Decision making in the forest value chain

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The primary objective of this proposal is to develop decision support tools, enhancing the competitiveness offuture Canadian forest bioeconomy value chains through analytics. Analytics enable organizations to turncomplex challenges into substantial opportunities by transforming data into information and information intoinsight for better decision-making and result improvement. Another key objective is to leverage Big Data inconjunction with analytics techniques and tools to reduce pollution, thereby stimulating the viability offorest-based communities and making logistics and transportation operations more efficient. This proposal ispart of the FORAC 4.0 research program and extends from successful research efforts conducted by theresearch consortium over the last 15 years. Both industrial leaders and academics have identified the problemsaddressed. On our end, we assembled a multidisciplinary team of researchers and students from the industrialengineering, business analytics, forest engineering, and computer science fields. In so doing, we identified akey factor for success in research and technology transfer: a close collaboration with industrial partners. Thesepartners will provide problem insight, data, facilities, result analysis for case studies, and be receivers oftechnology transfer. Thirteen multidisciplinary and team-trained HQP will be an important outcome duringthis proposal (4 Ph.D., 5 M.Sc., and 4 internships).