As part of a larger study on ranger culture and operations, this present research is a process evaluation of the intelligence approach utilised by the UWA. As opposed to an impact or outcome evaluation, which involves measuring the problem and systematically comparing changes based on an evaluation design (Eck 2011), a process evaluation focusses on examining “the underlying processes of what took place during a crime reduction initiative” (Ratcliffe 2008, p. 189). In essence, a process evaluation assesses how a program is implemented (Gibbs et al. 2015).
Data collection occurred in July and August 2014. As part of the study, the author met with top management at the UWA headquarters in Kampala, the capital and largest city in Uganda, to discuss the current state of intelligence initiatives within the organisation, as well as what is required for the development of a dedicated crime and/or intelligence units within the various conservation areas located throughout the country. Considerable time was also spent interacting with rangers and management at a number of different national parks in Uganda, including Kibale, Lake Mburo, and Queen Elizabeth. It was felt that unless ground-level perspectives were collected, any discussion on the implementation of an intelligence-led approach or crime analysis unit would be moot given the variability in context and site-specific realities.
Formal interviews (n = 89) were conducted with law enforcement (including intelligence) and community conservation rangers and supervisors. Additionally, informal discussions with rangers from other departments (e.g. tourism) were also completed. Supplementing the formal interviews and informal discussions were the author’s own personal fieldnotes and narratives.
The status of crime and intelligence analysis within the UWA
Prior to discussing the current status of crime and intelligence analysis in the UWA, it is worth first mentioning the data collection and management practices of the UWA. A truism in crime and intelligence analysis is that an analysis is only as good as the data it is based on. In other words, analysis requires proper data management and is premised on the appropriate collecting, collating, and storing of data. Fortunately, the importance of data management is embedded within the UWA.
One type of data used to assess criminal activity by the UWA is patrol information. Data is collected through law enforcement monitoring (LEM) or ranger-based data collection (RBDC). LEM or RBDC is the practice of collecting data during patrols on illegal activities, wildlife, and the environmental status of the protected area (e.g. vegetation) through ranger patrols (Moreto et al. 2014). Such data is collected through GPS devices and uploaded into a centralised open-source database referred to as the Management Information System or MIST in order to assess trends. Recently, the UWA has begun to adopt the Spatial Monitoring and Reporting Tool (SMART). SMART is similar to MIST in that it is a bottom-up program that utilises RBDC, however, SMART provides advanced analytical capabilities to facilitate near real-time decision making and resource allocation.k,l In addition to this, the Wildlife Conservation Society (WCS) has developed an online Wildlife Crime Database that allows the UWA to track offenders, establish offender profiles, and track court cases.m
Although such data management programs are undoubtedly useful, a main limitation is the absence of analysts within the organisation. While the foregoing can provide insight and information, actionable intelligence requires the involvement of analysts. Moreover, crime and intelligence analysis should extend beyond simply looking and reporting information as analysts should be actively engaged in problem solving as well (Clarke and Eck 2005; Eck and Clarke 2013). In other words, analysis requires more than simply presenting or reporting information; it requires an attempt to better understand the intricacies of criminal activity, including the situational (e.g. spatiotemporal patterns) and individual (e.g. modus operandi) elements, as well as identify areas for prevention. Importantly, such analysis should be grounded and informed by theory, which is also currently lacking within the UWA.
While the UWA administration and management at the headquarters recognise the potential value of crime and intelligence analysis, such activities are not currently practised or utilised. This is partly attributed to limited resources and training available, as well as a lack of general knowledge of the area. Fortunately, the UWA has begun to engage in intelligence-related initiatives. In 2013, the UWA launched its intelligence unit, which is currently housed within the law enforcement department.n Trained in military intelligence, the UWA intelligence rangers are versed in counterintelligence, operational intelligence, criminal investigations, and information and evidence gathering. Intelligence rangers, however, are not trained in crime intelligence analysis.
