Why MEL belongs in the proposal from day one

7 min read

Short answer: Monitoring, evaluation, and learning (MEL) belongs in the proposal because reviewers score how you will prove results. That proof has to be designed, staffed, and budgeted before the award. Set indicators while you design the program, plan a baseline, budget for data collection, and name who collects data and who uses it. Done early, it makes every report easier.

There is a familiar moment a few weeks after an award. The grant agreement arrives with a results framework attached, and someone asks who is doing the baseline. Nobody budgeted for it. The indicators in the proposal were written in an afternoon. Two of them cannot be measured with the data the program will collect. The first report is due in three months.

None of that is a reporting problem. It is a design problem that started in the proposal.

What reviewers look for

Reviewers read the MEL section to answer one question: if we fund this, will we be able to tell whether it worked? They look for indicators tied to the stated outcomes and a starting point to measure change against. They also look for a realistic way to collect the data, with people and money assigned to the work.

Public funders write these expectations into their rules. Under the US Uniform Guidance, federal agencies should state in the award what the recipient must measure and report. That can include expected outcomes, indicators, targets, baseline data, or data collections (2 CFR 200.301). If those requirements will appear in the award, a proposal that already plans for them reads as ready. One that does not reads as a future problem.

Four things to settle before you submit

1. Indicators, set during design

Write indicators at the same time as the outcomes, not after. Each one should measure a change named in the program logic, with a clear definition, a data source, and a collection schedule. If you cannot say where the number will come from, the indicator is not ready.

Keep the set small. A handful of indicators the team will actually collect beats a long list that dies in the second quarter.

2. A baseline you can measure change against

Change needs a starting point. Decide what the baseline is, when you will collect it, and whether existing data can serve. Sometimes the honest plan is to collect the baseline in the first months and set final targets once you have it. Say so in the proposal. Reviewers respect a plan more than a target that was clearly guessed.

3. A budget for the work

Data collection costs money: staff time, travel, tools, survey design, data cleaning, and sometimes an external evaluator. If the budget has no lines for these, the MEL plan is a wish.

The federal cost rules explicitly allow performance management and program evaluation costs to be charged directly to an award when they relate to that specific award (2 CFR 200.413). Other funders vary, so check the call. But budgeting for evidence is normal, and leaving it out tells the reviewer you have not thought it through.

4. Roles: who collects, how often, and who uses it

Name the roles. Who collects each piece of data, how often, who checks it, and who reviews it to make decisions. The last role matters most. Data nobody uses is a cost with no return, and reviewers also want to know how learning will change the program during delivery.

A worked example

The following is an invented example for illustration, not a real client. A livelihoods program will support women's savings groups. Its first proposal draft has a single MEL sentence: "We will monitor progress and report to the funder quarterly."

Built in from day one, the MEL section becomes a short plan:

The program itself did not change. What changed is that a reviewer can now see how the team will know whether it is working, and the team will not discover the gaps after signing.

What changes when MEL starts early

The benefits show up long after submission. Reports become easier, because the data was planned around the questions the report must answer. Program changes become easier to defend, because the team can show what the evidence said. Renewal proposals become stronger, because they rest on results rather than activity counts.

The reverse is equally predictable. MEL added after the award usually measures what is easy to count, which tends to be outputs. For the difference between those and the outcomes funders want, see our article on outputs vs outcomes.

Size the work to the grant

A small grant does not need an elaborate system. A few clear indicators, a simple baseline, and a named person can be enough. A large, multi-year award needs more: a full MEL plan, indicator reference sheets, and sometimes an external evaluation. Match the effort to the size of the decision the funder is making.

Who should help write the MEL section

Program staff know what can realistically be collected. Finance knows what data collection will cost. Leadership knows which decisions need evidence. When one person drafts the MEL section alone, it often reads well and then proves hard to deliver.

Quick checklist for the MEL section

• Every outcome has at least one indicator with a data source
• A baseline is planned, with a date
• MEL costs appear as real budget lines
• Roles for collecting, checking, and using data are named
• The MEL section, the program logic, and the budget use the same terms

How Edit Right helps

Our Monitoring, Evaluation, and Learning service builds MEL into proposals from the first outline. MEL Map, our MEL plan model, connects results logic, measurement, data quality, and learning, and Data Diamond keeps the numbers credible from one report to the next. For the full plan after the award, see how to write a MEL plan that works in practice.

Frequently asked questions

How detailed should MEL be at proposal stage?

Detailed enough to show the logic, the indicators, the baseline plan, the budget, and the roles. The full MEL plan, with indicator reference sheets and tools, usually follows in the first months after award.

What if the funder does not ask for a MEL section?

Include a short one anyway, inside the approach or management section. Reviewers still want to know how you will show results, and you will need the plan to report.

Can small organizations do this?

Yes. Scale it down rather than leave it out. A few indicators, a simple baseline, and a monthly review meeting are enough for many small programs.

Sources

1. Electronic Code of Federal Regulations, 2 CFR 200.301, Performance measurement. https://www.ecfr.gov/current/title-2/subtitle-A/chapter-II/part-200/subpart-D/section-200.301 (accessed November 13, 2026).
2. Electronic Code of Federal Regulations, 2 CFR 200.413, Direct costs. https://www.ecfr.gov/current/title-2/subtitle-A/chapter-II/part-200/subpart-E/section-200.413 (accessed November 13, 2026).

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