Crime Science Approach to Organised Crime

497

Further Discussion

Beyond the Network: A Crime ScienceApproach to Organized CrimeGordon Stovin∗ and Chris Davies∗∗

Gordon Stovin and Chris Davies are crime intelligence analysts at West Mercia Constabulary. In this article, they respond toFelia Allum’s commentary on the current state of research and practice around the subject of organized crime1 in which shesurmised that ‘. . . communication between the academic community and law enforcement agencies . . . remains poor.’ Theauthors agree with this statement and argue that in their capacity as practitioners they are trying to do something about this.Much of the current literature on organized crime appears to start and stop at a descriptive level with few empirical studies.This description does not always benefit the practitioner and rarely informs the law enforcement response to organized crimebeyond describing the criminal network. This paper tests the use of Ratcliffe’s hotspot matrix2 as a toolkit for understandingthe role that place and time play within an organized criminal network.

IntroductionThe fact that organized crime is on the UK polic-ing agenda is undisputable and is evidenced by theneed to dedicate an entire edition of OUP’s Polic-ing journal to the subject matter (Neyroud andWaddington, 2008). The fact that the subject oforganized crime warrants further research is sim-ilarly stark and unavoidable. In 2005, Her Majesty’sInspectorate of Constabulary (HMIC) publishedClosing the Gap,3 in which the UK police forces’ability to fully understand, let alone deal withthe problem of organized crime, was called intoquestion:

. . . it is worrying that so many gaps ex-ist in our knowledge of organized crim-

∗Gordon Stovin, Principal Crime Intelligence Analyst, West Mercia Constabulary HQ, Worcester, UK. E-mail: [email protected]∗∗Chris Davies, Intelligence Analyst (Serious & Organised Crime Unit) West Mercia Constabulary HQ, Worcester, UK.

1 Allum (2008).2 Ratcliffe (2004).3 HMIC (2005).

inal enterprises and markets---withoutdetailed, sophisticated analysis of thistier of criminality forces cannot targeteffectively those who pose the greatestrisks to communities and the economy.

Fortunately, law enforcement within the UK hasmoved on and there are examples of progressbeing made since this report. One such example isthe home grown attempt at understanding the UKorganized crime problem through the introductionof an organized crime group mapping methodologyreferred to by Gilmour (2008). Gilmour’s article it-self clearly shows the capacity and willingness of theUK police to understand organized crime from bothpractitioner and academic corners. However, this

Policing, Volume 2, Number 4, pp. 497–505doi: 10.1093/police/pan062C© The Authors 2008. Published by Oxford University Press on behalf of CSF Associates: Publius, Inc. All rights reserved.For permissions please e-mail: [email protected]

by guest on February 15, 2011

policing.oxfordjournals.orgD

ownloaded from

http://policing.oxfordjournals.org/

498 Policing Article G. Stovin and C. Davies

combined research, seeking to find ways in whichunderstanding organized crime takes law enforce-ment forward in actually tackling this criminality,is in a minority. Allum (2008) identified the lackof communication between academia and law en-forcement within the UK, an argument that Pease(2008) seems to take forward in his call for morecrime science.

An opportunity for crime scienceIt is possible to group much of the available literatureon organized crime into four key themes:

� Network analysis� Legislation� Links to terrorism� Case studies.

We must confess from the outset that this is a hugegeneralization on the available literature and thatthis article does not seek to serve as a comprehensivereview on the subject.4

Organized crime groups are often described bymeans of network analysis, a practice that is popula-rized within the intelligence community. Such net-work diagrams are an ubiquitous way of describingorganized crime groups and lend themselves to thefield of social network analysis (SNA). The work ofindividuals such as Malm (2006) and Bichler andMalm (2008) offers demonstrable examples of theinsight that SNA can bring to the understandingof organized crime in highlighting possible intelli-gence, prevention and enforcement opportunities.However, such charts are static and lack some of theimportant crime science features such as time andplace.

Studies have also been published on the impactof legislation in the fight against organized crime.

