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Supply planning is a challenge for the forest industry in the context of natural forests characterized by heterogeneity among raw materials. Several mathematical models have been proposed in the literature to support forest planning, though few have been used by companies. The complexity of the natural environment and the expertise required to use these models limit their application. Nevertheless, these tools can significantly improve profitability. Three main elements were analyzed to assess benefits fostered by computer-optimized planning: (i) assessing the potential of implementing mathematical optimization in companies, particularly by pinpointing the additional resources necessary; (ii) determining the benefits of mathematical optimization to support planning decisions in an industrial context; and (iii) analyzing the impact of variation in information precision. LogiLab, an optimization software was used to find the optimal allocation of raw materials to an industrial network of five mills. The plan produced using optimization was compared to the plan generated by company personnel. The optimized plan generated a nearly 20% greater net profit than the current planning method. This difference was in part due to the more efficient allocation of raw materials to mills. It also highlighted numerous benefits, including a 50% reduction in the time required to produce plans. Furthermore, if attributed volume can be distributed among sawmills, it would be possible to save CAD 3.21/m3 using optimized plans, greatly exceeding initial costs related to system implementation.