SimDec in Cartoons – Explaining Uncertainty Analysis Visually

When thinking about how to explain SimDec, the idea of using cartoons emerged.
It started as a simple communication experiment — and an excuse to learn animation — but became a fun and effective way to visualize the logic behind simulation decomposition.

Below are three short videos that introduce SimDec through simple stories and playful metaphors.

🦉 1. Investment problem: the owl and the bird hotel

Once upon a time, an owl wanted to invest in a bird hotel. She made all the right calculations — and the project looked unprofitable. But when she included uncertainty about future visitors, she got a distribution of possible profits instead of one number.

Most outcomes were still below zero. Then came the twist: by decomposing that distribution into scenarios, the owl discovered the structure behind uncertainty.
If only small birds come — the project fails.
If big birds visit — there’s a small chance of success.
But if squirrels join — the project turns profitable.

The owl invested, got rich, and lived happily ever after — using simulation decomposition ever since.
SimDec. Analyzing uncertainty — easy.

📦 2. What’s inside your investment model?

Imagine your investment model as a black box. It has input factors and one profitability output.
You can test sensitivity one factor at a time — or run a Monte Carlo simulation where all factors vary together. The result is a probability distribution, but it doesn’t show how individual factors interact.

SimDec solves this by decomposing the distribution according to several inputs at once.
It reveals both the big picture and the influence of individual factors, helping you steer your project toward the desired profitability range.
SimDec. Analyzing uncertainty — easy.

⚡ 3. Choosing an energy investment strategy

Imagine an energy company deciding how to invest in a new renewable power plant.
Costs, production, and electricity prices are uncertain — and three strategies are on the table:

1. Selling at market prices,
2. Signing a fixed-price contract,
3. Applying for a subsidy.

A standard Monte Carlo analysis shows the contract strategy as least risky. But applying SimDec changes the story:

• Under market conditions, uncertainty dominates and steering is impossible.
• Under a fixed contract, high production and optimistic cost scenarios become profitable.
• Under a subsidy scheme, all high-production cases are above zero — guaranteed profitability.

Using SimDec revealed hidden structure in uncertainty, changed the investment decision, and avoided potential loss.

🎬 Reflection

These animations started as a way to explain SimDec simply — but they also demonstrate what makes the method unique: it brings structure, intuition, and actionability to complex uncertainty.

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