Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia

Research output: Working paper

Abstract

The UN Sustainable Development Goals (SDGs) create a global need to deliver on an agenda which relies heavily on quantitative data. This creates a demand for human capital with the requisite statistical and data skills to work on the challenges represented by the SDGs. Increasingly, long-term domestic solutions to the building of statistical capacities are being sought, in order to decrease the dependency on external support and ensure a sustainable flow of qualified professionals.

In this paper we argue for the value of thinking of statistical capacity as a pipeline which needs to begin in the education system, and illustrate how investment in this end of the pipeline can deliver a more sustainable and long-term pathway to building up the holistic skills-base to enable the challenges of the SDGs to be tackled. We describe an existing tried-and-tested experiential learning model called Q-Step based on developing skills in the workplace, and propose that the successes of this partnership-driven model illustrate how ‘data fellowships’ can fulfil some of the unmet capacity needs of the data revolution for sustainable development.

We illustrate our argument through a practical exploration of the development of such a learning model in Colombia. Although there are challenges in ensuring that educational access is equal, we demonstrate that there are significant opportunities and a data fellowships model opens doors for addressing local skills gaps to help deliver the SDGs.

Bibliographical metadata

Original languageEnglish
Place of PublicationManchester
PublisherUniversity of Manchester, Global Development Institute
Number of pages18
Publication statusPublished - 2021

Publication series

NameDigital Development Working Paper Series
PublisherCentre for Digital Development, Global Development Institute