Shooting Stars

• Published date: 01 June 2017
• Date: 01 June 2017
• DOI: 10.1177/1098611116671309
• Subject Matter: Articles

Article
Police Quarterly
2017, Vol. 20(2) 164–188
Shooting Stars:
! The Author(s) 2016
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Estimating the Career
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DOI: 10.1177/1098611116671309
Productivity
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Trajectories of Patrol
Officers
Luke Bonkiewicz1
Abstract
This study analyzes two decades of data from a municipal police agency and describes
the average patrol officer career productivity trajectory. We find that declines in prod-
uctivity begin immediately after the first year of service and worsen over the course of
officers’ careers. After their 20th year, patrol officers generate 88% fewer directed
patrols, 50% fewer traffic warnings, 58% fewer traffic citations, 41% fewer warrant
arrests, and 57% fewer misdemeanor arrests compared to officers with 1 year of
experience. Using a patrol officer productivity metric called Z-score per Productive
Time (Z-PRO), we estimate that each additional year of service decreases an officer’s
overall productivity by about 2%. Z-PRO also indicates that after 21 years of service, an
average officer will be approximately 35% less productive overall than an officer with 1
year of service.
Keywords
patrol officers, productivity, Z-PRO
Law enforcement agencies and their jurisdictions invest a substantial amount of
resources to train, equip, and maintain a police force. In return, police super-
visors and citizens expect that police of‌f‌icers—specif‌ically, patrol of‌f‌icers—will
use their time productively to reduce crime, improve community safety, and
foster partnerships with community members (Bittner, 1970; Goldstein, 1987),
1Lincoln Police Department, Lincoln, NE, USA
Corresponding Author:
Luke Bonkiewicz, Lincoln Police Department, 575 S. 10th Street, Lincoln, NE 68508, USA.
Email: lukebonkiewicz@gmail.com

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Bonkiewicz
165
despite their perceived status as outsiders in the community (Van Maanen, 1973).
Conversely, if community members perceive of‌f‌icers as lazy or unproductive,
they may be less likely to cooperate with law enforcement of‌f‌icers (Sunshine &
Tyler, 2003). Yet patrol of‌f‌icers are not uniformly productive throughout their
careers. Rather, they pass through dif‌ferent career phases which af‌fect their
attitudes, organizational commitment, perception of the job, and ultimately,
their performance (Barker, 1998; McElroy, Morrow, & Wardlow, 1999).
Intuitively, many police supervisors may suspect that older of‌f‌icers are less pro-
ductive than newer of‌f‌icers, but questions remain. This article analyzes the fol-
lowing queries: What is the overall career productivity trajectory of an average
generalist patrol of‌f‌icer (i.e., is the trajectory monotonic or curvilinear) and when
do the most signif‌icant increases or decreases in productivity occur?
Answering these questions not only helps agencies to quantify productivity
losses and gains across time but also allows them to establish a productivity
baseline against which to measure their own of‌f‌icers. Additionally, this informa-
tion may help agencies more accurately forecast expected performance declines
and prevent lagging productivity through interventions, such as career planning
and development or patrol reassignment. Finally, prior research has proposed
that certain stages characterize a police of‌f‌icer’s career, and this study provides a
quantitative, empirical test of those theories.
Literature Review
Measures of Patrol Officer Productivity
Hatry (1976) identif‌ied two main dimensions of worker productivity: ef‌fective-
ness and ef‌f‌iciency. Ef‌fectiveness refers to an organization’s quality of service,
whereas ef‌f‌iciency measures an organization’s ability to maximize outputs while
using the minimum amount of resources. Traditionally, both law enforcement
agencies and police scholars have evaluated police productivity using measures
of ef‌f‌iciency. These variables are easier to record and track, such as the number
of arrests, calls for service (CFS), or traf‌f‌ic citations, and ef‌f‌iciency-based data
are often more available than measures of ef‌fectiveness.
However, before discussing specif‌ic measures of productivity, we recognize
that policy makers and scholars have begun broadening traditional measures of
patrol of‌f‌icer performance to include many other aspects of policing. Gorby
(2013) argues that traditional measures are inadequate because they ‘‘fail to
provide an accurate evaluation, as most performance in policing is subjective
and dif‌f‌icult to measure’’ (p. 392). Some research has found that traditional
measures of extremely productive of‌f‌icers (i.e., those with high arrest activity)
may actually be correlated with citizen complaints about excessive force (Brandl,
Stroshine, & Frank, 2001), while other studies have found that in smaller juris-
dictions, police chiefs view high arrest rates and citation rates as potential

