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FOREST PATHWAYS
Joint Call 2026 - Partnering
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Partnering
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Pekka Aarnisalo
Finland
STE Analytics
Small- and medium-sized enterprises (SMEs)
System Dynamics; Forest Markets; Value Chains; Scenario Modelling; Decision Support; Causal Modelling
TOPIC 4 – Forest Value Chains, Markets and Governance
STE Analytics is looking to join a FORESTPathways consortium under Topic 4, Forest Value Chains, Markets and Governance, as a specialist modelling and decision-support partner.
We bring over 20 years of experience in building system dynamics and structural causal models to support complex industrial and strategic decision-making. Our approach combines scenario analysis, expert knowledge, data and AI-assisted decision support to represent feedback loops, delays, constraints, investment decisions and behavioural responses that shape how markets and value chains develop over time.
STE has extensive experience modelling forest-product and wood-product markets, including pulp, paper, packaging, sawn timber and lumber, across Europe and North America. Our models have been used by industrial companies for market outlooks, scenario analysis, tactical steering, investment evaluation and strategic planning.
In a FORESTPathways project, STE could contribute an integrated dynamic model connecting factors such as forest-resource availability, production capacity, demand, trade, energy and input costs, recycling and circularity, investment decisions, policy measures and industrial transformation pathways.
The model could be used to compare alternative scenarios, identify systemic risks and trade-offs, test policy and business interventions, and assess how changes propagate across forest-based value chains over time.
We are particularly interested in collaborating with partners bringing expertise in biodiversity, forest science, lifecycle assessment, circular bioeconomy, environmental economics, policy and governance. STE can integrate results from these disciplines into a common system-level simulation and decision-support framework.
Our AI-assisted interface can also enable researchers, industrial partners and policymakers to explore model behaviour and what-if scenarios through natural language and receive explainable insights grounded in the underlying simulation.
We bring over 20 years of experience in building system dynamics and structural causal models to support complex industrial and strategic decision-making. Our approach combines scenario analysis, expert knowledge, data and AI-assisted decision support to represent feedback loops, delays, constraints, investment decisions and behavioural responses that shape how markets and value chains develop over time.
STE has extensive experience modelling forest-product and wood-product markets, including pulp, paper, packaging, sawn timber and lumber, across Europe and North America. Our models have been used by industrial companies for market outlooks, scenario analysis, tactical steering, investment evaluation and strategic planning.
In a FORESTPathways project, STE could contribute an integrated dynamic model connecting factors such as forest-resource availability, production capacity, demand, trade, energy and input costs, recycling and circularity, investment decisions, policy measures and industrial transformation pathways.
The model could be used to compare alternative scenarios, identify systemic risks and trade-offs, test policy and business interventions, and assess how changes propagate across forest-based value chains over time.
We are particularly interested in collaborating with partners bringing expertise in biodiversity, forest science, lifecycle assessment, circular bioeconomy, environmental economics, policy and governance. STE can integrate results from these disciplines into a common system-level simulation and decision-support framework.
Our AI-assisted interface can also enable researchers, industrial partners and policymakers to explore model behaviour and what-if scenarios through natural language and receive explainable insights grounded in the underlying simulation.
STE Analytics is a Finnish SME with over 20 years of experience in developing system dynamics, structural causal, and simulation models to support complex industrial and strategic decision-making.
We combine expert knowledge, historical data, and mathematical simulation to understand how interconnected systems behave over time. Our models capture causal relationships, feedback loops, delays, constraints, and organisational decision rules, enabling scenario analysis, impact assessment, and evaluation of alternative strategies and policies.
STE has extensive experience in forest-product and wood-product markets, including pulp, paper, packaging, sawn timber, and lumber, as well as in energy, chemicals, metals, and manufacturing. Our work covers European and North American markets.
We have also developed an AI-assisted interface that enables both technical experts and non-technical decision makers to explore simulation models using natural language, test what-if scenarios, and receive explainable insights grounded in the underlying model.
In collaborative R&D projects, STE can contribute system dynamics modelling, structural causal analysis, scenario development, expert-knowledge capture, impact assessment, and AI-assisted decision-support solutions.
We combine expert knowledge, historical data, and mathematical simulation to understand how interconnected systems behave over time. Our models capture causal relationships, feedback loops, delays, constraints, and organisational decision rules, enabling scenario analysis, impact assessment, and evaluation of alternative strategies and policies.
STE has extensive experience in forest-product and wood-product markets, including pulp, paper, packaging, sawn timber, and lumber, as well as in energy, chemicals, metals, and manufacturing. Our work covers European and North American markets.
We have also developed an AI-assisted interface that enables both technical experts and non-technical decision makers to explore simulation models using natural language, test what-if scenarios, and receive explainable insights grounded in the underlying model.
In collaborative R&D projects, STE can contribute system dynamics modelling, structural causal analysis, scenario development, expert-knowledge capture, impact assessment, and AI-assisted decision-support solutions.