Define
Translate the decision problem into variables, constraints, assumptions, and outputs.
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Professional service 05
Mathematical & Quantitative Modelling
Purpose-built models for forecasting, optimization, scenario testing, and strategic planning.
Discuss this service
I build transparent quantitative models that make complex systems easier to test and manage. Models are designed around a real decision—forecasting demand, allocating resources, evaluating risk, or comparing strategic scenarios—not around complexity for its own sake.
What this work helps you achieve
- Explicit assumptions and model logic
- Scenarios that reveal key sensitivities
- Forecasts with uncertainty made visible
- A practical tool that users can update and interrogate
A real-world workflow
Clear stages. Visible progress.
Every engagement is adapted to its context, while keeping the work transparent and collaborative.
Construct
Build and document the model using the most appropriate mathematical structure.
Test
Calibrate against evidence, validate behaviour, and run sensitivity and stress tests.
Transfer
Deliver the model, explain its limits, and train users to update scenarios safely.
Typical deliverables
What you can receive
- Forecasting and scenario models
- Optimization and resource-allocation models
- Simulation and sensitivity analysis
- Model documentation and assumptions register
- Decision tools and user guidance
Tools & technologies
Selected toolkit
- MATLAB
- R
- Python
- Stata
- SPSS
- Excel
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