In the early hours after Hurricane Sandy struck the eastern United States very little was known with reasonable certainty about how the storm was affecting specific areas, particularly those areas with a disproportionate share of low-income and socially-vulnerable people.
Direct Relief was busy at the time assembling and cross-referencing datasets on everything from weather forecasts to pharmacy status to electrical power to clinical health conditions and demographics in an effort to gain a more complete understanding about the probable impacts on our partners, the patients they serve, and the health needs that would result to which we were capable of responding.
Palantir’s cutting-edge data integration and analysis platform amplified the scale, speed, and precision of this work in significant ways, which in turn amplified Direct Relief’s capacity over the coming days and weeks to respond in efficient, timely and accurate ways in order to mitigate the impact of the storm on the region’s most vulnerable people.
As Direct Relief’s CEO, Thomas Tighe phrased it during a recent talk he gave at Palantir’s Palo Alto headquarters Feb. 18th, “When an emergency event happens, the urgency to act is very high and the information upon which to act is very low. One of the great challenges that Palantir is trying to help Direct Relief and other groups solve is, ‘how can you have better information upon which to act, particularly when there’s an urgent need to act?”
As preparations continue for new emergencies which may arise, Direct Relief is focusing on helping to solve the informational problems associated with disaster response through better data collection, aggregation and analysis. Our collaboration with Team Rubicon and others on Palantir’s recent commitment to the Clinton Global Initiative is a leading example of how intelligent partnerships built around the best informational tools available can help to improve the quality, pace and targeted effectiveness of response to emergency events, by a broad range of actors, particularly during the immediate hours and days when responders have traditionally known the least.
