Planning, forecasting, test-driving your strategy

Use simulation to discover new ways of improving the business, without risking it

Most business decisions, whether strategic or operational are made without any option to 'undo' and mistakes can be costly. Furthermore, we only have one physical reality to try something new. For these reasons simulation models allow managers to assess the impact of a decision before it is made. With a rich history dating back to the 1950's, this is one of the earliest applications of computers in management science.

We have a long track record of working with clients to define, implement and maintain simulation models for decision support across many industries, functions and time scales. From near-operational, day-to-day planning of production lines in manufacturing plants to long term scenario analyses of cycles in asset-heavy industries using System Dynamics.

Our consultants have experience working with all the main simulation paradigms and many associated tools, including:

  • System Dynamics (Vensim, AnyLogic, Jitia)
  • Agent-Based Modeling (AnyLogic, Python, C)
  • Discrete Event Simulation (Arena, AnyLogic)
  • Monte Carlo simulation (R, MatLab, SPSS, Python, Excel)

We also build custom simulations, visualisations and integrations, e.g. running the simulation on a tablet, in the browser, offline in Excel, or scaled up on a powerful cloud cluster.

Stages in a simulation project

How to build a simulation model


Analyse the nature of the business problem

Collect Data

Identify internal and external sources, stage and clean data


Confirm blueprint with stakeholders

Refine and Calibrate

Align model with reality - measurable and perceived


Gradually expand scope/dimensionality/detail until fit for purpose

Analyse & Visualise

Use model to visualise results, show sensitivities and inform business decisions

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Case studies

How this approach has helped our clients


A manufacturing plant in an industry-leading B2B company with several major brands wanted to reduce the number of production lines whilst maintaining or increasing the number of different SKUs made at the facility.


We built a production simulation tool that allowed testing the setup and manning of the production lines, measuring hours worked, throughput etc. Adding an optimisation module on top of the simulator, the next generation of the tool was able not just to analyse the setup, but also to schedule production.

The tool and simulation was first prototyped in Excel and later integrated into daily floor routines via a bespoke tablet app that allowed to live-update the simulation in real-time.


Asset investment decisions and other long term strategic choices are more often than not based on 'gut instinct' instead of deductive reasoning, simply because the latter is not an option when making judgements regarding the future. Executives can improve their strategic foresight with scenario-based analysis.


Applying System Dynamics, a modelling technique based on a research tradition at MIT - our consultants have built a number of dynamic simulation models of industries and markets characterised by expensive assets with steep price curves from supertankers to inner city condominiums.

Dynamic simulation models are based on an explicit understanding of market drivers and their interdependencies, including feedback loops.


A pharma company ran a complex simulation on the cost and benefits of different cancer tests.

Due to the complexity of the results and the variety of underlying assumption, communicating key advantages of their tests to key stakeholders and payers proved difficult.


We developed a highly interactive web-tool that shows the key visuals of the simulation. Quick scenario selection and change of key parameters, as well as multiple sensitivity analyses and cost-benefit charts allow stakeholders to identify easily under which circumstances the client's test is the best choice.

What our clients say about us:

Asset acquisition timing

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Contact us

We'll simulate your plant, process or industry

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