The development of the WILD LEO pilot project is a step in the right direction to address the absence of analysts within the UWA.o The WILD LEO project involves the use of low-cost GPS cameras to document criminal activity during ranger patrols. The photographs are then mapped and analysed using open source GIS software by a trained crime analyst. Reports are then developed for tactical and strategic decision-making (see Lemieux 2015). What is unique about the WILD LEO project is that it also utilises an offender database with GPS-tagged photographs acting as supporting evidence for the UWA’s prosecution.
With MIST, SMART, an online Wildlife Crime Database, and the WILD LEO project, the UWA has the information technology foundation needed for crime and intelligence analysis to occur. However, unless analysts become a more central element within the organisation, the analytical capabilities of the agency will remain limited. Furthermore, with the exception of the Wildlife Crime Database, the information technology described above is also primarily focussed on conservation areas and does not extend or incorporate the UWA headquarters. Moreover, all have an explicit emphasis on the law enforcement department. Arguably, wildlife crime is not the sole responsibility of the law enforcement department and other departments within the agency can contribute information to help better understand illegal activities that threaten Uganda’s wildlife and PAs.
In essence, a conceptual framework and operational model for a cohesive intelligence-led approach is lacking within the UWA. Both a framework and a model are needed to guide the processes, designate the roles and responsibilities of key actors, ascertain avenues for required resources, training, and collaboration, and to help develop agency and department objectives and outcomes. Furthermore, without these, crime and intelligence analysis within UWA will achieve limited success.
Introducing an integrated intelligence-led conservation framework and the ranger analytic intelligence network
Developing intelligence-led conservation: a conceptual framework
Despite the potential benefits of a traditional ILP model, it is argued that an adapted model is required to accommodate the unique characteristics, objectives, organisational structure, available resources, and problems faced by the UWA. As the overall goal for the UWA is conservation and not policing, the development of a separate and unique intelligence-led conservation (ILC) framework is required. In other words, the apprehension of offenders and the prevention of criminal activity is only a part of the wider conservation agenda, which includes reducing human-wildlife conflict, developing community-based conservation initiatives and problem solving, and promoting tourism. Thus an ILC framework is introduced to adapt and extend the principles of ILP.
Importantly, an ILC approach promotes the notion that intelligence is not solely the responsibility of the law enforcement department nor is it only useful for crime-related purposes. Essentially, the notion that intelligence-led practices should be housed within one unit fails to take advantage of the resources both within and beyond the organisation and acknowledge the inter-related nature of conservation issues. ILC embraces a broad definition of intelligence by recognising that information useful for conservation can be found within the different units in the UWA. Further, an all-inclusive approach is required in order to utilise information that can be converted to actionable conservation intelligence by providing a more accurate measure of the UWA’s overall goal of conservation (i.e., arrests combined with wildlife population figures may provide more insight on the effectiveness of specific initiatives). Therefore, conservation intelligence is defined here as analysed information that combines crime analysis, criminal intelligence, wildlife and protected area information, and community-based knowledge for informed conservation initiatives.
Although the organisational structure of the UWA is favourable for establishing an ILC framework given its top-down paramilitary hierarchy and tourism business model, it currently does not have an intelligence-led agency-wide mandate. It is argued that the various departments within the UWA should be incorporated within an ILC framework since information originating from one department can also be useful to other departments. To efficiently and effectively utilise information obtained from rangers, community members, and other agencies, dedicated analysts must also be incorporated within the UWA. Analysts should be housed within different departments in each conservation area, as well as within the UWA headquarters to ensure that individual analysts are not overwhelmed. Moreover, analysts will be able to more readily guide rangers within their department on how to appropriately collect data and provide findings when approached. It is hoped that their familiarity with rangers within their department results in facilitating trust and respect, as well as reduce personnel issues that may occur if the analyst is not acclimated with the departmental culture (see below).
While analysts should also be trained according to the needs of their department, a general unified approach to data management would need to be established. This would help streamline information sharing between the departments and ensure data quality by reducing data- and human-related errors (e.g. improper data entry). Information can then be triangulated and contextualised to enrich organisation-wide intelligence as combined information on wildlife populations, community relations, and arrests can provide more insight than relying solely on one data source. Additionally, analysts should be responsible for reviewing and researching the relevant literature in order to conduct theoretically grounded and empirically supported analyses and present an intelligence product useful for conservation area decision-makers. Importantly, having a dedicated department analyst also facilitates easier collaboration with external agencies by allocating a central figure as a point of contact.
