The myth of forecasting impossibility

In our previous blog article, STE Analytics CEO Pekka Aarnisalo wrote about structure as a driver of market behaviour and how you can utilise it to your benefit. In this article, he digs a bit deeper and introduces our practical forecasting tool.

The belief that we can’t know the future often comes from exposure to low-inertia, high-volatility domains like stock trading or geopolitics. But that belief becomes counterproductive when extended to systems where:

• Structural stability dominates randomness.
• Behaviour is largely shaped by internal feedback, not just external shocks.

If we ignored structural inertia and dismissed forecasting altogether, we’d be flying blind in domains where structure actually gives us a map.

Structure as a strategic asset

In systems with strong inertia, the future isn’t a blank slate – it’s already shaped by decisions and constraints that are in place today. That’s why our quarterly market outlooks aren’t just forecasts. They’re decision support tools.

They help clients see what’s coming – not because we can predict surprises, but because we understand the structure that shapes them.

Reframing forecasting as understanding

So instead of asking, can we predict the future, a better question is:

How much of the future is already shaped by what’s structurally baked into the system?

In systems with structural inertia, a large portion of future behaviour is already determined by present structure and policies. That’s not just theory – it’s demonstrable through well-calibrated system dynamics models.

So much of what will happen in the next year, or three, or five, is already unfolding: 

• The structures are in place.
• The feedback loops are in motion.

When we understand the system structure, not just the surface, we see how tomorrow takes shape not from chaos, but from the momentum of today.

Every decision uses a model – whether you see it or not

Whether we realise it or not, every decision we make relies on a model. It might be:

• a mental model based on experience and intuition
• a formal, mathematical model that’s been built to represent reality more explicitly.

Intuition has its place, but it’s also vulnerable to bias, blind spots, and inconsistency. That’s where system dynamics comes in. It offers a way to make mental models explicit, test assumptions, and bring transparency to decision-making.

When the goal is to understand structure and simulate future outcomes, system dynamics offers one of the most realistic and useful frameworks available.

From structure to simulation: a practical forecasting tool

Our modeling approach at STE Analytics follows a three-step process:

1. Identifying the structure – market rules, production capacities, customer behavior, and physical constraints.
2. Translating the structure into equations and feedback relationships.
3. Simulating the system to explore different scenarios and forecast future outcomes.

This approach brings powerful benefits:

• Scenario testing: exploring how a change in policy or capacity might ripple through the system.
• Clarity: showing how decisions connect to outcomes.
• Confidence: supporting decisions with a grounded understanding of the system’s behaviour.

With this tool, your capacity to forecast market behaviour expands, and you are able to react accordingly, gaining a competitive edge.

If you’re interested in learning more, we’re here to help!