# First-Principles Approach to Modeling

Our strategy is grounded in a dedication to applied mathematics and a first-principles approach to problem-solving.

Our strategy is grounded in a dedication to applied mathematics and a first-principles approach to problem-solving. This means that instead of beginning with assumptions about the problem and its solution, our path starts with a deep analysis of the problem to be solved, the nature of the data available, and the core needs of the end user. We find that this first-principles approach yields robust, tailored solutions that outperform black box or ad hoc options when operating live with real-world data. This approach requires not only skill and discipline but also confidence in the ability of mathematics to model a system or process and provide the basis for sound decision-making and insight in operational settings.

*“The miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve. We should be grateful for it and hope that it will remain valid in future research and that it will extend, for better or for worse, to our pleasure, even though perhaps also to our bafflement, to wide branches of learning.” – Eugene Wigner (1902 – 1995)*

For over 35 years, Metron has proved Wigner’s conjecture holds true. In fact, we are so used to this phenomenon that we take it for granted. Nonetheless, it is supremely rewarding when a mathematical model you have developed provides good guidance for making decisions or providing insight into the operation of a complex system.

A significant aspect in crafting these models is determining which factors are most important and which can be safely discounted. Mathematical models are by necessity simplifications of reality so understanding where to focus is of paramount importance. As George E. P. Box noted:

*“All models are approximations. Assumptions, whether implied or clearly stated, are never exactly true. All models are wrong, but some models are useful. So the question you need to ask is not ‘Is the model true’ (it never is) but ‘Is the model good enough for this particular application?” – George E.P. Box (1919 – 2013)*