Methodology
A single-point NPV hides risk. We model the distribution.
Most technical reports end in one number. That number implies a certainty the underlying geology and markets never had. ROGUE's models carry the uncertainty through to the decision — so what lands on your desk is a range you can defend, not a guess dressed up as precision.
From inputs to decision
- 01
Input distributions
Price, grade, cost, and schedule ranges — not single-point assumptions.
- 02
AI and Solver Simulation engines
Turning Technical Geological and Environmental metrics into Monte Carlo analysis, running thousands of scenarios through the DCF, WACC, NPVs and/or MAP models yielding probable plays and risk management.
- 03
P10 / P50 / P90 outputs
Econometrics and Stochastic modelling into probabilities-weighted range of outcomes, not just one number.
- 04
Strategic Decision-Making from a Systemic Perspective
A defensible economic case, with the risk made explicit.
Case study
HERMES: shutdown-frequency optimisation under volatile copper prices
HERMES is a Python and Monte Carlo model built from the founder's MSc research, modelling shutdown-frequency optimisation for a Tier-1 copper concentrator under volatile copper prices. It is presented here honestly as a modelled scenario, not a live client deliverable.
Planet, People, Profit
ESG risk is priced the same way price risk is
Community and environmental risk aren't a compliance appendix — they're a cost, schedule, and licence-to-operate variable within the same model. GRI indicators, Indigenous land-use considerations, and UN Sustainable Development Goal resource-respect metrics translate into probability-weighted risk, the same way a price scenario does.
The grounding is two-sided: an MBA Global Sustainability holistic approach and our environmental fieldwork on the ground. Different disciplines, same output — a number the model can use.
Tools
- Python
- Monte Carlo simulation
- Scenario dashboards
- Excel / Solver cross-validation
- Customised AI Modelling for your project