Finding problems: the real purpose of monitoring

Most monitoring systems are broken in the same way. They sit parallel to implementation. Evidence gets collected but it doesn't inform decisions. A clearer sense of purpose can help.

Here’s a simple framing, and I think it's the right one:

Monitoring exists to find problems quickly.

I'm talking here about monitoring individual projects, interventions or investments — not portfolio management, which is a different thing.

Whenever you support partners to try something new, you're not sure what's going to work and problems will inevitably emerge. Some will be surmountable and some won't be. Either way, your job is to find them, understand them, and respond appropriately. This is "adaptive management" in action.

How does this work?

Consider how a scientist approaches an experiment. Before running it, she commits to a prediction. Whether she's right or wrong, something has been learned. The prediction is what makes learning possible.

We do the same thing. A theory of change (or results chain) is a set of predictions. If those predictions are explicit, reality will either confirm or contradict them — and contradiction is precisely what you're looking for. It functions like an alarm that demands your attention.

Take a concrete example. Suppose you're supporting a company to introduce a new agricultural input to smallholder farmers. If you commit to the prediction that most farmers who try the input will purchase it the following season (explicitly include it in your theory or change), it follows that you should be monitoring repurchase rates. If repeat purchases are low, you’ve found a problem that demands explanation.

Similarly, if you've predicted that the company will invest in distribution as sales grow (explicitly include it in your theory or change), it follows that you should be monitoring that investment. If investment stays flat despite growing sales, you've found a problem that demands explanation.

Gaps between prediction and reality focus our attention.

Absent or vague predictions mean the alarm never sounds because there's no gap — you're never proven wrong.

So what happens when the alarm goes off? Two possible scenarios.

Scenario 1: you've found a problem you don't yet understand. This is your cue to investigate. Investigate until you understand what's causing it — then you're in Scenario 2.

Scenario 2: you've found a problem and you understand what causing it. This is your cue to adjust your approach — or, in some cases, abandon the intervention entirely and move on.

In both cases, you are making proactive, evidence-based decisions. That is adaptive management. And it is, or should be, the point of monitoring.