Daniel S. Lawrence
RTI INTERNATIONAL, POLICING RESEARCH PROGRAM

May 2018
This brief describes the results of the Urban Institute’s evaluation of the Milwaukee
Police Department’s body-worn camera program. From October 2015 to December
2016, the Milwaukee Police Department (MPD) deployed body-worn cameras (BWCs)
in a phased rollout to all of its roughly 1,100 patrol officers. Through a randomized
controlled trial of 504 officers, the Urban Institute found that those who wore BWCs
conducted fewer subject stops and were less likely to receive a complaint than officers
that did not receive cameras. However, BWCs had no effect on whether officers
engaged in use of force during the study period.
As the police department for the largest city in Wisconsin—a city with a very diverse population—
the MPD pursues partnerships with the community to reduce crime, fear, and disorder through several
initiatives, including the use of data-driven policing. But challenges to improving police-community
relations and public trust remain, especially in neighborhoods with high rates of poverty and violent
crime. Police-community relations were particularly strained in 2014 after the high-profile shooting of
Dontre Hamilton by an MPD officer.1 The officer involved was fired but was not charged with a crime,
which sparked a series of protests across the city. As a result, there was an outcry for MPD officers to be
equipped with BWCs, including a petition on Change.org with 2,300 signatures and several proposals
from Milwaukee aldermen and Mayor Tom Barrett.

 Officer with a collar-mounted body-worn camera. Photo provided by the Milwaukee Police Department.

Under this increased scrutiny and political pressure, the MPD began developing its BWC policy and
rollout plan in mid-2015. Between October 2015 and December 2016, the MPD equipped all patrol
officers with the model of BWC seen above. These cameras are small devices that officers can mount on
their head, collar, or shoulder and use to record audio and video of their interactions with community
members. The cameras have a small buffering period that captures video of the 30 seconds immediately
before the officer turns the camera on. No audio is captured during the buffering period.
The BWCs were meant to increase transparency and accountability within the MPD by providing
better accounts of officer-community interactions and behaviors. The MPD also hoped BWCs would
enhance the collection of evidence. The MPD partnered with researchers from the Urban Institute to
develop a rigorous evaluation of the department’s use of this technology. This partnership was
supported by funding from the US Department of Justice through the Bureau of Justice Assistance’s
Strategies for Policing Innovation program. Strategies for Policing Innovation also gave the MPD access
to subject-matter experts who provided guidance on the BWC policies and rollout.

Body-Worn Camera Rollout and Evaluation
With input from Urban, the MPD completed a four-phased deployment of BWCs to support Urban’s
evaluation (table 1). Phase 1 included a pilot program in late 2015 involving roughly 15 percent of MPD
officers. In phase 2, Urban worked with the MPD to initiate a randomized controlled trial (RCT) in which
252 officers were randomly assigned a BWC (the “treatment group”) and 252 officers continued their
work without BWCs (the “control group”). An additional 16 officers who were not part of the RCT were
also given BWCs in phase 2. In phase 3, 238 officers who were not part of the RCT were equipped with
BWCs. Finally, phase 4 distributed BWCs to the 252 control group officers and an additional 171
officers not involved in the RCT. It is worth mentioning that the MPD delayed the final deployment of

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 cameras from September 2016 to December 2016 at the request of the Strategies for Policing
Innovation program and the Urban research team to ensure that there would be sufficient follow-up
time to collect data from the officers involved in the RCT.
As part of our RCT, we analyzed differences between the treatment and control groups on several
outcomes related to officer behavior, including arrests, traffic stops, subject stops, citizen complaints,
and use of force. We used difference-in-differences (DiD) estimations for these analyses. This approach
allowed us to control for the differences and changes between the two groups during the
preintervention period (the nine months before March 21, 2016) and postintervention period (the nine
months after March 21, 2016). More information about this approach and the balancing diagnostics of
the RCT, as well as the regression coefficients from the DiD estimations, is presented in the appendix.
TABLE 1

Milwaukee Police Department Body-Worn Camera Deployment
Phase
1
2
3
4

Description
Pilot demonstration
RCT treatment group
officers
Officers not involved in
the RCT
RCT control group
officers

Number of body-worn
cameras distributed

Districts
targeted

Month of
deployment

182
252 treatment group officers
+ 16 non-RCT officers
238

2, 5, NTF
1, 2, 3, 4, 6, 7

October 2015
March 2016

1, 2, 3, 4, 5, 6, 7

June 2016

252 control group officers
+ 171 non-RCT officers

1, 2, 3, 4, 5, 6, 7,
NTF, others

December 2016

Source: Urban Institute.
Note: RCT = randomized controlled trial; NTF = Neighborhood Task Force.