Notably, and purely from a crime intelligence perspective, an ILC approach supports the sharing of information within the UWA and with outside law enforcement agencies. This is crucial for unpacking the intricacies of wildlife crimes, particularly complex forms like wildlife trafficking. As has been noted before, the current push for ILP approaches facilitates an environment whereby intelligence from the UWA, local police, customs, and international agencies like INTERPOL could be combined to develop an in-depth assessment of potential offenders, transportation routes, and tactics.
The ranger analytic intelligence network: an operational model for intelligence-led conservation
The operational model for ILC proposed here is referred to as the RAIN.p Displayed in Figure 1, the RAIN model incorporates five key departments within the UWA: community conservation, monitoring and research, tourism, legal, and law enforcement. Each department has its own unique objectives and data; all of which are useful in providing a comprehensive assessment of the status of conservation areas in Uganda.
While information derived from these departments contribute to conservation intelligence as a whole, they can also specifically contribute to crime intelligence as well. As mentioned, the broader ILC framework ensures that the UWA recognises and internalises the value of intelligence generated from non-law enforcement sources (e.g. community conservation) for law enforcement initiatives. For example, the tourism department can provide insight on tourism companies that may be engaged in illegal off-trackingq activities, while the legal department can provide information on repeat offenders. Likewise the community conservation department may be able to obtain information from reliable and trustworthy informants from the local communities that can both identify areas of concern for its own department (e.g. human-wildlife conflict), as well as for the law enforcement department (e.g. retaliatory killing of wildlife). Lastly, the monitoring and research department can provide data on wildlife population counts, which would be a useful supplementary metric to assess law enforcement efforts.
Figure 2 provides a simplified representation of the processes involved within the intra-agency flow of information and intelligence, as well as decision-making and planning from an ILC framework. First, data and information is collected by frontline rangers and provided to the department analyst within the conservation area. Once information is analysed and developed into an actionable intelligence product, it is then shared with the department supervisors (e.g. head ranger, warden) to support decision-making and planning at the department-level. Supervisors then provide the intelligence reports, along with information on decision-making and planning, to the conservation area manager. The conservation area manager then develops both long- and short-term plans with the management at UWA headquarters.
As shown, analysts within the conservation areas also directly share information and intelligence with the analysts located at the headquarters. This helps provide the UWA with the necessary information to assess countrywide trends, areas of concern, and avenues for resource allocation. Furthermore, by examining information and intelligence from the different conservation areas, it may be possible to further unravel complex wildlife crimes (e.g. wildlife trafficking) as offenders may be operating in several conservation areas. Indeed, within the RAIN model, the headquarters acts as an in-house fusion center that is responsible for receiving, analysing, and disseminating information obtained from the various conservation areas in Uganda.
As shown in Figure 3, analysts within the conservation areas and at the headquarters also play a central role in inter-agency information and intelligence sharing as well. Analysts would be able to provide and receive valuable information from local police, customs, NGOs, and other agencies and stakeholders with a vested interest in conservation (e.g. INTERPOL). Such information could then be combined with UWA-based data to develop actionable conservation intelligence useful for collaborative strategic, operational, and tactical planning.
Considerations for the implementation of ILC and the RAIN
As a conceptual framework and operational model, ILC and the RAIN may be a promising option for the UWA. As noted, the information technology capacity of the UWA is sufficient to implement an ILC approach. However, it is worthwhile to consider some additional factors as well. It is important to note that the following are not mutually exclusive. Furthermore, although the focus of the current study is on the UWA and may not be generalisable to other areas, based on the literature and discussions with researchers working in other places, it is believed that the following may also be applicable to protected areas in other developing countries as well.
Sustainability and feasibility of implementing an ILC approach
Information technology and conservation intelligence analysis will not have a long-lasting impact if it is not sustainable or feasible at the ground level. Indeed, one of the main complaints heard from rangers, supervisors, and management was the difficulties they currently encountered with specific devices and software programs. Similar issues related to the lack of infrastructure and support for information technology and crime analysis and its negative influence on patrol officers has been noted before (Manning 2001).
