Are You Measuring Too Much? Why More Data Doesn’t Always Mean Better Evidence

Nobody sets out to build a complicated M&E system. You grow into one.

A new funder asks for an extra indicator. A programme picks up another reporting requirement. A survey gains three more questions because the answers might come in handy one day. An old spreadsheet stays in place because nobody is sure whether anyone still uses it. None of it looks like much at the time. Then one day you open your monitoring framework and realise you are maintaining something nobody designed.

If that sounds familiar, you are in good company. It is one of the most common things we see at Fundamental, and one of the most fixable. New indicators go in; old ones almost never come out. There is even a name for it, indicator creep, and it is worth watching, because every measure costs something.

So here is a question worth your time: are you measuring what matters?

Every data point asks something of someone

On paper an indicator is a line in a framework. In practice it is somebody’s Tuesday. Someone collects the information, checks it, captures it, stores it, and if it is going to mean anything, someone eventually must sit down and work out what it is telling them.

Your team is already carrying programme delivery, community relationships and reporting deadlines. In a lot of NPOs the person who runs M&E also runs something else, often on a two-year grant with no allowance for systems work at all. Every extra field on a form lands on that person.

It also lands on the people you serve. A single survey question takes a minute to answer. But when the same households are asked over and over to fill in forms and hand over details of their lives, those minutes add up, and so does the feeling of being researched rather than served. If you are going to ask people for information, you owe them a clear idea of what you plan to do with it.

“It might be useful” is a low bar

One of the easiest ways a system grows is through information that might come in handy. Maybe it would help to know this. Maybe somebody will ask for that later. Trouble is, almost anything could be useful, and that on its own is not a reason to collect it.

Not every number has to drive a decision next week. Some information exists for accountability, some feeds analysis you will only do in three years, and some is simply required by a funder or a board. All legitimate. But you should be able to say out loud why it is there. When you go through a framework properly, the problem is often not too many indicators. It is that the purpose behind them seems to have gone missing.

When more starts working against you

We assume more information brings more certainty. Sometimes it does. But there is a point where volume starts eating quality. Long forms get completed carelessly. Complicated spreadsheets break. Big frameworks need more checking and more chasing. And when your team is collecting things that feel disconnected from the work in front of them, data collection stops being a way of understanding anything and becomes a task to get through.

So, on paper, you can end up looking like an organisation with a comprehensive system while actually wrestling with gaps, inconsistencies and measures nobody has opened in two years. A small set of indicators you understand well and collect properly will give you a stronger evidence base than a large framework you cannot keep up with. This is not an argument for simplicity for its own sake. Complex programmes sometimes need complex measurement. The question is whether your system is complicated because the work is, or just because nobody has looked at it in a while.

Not every indicator has the same job

Part of what makes simplifying hard is that organisations collect information for different audiences and different reasons. Some indicators exist because a funder requires them. Some help management see whether implementation is on track. Some matter most to programme staff on the ground. Others speak to whether the organisation is contributing to change over the longer term.

These are genuinely different jobs, which is why it helps to look at a framework and ask what role each measure is actually playing. Is this required for accountability? Does it help the team manage delivery? Does it tell us something real about an outcome? Does it support a decision that needs to be made? Is anyone using it at all? Are we already gathering something similar elsewhere?

That kind of review often reveals something useful: the problem isn’t always too many indicators. Sometimes it’s that the purpose behind them has become unclear

Try this: what if you stopped?

Pick one indicator and ask what would happen if you stopped collecting it tomorrow.

Sometimes the answer is immediate. You would lose the ability to report against a real commitment, or lose sight of an outcome you care about. Good. It has earned its place. Sometimes the answer is much less clear. It appears in a report but never gets discussed. It has been collected for four years without shaping a single decision. Nobody can remember who asked for it. That does not automatically mean it should go, but somebody should look at it properly.

An M&E system shouldn’t be treated as something designed once and preserved forever. Programmes change. Funding relationships change. Priorities shift. What an organisation needs to know changes along with them, and reviewing what’s being measured is simply part of keeping the system healthy.

Every measure should earn its place

Strong M&E is not a competition to see how much you can measure. It is about knowing your work well enough to make good decisions about it. So for any indicator, question or data field: why are you collecting this? Who uses it? What does it help you understand? Are you already capturing it somewhere else? Is the value worth the effort?

Simple questions, but they lead to far more purposeful systems. And sometimes strengthening an M&E system doesn’t begin with adding another indicator. Sometimes it begins with looking carefully at what’s already there because more data doesn’t automatically create better evidence. Better evidence comes from collecting the right information, for a clear reason, and having the capacity to actually use it.

Continue the journey with Fundamental

If you are ready to build a clearer, more intentional M&E system, our guided learning pathways are designed to meet you where you are. Seeds of Strength for Organisations walks teams through a practical, mentored process of strengthening their systems. Seeds of Strength for Practitioners is for individuals wanting to deepen their applied MEL skills and grow their confidence.

The work you do matters, and we are here to support you along the way. Tools for change, wherever you are starting from.

Explore Fundamental’s courses and find the pathway that fits you: https://fundamentaltools.co.za/courses/