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At the heart of any policy intervention is the data that is representative, granular, as well as available with regular frequency. Traditionally, the data used for policy interventions were mostly collected, maintained, and disseminated by the government. It was certainly necessary given that centralised planning is how we took public policy decisions. However, this gave the government the monopoly rights over the data and its usage. However, the data architecture has undergone structural changes in the last two decades. With the advent of data science and our ability to extract unstructured data, various private parties can generate and store data that can be used for policy making. This requires a new kind of expertise which is best left to the private players while the government takes on a more enabling role.

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