New needs and training modalities for the sustainable transfer of know-how on food and agriculture statistics in the COVID-19 era



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Food and Agriculture Organization of the United Nations

Author Pietro Gennari, Valerie Bizier, Cristina Petracchi and Dorian Kalamvrezos Navarro

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The Sustainable Development Goals (SDGs) Global Indicator Framework (GIF) has multiplied training needs due to the large number of new indicators to be monitored by countries, whereas COVID-19-related social distancing restrictions have provided an unexpected springboard for the proliferation of cutting-edge virtual training tools and modalities. This has exposed a panoply of new data-related skills needed by contemporary statisticians, and therefore the types of training that could be most appropriate for acquiring these skills. This paper analyses the changing context and nature of training, with particular reference to the experience of FAO as a custodian agency for a large share of SDG indicators. The combination of different learning modalities, appropriately blended into a coherent learning programme, is shown to have the greatest impact, with one modality reinforcing the strengths and dampening the limitations of another.

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