Owing to the ravaging effects of Covid-19 ,a local agriculture knowledge specialist has implored African governments to adopt digital dashboards which enhance data collection which can inform socio-economic forecasting models.
Writing on his weekly blog, the Knowledge Transfer Africa director Charles Dhewa says digital dashboards presents discernible information compared which most African countries rely on.
“In a digital sense, dashboards try to present comprehensive information in real time as opposed to basing decisions on historical data scattered in different government departments and projects.
“Formal institutions have awakened to the fact that relying on historical data is like driving while looking in the rear view mirror,” argued Dhewa.
The knowledge specialist believes that digital dashboards will quicken the recovery efforts of African countries from Covid-19.
“Where governments, development organizations and communities used to rely on historical data and intuitions to plan, recovering from COVID19 will most likely depend on how data is collected, analyzed and made sense in real-time of through dashboards.
“The pandemic has strong interdependence between African countries and food systems through cross-border trade that has continued to feed populations. Unfortunately, the movement of food largely uncaptured and unnoticed yet such details should be reflected on national dashboards,”he added.
However, Dhewa said in the absence of digital dashboards there is the need for African governments to touch base particularly with the agriculture sector stakeholders.
“In the absence of a robust dashboard, most agricultural policies are based on literature review and lack current market trends as well as information that should be flowing in real-time from the grassroots. Where data is lacking, policy makers should at least be informed by audiences who are the ultimate implementers of the policy especially supply chain actors like farmers and processors as well as exporters most of whom can be classified as small to medium scale.”
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