4 For a more useful review of the literature, refer to Gabor (2003).5 Proceeds of Crime Act 2002, available online at http://www.opsi.gov.uk/acts/acts2002/ukpga 20020029 en 1 (accessed 16September 2008).6 Home Office, 2006.7 There are so many. This website provides a very comprehensive list of interesting literature: http://www.yorku.ca/nathanson/bibliography/genres.htm (accessed 28 August 2008).

Like many other countries, the UK has sought totake the financial incentive out of crime with theintroduction of the 2002 Proceeds of Crime Act.5 Avariety of studies have sought to provide commenton the effectiveness of such types of legislation (e.g.Favarel-Garrigues et al., 2008; Sproat, 2007)6 andwhilst commentary on the effectiveness of legislationis undoubtedly useful to those involved in socialand legal policy, its immediate utility within lawenforcement is considerably less so---at best, in lawenforcement it serves to illustrate the limitations ofsuch legislation.

Organized crime is frequently compared with orlinked to terrorism. Cynical authors might suggestthat the link between terrorism and organized crimereflects the current climate in which terrorism oftentakes centre stage. Ridley (2008) provides a refresh-ing view where the linkages between these two crimephenomena are called into question. But when con-sidering evidence of any cross-over to one side, weshould ask how much these comparisons help whentrying to understand organized crime, with a viewto tackling it.

Finally, there are case studies of organized crimegroups and, generally, the enforcement initiativesused against them.7 These studies are extremely use-ful in understanding approaches to crime controlthat have been employed, and provide an insightinto the nature of the criminal organization (e.g.Huisman, 2008). However, these examples can beliethe varied nature of organized crime (von Lampe,2008) and, if the groups within these case studieswere viewed as representative of all organized crime,one would be forgiven for having a slightly skewedview of what an organized crime group is. Thiseffect is potentially further compounded by whatFelson (2006) refers to as the ‘TV fallacy’ where law



ownloaded from


A Crime Science Approach to Organized Crime Article Policing 499

enforcement might be fooled into considering orga-nized crime solely in terms of rigid hierarchical orfamilial structures.

Under no circumstances are any of the themesconsidered as redundant to the law enforcementpractitioner---some are just more immediately use-ful than others. However, there is an opportunityto further our understanding of organized crime,taking a crime science approach, with the expressview of providing that insight that will assist law en-forcement intervention. This paper does not seek todefine crime science8 or argue its case as a disciplineseparate to criminology---Pease (2008) has alreadydone that far more eloquently than we could. Thefollowing example demonstrates what the authorsbelieve is an example of the crime science approachto organized crime.

BackgroundWe have already outlined that organized crimegroups are often described using a form of SNA withresulting charts depicting the criminals involved andthe context in which they know and interact withone another. This is a widely accepted approach for‘mapping’ organized crime groups and is referred toby Gilmour (2008) as a ‘business-as-usual’ approachto organized crime. This work seeks to build on thisprocess.

Whilst the network-based approach is clearly auseful one and lends itself to understanding an or-ganized crime network, this type of ‘mapping’ hasits limits, specifically with respect to the inabilityof the chart to explain the extent of any ‘criminalcooperation’ and the nature of the organized crimeproblem (Felson, 2006).

8 For definition, see Laycock (2003) available at http://www.jdi.ucl.ac.uk/publications/short reports/launching.php (accessed16 September 2008).9 Ratcliffe’s hotspot matrix (2004) is a system for identifying and classifying the spatial and temporal components of crimehotspots. Three categories of spatial hotspot (dispersed, clustered or hotpoint) and three categories of temporal hotspot(diffused, focussed or acute) are combined to form a 3 × 3 hotspot matrix. Describing a crime problem using this matrixapproach enables operational commanders and crime prevention practitioners to infer the nature of the law enforcementresponse. It can also be used to suggest the type prevention, intelligence or enforcement response. The matrix itself handilysurmises the typologies of hotspot and reduces much of the perceived complexity around spatiotemporal analysis intosomething that is easy to communicate. Furthermore, this does not require a particular geographic information system onwhich to run.

