Creating a culture of using monitoring data to learn

Tags: Learning, culture, capacity

This is one of a series of stories that complement the BEAM Monitoring Guidance. It offers a practical example of how a market development programme has solved a typical monitoring or evaluation challenge.

The Revitalizing Agricultural Incomes and New Markets (RAIN) project, implemented by Mercy Corps and funded by the U.S. Department of Agriculture, aims to generate economic prosperity and improve food security in northern Uganda. (see also RAIN's adoption of the CLA approach)

The programme has three core objectives: to enhance farmers’ profitability and productivity; catalyse local business; and expand access to financial services.

The challenge

When I initially started working as the Monitoring and Evaluation (M&E) Manager on the RAIN project, M&E was seen in a very different way to how it is now. The view of M&E then was a ‘traditional’ one, whereby the M&E team were seen as auditors and policemen. The RAIN team were very talented and came from a range of backgrounds and therefore had different skills and perspectives, which the M&E team needed to accommodate.

RAIN had seven different sector interventions. This was a challenge for me as I could not be in seven places at the same time to know what information each intervention needed in order to learn and adapt. It was therefore important to find a way to make M&E a part of every team member’s role, and develop a culture that supported this shared responsibility of learning.  

The solution

To overcome this challenge, which is not unusual in market systems development programmes, RAIN had to change its learning culture and how it viewed the role of M&E. Here are some of the ways we did this:

• Make the starting point for monitoring and data collection stem from what type of information the intervention manager needs. By asking them this question, you are letting them own the process. Sometimes we may want to ask very technical questions and measure complex indicators, but we do not need this data to improve what we are doing. By starting with what the intervention manager wants to know, we can keep our monitoring simple and lean. M&E just brings the technical lens and gives validity to the questions that the implementation team are asking.
• The M&E team are like teaching assistants: we help the intervention teams to find their skills in M&E by asking what their strengths are, and where they are coming from. This way we help the implementation team to learn and be less afraid of engaging in the M&E processes. It is important to embrace more qualitative methods that the implementation teams understand and trust, and therefore are willing to use and engage with.
• Show the implementation teams how much intuitive knowledge they have and how much they know about the sectors they work in, then make the focus of M&E to collect the data to back-up this knowledge.
• On a quarterly basis, the intervention teams provide a short informal report on what they have done, and then the M&E team take the time to ask about the logic pathways of what they are doing, and help them to pull out the learnings. We ask: what new things do we know? And then challenge the team to use these learnings.  
• Encourage all team members to view M&E as a part of their role, including junior members of the team.  It is important that ownership of M&E is actualised at all levels of the team. This includes soliciting ideas from junior team members on new ideas and involving them in M&E processes.  
• Build the implementing team's knowledge and skills in areas that support documentation of the processes and changes. It is important that implementation teams are tracking their own interventions and feel empowered to do this data collection themselves where possible.  

Through these approaches, I found that, in time, the RAIN team was able to build a culture of open but bold thinking and regular but intentional reflection.

Do you have something to add, or want to ask a question? Please comment below or contact the author.

To learn more, see the BEAM Monitoring Guidance on a culture for adaptive monitoring.