In particular, rangers described their frustration with having limited access to electricity. This often made it challenging to use devices (e.g. GPS) needed for data collection. Moreover, software that depends on a reliable network was found to be incompatible with the realities that rangers faced, especially in protected areas with inconsistent or non-existent cellular reception (i.e., software programs that require internet access to upload or view data). Frustrated with the inability to upload data, some supervisors surmised that information was being lost or unaccounted for.
The development of the RAIN would need to explicitly address such issues to reduce problems with its successful implementation, as well as to alleviate personnel discontent. Unfortunately, and as noted above, issues with resources and infrastructure may hinder the UWA’s ability to do so. For example, one way to address the issue of electricity is through the increased use of solar panels. While there are some solar panels currently being used in some protected areas in Uganda, it is rare. In order to potentially address the problem of poor cellular reception, cellular boosters may be used, but even that technology may be ill-suited for the bush.
Furthermore training for staff (see below) will undoubtedly cost the UWA a significant amount of money. Given the limited resources currently available to the organisation, the RAIN could train rangers to become in-house instructors. Rather than sending a limited number of rangers for intelligence training in other countries, UWA trainers would be able to provide initial and refresher training specifically suited for Ugandan PAs to all rangers and personnel within the organisation.
Interpersonal dynamics of intra- and inter-agency cooperation, collaboration, and information sharing
A key element for RAIN is intra- and inter-agency cooperation and collaboration. Given the size of the UWA, the ability to share information is crucial. However, intra-agency cooperation should not be taken for granted nor should it be immediately expected. Indeed, Gore (2011) advised that exploring and understanding the human dimension of conservation science is crucial in the development, implementation, and evaluation of policy. In other words, it is important to recognise that interventions are very much rooted in several social systems, including individual, interpersonal, institutional, and infra-structural (Pawson 2009).
For example, the ambiguous role of the intelligence rangers within the UWA has resulted in internal mistrust amongst the ranger population as some rangers believe that the intelligence rangers are more focussed on investigating internal affairs (i.e., identifying ranger wrongdoing; see Moreto et al. 2015). This has led to a lack of trust between law enforcement and intelligence rangers. In fact, due to this underlying tension, some law enforcement rangers described how they would not provide information to the intelligence rangers even if they had access to it.
Additionally, by developing a reciprocal relationship with other agencies, an environment of information and resource sharing may be possible. Fortunately, such collaboration is occurring to a certain extent. For instance, the UWA and local police conduct joint operations to target known poachers. In general, it would be beneficial for the UWA to continue to develop a collaborative relationship with law enforcement agencies within and outside the country. Unfortunately, the relationship with other agencies, including the police, can be contentious at times. For example, alleged issues related to corrupt practices have at times caused distrust and moral cynicism amongst and between these agencies.
Understanding ranger organisational and occupational culture
Beyond technical and training considerations, another important aspect that warrants reflection is the role of organisational and occupational culture (see Moreto 2013). Similar to traditional forms of policing, advancements in information technology must not be viewed and assessed simply on its instrumental effects; rather, its influence on the interpersonal dynamics of organisations and policy as well (see Manning 2008). Research has shown the importance of examining organisational and occupational police culture to better understand a variety of formal and informal facets related to policing, including corruption, discretion, job satisfaction, stress, managerial values, and personnel relations, amongst others (see O’Neill et al. 2007; Moreto 2015; Paoline and Terrill 2014), as well as understanding factors that may facilitate or restrict change (Chan 1997). Previous scholars have also explored the impact of the information technology age on policing, police organisations, and police (Chan 2001; Ericson and Haggerty 1997), as well as the link between police culture and crime analysis (Cope 2004). In general, such research has been insightful in better understanding the often-ignored human and interpersonal dynamics of information technology.
