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Problem Tree Analysis needs the right participants, but the facilitator matters more.

I have watched two facilitators run the same Problem Tree workshop — same participants, same focal problem, same protocol — and produce two different trees.

The facilitator shapes what causes become visible through dozens of micro-decisions: whose contribution gets probed further, whose gets summarized quickly, when to push deeper and when to move on, which root is placed at the bottom of the tree and which becomes a branch. These decisions appear procedural. They are analytically consequential.

I have reviewed hundreds of Problem Trees from Cambodia NGOs. The pattern is consistent: technical causes — knowledge gaps, resource limitations, capacity weaknesses — are mapped in detail. But the power dynamics, institutional incentives, and political interests that sustain those technical conditions are absent — or reduced to a single vague entry.

This is not always dishonesty. It is often a rational organizational response. A facilitator who names powerful economic interests as a root cause of illegal logging — or political patronage as a root cause of weak enforcement — is naming causes the project cannot address and relationships the organization cannot afford to damage. An unskilled or cautious facilitator steers away from those causes without the room even noticing.

A skilled facilitator does the opposite: designs the session to surface what institutional pressure tends to suppress, and builds validation steps that test the tree against evidence and against the voices of those who were not in the room.

What causes do you find most difficult to name in a Problem Tree — and what makes it difficult?

From From Problems to Impacts by Narith Khim (2026)

The most common design error I see across Cambodia is writing outputs where outcomes should be.

"Three training sessions conducted." "Materials distributed to 50 villages." These are outputs — things the project delivers and controls. An outcome is different: it is a change in the target group — what the specific people the project is designed to reach know, believe, or do differently as a result.

When you write outcomes as outputs, you build a monitoring system that measures delivery — not change. At the end of the project, you can prove you delivered. You cannot prove anything changed in your target group because of it.

A simple test: after every output, ask "And then what happens in the target group?" That answer is your outcome. Outputs are what projects guarantee. Outcomes are what projects must influence. Confusing them produces designs that serve the report more than the people the project is meant to reach.

What output-written-as-outcome do you see most often?

From From Problems to Impacts by Narith Khim (2026)

I have reviewed hundreds of project documents across Cambodia. Fewer than ten impact statements began with "Contributed to."

Most begin with "Improved," "Reduced," or "The project achieved" — claiming that the project alone caused changes that were produced by many actors and conditions at the same time. This is not dishonesty. It is a gap in training.

No single project reduces maternal mortality alone. "Contributed to improved maternal health outcomes alongside government health investments" is a claim evidence can support. "Improved maternal health outcomes" is not.

"Contributed to" is not a weaker claim. It is an honest one — and a stronger professional position than an attribution claim that collapses under evaluation scrutiny.

Every major donor framework requires contribution language at the impact level. The standard exists. What is missing is the training.

Have you ever been pressured to write attribution language at the impact level? What drove it?

From From Problems to Impacts by Narith Khim (2026)

Most of us working in the social development sector are familiar with project results — especially **outputs, outcomes, and impacts**.

Yet when we look more closely, these concepts are not always defined in the same way. Different scholars, donors, and development agencies often use the same terms differently. For practitioners, learners, and even experienced professionals, this can make it difficult to know where to agree, where to differ, and how to apply these concepts in real project design.

My newly published book, ***From Problems to Impacts: Problem Trees, Results Chains, Logframes, and Theory of Change in Practice***, explores this issue carefully.

In the book, I examine how different scholars and development agencies define project results, the reasoning behind their positions, and where these interpretations converge or diverge. I also share my own perspective, shaped by more than 20 years of practical experience in project design, monitoring, evaluation, and capacity building.

If you work in project design, M&E, proposal development, or organizational learning, I hope this book will offer practical value.

The book is now available on Amazon. Search for ***From Problems to Impacts*** to explore it further.

From Problems To Impacts is available on Amazon now!

My first book, From Problems to Impacts, is nearly ready for publication.

At around 600 pages, it’s a hands-on guide to results-based project design—written for development practitioners, evaluators, and students who want to go beyond templates and develop clear, structured thinking.

The book walks through the full design process—from problem analysis to Results Chains, log-frames, and Theory of Change. More importantly, it focuses on why these frameworks work (or fail), helping readers ensure the logic behind their designs actually makes sense.

Built on over 20 years of field experience in Cambodia, it draws on real cases from sectors like health, education, governance, conservation, and livelihoods—highlighting common challenges and how to address them in practice.

Inside, you’ll learn how to:
• Identify root causes using Problem Tree and Objective Tree analysis
• Build Results Chains that clearly define who changes, what changes, and why
• Develop log-frames and Theories of Change that are coherent, defensible, and practical

Whether you’re designing a project, leading a workshop, or reviewing an existing program, this book offers a structured and realistic approach to improving design quality.

More updates coming soon.

If you want to design stronger, results-based projects with confidence, join our 2-day in-class intensive training on Problem Tree, Results Chain, Logframe & Theory of Change.
📅 31 Jan – 1 Feb 2026
📍 Coffee Culture, Phnom Penh, Cambodia
🎓 Facilitator: Khim Narith, Project Design & MEAL Specialist
👉 Register now: https://forms.gle/EMH2wvdbjSuUqTsU8

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