Andrea Feunekes
CEO, Remsoft
The complexities of the forestry industry are an untapped opportunity for transformative AI analytics. One Canadian company is seizing the moment.
Intelligent analytics and artificial intelligence (AI) are revolutionizing efficiency in almost every industrial sector, but not all operations are created equally when it comes to machine learning. The more intricate the workflow, the more robust the AI needed to tackle it, and the greater the rewards of doing so effectively. And it’s hard to find workflows more intricate than those on the forestry block.
“Forestry is one of the most complex sectors for analysis,” says Andrea Feunekes, CEO of Remsoft. “You’re working with a biological asset, so there are a lot of variables that you wouldn’t see with hard assets like buildings. There are also concerns like sustainability and the social license to operate, which add complexity that other sectors don’t necessarily have. Factor in the low margins the forest industry operates under and you have a critical need to squeeze out every bit of efficiency possible.”
AI sees the forest and the trees
Remsoft has a long history of developing mathematical optimization software for the forestry industry, and in 2021 it’ll be bringing its first fully AI-enabled analytics offering to the market, focusing on forest-to-mill operations. “We’re always aiming to take the guesswork out of forestry,” says Feunekes. “Each company is making literally thousands of small decisions every day that impact productivity. The AI component can pull together disparate pieces of information to provide insights that a human might not recognize.”
Whether it’s identifying that work on a harvest block is going to be behind schedule well before the workers themselves realize or revealing the hidden variables driving output volume, AI systems can quickly guide the tweaking of plans and processes for the future. It’s the key to better informed decision-making and maximized efficiency in a loop of continuous improvement from the forest to the mill.
