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Bringing Decision Analytics to Agriculture R&D - Syngenta's Edelman Prize Winning Effort

Jack Kloeber, Kromite
August 17, 2016 (SDP Webinar Invited Talk Co-Sponsored with DAS, Edelman Prize Winner)

Syngenta, a leading developer of crop varieties (seeds), is committed to bringing greater food security to an increasingly populous world by creating a transformational shift in farm productivity. Syngenta Soybean R&D is leading the corporate plant-breeding strategy by developing and implementing a new R&D model that is enabling the creation of an efficient and effective soybean breeding strategy. The combination of advanced analytics and plant-breeding knowledge is identifying opportunities to increase crop productivity and optimize plant-breeding processes. Discrete-event and Monte Carlo simulation models codified Soybean R&D best practices, and stochastic optimization helped find the best soybean breeding plans and strategically align its research efforts. As a result, Syngenta estimates that it will have saved more than $287 million between 2012 and 2016. The presentation will focus on the Decision Quality aspect of supporting this effort.

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Keywords: evaluation anamod, decision quality decqual, optimization optz, simulation mcsim, analytics bigdata, modeling modtree

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