Over the past decade, we have witnessed an unprecedented explosion in data and in the way that analytics is being used to generate insights  from such data. For example, in agriculture we used to rely mainly on subjective interpretation of weather or the farmer’s almanac to support farmer’s productivity. Now, we rely on remote sensing and predictive analytics to forecast yield, crop health, when or what to plant, etc. In healthcare, our polio eradication campaigns used to be targeted uniformly across geographies causing supply chain and coverage estimation nightmares. Now, we rely on analytics to help predict and smartly focus our interventions. This transition from diagnostic to predictive problem solving is happening across research, academic, commercial and non-governmental global development efforts, albeit with different incentives and underlying assumptions about the Data Value Chain (DVC).

I’ll describe my journey from a commercial global innovation lab to the Bill & Melinda Gates Foundation, starting with our work in Africa (Nairobi, Kenya) to set up the first commercial research lab on the continent that is focused on applied and far-reaching exploratory research. I will describe how data and its usage have emerged as one of the most important global public goods at Gates Foundation; in particular, how we are using innovative technologies across the DVC to shape/influence our program strategy teams and the engagement with our partners in pursuit of our core belief that all lives have equal value. In light of these, I will motivate a unifying DVC and global data architecture that will enable data scientists and others from the research, academic, and commercial communities to contribute toward global public good (data science for social good) and help to make tomorrow better than today for billions of people.