Program Metrics Teach Nuru about Job Specialization
I mentioned a few weeks ago that we have gathered a lot of data related to many of our program metrics. The analysis and QC that we were conducting back then and have continued since have gone very well.
At this point we have finished the first round of analysis and QCing for the baseline data for the Education program’s literacy assessment, which, as a reminder, was done with the Uwezo tool. We have baseline literacy levels for boys and girls by grade level at several of the schools where the education program has been conducting interventions. In time, we will conduct a subsequent test of these students to see whether or not we have, to use one of Jake’s old favorite phrases “moved the needle” on literacy.
David and the team in the field are working for the remainder of this month on continued QCing of the data that was collected for the household survey at the end of last year. As you might recall from a previous post about that, that survey was mostly about Healthcare and the Water and Sanitation program (which I have referred to here on this blog as the WatSan program, but should be referred to as the WASH (WAter, Sanitation, and Hygiene) program). So we expect that we will have baseline data for those three programs ready to share by perhaps the end of April if you are interested. I will not be posting actual data on this blog, for the most part, so if you want data from us, let me know then. (email@example.com)
As for Ag and CED, we already have baseline data for a couple of their program metrics, and are in the process of gathering it for the rest. Those programs are a bit different than the other three, because data has been a huge part of running the work that they do from the beginning, so they have automatically had metric values. The work we are doing with them is around organizing the data and cleaning it so that we have faith in it.
As is the case every day we do this work, we learned a lot of lessons throughout the process of conducting these assessments. One of the lessons was about what we have the Kenyan staffers spending time on. We have a team of five Kenyans who are M&E specialists in the field, as we have mentioned here. These five staff members have been fully occupied with the grueling work of getting around the entire community and conducting these household surveys and Uwezo assessments during the past few months.
Some of them enjoy this kind of work very much and thrive in it, and others thrive much more behind a computer screen or working directly with program managers to strategize about program and metric system design and implementation.
Because of these differences in skills and preferences, David and Rogonga have come up with a proposal to specialize roles on the Kenyan M&E team into three categories: Advising, Data Collection, and Data Entry and Analysis.
They are working hard with the Kenyan team to move people’s titles around, formulate these new roles, and get team member’s into them.