Say you want to start keeping bees. How can you tell if you are doing a good job? They can take care of themselves. They’ve done so for million of years. You are just trying to help them a bit; fighting diseases, keeping them warm in winter, maybe planting flowers they like.
Monitoring involves taking a close look at your friends’ behaviour and things you can check in and around the beehive; carcases, signs of diseases or insects, and the amount of eggs and larvae, nectar and pollen collected.
It’s a specialist area. Or is it?
The development sector is made up of projects. Often they are one-off investments of public resources in a real-life situation with the aim of having a positive effect on e.g. the planet or the quality of lives of people or animals. But there are no guarantees any project will work as designed. Real-life is hard to model; it changes and people are often resistant to new things.
So we use monitoring and evaluation (M&E) methods and models to track the success rate, to learn from it and adjust activities accordingly. M&E is important and needs to be done well. But often these logical models become so elaborate and complex, that they lose their logic and become hard to understand and use in practice.
- M&E = Monitoring and evaluation
- PME = Planning, monitoring and evaluation
- PME = Participatory monitoring and evaluation
- DME = Design, monitoring and evaluation
- MEL = Monitoring, evaluation and learning
- MERL = Monitoring, evaluation, resolution and learning
- PMEL = Planning, monitoring, evaluation and learning
- PMEAL = Planning, monitoring, evaluation, accountability and learning
And who are they for? Is it possible to capture the key questions of all the parties involved in one
model? The funder might ask: which investment is most cost-efficient? The implementer might ask: what scales best and can help me in securing more funds? And the beneficiary might ask: how can I take better care of my family?
What can we learn from the commercial sector?
A term I like is ‘key success factors’; what works best to achieve a positive result, that I need to do more of. An example is the symbolism in the (old) logo of a previous employer, AkzoNobel; holding on to the good with the left hand, while looking to the right, to where you are going, stretching yourself to achieve the best of your abilities.
But you are not working in isolation. Projects involve partners, locations, timelines and target groups, each with their own quirks or special requirements. In other words, assumptions made in a theory of change or a logical framework of change may prove wrong. So the model and even the work you planned to perform in the project may need to change, based on changing realities.
Where data comes in
It is useful to think ahead about what you need to consider to determine if you are successful, like a beekeeper’s checklist. It gives a structure to the collection of facts, i.e. the data. A part can be standard – all beekeepers will check the opening to the hive, for example. Another part may be context-specific, for example depending on the season. Yet another part may be open, for example feedback systems to collect data on satisfaction among the target beneficiaries.
But collecting data is not enough. Immediate evaluation and action may be required to do a good job. In large projects there are often many layers between the data collection, analysis, conclusion-drawing and decision-taking on the way forward. This can be very detrimental. An inspiring example my colleague Joy pointed out recently involves a decision-making tool on child malnutrition in India. The Akvo FLOW cascading questions feature is used by one of our partners to enable field workers to give immediate advice to families.
So we plan, implement, monitor and adapt as needed. The shorter the cycle and the more ‘daadkrachtig’ the pivot [don’t understand this], the more likely the money will be used effectively.
Many of our partners use Akvo FLOW to monitor their work. In future, Akvo DASH [explain what this is] will be a major contribution to removing the time delay in processing facts and turning them into insights for use in both offices and in the field. New features we will see in Akvo FLOW include standard indicator libraries [what’s that?], survey templates and links to project pages on RSR to communicate real-time in- and outside the organisation on the work’s progress. I look forward!