Similarly, crime hotspots---maps depicting areasof relatively high offence density---are an equallyubiquitous part of the intelligence-led approach totackling volume crime as they allow for law en-forcement agencies to direct their resources to ar-eas with the highest need. Furthermore, the natureof the hotspot in terms of its spatial and temporalcomponents is likely to inform the law enforcementresponse in order to tackle the problem (Ratcliffe,2004). It is our assertion that whilst the use of net-work analysis is almost commonplace amongst prac-titioners tackling organized crime, the use of hotspottechniques is considerably less so. Where the tempo-ral or geographic qualities of organized crime groupsare considered, they appear to be confined to otheraspects of crime and disorder that infer organizedcrime and not the organized criminal activity itself,which is largely unreported. For example, acquisi-tive crimes are often mapped to infer the locationand impact of a controlled drug market whereas thedrug dealing activity is rarely studied for its spatialand temporal qualities.

This study seeks to examine the feasibility of usingRatcliffe’s ‘hotspot matrix’9 by applying this useabletoolkit to spatially and temporally coded intelligencereports relating to organized crime.

MethodA sample of 15 organized crime groups, whose pri-mary area of criminality related to controlled drugs,were selected to examine the utility of the hotspotmatrix when applied to organized crime. Drugs net-works were selected for practical purposes---that isa prevalence of identifiable networks---and also be-cause the activity engaged in by these groups was



ownloaded from



not immediately evident from the reported crimefigures.

The networks themselves were chosen with as lit-tle previous knowledge of the group members aspossible to avoid any resulting bias. Each of the 15crime groups used:

� Were selected around a key individual with onlytheir immediate criminal associates includedwithin the resulting crime group.

� Consisted of members who were linked by re-cent intelligence to the supply of controlleddrugs. That is, specific intelligence reports(submitted during 2007) detailing the groupmembers involvement in drug supply. Thismainly related to Class ‘A’ and typically in-volved heroin as a commodity, although notexclusively.

� Were deemed to consist of organized criminals/people capable of committing organized crime.In each case, the criteria for organized crimeoutlined by Cornish and Clarke (2002) wereapplied as a litmus test to the group’s activities.As groups, they also displayed at least six of thecharacteristics identified by Van der Heijden(1996) as being essential for the group to beconsidered to be organized.

The resulting groups averaged thirteen membersand ranged from groups as small as six to one with23 members.

Once the groups were selected, all intelligence re-ports relating to all group members for each of thegroups were retrieved for a 12-month period (inthis case the calendar year 2007). This resulted in atotal of 4,874 intelligence reports. The numbers ofsuch reports varied from one group to another andranged from as few as 98 intelligence reports on onegroup to as many as 788 reports for another. Eachof these reports were then assessed for any spatialand temporal components, that is, any reference toa mappable location and also reference to a specificdate. A summary of the crime groups, their size, to-

10 For a comprehensive review of this method, refer to Chainey et al. (2002).

tal number of intelligence reports and number ofthose that contained both useable spatial and tem-poral information are included within the findingssection of this paper (see Figure 1).

Those intelligence reports containing both spatialand temporal elements were then mapped using ageographical information system and subject to fur-ther spatial and temporal analysis, in order to allowthe hotspot classification necessary to use Ratcliffe’shotspot matrix. The first part of this classificationprocess involved the production of simple kerneldensity estimation hotspots10 and was created fromthe mapped intelligence reports. It is beyond thescope of this paper to detail the pros and cons of thishotspot technique. However, it was selected becauseit is a commonly used method of identifying hotspotareas for crime within UK law enforcement. Wherehotspots were identifiable using this method, thesewere then reexamined by overlaying the point dataonto the area identified as being a hotspot. By ex-amining the distribution of the point data (i.e. theintelligence reports) within the hotspot, Ratcliffe’scriteria could be applied. This allowed each hotspotto be described as being either of the following:

� Dispersed---the points that make up thehotspot were dispersed throughout the hotspotarea.

� Clustered---the points that make up the hotspotshowed clear evidence of clustering at one ormore points within the hotspot area.

� Hotpoint---all the points that make up thehotspot were co-located at the same point (inthe centre of a circular hotspot).

