The Fujitsu project team aimed to create globally replicable solutions that would help the client in deeper ways than just solving the problem at hand – as Nicholas calls “innovation consulting.”
Through design thinking workshops and feasibility testing, they identified targets with high business value. Nicholas found that for modeling, the technique of combinatorial optimization (*3) proved most effective and was convinced that the Digital Annealer and background IP (intellectual property) for AI/machine learning could help extract new business value.
Planning, scheduling, routing, and allocation were found to be technically feasible and easy to solve based on a handful of production facilities and past and current experiences. But the final test was whether the entire supply chain network could be solved in a single moment, holistically, encompassing the complex supply chain, from raw material acquisition to final delivery of products. The result? An ability to simulate the entire global agricultural supply chain across 170 production facilities, solving a once intractable problem, to unlock new levels of supply chain resiliency.
Nicholas' innovation and leadership skills were highly valued by Bayer, where the Fujitsu team leveraged the Digital Annealer to find an optimal solution for material procurement in only 300 seconds.
The team also leveraged their “toolkit” of innovative approaches for dealing with complex AI / machine learning and optimization problems.
“In this way,” Nicholas recalls, “the lifecycle and supply chain of seed production can be streamlined and made more efficient, marking a new path toward sustainable manufacturing.”
(*3) Combinatorial optimization: Method of optimization in which a large number of results are obtained in a single process, rather than trying various combinations sequentially.