Intelligence - Led Policing:
How the Use Of Crime Intelligence Analysis Translates in to the Decision-Making
findings provide the reader with a hierarchical picture of difference within the organizational
decision-making process. Regarding the main explanatory variables, it is found that among the
six crime analysis functions, the statistical analysis, crime analysis, and intelligence analysis
functions were consistently associated with all of the dependent variables. Survey analysis
is significantly associated only with command-level managers’ decision-making, whereas
patrol strategy analysis is significantly associated with both command-level managers’
and patrol officers’ decision-making within the organization. Finally, displacement/diffusion
analysis is not significantly associated with any of the dependent variables.
As indicated above, survey analysis is associated only with the highest level of
decision-making within the organization. This latent variable was a factor loading for analyses
of citizen surveys, environmental surveys, employee surveys, and victim surveys. Therefore,
it makes sense that the highest level of ranking personnel within the organization would pay
more attention to the results of such surveys. Put differently, what the citizens, for example,
think about the organization would not matter to detectives and patrol officers as much as
it would to command-level managers. Secondly, patrol strategy analysis is associated with
command-level and street-level decision-making but not with the detective level. Usually,
command-level managers set the strategy for patrol based on the crime analysis output,
and patrol officers adjust their patrol path and time accordingly. However, detectives who
conduct investigation may not find the output of patrol strategy analysis to be relevant to
or helpful for their investigations. Overall, these significant findings support the literature
(Demir, 2009; Mamalian & LaVigne, 1999; Reinier et al., 1977).
Displacement/diffusion analysis was not significantly associated with any of the
dependent variables. One of the explanations could be that this type of analysis might not
be used widely and actively but only conceptually on paper. In other words, for a study in
2000, that type of crime analysis might not have been commonly or frequently used. Another
explanation could be that this type of crime analysis might not be considered applicable or
useable by police personnel. For instance, in policing, the “maps are only relevant when
they are seen as valuable in use, needed for something [italics added]. Metaphorically,
databases and their links, the terminals, even computers, are really only ‘dumb pipes’
through which data flow. They represent capacity, future utility, but they must be implicated
in some process to become useful” (Manning, 2001: 99).
The current study found that having a crime analysis unit within a law enforcement
agency matters at all levels of organizational decision-making. Put differently, when an
organization has a crime analysis unit, the command-level managers, patrol officers, and
detectives are perceived to use crime analysis efforts in organizational decision-making. This is
the only control variable that is significantly associated with all of the dependent variables. This
finding makes sense, as these consumers or clients (i.e., decision-makers) are the ones who
may benefit by interacting with the crime analysis unit. However, this finding does not shed
light on where in the organizational structure a crime analysis unit would be more effective.
Although there were significant findings and arguments about unions in the literature
(Goldstein, 1979; Guyot, 1991; Kadleck, 2001; Sadd & Grinc, 1996; Walker, 1992; Walker
& Katz, 2005; Zhao & Truman, 1997), no significant relationship was observed in the current
study. Similarly, police organizational literature (King, 1998; Langworthy, 1986; Maguire,
International Journal of Security and Terrorism • Volume: 4 (1)
1997, 2003; Zhao, 1996) used agency size and/or hierarchy in various models as critical
variables, where these variables were mostly found to be significant. In the current study,
agency size was significantly and negatively associated only with patrol officers’ decision-
making. Hierarchy, on the other hand, was not significantly associated with any of the
The authors of the crime analysis survey data set, O’Shea and Nicholls (2002, 2003)
controlled for crime on the quality of crime analysis, which was not significant. Similarly,
the researchers in the current study controlled for crime on the organizational decision-
making variable, but crime was not significant. However, in one sense, because the main
triggering event in the United States that led to the intelligence-led policing movement was
an external terrorist attack (i.e., a crime), it was hoped that crime also would matter in the
models studied. Finally, controlling for agency budget also made no significant difference
in the models. The world is experiencing financially critical times, where budget is expected
to be associated with the dependent variables in the current study. In that regard, would
the agency budget variable make any difference on organizational decision-making in Great
Britain, where financial constraints in the United Kingdom was one of the main reasons for
the development of intelligence-led policing?
Overall, the current study has contributed to the literature by doing a partial testing of
one version of intelligence-led policing. First, the 3-i model has not been empirically tested
before, even partially, although it was discussed in the literature and applied to policing in
agencies such as the New Jersey State Police and the Australian Police Forces (Ratcliffe,
2002, 2003). The findings in this study support the 3-i model of intelligence-led policing,
which holds that there is an association between crime intelligence analysis and decision-
This study is the beginning of further attempts and studies for the researchers, as it prompted
him to ask more questions that need answers. Intelligence analysis, crime analysis, and
statistical analysis can be effective tools in the organizational decision-making process,
regardless of the rank of the person making decisions. For instance, command-level
managers can make decisions about operational planning, personnel deployment, resource
allocation, shift hours, and the like based on the results of the three types of analysis (i.e.,
intelligence, crime, and statistical). Detectives, on the other hand, can strategically narrow
the focus of their investigations rather approach them in a broader, more random way that
may require more time and effort. For example, if the analysis results indicate a link between
the suspect and a convenience store in a particular area with a pattern of criminal activity,
detectives can focus more of their efforts on that area and operate more efficiently. Finally,
patrol officers may be more alert in particular areas of the community, at particular times,
and about particular individual profiles based on the analysis product, rather than randomly
patrol their precinct. In that regard, the findings of the current study have implications for all
three levels, or ranks, in the hierarchical structure of policing.
As indicated previously, because the current study only partially tested the 3-i model,
the other part of the model still needs to be tested. The researchers tested the association
of crime analysis functions with the decision-making component only. The criminal
environment and its subjects should be studied and explored carefully with appropriate data
and methodology in order to see the whole picture of 3-i model. It is hoped that this study
will encourage scholars to conduct further studies that test the effectiveness and efficiency
of this most recent and popular policing model. Moreover, further research is still required to
determine how effective crime analysis functions and efforts are in terms of organizational
decision-making, as the literature is lacking in this area.
In conclusion, any new policing model should be selected, applied, and implemented
cautiously, patiently, and smartly. As Goldstein (1990) wrote: “Since the benefits of change
[, if any,] are not immediately demonstrable, new approaches are vulnerable to attacks
arising from ignorance of the complexity of policing, an intolerance of the unfamiliar, and a
lack of patience” (p. 50). Therefore, the investment should be a smart choice that does not
lead to inefficiency and ineffectiveness. The selected policing model should have at its center
the analytical techniques and tools that support the decision-making process in dealing with
crime and criminals both proactively and reactively.
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