Once classified in this manner, the hotspots werethen examined for their temporal aspects. This wasachieved by using simple peak time analysis relatingto the day of the week that the intelligence reportsreferred to. Day of week was decided upon for twopractical reasons, the first being that the availabledata did not frequently lend itself to any greaterlevel of detail (e.g. time of day). It was also felt that



ownloaded from



NameMembership(number in

group)

Total number of intelligence reports

Number that have spatial

and temporal components

%-age of 'mappable'intelligence

reports

OCG1 7 247 88 35.63%OCG2 23 420 88 20.95%OCG3 13 310 69 22.26%OCG4 7 174 25 14.37%OCG5 9 173 43 24.86%OCG6 23 543 81 14.92%OCG7 16 483 84 17.39%OCG8 14 177 50 28.25%OCG9 14 788 193 24.49%OCG10 6 98 21 21.43%OCG11 11 237 67 28.27%OCG12 15 511 74 14.48%OCG13 9 167 65 38.92%OCG14 10 308 127 41.23%OCG15 13 238 49 20.59%Total 190 4874 1124 23.06%

Figure 1: Summary table of organized crime groups

day of the week would provide the appropriate levelof information to operational decision makers whendeciding on the nature of the law enforcement re-sponse. It is worth noting that this was the day of theweek that the intelligence report referred to and notthe day of the week when it was reported or created.

The hotspots were then further classified based onthe temporal analysis and using Ratcliffe’s criteria,as either of the following:

� Diffused---the intelligence reports relate tomost, if not all, days of the week with no clearlyobvious risk presented on any one particularday.

� Focussed---although the intelligence reports re-late to most, if not all, days of the week there isan increased level of risk attributable to one ormore days.

� Acute---the intelligence reports clearly relate tojust one or two days and no others.

In this way, each of the hotspots identified fromintelligence reports for each of the 15 crime groupscould be categorized using the hotspot matrix.

Methodological issuesFrom the outset we needed to be mindful of thenature of what we were trying to map, namely, in-telligence. The practice of intelligence is often per-ceived by other areas of law enforcement as a shady,clandestine or morally dubious activity (Ratcliffe,2008a) and there can be little doubt that the sourcesof this intelligence are considered in much the sameway. Cope (2004) outlines the problems associatedwith striving for intelligence-led policing but be-ing faced with policing-led intelligence. This, theauthors strongly believe, is an inherent limitation ofany intelligence-based approach to organized crime.However, by using intelligence in a strategic mannerto understand and inform decision making whentackling organized crime, a fundamental step ismade towards applying an intelligence-led approachto law enforcement (Ratcliffe, 2008b; Ratcliffe andGuidetti, 2008).

The problems with intelligence aside, there werealso classification issues raised when trying to de-scribe each hotspot using the hotspot matrix. A lackof definitive rules for classification leads to some



ownloaded from



inevitable debate over which ‘box’ to put the or-ganized crime group in. Furthermore, some crimegroups could be put in more than one box, withmultiple hotspots identifiable for more than oneorganized crime group. According to Chainey andRatcliffe (2005): ‘The key is not to get hung up onexact definitions of each type of spatial and tempo-ral pattern . . . there may be some value in identi-fying crime hotspots that lie on the boundaries . . .’.Relieved to find this quote, we felt that the debateitself, to which part of the matrix the hotspot mostbelonged, was extremely beneficial. Trying to un-derstand the differences between the two spatial ortemporal patterns was, the authors felt, an impor-tant step towards understanding the nature of thecrime group.

FindingsOf the 15 organized crime groups used for thisstudy, two lacked sufficient available intelligence tobe examined for either their spatial or temporalqualities---namely OCG4 and OCG10 (see Figure 1).

Whilst the size of the crime groups in terms ofmembership and the numbers of intelligence reportsattributed to them varied considerably, it was feltthat this was a good reflection of the varied natureof organized crime. Of considerable interest was thequantity and proportion of the intelligence reportsthat could be used to map the intelligence and pop-ulate the hotspot matrix. More is made of this in thecommentary section. Suffice to say, an overall ‘map-pable’ rate of 23% was thought to be a very positivestart.

