Author(s): Pulse Lab Jakarta
Approaches to data collection for development programming have commonly relied on official statistical data in combination with surveys to plan, implement and monitor progress and impact for interventions. Today, the emergence of big data has resulted in a paradigm shift, with increasing use of non traditional data to promote more effective and responsive interventions across various domains. Contributing to the global Data Powered Positive Deviance initiative, Pulse Lab Jakarta conducted data analytics research by merging traditional statistical data with Earth Observation big data to identify potential rice producing villages across Indonesia that might be faring better than others, referred to as positive deviants (PDs). Our team recently wrapped up the pilot study and this post is intended to capture the process that they undertook. We are also pleased to share the technical report, detailing the preliminary results, key learnings, along with some actionable recommendations for future work in the agriculture domain.