Selected work

Where analysis steers decisions, not just dashboards.

Examples by sector

What does a scenario analysis look like in practice? Six fictional cases using public sector data.

Warehouse capacity expansion

A logistics provider considers a €3.5M warehouse expansion based on a capacity rule of thumb. The analysis shows that without expansion, capacity runs out in 100% of scenarios within three years.

"Should we expand?" → "What does 12 months of waiting cost?"

Housing project phasing

A developer hesitates on phase 2 of a €30M project. The analysis shows that waiting costs €50K per month and lowers expected net profit from €1.7M to €1.3M. Waiting makes it worse, not better.

"Is now a good time?" → "What does each scenario cost?"

Financial services

Payment platform rollout to new market

A fintech considers expansion to Belgium based on a single adoption forecast. A 6-month pilot costs time but acts as a filter: the probability of losses exceeding €1M drops from 28% to 16%.

"Should we go for it?" → "Which entry strategy fits the uncertainty?"

Production line scale-up

A manufacturer wants to expand based on a full order book. The analysis delivers a trigger-based decision rule that halves overcapacity and preserves more margin.

"Should we expand?" → "At what trigger point is it justified?"

Store expansion

A retail chain wants to open 4 stores. The analysis shows that phased opening (2+2) reduces the chance of a costly closure from 62% to 44%.

"Where do we open?" → "How many at once is responsible?"

Food production

Production line scale-up

A food producer wants to build a second line for one large retail contract. Co-packing as a bridge reduces stranded risk from €1.5M to €40K.

"Do we build the line?" → "How do we contain the contract risk?"

Deep dives

Extended technical cases. Full details available on request.

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