Main Findings
The following results are specific to Urban’s RCT, which was conducted between March 21 and
December 20, 2016.
Figure 1 shows the changes in the average number of arrests per officer from the preintervention
period to the postintervention period for the treatment and control groups. Treatment group officers
(those wearing BWCs) and control group officers had a similar average number of arrests during the
preintervention period (13.79 and 13.50). However, both groups experienced a similar decline in the
average number of arrests between the pre- and postintervention periods. The DiD estimations
presented in the appendix tell a similar story: there was a significant drop in overall arrests across both
groups, but equipping officers with BWCs did not affect how many arrests officers made.

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 FIGURE 1

Average Number of Arrests
Treatment group (with cameras)
Control group (no cameras)

16

13.79

14

13.50
12.19

12

11.96

10
8
6
4
2
0

Preintervention
(before cameras)

Postintervention
(after cameras)
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As detailed in figure 2, MPD officers on the whole conducted slightly more traffic stops in the nine
months following implementation of the BWC program compared with the nine months previous.
However, there was no significant difference between treatment group officers and control group officers.
FIGURE 2

Average Number of Traffic Stops
Treatment group (with cameras)
Control group (no cameras)

130

125.75
125

122.00

121.01
118.87

120
115
110
105
100

Preintervention
(before cameras)

Postintervention
(after cameras)
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THE MILWAUKEE POLICE DEPARTMENT’S BODY-WORN CAMERA PROGRAM

 As another measure of officer activity, figure 3 depicts the changes in subject stops by officers in the
treatment and control groups. Subject stops are when an officer temporarily detains a person for
questioning, investigation, and so on. Although officers in both groups conducted fewer subject stops on
average after implementation of the BWC program, this drop was greater in the treatment group (46.15
stops compared with 26.85) than in the control group (48.85 stops compared with 30.95). This
difference was statistically significant in the DiD estimations, indicating that BWC-equipped officers
conducted approximately 8 percent fewer subject stops than officers without BWCs.
FIGURE 3

Average Number of Subject Stops
Treatment group (with cameras)
Control group (no cameras)
60
50

46.15

48.85

40
30.95
26.85

30
20
10
0
Preintervention
(before cameras)

Postintervention
(after cameras)
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Community members may file a complaint against an MPD officer for several reasons, including
issues regarding the officer’s competence, integrity, or behavior during their encounter. To assess how
BWCs may have affected complaints, we compared the share of officers in both groups who had at least
one complaint lodged against them in the pre- or postintervention period (figure 4). We found that a
greater share of officers assigned to the treatment group had at least one complaint against them in the
nine months before implementation of the BWC program (10.71 percent) compared with officers in the
control group (7.54 percent). However, after BWCs were deployed, these trends reversed. In the nine
months after the program, fewer officers equipped with BWCs had a complaint against them than
officers without BWCs (9.52 percent compared with 12.7 percent). The DiD estimations confirm that
wearing a BWC reduced an officer’s odds of receiving a complaint by more than 50 percent, though this
difference only approached statistical significance.

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 FIGURE 4

Share of Officers with One or More Complaint
Treatment group (with cameras)
Control group (no cameras)
14%

12.70%

12%

10.71%
9.52%

10%
7.54%

8%
6%

4%
2%
0%
Preintervention
(before cameras)

Postintervention
(after cameras)
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Our final measure of officer behavior was use of force. We examined the share of officers who
engaged in at least one use-of-force incident in the nine months before and after implementation of the
BWC program (figure 5). The chart below shows a slight increase in the share of treatment group
officers who engaged in use of force between the pre- and postintervention periods, compared with a
slight decrease in the share of control group officers who did so. However, the results of the DiD
analyses were not significant, indicating that BWCs had no impact on use-of-force incidents.
FIGURE 5

Share of Officers Involved in One or More Use-of-Force Incident
Treatment group (with cameras)
Control group (no cameras)
45%
40%
35%

40.08%
34.13%

37.70%

35.32%

30%
25%
20%
15%
10%
5%
0%
Preintervention
(before cameras)

Postintervention
(after cameras)
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 Key Takeaways
There are several key takeaways from the findings presented above. First, officers wearing BWCs
conducted significantly fewer subject stops than officers without cameras. However, patterns of
arrests and traffics stops were similar across the two groups. This indicates that officers equipped with
a BWC became more selective in who they approached and stopped during their patrol activities, but
BWCs may have had no effect on whether officers stopped a vehicle or made an arrest.
The second takeaway from our study is that BWCs appear to have reduced complaints against
MPD officers. However, it is not clear if complaints were reduced because BWCs had a “civilizing effect”
during police-community interactions (White 2014) or because community members were more
reluctant to lodge a complaint against an officer wearing a BWC. If it is the former, and BWCs lead to
more peaceable police-community interactions, the MPD should explore ways to make BWCs even
more noticeable to community members during public encounters. For example, the MPD could require
its officers to tell people at the beginning of an interaction that they are recording audio and video
(current departmental policy recommends, but does not mandate, that officers tell community members
they are recording an encounter).
Finally, BWCs had no effect on whether officers engaged in use of force. Although this may be
surprising to some, it is consistent with findings from other recent studies (Ariel et al. 2016a, 2016b;
Yokum, Ravishankar, and Coppock 2017). Also, although BWCs did not reduce officers’ use of force in
our study, the MPD had experienced declines in the department’s overall use of force in each year
leading up to this study from 2013 to 2016 (Brandl 2017). Given this trend, our study may be
documenting a preexisting increase in restraint regarding use of force. In other words, it is unlikely that
the BWC program would significantly decrease use of force if officers were already following
departmental policy and guidelines on appropriate use of force.