Figure 2 provides a summary of the hotspotsthat each of the remaining 13 crime groups dis-played. It is notable that each of the remaining crimegroups displayed at least one hotspot and that eachof these could be categorized using the hotspot ma-trix. Three of the ‘boxes’ within the matrix werenot populated using the available 13 crime groups.However, each of the spatial and temporal categories

11 Whilst it appeared to be a diffused hotspot the points all lay along one road and might therefore be interpreted as clustered.12 Which is what that the authors feel this study represents.

could be evidenced using one or more of the crimegroups. Groups 5, 12 and 15 each displayed two dif-ferent types of hotspot whereas group 13 was, wefelt, on the border between two of the spatial cate-gories depending on whether the data points wereinterpreted.11 Please note that it was not felt thata group-by-group description of each hotspot wasnecessary (complete with maps showing hotspotsand temporal patterns); however, they are available.

Commentary and conclusionsWe believe that there are four key implications ofthis work:

� The utility of the hotspot matrix� The strategic role of intelligence� Going beyond the network approach to orga-

nized crime� The opportunity for crime science.

Firstly, as a proof of concept,12 there is utility inusing Ratcliffe’s hotspot matrix (2004) to describeorganized crime phenomena as both place and timecan play a role in seeking to understand an organizedcrime network for the purpose of law enforcement.There are logistical benefits from looking at orga-nized criminality using this technique. For example,this could be used to understand where and whenfuture intelligence assets might be deployed so asto have a better chance of locating the targets. Itcould also be used to help avoid so called ‘blue onblue’ situations. However, in order to go beyond thisoperational planning stage, it is important that theposition of the organized crime group within thehotspot matrix can be translated into some kind oflaw enforcement response. Figure 3 provides someindication of how this might look; however, we muststress that it was not the aim of this study to drawup a definitive response menu.

Secondly, this study shows that intelligence can beviewed in much the same way as offence or incident



ownloaded from



Figure 2: Summary of organized crime group classification using Ratcliffe’s hotspot matrix (2004)

data and is therefore subject to spatial and temporalanalysis. Ultimately, it can allow the criminality itrefers to, to be categorized using the hotspot matrix,which in turn can be used to inform the law en-forcement response. Just under a quarter of all theintelligence reports reviewed whilst carrying out thisstudy contained information about where and when(and not just who, what, why and how). This re-search shows that, where present, spatial and tempo-ral information can have strategic as well as tacticalimplications and thus form part of an intelligence-led response to organized crime (Ratcliffe, 2008b).The authors suggest that by increasing awareness onhow place and time can be used to inform opera-tional decision making, beyond simply reacting tothe intelligence, a greater emphasis is placed on theprevalence and reliability of this information withinthe intelligence reports.

13 Presented at the International Crime Science Conference, London, 2008. Included as personal communication with theauthor.

Spatial and temporal patterns are identifiable fororganized criminal networks and these would bemissed if a solely network-based approach to or-ganized crime was adopted. The title of this paper,going beyond the network, was a deliberate suggestionon our part that place and time are important andoverlooked in the field of organized crime. How-ever, we are not professing to be the only peoplelaying this claim with empirical research. Rossmo’srecent work on the geographic profiles of terroristattacks13 and McCord and Ratcliffe’s (2007) study ofdrug markets in Philadelphia are both examples ofthe importance of place within organized criminalnetworks.

Finally, we see this as an example of taking acrime science approach to understanding organizedcrime, one that seeks to use existing theories that canbe related to organized crime and test these using



ownloaded from



Figure 3: Example of a possible response guide for organized crime groups

empirical data with the explicit view to informingthe law enforcement response.

ReferencesAllum, F. (2008). “Special Edition on Organized Crime:

Editorial.” Policing 2: 2–6.

Bichler, G. and Malm, A. (2008). “A Social Net-work Analysis of the Evolution of the Environmen-tal Criminology and Crime Analysis (Ecca) Sympo-siums.” Crime Patterns and Analysis 1: 1. Availableat http://eccajournal.org/V1N1S2008/Bichler and Malm.pdf (accessed 16 September 2008).

Chainey, S. and Ratcliffe, J. H. (2005). GIS and Crime Map-ping. Chichester: Wiley.

Chainey, S. P., Reid, S., and Stuart, N. (2002). “When is aHotspot a Hotspot? A Procedure for Creating StatisticallyRobust Hotspot Maps of Crime.” In Higgs, G. (ed.), Inno-vations in GIS 9. London: Taylor and Francis.

