Development Transformations (DT), a veteran owned small business, has been working on behalf of USAID and other donors in conflict and transition countries for the past decade. From first-hand experience, DT understands the challenges of working effectively in such environments, in particular of designing, implementing, and measuring impactful programs on the ground. Critical to transition programming is the use of conflict assessment tools to better understand the local context. DT frequently employed USAID analytical frameworks such as the Conflict Assessment Framework (CAF) and also aided in the development of the District Stability Framework (DSF).
Informed by conflict theory and best practices, these frameworks provide a rigorous process for understanding the root causes of conflict at both the national and sub-national levels. Developed through a transparent and participatory process with local stakeholders and partners, root cause analysis is used to tailor program objectives to identify and help mitigate identified causes of instability. This analysis also helps ensure existing development programs are sufficiently “sensitive” to conflict dynamics on the ground.
In 2017, DT recognized upon reflection that their experience with these frameworks and lessons learned in transition contexts need to be developed based upon an evidence-based approach to programming. DT’s analytic framework, SENSUSTM, represents an agile synthesis of methodologies that formalizes the process of not only incorporating local perception data into a framework for analyzing conflict, but also interpreting those findings in partnership with local actors to co-design localized intervention activities. SENSUS has four primary components:
- Primary source data collection by local researchers to gain awareness of local perceptions, grievances, and resiliencies;
- Co-analysis of data by local stakeholders and SENSUS experts, using context specific analytical filters, to identify key drivers;
- Co-design of local intervention strategies to mitigate identified drivers; and,
- Context specific indicators to measure and visualize results.
DT created SENSUS to challenge assumptions; Experience taught the DT team that local perceptions are critical to understanding community-level dynamics. Seeing a problem from the community’s perspective provides the context required for rigorous analysis and community inspired collaborative program design. Local researchers collect primary source data through quantitative sample surveys and qualitative key informant interviews (KIIs). DT uses technology-enabled mechanisms like smartphone-based and digital media collection tools to conduct the field research. DT’s emphasis on the efficient deployment of mobile technology reflects the prioritization of local-level data and the respect of the risks field researchers take. The data collection results and analytics can be viewed geospatially, in real-time, on DT’s Knowledge Management System (KMS).
Once the data is collated in DT’s KMS, local stakeholders (key researchers, local partners, and/or community stakeholders) and DT SENSUS experts analyze the results to identify and prioritize the key drivers underlying those perceptions. Isolating key drivers is critical to the SENSUS process, as it prioritizes conflict drivers by importance to the community and uses context specific analytic filters to break large data sets down into discrete, actionable categories to produce concrete and detailed parameters for activity design.
SENSUS, with key stakeholders, generates objectively measurable, localized outcome indicators to monitor activity implementation benchmarks against program objectives. Overall, SENSUS measures the impact of activities and visualizes these metrics in meaningful ways (see Figure 2 below).
DT has employed SENSUS on behalf of a variety of donors in Syria, Iraq, Libya, and Yemen. Using SENSUS, DT has designed and implemented effective counter-violent extremism programming to counter drivers of radicalization in vulnerable communities of strategic importance. For example, during a six-month pilot program funded by the U.K. Foreign and Commonwealth Office, DT and local stakeholders isolated the systemic causes of radicalization in three communities in Idlib and successfully implemented grant activities to reduce violent extremism.
The community activities resulted in the local extremist organization first attempting to co-opt our activities and, when those attempts were unsuccessful, DT’s attempt to disrupt them prevented further community mobilization against their activities. Perception surveys showed decreasing support for extremist organizations in target communities, suggesting our activities were correctly targeted at systemic drivers of radicalization.
SENSUS ensures iterative learning as perception data populates in real-time and activities are continually adjusted to adapt to changing dynamics on the ground. Based on KIIs during the implementation of the Idlib activities, DT worked with local partner to adjust and refine on-going interventions. This hyper-local approach, with real-time feedback built in, ensured that 80% of planned activity outcomes despite the rapidly evolving dynamics in Idlib at the time were achieved.