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 Appendix. Randomized Controlled Trial Methodology
To randomly select the 504 officers who would be included in the study, the MPD and the research
team conducted a stratified random sampling procedure, where the strata included the officer’s race
(non-Hispanic white or nonwhite) and shift (power, late, day, or early). The sample of officers from each
district was matched to the proportion of officers that district represented in the department. For
example, officers in district 1 represented 12 percent of the overall department, thus officers from
district 1 made up 12 percent of the overall sample.
Officers from district 5 and the Neighborhood Task Force received body cameras during the first
phase of deployment.2 For the phase 2 rollout, Urban identified 854 officers assigned to district 1, 2, 3,
4, 6, or 7 who were active and eligible to receive a BWC. Reasons for ineligibility included promotions or
transfers to limited-duty jobs or “desk jobs” (where a camera would not be needed) and planned family
leave or other extended absence from the department during the study period. A randomly selected
pool of 666 officers was identified as eligible for the study, and 504 were randomly assigned into the
BWC-equipped treatment group or the business-as-usual control group (which was later given BWCs as
part of phase 4). Additional cross-checks were conducted to confirm that all 504 officers were eligible
for the study. A small handful of officers was identified as ineligible because of district reassignment
after randomization but before being equipped with a BWC. These officers were replaced with similar
officers from the remaining officers in the pool. The treatment group officers received their cameras
around March 21, 2016, and the control group officers received their cameras around December 20,
2016, allowing for a nine-month study period.
Balance between groups on key officer characteristics was assessed using the Cohen’s d effect-size
statistics presented in table A.1. Balance was assessed between the treatment and control group
officers from the experiment (n = 504) and in comparison to the rest of the officers in the department,
who were eligible to receive a BWC during phase 2 (n = 854). Because the study period was nine months
long, the month averages for the nine months before the March 2016 BWC implementation were
aggregated for each officer. Outcomes reviewed are the number of arrests, number of proactive
activities, number of citizen complaints, a dichotomous variable of officers with one or more citizen
complaints, number of use-of-force incidents, and a dichotomous variable of officers with one or more
use-of-force incidents. Imbalance would be exhibited by Cohen’s d in excess of 0.20 and a t in excess of
1.96. None of the tests found significant differences between the treatment and control groups, and
only the difference in subject stops between the RCT group and the rest of the eligible officers was
found significant. As such, we determined that these groupings were balanced in their composition.

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 TABLE A.1

Group Balance Diagnostics
Treatment versus Control (n = 504)
Treatment
Control
group
group
Mean (SD) Mean (SD)
t
d
Arrests
Traffic stops
Subject stops
Complaints
(one or more)
Use-of-force
incidents
(one or more)

13.79
(11.53)
121.01
(120.40)
46.15
(53.05)

13.49
(13.16)
118.87
(121.42)
48.85
(56.19)

0.11 (0.31)

0.34 (0.48)

RCT Group versus Department (n = 854)
RCT
Other
group
officers
Mean (SD) Mean (SD)
t
d
13.64
(12.36)
119.94
(120.80)
47.50
(54.61)

12.42
(13.80)
126.93
(157.55)
56.77
(73.75)

-.11

0.09 (0.29)

.12

0.37 (0.48)

-0.27

-.02

-0.20

-.02

0.56

.05

0.08 (0.26)

-1.23

0.40 (0.49)

1.38

-1.36

-.09

0.73

.05

2.11*

.15

0.11 (0.31)

0.70

.05

0.37 (0.48)

0.01

.00

Source: Authors’ calculations.
Notes: RCT = randomized controlled trial; SD = standard deviation.
* p < .05; ** p < .01; *** p <.001