Cope, N. (2004). “Intelligence Led Policing or Policing Led In-telligence? Integrating Volume Crime Analysis into Polic-ing.” British Journal of Criminology 44(2): 188–203.

Cornish, D. B. and Clarke, R. V. (2002). “Analyzing Or-ganized Crimes.” In Piquero, A. R. and Tibbetts, S. G.

(eds), Rational Choice and Criminal Behaviour: Recent Re-search and Future Challenges. New York: Routledge, pp. 41–63.

Favarel-Garrigues, G., Godefroy, T., and Lascoumes, P.(2008). “Sentinels in the Banking Industry: Private Ac-tors and the Fight against Money Laundering in France.”British Journal of Criminology 48: 1–19.

Felson, M. (2006). “The Ecosystem for Organized Crime.”HEUNI Paper No. 26, HEUNI, Helsinki.

Gabor, T. (2003). “Assessing the Effectiveness of OrganizedCrime Control Strategies: A Review of the Literature.”Department of Justice, Ottawa, ON, Canada.

Gilmour, S. (2008) “Understanding Organized Crime: ALocal Perspective.” Policing 2(1): 18–27.

HMIC. (2005). “Closing the Gap: A Review of the Fit-ness for the Purpose of the Current Structure of Polic-ing in England and Wales.” Home Office, London.Available at http://police.homeoffice.gov.uk/publications/police-reform/Closing the Gap 2005.pdf (accessed 16September 2008).

Home Office. (2006). New Powers Against Organised and Fi-nancial Crime. London: Stationery Office.

Huisman, S. (2008). “Investigating Chinese Crime En-trepreneurs.” Policing 2: 36–42.



ownloaded from



Laycock, G. (2003). Launching Crime Science. London: Jill Da-ndo Institute of Crime Science, University College London.

Malm, A. (2006). Marijuana Cultivation in British Columbia:Using Spatial and Social Network Analysis Techniquesto Inform Evidence-Based Policy and Planning. Ph.D.thesis, School of Criminology, Simon Fraser University,Canada.

McCord, E. S. and Ratcliffe, J. H. (2007). A Micro-SpatialAnalysis of the Demographic and Criminogenic Envi-ronment of Drug Markets in Philadelphia, Australianand New Zealand.” Journal of Criminology 40(1): 43–63.

Neyroud, P. and Waddington, P. A. J. (2008). “Special Editionon Organized Crime: Introduction.” Policing 2: 1–2.

Pease, K. (2008). “How to Behave Like a Scientist?” Policing2: 154–159.

Ratcliffe, J. H. (2004). “The Hotspot Matrix: A Frameworkfor the Spatio-temporal Targeting of Crime Reduction.”Police Practice and Research 5: 5–23.

Ratcliffe, J. H. (2008a). “Intelligence-Led Policing.” InWortley, R., Mazerolle, L., and Rombouts, S. (eds), En-

vironmental Criminology and Crime Analysis. Cullompton,Devon: Willan.

Ratcliffe, J. H. (2008b). Intelligence-Led Policing. Cullompton:Willan.

Ratcliffe, J. H. and Guidetti, R. (2008). “State Police Investiga-tive Structure and the Adoption of Intelligence-Led Polic-ing.” Policing: An International Journal of Police Strategiesand Management 31(1): 109–128.

Ridley, N. (2008). “Organized Crime, Money Laundering andTerrorism.” Policing 2: 28–35.

Sproat, P. A. (2007). “An Evaluation of the UK’s Anti-moneyLaundering and Asset Recovery Regime.” Crime Law andSocial Change 47(3): 169–184.

Van Der Heijden, T. (1996). “Measuring Organized Crimein Western Europe.” In Pagon, M. (ed.), Policing in Cen-tral and Eastern Europe: Comparing First Hand Knowledgewith Experience from the West. Slovenia: College of Policeand Security Studies. Available at http://www.ncjrs.gov/policing (accessed 16 September 2008).

Von Lampe, K. (2008). “Organized Crime in Europe: Con-ceptions and Realities.” Policing 2: 7/17.



ownloaded from


Documents

Crime Science Approach to Organised Crime