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166
Police Quarterly 20(2)
indicators of poor performance (Sanders, 2010). To put the point more broadly,
if traditional police ef‌f‌iciency measures are misconstrued or abused, they will not
validly assess the function of the police in society (Fielding & Innes, 2007).
Consequently, many police departments are moving beyond raw arrest data to
more ef‌fectiveness-based measures of performance, including not only commu-
nity crime rates but also use of force incidents, citizen complaints, and customer
satisfaction, among many others (Davis, Ortiz, Euler, & Kuykendall, 2015).
Nonetheless, scholars note that analyzing raw productivity outputs remains
as a useful, valid method for evaluating patrol of‌f‌icers (Behn, 2003; Wang,
Vardalis, & Cohn, 2000), so long as supervisors and agencies evaluate patrol
of‌f‌icers in other dimensions, such as ethics, misconduct, and of‌f‌icer–citizen inter-
actions. Self-initiated activities compose a large portion of a patrol of‌f‌icer’s
daily tasks (Famega, Frank, & Mazerolle, 2005), and analyzing arrest and cit-
ation rates still gives police supervisors a method of identifying proactive and
indolent of‌f‌icers. Moreover, productivity and ef‌f‌iciency metrics remain as
core components of CALEA1 performance dimensions (Davis et al., 2015).
While obsessing over an of‌f‌icer’s number of misdemeanor arrests is a myopic
evaluation of that of‌f‌icer’s abilities and use of time, traditional measures of
patrol of‌f‌icer productivity still include a wide variety of activities that accurately
gauge how of‌f‌icers spend their time and how communities benef‌it from
their activities. In fact, one could argue a police department’s response to
many quality of life aspects can be measured by traditional police measures.
It seems reasonable that citizens want to live in communities with low levels
of narcotics traf‌f‌icking, motor vehicle collisions, and robberies (for instance),
and thus, citizens expect of‌f‌icers to arrest drug dealers, conduct traf‌f‌ic enforce-
ment, and apprehend thieves and robbers. Of‌f‌icers can counter accusations of
indolence by displaying the number of narcotics arrests, traf‌f‌ic citations and
warnings, and misdemeanor and felony arrests. True, these are traditional meas-
ures of policing, but they demonstrate to both the public and police supervisors
that they are not simply taking CFS and wasting time which could be spent on
self-initiated activities.
Numerous studies have examined patrol of‌f‌icer productivity using raw arrest
outputs, acknowledging that arrests are the most basic and most readily avail-
able performance indicator (Chappell, MacDonald, & Manz, 2006; Crank,
1990). Other studies have used traf‌f‌ic citation rates and drug arrests to estimate
productivity (Johnson, 2009, 2011), as well as clearance rates made by arrests
and subsequent crime reduction (Garicano & Heaton, 2010).
More recent approaches have analyzed arrest raw outputs in more sophisti-
cated ways. For example, Van Meter’s (2001) zero-based approach analyzes not
only an of‌f‌icer’s productive use of time, but also nonscheduled absenteeism, and
the cost of preventable errors and remedial training. Other police scholars have
used Z-score summaries of arrests, citations, and traf‌f‌ic stops (among other
outputs) to evaluate patrol of‌f‌icers (Shane, 2011). This method allows

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Bonkiewicz
167
supervisors and agencies to evaluate an of‌f‌icer’s outputs relative to department
averages. Some police agencies have completely overhauled their evaluation
metrics and implemented performance assessment review systems which f‌lag
of‌f‌icers who exceed certain performance or productivity thresholds (e.g., use
of force incidents or citations issued; Davis, Henderson, & Ortiz, 2005; Ortiz,
Henderson, Miller, & Massie, 2002).
In introducing a metric called Value Over Replacement Cop (VORC),
Bonkiewicz (2015) identif‌ied several issues with current patrol of‌f‌icer productiv-
ity metrics. First, many metrics do not account for the diverse number of patrol
activities, instead focusing only on a few outputs or activities. Second, agencies
and metrics frequently do not prioritize and weight these outputs; a multifelony
arrest of a sex of‌fender or narcotics traf‌f‌icker, for example, involves more work,
greater investigative skill, and may benef‌it the community more than a simple
traf‌f‌ic warning. Third, existing metrics and methods consistently fail to evaluate
patrol of‌f‌icers in terms of their productive time (Hatry, 1976). Patrol of‌f‌icers
handle CFS, write reports, and assist other of‌f‌icers—activities which all decrease
the amount of time available to write tickets, conduct investigative f‌ield contacts,
and make arrests....