In forest industry, procurement activities planning is a complex task. It requires taking into account a lot of information such as forest inventories, final products demand, seasonality in forest sectors and production capacity. This information should be provided by different stakeholders in the supply chain such as mill managers, forest engineers, sales managers, etc. The collaboration between these stakeholders is necessary to exchange information and support the planning task.
Several researches have been done in order to support forestry companies in improving their planning process and thus making better decisions. For this purpose, some authors adopted an operational research approach. Previous work showed that optimization models can be integrated into forest manufacturing processes and that they help planning forestry operations efficiently and easily. In fact, they reduce planning time as most of them (models designed to plan transport, harvesting, etc.) take only a few minutes to find the optimal solution. Furthermore, it has been proved that they increase profit by more than 5%.
However, despite their advantages, optimization models are rarely implemented in the forest industry. They do not meet the companies needs. Indeed, planning is still done manually, by a trial/error approach. Engineers rely on their knowledge, experiences and intuitions to plan different activities (harvesting, processing in mills, sales, etc.).
What could be the reasons limiting the adoption of these models by forestry companies?
Several researches have been done in order to support forestry companies in improving their planning process and thus making better decisions. For this purpose, some authors adopted an operational research approach. Previous work showed that optimization models can be integrated into forest manufacturing processes and that they help planning forestry operations efficiently and easily. In fact, they reduce planning time as most of them (models designed to plan transport, harvesting, etc.) take only a few minutes to find the optimal solution. Furthermore, it has been proved that they increase profit by more than 5%.
However, despite their advantages, optimization models are rarely implemented in the forest industry. They do not meet the companies needs. Indeed, planning is still done manually, by a trial/error approach. Engineers rely on their knowledge, experiences and intuitions to plan different activities (harvesting, processing in mills, sales, etc.).
What could be the reasons limiting the adoption of these models by forestry companies?
Thats unfortunate that methods can't be applied in real world! Well, why we develop theories in first place!!
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