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Digital Extension and Advisory Services (EAS) have evolved to deliver more need-based advisories at scale ranging from broadcast media to Artificial Intelligence (AI)-backed applications. Over the years, rapid growth in the number of digital EAS providers has seen the use of varied channels to deliver similar advisories that are generic. Very few of these have succeeded in providing content that is relevant to a specific situation or problem farmers are dealing with. While the large amounts of data generated through these digital advisory tools can be used to provide data-informed advisories that are more specific and customized to the diverse needs of farmers, very little progress has been made in this direction. Data is the new oil which is of no use until it is refined, processed, and turned into actionable insights. However, processing and analyzing big data is extremely complex. Making sense of big data is an evolutionary process that calls for the realization of its potential and the streamlining of numerous procedures. This also means that the capacities of EAS in using the massive data generated from these digital advisory services/tools need enhancement. Combining datasets from these varied sources and the application of big data analytics to derive insights often require collaboration between multiple organizations and departments to create a flow of activities, as organizational silos are blocking the flow of data for decision-making.
