KM, learning and rocket science

Riff Fullan, 06 July 2015
KM, learning and rocket science

A recent visit to our program office in Pakistan reminded me about the multiple possibilities around promoting more knowledge and learning (K&L) in our work, including both within the organisation and amongst the partners we are working with. I was facilitating an exercise looking at how our program in Pakistan could strengthen the K&L element in its M&E systems. We focused on two projects, one a Water, Sanitation and Hygiene (WASH) project, and one a broader livelihoods project.

What we confirmed when we looked more closely at the various M&E activities people were involved with was that over a number of years (plus or minus 10), the M&E systems have become quite well-developed, and the collecting and reporting on data are working reasonably well. On the other hand, there was a feeling that a lot of energy was going into the whole process, but the resulting outputs were not anchoring learning as well as they could. The accountability requirements to our donors are being nicely fulfilled but still, people feel there is a gap, especially around broader questions of project steering.

After discussing various possibilities, we came to the conclusion that opportunities for joint reflection were not fully taken up, and the outputs produced were not so effective at sharing what was being learned by the various stakeholders. This is not a unique story. Of course, this is a challenge in general with many M&E systems that are designed to report against logframes and the outcomes and outputs associated with them. When the mechanisms for collecting and processing data and information are put together, it is natural to focus a lot of energy on indicator reporting, but there is a lot more to learning than tracking and reporting on indicators.

For me, one of the biggest challenges is ensuring that opportunities for collective reflection are created and taken up. For example, where providers of data are not well-connected to the process beyond being data sources, it is often challenging to get them to provide it in a timely and comprehensive way, which is understandable because they don’t see what happens with the data, how it is used, how it affects project implementation. In other words, they don’t have much of a sense of ownership. Another important thing to think about is that data collected around indicators generally does not have the richness that discussion and joint reflection bring to the equation.

I often think about how complicated it is to do good knowledge sharing and learning, to practice what we preach when it comes to good K&L behaviour, but my experience in Pakistan reminded me it is not always so complicated. The solutions we came up with were really not earth shattering: putting some effort into finding and telling good stories, investing a bit more time in analysis of M&E results, consulting communities more closely about impact. All of these are relatively small adjustments to what is a well-functioning system to help project staff and program management to understand what is happening more deeply, and to act on that understanding to improve the effectiveness of our work.

So, the message I came back with was it’s not always about rocket science, sometimes just a little shift of attention and energy can go a long way.

Riff Fullan

Riff Fullan

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