How the models are built and checked.

Dynamic Risk & Resilience Modeling

System dynamics

Problem

Static risk registers and heat maps score a threat once and freeze it. They can't show how a disruption compounds through delay, capacity limits, and the responses of the people and systems around it — which is usually where the real damage happens.

Approach

We build a system dynamics model of your network's disruption pathways — stocks, flows, and the feedback loops connecting them — calibrated against real network structure and, where available, historical reference modes.

Output

A working model, a set of early-warning indicators tied to it, and stress-test scenarios you can defend to a board or a regulator — not a one-time score.

Fits when

Your current risk process treats disruptions as independent events, or your resilience metrics haven't been able to explain why a "low probability" risk turned into a long-tail recovery.

Network Design Optimization

MILP / stochastic programming

Problem

Facility, sourcing, and capacity decisions typically get optimized on landed cost alone. Resilience and flexibility show up afterward, as a qualitative overlay, which means they lose every time to a cheaper number.

Approach

Mixed-integer and stochastic optimization models that put a number on flexibility — deferral, expansion, dual-sourcing, switching — alongside cost, so the trade-off is explicit rather than assumed.

Output

Candidate network configurations with quantified cost-resilience trade-offs, sized for the capital allocation conversation you actually need to have.

Fits when

You're facing a re-sourcing, capacity expansion, or footprint decision and want the resilience value of each option priced, not asserted.

Systems Diagnostics & Executive Workshops

Causal mapping / simulation

Problem

Teams routinely diagnose structural problems as behavioral ones — blaming a supplier, a planner, or "poor communication" for dysfunction that a system dynamics reading would trace to the structure itself. The bullwhip effect is the textbook case.

Approach

Facilitated causal loop mapping with your team, backed by simulation exercises — including live, game-based demonstrations — that let people feel the dynamic before they're asked to accept the diagnosis.

Output

A shared causal model your leadership team actually agrees on, and a clear read on which fixes are structural (durable) versus behavioral (temporary).

Fits when

You've tried the obvious fixes — more communication, tighter forecasts, new SOPs — and the same problem keeps resurfacing in a different form.