Building Policy Skills of Local Partners

Today the Namati Myanmar Team is excited to be working with our local partners to build their skills to do their own policy advocacy work-- including writing policy briefs using case data. Over the last year the Namati Myanmar Team has built a strong policy advocacy portfolio of its own; this week’s training is the first in a series of trainings designed to move Namati’s advocacy beyond just our own voice, and to help our local partners develop the skills to do policy work at many different levels of government.

There is a lot of excitement in the room, but also a lot of confusion and skepticism-- in Myanmar, even using words like “policy” and “advocacy” as of two years ago was dangerous with the military government. The new government is skeptical of engaging with Civil Society for its own reasons, too.

Have others had experience in trying to train local groups on policy advocacy in this type of environment? What examples or stories have you used to convince local partners (primarily of activist backgrounds) of the importance of using data and short client stories to seek systemic change?

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This week we had our second workshop with local partners, this time focused on using data for policy change. We had two paralegals join, too! A couple of modules we used that seemed particularly helpful are:

Connecting the levels of questions and goals a) Start with the big idea you want to achieve: ex: gender equality in Myanmar [we find this is often the level our activist friends are thinking on] b) Decide what “policy level” question from your work can help lead us there: ex: "If women in Myanmar had strong land rights, we would be once step closer to gender equality. So, how do women experience land rights in Myanmar?" c) Ask what our data can tell us about this question: ex: do women own more or less land than men? does the government take longer to process cases with female clients?

Doing data analysis a) Clean your data b) graph your data c) ask yourself "what is this graph saying?" d) ask yourself "why is this what the graph is saying? Is it what I expected? If so, why might it be? If not, why might it be?" e) ask yourself "What other information do I need to help feel confident in my interpretation of the graph?" f) go collect that extra information e.g. make a different graph, have a focus group discussion with client, interview some government officials, etc. g) Decide whether to include the graph in your final policy paper; discarding a graph that just doesn’t make sense is OK!

How are other teams or organizations using data in their policy work or training others to do the same? what modules have you found helpful @namati_citizenship

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