ABSTRACT

The previous chapter charted the evolution of UNPOL form and function in UN peace operations and identified some of the major challenges they face in deploying missions and implementing mandates. This chapter explores one avenue for addressing those challenges: Monitoring and Evaluation (M&E). It has been argued that M&E is crucial for realising effective peace operations.1 However, despite its purported importance, current efforts have not been able to meet the needs of the peace operations apparatus.2 M&E is critically important to the smooth functioning of UN peace operations but it is particularly difficult to conduct given the unique operational circumstances, methodological challenges and a context of political pressure. This chapter examines current convention in this domain. It proceeds in four sections. First it clarifies what is meant by M&E. Second, it reviews and critically assesses current M&E tools within the UN peace operations apparatus.3 Third, it identifies and analyses the extant literature on M&E in (international) policing. Finally, it draws together the major shortcomings and challenges associated with these approaches in relation to the specific M&E needs of police in peace operations. I argue that the M&E approaches employed by the UN to date may be necessary but are not sufficient for the short-or longer-term needs of UNPOL. The specific context and objectives for police in modern peace missions render unique challenges that defy the application of M&E tools forged in different circumstances but that extant efforts largely fail to reflect this. Therefore, I posit that UNPOL require a tailored approach that can overcome the shortcomings with the extant orthodoxy. Implicit assumptions, a counterproductive incentive structure and problematic dependencies constrict the perspective of current M&E orthodoxy, rendering assessments blinkered to certain phenomena. I argue that overcoming these challenges requires addressing seven sets of criticisms relating to outcome/impact focus, flexibility, data diversity, context-sensitivity, holism, participation and learning-orientation.