Leading the M&E
You are the M&E lead for your country's Child Guarantee plan. You have a small team and a limited budget. The Ministry of Finance asks for results fast. Over the next 36 months you will make five decisions. Each is tricky: the option that looks right under pressure can bring additional costs later.
How this works
For each decision you will choose one of three options, then see how it plays out over the months that follow. There is no going back after you choose, but you can replay the entire scenario at the end.
The timeline marks the five decision points, from month 1 to month 30 of 36.
The plan is signed. You have a three-person team. The Minister wants a public dashboard in six months, before the summit.
What do you do in these six months?
A strong choice
By month 6 you have no dashboard for the summit, but you have a map of what data exist, a governance structure that holds the other ministries, and a roadmap covering the gaps.
Viable, with conditions
You make visible progress early. The condition: without the diagnostic you keep discovering gaps and overlaps as you go, and governance built in parallel tends to grow around individuals rather than institutional roles, which does not survive a government or staff change.
The high-risk path
It launches for the summit and looks impressive, but with no indicator logic or governance beneath it, the dashboard displays data no one can stand behind. You spend the following months rebuilding underneath a product that is already public.
Governance is forming. You need indicators. A ready-made list is available; your team is stretched.
How do you build the indicator set?
A strong choice
It starts slowly, but every indicator traces to a result you meant to produce, and each fiche adds feasibility the whole system can rely on.
Viable, with conditions
You get a credible, EU-comparable set quickly. The condition: you must still map those indicators back to your own measures, or you are reporting on a framework rather than on your plan.
The high-risk path
Everything is reportable immediately, but you are now measuring activity rather than results, and the intervention logic has to be reconstructed later.
Data are coming in from three ministries. Some figures look implausible. Fixing this will slow reporting.
What do you do about data quality?
A strong choice
Reporting slows while you build the checks, but your numbers are trusted. Verification is one of the two components most countries leave for last.
Viable, with conditions
A pragmatic compromise that catches the worst errors where they matter most. The condition: be explicit about which figures are assured and which are provisional whenever you report them.
The high-risk path
You meet the deadline, but without an audit process the whole system’s credibility is in question.
The Ministry of Finance wants proof the measures work. There is budget for one evaluation.
What evaluation do you commission?
A strong choice
The assessment tells you which measures can be evaluated, so the evaluation you commission afterwards returns usable findings.
Viable, with conditions
A process evaluation gives Finance something real about how implementation is going. The condition: it is a first step, and it sets the ground for a later impact evaluation.
The high-risk path
It is exactly what Finance asked for, but if the measures were never evaluable, the evaluation returns inconclusive findings at high cost.
You have two years of data and a dashboard is nearly ready. The next reporting cycle is approaching.
How do you make the evidence count?
A strong choice
The least visible of the three options, and the only one that closes the loop: evidence reviewed, decisions changed, funding moved toward what works. This is the twelfth component, the one almost every country leaves unbuilt.
Viable, with conditions
Transparency and a visible product, both genuinely valuable. The condition: a dashboard shows evidence, but someone still needs to act on the data.
The high-risk path
The reporting obligation is met. However, the system does not learn, which is exactly the gap this whole activity has been about.
Seen together, the five strong choices trace a single line
Governance before tools, logic before data, quality by design, evaluability before evaluation, and evidence-use before public dashboards. In every case the high-risk option was the one that looked most responsive under pressure. The countries that built M&E systems that lasted resisted exactly those shortcuts.
Apply this to your context
- Which of these five decisions are you facing right now?
- Where is the pressure in your own system pushing you toward the plausible shortcut, and how could you resist it?
Take this to your team: leading the M&E
Leading an M&E system means making the unpopular decisions first. Under pressure, the responsive choice, the quick dashboard, the ready-made indicators, the big evaluation, is usually the one that brings more costs. These are the five decisions that determine whether the system reports or learns. Tick the ones you are facing now.
The five decisions
- Governance before tools. Run the diagnostic and build two-tier governance before making anything visible. Resist: the dashboard before the summit.
- Logic before data. Write a theory of change first, then draw indicators from the results chain. Resist: the indicators for which the data already exist.
- Quality by design. Build verification and auditing into the routine to ensure credibility. Resist: reporting unchecked data because the systems are official.
- Evaluability before evaluation. Check the measures are evaluable before commissioning the evaluation. Resist: the full impact evaluation before an evaluability assessment.
- Evidence use before dashboards. Set a standing governance moment where evidence is reviewed and acted on. Resist: publishing the dashboard and moving on.
Put these to your team
- Which of these five are we facing right now?
- Where is the pressure pushing us toward the plausible shortcut, and who is applying it?
- What would doing the unpopular thing first look like this quarter?