2020 CONCORDIA AMERICAS SUMMIT

Working with Data in Latin America: Strategies & Challenges

Main Stage

Programming Sponsor: Rubicon

• For Steve Bennett, data is not an end in and of itself. Rather, it is a means to help entities, especially governments, make smarter and faster decisions. The SAS Institute partners with governments across the globe, helping them manage, prepare and synthesize data that can then be used to inform decision making. 

“With sustainability, you can make a big impact if you take things one step at a time and show value,” Steve Bennett.

• Rubicon is a technology company with an ambitious mission to end waste. According to Renaud de Viel Castel, Rubicon has created an innovative platform that connects customers (who generate waste, including commercial, municipal, and residential waste) with haulers (who collect waste). This platform brings visibility, transparency, and, critically, actionable data. 
• When encouraging governments to adopt a more data-centric approach, Bennett recommends starting small. He suggests first choosing a small, specific issue that has the potential to see early, rapid success and demonstrating the value of applying data to that particular issue; from there, one can scale up efforts. 

“With our technology—which can, for example, identify the color of the trash bins outside—we can map which neighborhoods are recycling more, which ones less, and thus give solid evidence to drive recycling campaigns,” Renaud de Viel Castel.

• De Viel Castel acknowledged the concerns that Rubicon’s constituents may have around data privacy and security. He explained that Rubicon ensures that its algorithms only capture necessary data; for example, if the algorithm is set up to recognize and extrapolate data about blue bins, it will blur out and fail to save anything outside of those blue bins. 
• In order to be efficient with network bandwidth, Bennett recommends pushing analytics “out to the edge.” With this approach, devices that are deployed to various settings (such as drones) perform the vast majority of the data analytics; these devices then only communicate back insights from the data rather than the data itself, which can be colossal.