data systems strengthening

i have been saying for some time that my next moves will be into monitoring and vital registration (more specifically, a “poor richard” start-up to help countries to measure the certainties of life: (birth), death, and taxes. (if village pastors could get it done with ink and scroll in the 16th c across northern Europe, why aren’t we progressing with technology??! surely this is potentially solid application of the capacity of mobile phones as data collection and transmission devices?).

i stumbled onto a slightly different idea today, of building backwards from well-financed evaluation set-ups for specific projects to more generalized monitoring systems. this would be in contrast to the more typical approach of skipping monitoring all together or only working first to build monitoring systems (including of comparison groups), followed at some point by an (impact) evaluation, when monitoring is adequately done.

why don’t more evaluations have mandates to leave behind data collection and monitoring systems ‘of lasting value,’ following-on an impact or other extensive, academic (or outsider)-led evaluation? in this way, we might also build from evaluation to learning to monitoring. several (impact) evaluation organisations are being asked to help set up m&e systems for organizations and, in some cases, governments. moreover, many donors talk about mandates for evaluators to leave behind built-up capacity for research as part of the conditions for their grant. but maybe it is time to start to talking about mandates to leave behind m&e (and MeE) systems — infrastructure, plans, etc.

a potentially instructive lesson (in principle if not always in practice) is of ‘diagonal’ health interventions, in which funded vertical health programs (e.g. disease-specific programs, such as an HIV-treatment initiative) be required to also engage in overall health systems strengthening (e.g.).

still a nascent idea but i think one worth having more than just me thinking about how organisations that have developed (rightly or not) reputations for collecting and entering high-quality data for impact evaluation could build monitoring systems backwards, as part of what is left behind after an experiment.

(also, expanding out from DSS sites an idea worth exploring.)

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