Near real-time data from field-level ag extension officers to aid high-level government decision-making

I am quite excited about some upcoming ‘action research’ projects at IFPRI-Bangladesh. One such pilot project (with support from CIMMYT and 1-CG COVID hub funding) involves developing a tool which will allow field-level officials of the Department of Agriculture Extension (DAE of the Ministry of Agriculture) to report the most pressing problems farmers are facing all around Bangladesh. These could be, for example, higher agricultural input or lower output prices, or the lack of availability of certain types of input (fertilizer, pesticide, etc.), as well as other environmental and market-related problems (say, lack of buyers during the COVID lockdown) faced by farmers. The idea is to produce a near real-time, nicely visualized data for top-level policymakers, who don’t otherwise have this kind of collated information available to them. Geographical hotspots, where potential adverse events are taking place, can also be identified faster.

This tool could potentially be very useful for the government . It’s also likely that this type of data will be trusted more by top-level decision-makers, since these would essentially be their own data (reported by field-level government officials). Geographical hotspots, where adverse events are taking place, can also be identified faster. For example, locations where fertilizer supply has taken a dip for some reason or some other type of input prices has suddenly increased can be identified sooner, which could lead to a proper investigation and a faster resolution of such issues.

If the piloting goes well, we plan to implement this work nationally and afterwards, (if there is enough interest) with some other government agencies. For example, the Ministry of Women’s and Children’s’ Affairs could have data from sub-district level health complexes about the height/weight of new-borns. If there is a location, where suddenly the Weight-for-Height-Z score (which is a measure of thinness/wasting of children) has decreased due to a possible aggregate shock in the local economy, it can be identified sooner.

I think these tools could help with faster and more efficient decision-making from the top level of the government, and also identify geographical hotspots where possible adverse events are happening. This pilot could make a difference and I am quite excited about working in it.

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