More about me
Jean Providence Nzabonimpa (PhD) is a social, behavioral, educational, and public health researcher and evaluator, a development and humanitarian practitioner with 16 years of experience in project design, implementation, performance monitoring, outcome and impact evaluation, social marketing, and applied research. Using behavior change theories and communication as an approach to achieve project outcomes and impact in public health, education, and other social development sectors, currently keen on human face in technology, he brings rigorous methodological approaches to development interventions, generating and using evidence for decision-making and impact.
With specialization in mixed methods research, he innovates methodologically when it comes to impact, behavior change, and user experience research and evaluation. With more than 30 research and evaluation studies, coupled with a strong background in education, language use, and public health, he uses advanced social science evaluative, analytical, communicative, and programmatic knowledge and skills to generate evidence and insights to impact the lives of the poor and vulnerable people. Since 2009, he is an apt user and advocate of ICT in program monitoring and evaluation for real-time access to data and evidence. Expert user and trainer in data analysis using SPSS (expert level) and STATA (lesser extent) for quantitative data analysis, ATLAS.ti and MAXQDA for qualitative data analysis. He is certified in SCRUM fundamentals, in ATLAS.ti as a professional trainer, a certified peer-reviewer.
Jean Providence Nzabonimpa
Monitoring and Evaluation Expert The African Capacity Building FoundationDear John,
Happy 2021 to you and all our colleagues on the platform!
Thanks for raising a critical and much-intriguing question worth looking into as evaluators. I am sure I cannot do justice to the important points you have raised but at least I can share my two cents. I hope colleagues will also keep coming in for a richer discussion.
It is true we assume we understand issues affecting local communities. We thus design interventions to meet their needs. I completely agree with you. There are important factors unknown at the design stage of development interventions. When little is empirically and theoretically known about a community, little may be done and achieved. Ideally, we need to known the unknowns to design proper interventions and serve better the target communities. But it is unfortunate that it does not work all the time like that, it is not linear, more so in the pandemic-stricken era. We base on what we know to do something. In that process, we learn something new (i.e. evidence) which is helpful to redefine our design and implementation. The complexity of our times, worsened by COVID-19, has pushed all evaluators to rethink their evaluation designs and methods. It would be an understatement to point out that we all know the implications of social (I personally prefer physical) distancing. Imagine an intervention designed through face-to-face results chain as its underlying assumption to achieve the desired change! Without rethinking its Theory of Change (ToC), the logic underlying such an intervention may not hold water. This scenario may apply and rightly prove we need time-evolving ToC. In my view and professional practice, my answer is in the affirmative. We need time-evolving, evidence-informed ToC. We use assumptions because we do not have evidence, right?
Keeping the ToC intact throughout the life of a project assumes most of its underlying assumptions and logical chain are known in advance and remain constant. This is rarely the case. I believe the change of the ToC does not harm but instead it maximizes what we learn to do better and benefit communities. Let’s consider this scenario: assume X outputs lead to Y outcomes. Later on one discovers that A and B factors are also, and more significantly, contributing to Y than their initial assumptions on X outputs. Not taking into account A and B factors would undermine the logic of the intervention; it undermines our ability to measure outcomes. I have not used outcome mapping in practice but the topic under discussion is a great reminder for its usefulness. Few development practitioners would believe flawed ‘change’ pathways. Instead, I guess, many would believe the story of the failure of the ToC (by the way I hate using words fail and failure). Development practitioners’ lack of appetite to accommodate other factors in the time-evolving ToC when evidence is available are possibly the cause of such failure. In the end, evaluation may come up with positive and/or negative results which are counterintuitive, or which one cannot be linked to any component of the intervention. It sounds strange, I guess, simply because there are pieces of evidence which emerged and were not incorporated in the logic of intervention.
I guess I am one of those interested in understanding complexity and its ramifications in ToC and development evaluation. I am eagerly learning how Big Data can and will shed light on the usually complex development picture, breaking the linearity silos. As we increasingly need a mix of methods to understand and measure impact of or change resulting from development interventions, the same applies to the ToC. Linear, the ToC may eventually betray the context in which an intervention takes place. Multilinear or curvilinear and time-evolving, the ToC is more likely to represent the real but changing picture of the local communities.
I would like to end with a quotation:
“Twenty-first century policymakers in the UK face a daunting array of challenges: an ageing society, the promises and threats for employment and wealth creation from artificial intelligence, obesity and public health, climate change and the need to sustain our natural environment, and many more. What these kinds of policy [and development intervention] challenges have in common is complexity.” Source: Magenta Book 2020
All evolves in a complex context which needs to be acknowledged as such and accommodated into our development interventions.
Once again, thank you John and colleagues for bringing and discussing this important topic.
Stay well and safe.
Jean Providence