Difference-in-Differences
We used difference-in-differences (DiD) to estimate the difference between a treatment officer’s
postintervention and preintervention outcomes, relative to the same difference for the control officers
in the experiment. As we were dealing with both counts (aggregated to the nine-month period) and
dichotomous outcome variables, we used Poisson and logistic regression models for the DiD analysis.
The models we used included a regressor group, which was a dummy variable identifying whether an
individual officer was in the treatment group (1) or not (0). The regressor period was included as a
dummy variable for whether the total count of the outcome per officer was during the intervention
period (1) or the preintervention period (0). The product of the group dummy with the period dummy,
represented by a third regressor coefficient, was the DiD estimate of the effect of BWCs on the
outcome. We used the POISSON and LOGISTIC commands in Stata 15.1 to provide incidence rate
ratios and odds ratios of the DiD described above. Table A.2 presents the incidence rate ratios and odds
ratios for the group, period, and group x period predictors for each model.
TABLE A.2

Difference-in-Differences Results
Incident Rate Ratios
Arrests
Group
Period
Group x period
Constant
Chi2

1.02
0.89***
1.00
13.50***
49.63***

Traffic stops
1.02**
1.03*
1.01
118.87***
51.24***

Subject stops
0.94***
0.63***
0.92***
48.85***
2399.10***

Odds Ratios
Citizen
Use-of-force
complaints
incidents
1.47
1.78†
0.49†
0.08***
3.92**

0.77
0.82
1.43
0.67**
2.26**

Source: Authors’ calculations.
†
p < .10, * p < .05; ** p < .01; *** p < .001

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 Notes
1

The Milwaukee Journal Sentinel outlined the history of fatal interactions with Milwaukee police in a 2014 article.
“Dontre Hamilton case repeats pattern of deaths, calls for reform,” Milwaukee Journal Sentinel, December 22,
2014, http://archive.jsonline.com/news/crime/dontre-hamilton-historical-timeline-286608781.html/.

2

Neighborhood Task Force officers operate outside of district boundaries and are directed to patrol areas with
high crime rates.

References
Ariel, Barak, Alex Sutherland, Darren Henstock, Josh Young, Paul Drover, Jayne Sykes, Simon Megicks, and Ryan
Henderson. 2016a. “Report: Increases in Police Use of Force in the Presence of Body-Worn Cameras Are Driven
by Officer Discretion: A Protocol-Based Subgroup Analysis of Ten Randomized Experiments.” Journal of
Experimental Criminology 12:453–63.
———. 2016b. “Wearing Body Cameras Increases Assaults against Officers and Does Not Reduce Police Use of
Force: Results from a Global Multi-Site Experiment.” European Journal of Criminology 13 (6): 744–55.
Brandl, Steven G. 2017. An Analysis of 2016 Use of Force Incidents in the Milwaukee Police Department. Milwaukee, WI:
Fire and Police Commission.
White, Michael D. 2014. Police Officer Body-Worn Cameras: Assessing the Evidence. Washington, DC: Office of
Community Oriented Policing Services.
Yokum, David, Anita Ravishankar, and Alexander Coppock. 2017. “Evaluating the Effects of Police Body-Worn
Cameras: A Randomized Controlled Trial.” Washington, DC: The Lab @ DC.

About the Authors
Bryce E. Peterson is a senior research associate in the Justice Policy Center at the
Urban Institute. His research focuses on correctional policy, children of justiceinvolved parents, prison population forecasting, and technological interventions in
criminal justice settings.
Lilly Yu is a research analyst in the Justice Policy Center. Her research focuses on the
justice-involvement of young people and victims of crime.

Nancy La Vigne is vice president for justice policy at the Urban Institute. She publishes
research on prisoner reentry, criminal justice technologies, crime prevention, policing,
and the spatial analysis of crime and criminal behavior. Her work appears in scholarly
journals and practitioner publications and has made her a sought-after spokesperson
on related subjects.

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THE MILWAUKEE POLICE DEPARTMENT’S BODY-WORN CAMERA PROGRAM

 Daniel S. Lawrence is a research criminologist at the Policing Research program at RTI
International. His research interests are primarily in the law enforcement field,
specifically on police technology, police legitimacy and procedural justice, police
screening and hiring practices, and community policing.

Acknowledgments
This project was supported by Grant No. 2015-WY-BX-0006 awarded by the Bureau of Justice
Assistance. The Bureau of Justice Assistance is a component of the Department of Justice’s Office of
Justice Programs, which also includes the Bureau of Justice Assistance, the National Institute of Justice,
the Office of Juvenile Justice and Delinquency Prevention, the Office for Victims of Crime, and the
SMART Office. Points of view or opinions in this document are those of the authors and do not
necessarily represent the official position or policies of the US Department of Justice. We are grateful
to them and to all our funders, who make it possible for Urban to advance its mission.
The views expressed are those of the author and should not be attributed to the Urban Institute, its
trustees, or its funders. Funders do not determine research findings or the insights and
recommendations of Urban experts. Further information on the Urban Institute’s funding principles is
available at urban.org/fundingprinciples.

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