Training needs for theory and practice
Ranger analysts should be versed in both theory and technical application. Importantly, the training of analysts will not be adequate in order for RAIN to be successful. The training of rangers on the ground, as well as management is crucial for better data collection and better use of actionable conservation intelligence. Indeed, it has been noted that the ability of police managers to appreciate and understand analytical products influences whether such products are acted upon (Ratcliffe 2004). Additionally, training of staff helps establish the role that analysts have within the organisation to ensure that they are viewed as part of the support structure for decision-makers as opposed to being merely seen as technical specialists (Evans and Kebbell 2012).
Furthermore, variability in knowledge and understanding of technology undoubtedly influence the interpretations or the technological frames of different personnel (Orlikowski and Gash 1994). Similarities and disparities in the technological frame of rangers, analysts, and managers can be acknowledged and, if needed, remedied through proper training. By doing so, other issues, including problems associated with organisational or occupational culture, can be alleviated as expectations of the technology and of the staff (i.e. capabilities of analysts) may be more realistic and better understood.
As noted, current crime analyses in Ugandan protected areas is atheoretical. This is a void that crime science could help fill by providing insight from an environmental criminology perspective, as well as guidance in the development of prevention strategies (e.g. situational crime prevention). By providing analysts, rangers, and management with the requisite theoretical foundation necessary for analysis, analytical products and the tactical operations and strategic plans may prove to be more successful. Furthermore, by theoretically grounding decision-making, management will be able to justify policies prior to their enactment rather than relying on ad hoc explanations.
The need for qualitative data
Quantitative forms of crime and intelligence analysis tend to be the focal point in wildlife crime analysis. Qualitative data, however, is very much a part of crime analysis (Santos 2013). Recognising the value of qualitative data may result in a more inclusive approach to data collection and analysis through appropriate training and intra- and inter-agency collaboration. Moreover, and within the realm of crime science, qualitative research can contribute in unraveling important market dynamics (see Moreto and Lemieux 2014) that can contribute in the development of contextualised crime scripts useful in the identification of prevention pinch-points (Cornish 1994; Lavorgna 2014; although see Moreto and Clarke 2014).
Implementing and evaluating an ILC approach
Lastly, the development and implementation for ILP within developed countries has often occurred without explicitly performing process and outcome or impact evaluations. Sound policy, however, requires both forms of evaluation. While conducting both a process and outcome evaluation of RAIN may prove to be difficult—indeed, intelligence strategies in general are difficult to evaluate (see Ratcliffe 2008)—the UWA as a conservation agency has unique advantages compared to traditional police agencies. For example, although police agencies are becoming more progressive and open to collaborating with researchers, barriers still exist. Fortunately, as the UWA is familiar working with external researchers and is involved in its own research, implementing and evaluating the RAIN may be possible.
It is suggested that any evaluation of the RAIN must begin with proper initial inquiry as to what is being evaluated (i.e. performance indicators) and how to operationalise these concepts (Ratcliffe 2008). Since the UWA collects and has access to data sources (e.g. wildlife population counts) other than crime data, outcome measures can be developed through triangulated sources thereby providing a more inclusive assessment of the RAIN. Indeed, an intelligence-led approach may require the use of different data in order to effectively measure its success (Ratcliffe 2008).
As an ILC framework may be helpful for other conservation agencies, performing a process evaluation (similar to the one presented here) is just as important as its outcome counterpart since it provides insight on why specific processes worked or did not work, what can be done to address problems during development and implementation, and what changes can be done to make the program more effective and efficient (see Ratcliffe 2008; Gibbs et al. 2015). Additionally, any evaluation would benefit from adopting a realist perspective in order to specifically tailor the evaluation to the contextualised needs, concerns, and objectives of the UWA (see Pawson and Tilley 1997).
Subsequent outcome evaluations of the model could be conducted in several forms. For instance, pre-post or interrupted time series designs could be performed at each individual conservation area, as well as the organisation as a whole (see Eck 2011). Cost-benefits analysis could also be performed to assess model components and operational success. Such analyses would be particularly helpful for the UWA management at headquarters as well as in the conservation areas as a means of identifying alternative resources or approaches that would produce similar benefits with less costs (Roman and Farrell 2002).
