Jackline Musuya is a Monitoring, Evaluation, and Learning (MEL) specialist with a background in Applied Statistics and a Master’s in Monitoring and Evaluation. She works across health, development, and social impact programmes in East Africa, with a focus on strengthening evaluation systems, evidence-informed decision-making, and youth leadership in development practice.
Kenya
JACKLINE MUSUYA Member since 22/05/2026
Hewatele Limited
Monitoring and Evaluation Lead
My contributions
- Across the Global South, a paradox is unfolding, young evaluators are more qualified than ever, yet many remain locked out of leadership and decision-making spaces. A growing number of emerging evaluators are highly trained, technically competent, and increasingly experienced. They contribute meaningfully to complex evaluations, often in central sectors to sustainable development such as public health, agriculture, and climate resilience. Yet, many continue to have limited influence over priorities, methods, and decision-making processes. This is not a capacity problem. It is a systems problem...Read more
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 27/10/2026
In resource-constrained environments, excluding evaluative evidence from strategic and operational decisions creates more than an information gap. It increases the risk that already limited resources will be directed towards interventions that are ineffective, poorly targeted or unresponsive to changing needs.
One major risk is the continuation of activities based on assumptions rather than demonstrated results. Without evidence on implementation challenges, unintended outcomes and community experiences, organisations may continue investing in approaches that appear successful in activity reports but produce limited meaningful change.
A second risk is that the needs of less visible groups may be overlooked. Routine administrative data often capture what is easiest to count, while evaluations can reveal differences in access, participation and outcomes across locations and population groups. When evaluative evidence is excluded, decisions may favour well-documented needs while marginalising communities whose experiences are poorly represented in existing information systems.
Limited evidence use also weakens organisational learning. Teams may repeat implementation problems, lose valuable lessons when programmes close and struggle to explain why particular results were achieved. Under financial pressure, such mistakes become more costly because organisations have less capacity to absorb ineffective spending.
Finally, excluding evaluation findings can weaken accountability. Communities may provide feedback without seeing how their contributions influence programme decisions, while management responses and follow-up actions remain undocumented.
The solution is not necessarily to conduct more evaluations. It is to protect the use of essential evidence by integrating evaluation findings into planning meetings, resource-allocation decisions, risk reviews and management-response processes. When resources are scarce, evidence should become more influential, not less.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
Thank you, Rhode. This is an important reminder that cost-efficient evaluation begins with strong monitoring. Reliable routine data, participant feedback and usable information systems can reduce duplication and allow evaluations to focus on deeper questions, independent validation and learning.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
Thank you, Janet. You have captured the risk clearly: when M&E is deprioritised, organisations lose evidence, learning, and capacity at the same time. Maintaining core indicators and documenting lessons before programme closure can help prevent scarce resources from being spent without understanding what worked.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
I agree that AI’s greatest value may be not only faster analysis, but also helping evaluation offices synthesise existing evidence, identify gaps and prioritise where new evaluations are most necessary.
However, efficiency must be matched by institutional readiness, human validation and contextual judgement. The real test is whether AI-supported evidence improves decisions and learning without weakening quality, inclusion or accountability.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
In my context, organisations increasingly use community feedback forums, participatory monitoring and validation meetings to retain local perspectives when stand-alone evaluation budgets are limited.
The challenge is that local actors may contribute information without influencing the evaluation questions, interpretation or final decisions. Centring communities therefore requires more than collecting their views. It means involving them in defining what matters, making sense of findings and tracking whether agreed actions are implemented.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
I strongly agree that the solution is not choosing between accountability and learning, but embedding both into routine practice. Community-led monitoring, participatory scorecards and continuous feedback can help protect learning while keeping decisions grounded in community realities.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 21/10/2026
Thank you, Chamisa. Organisations in my context are using several practical approaches to balance accountability and learning:
The main constraint is that reporting has fixed deadlines and contractual consequences, while learning is often treated as optional. Leadership must therefore protect time for reflection and ensure that evidence is discussed before major programme decisions are made.
Kenya
JACKLINE MUSUYA
Monitoring and Evaluation Lead
Hewatele Limited
Posted on 13/10/2026
In my experience working in monitoring, evaluation and learning (MEL) across health and development programmes, funding constraints rarely eliminate the need for evidence. Instead, they often change how organisations generate and use it.
One of the most noticeable effects is the growing emphasis on accountability over learning. When resources are limited, organizations understandably prioritize donor reporting and compliance requirements. While these functions are important, learning activities such as reflection sessions, outcome assessments and evaluations are often postponed or scaled back. As a result, organizations may become better at reporting results than at understanding why those results were achieved and how performance can be improved.
Beyond learning, funding constraints can also affect accountability. When resources for evaluation and reflection are reduced, organizations may have fewer opportunities to systematically assess whether programmes are meeting the needs and priorities of the communities they aim to serve.
Funding constraints can also reduce the scope of evaluation. In many cases, organizations rely more heavily on routine monitoring data and conduct fewer in-depth studies. While this may provide sufficient information for reporting purposes, it can limit deeper insights into effectiveness, sustainability and unintended outcomes.
At the same time, financial pressure can create an opportunity to rethink evaluation practice. Rather than collecting more data, organizations are often compelled to make better use of existing information. This can encourage more focused evaluations, stronger integration of learning into routine management processes and greater attention to evidence that directly informs decisions.
In my view, the greatest risk is not conducting fewer evaluations. It is losing the space for reflection and learning that enables organizations to adapt. In resource-constrained environments, evidence becomes more valuable, not less, because decisions about priorities, investments and programme design carry even greater consequences.