Some misunderstandings about our discipline are loud and easy to dismiss. The dangerous ones are quiet. They are plausible enough to pass unchallenged in a corridor conversation, and they do their damage slowly, by shaping how an organisation builds its systems. Here are five I keep meeting.

Myth 1: MERL is for donors

Donors require MERL, and that requirement is often the proximate reason a system exists. But it is an error to conclude that MERL is therefore for donors. A system designed only to satisfy funders optimises for the wrong audience: it produces thick reports rather than usable signals, measures what is reportable rather than what is actionable, and is experienced internally as overhead.

A system designed for the people who actually run the programme, with the donor as a secondary audience, satisfies donors as a by-product because credible evidence is credible regardless of who reads it.

Myth 2: Monitoring and Evaluation Are Basically the Same Thing

They are not. Monitoring asks whether implementation is on track. Evaluation asks whether the implementation, even if perfectly on track, was worth doing.

A programme can have flawless monitoring data and still fail an evaluation because monitoring cannot tell you whether you chose the right strategy. The two are complementary, not interchangeable, and conflating them is how organisations end up measuring activity beautifully while missing the question of merit entirely.

Myth 3: Research Is for Academics, Not Practitioners

This is perhaps the most damaging myth because both communities have internalised it. Academics often write off practitioner research as insufficiently rigorous; practitioners write off academic research as insufficiently relevant. Both judgments are sometimes accurate and often unjust.

The truth is that programmes generate questions: Why did an intervention work in one district and fail in another? What really drives uptake in a hostile environment? These are questions that practitioners are uniquely positioned to answer and that the field needs in order to advance.

Research belongs inside MERL precisely because the most important development questions are practical ones.

Myth 4: Learning Happens Automatically When Data Is Shared

Sharing data is necessary but not sufficient. Learning requires deliberate routines: structured pause-and-reflect sessions, after-action reviews, decision logs, and follow-up mechanisms that close the loop between insight and action.

Without these, evidence accumulates in inboxes and dashboards while decisions continue to be made on the basis of habit, rumour, and the most recent crisis. A repository is not a learning organisation. The routines that connect documents to decisions are.

Myth 5: Good MERL Is Expensive MERL

Cost is correlated with rigour, but only loosely. Some of the most expensive evaluations produce findings that are neither credible nor useful. Some of the cheapest generate insights that genuinely change how a programme is run.

The discipline of right-sizing — matching methodological investment to the value of the decisions the evidence will support — is one of the most important skills a practitioner can develop, and it has almost nothing to do with budget size.

What Unites These Myths?

Each of these myths is a shortcut that allows an organisation to avoid a harder question.

Name the myth out loud, and the harder question comes back into view.

Take It to Your Practice

At your next team meeting, ask which of these five myths your organisation has quietly absorbed. The one nobody wants to discuss is usually the one doing the most damage.