Ontonix: "Optimal does NOT mean best"


Nowadays it is very popular to seek optimal solutions to a broad spectrum of problems: portfolios,  engineering systems, strategies, traffic systems, distribution channels, networks, policies, etc. But have you ever wondered if optimal really means best? Well, it does not. Optimality is not the most convenient state in which to function. The reason?

Optimal solutions are inherently fragile.

Our economy (but not only) is fragile because everything we do is focused on maximizing something (profits,  performance, success) while minimizing something else (risk, time, investment, R&D) at the same time. This leads to strains within the system. Everything is stretched to the limit (or as much as physics will allow). This is exactly what one should not do when facing turbulence. The focus should, instead, be on:

  • Solutions that are fit, not optimal.
  • Simplifiying business models and strategies.
  • Accepting compromises not seeking perfection. Improve, don’t optimise.

Read the full article: Ontonix – Complex Systems Management, Business Risk Management.

One Response to Ontonix: "Optimal does NOT mean best"

  1. Apparently there is a problem with a link in the article so to tempt the technically-minded in, here is an extract of lies lies beyond this link: http://www.marczyk.net/Beyond%20Optimization.htm

    “Complex systems are driven by so many interacting variables, and are designed to operate over such wide ranges of conditions, that their design must favour robustness and not optimality. In other words, robustness is equivalent to an acceptable compromise, while optimality is synonymous to specialisation. An optimal system is no longer such as soon as a single variable changes – something quite possible in a world of ubiquitous uncertainty. As the ancient Romans already knew, corruptio optimi pessima – when something is perfect, it can only get worse. When you’re sitting on a peak, the only way is down – when you’re optimal, your performance can only degrade. It is for this reason, that optimal systems are fragile. It is for this reason that a state of optimality is not the most probable state of a system.”

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