Resilience from the Atom to the Organization

There is not much that is influencing our lives more than the risk and its implications. The perception of the risk can range from the absolute panic to the greatest fun but actually: what does risk mean?

Risk is generally described as a chance of a loss (or a gain as a negative loss). It has a stochastic element (chance) and a tangible element (loss). Fractals, as mentioned in the next lines, help to differentiate purely stochastic motions, such as midges dancing in the evening summer light (also called Brownian motion) from apparently disordered systems having an underlying structure, which may be repeated stochastically. Examples are as clouds, coastlines, blood vessels, ocean waves etc.

If we look at the pyramid of Maslow, we notice that Safety is the second basic need after physiological priorities, but what is actually Safety? How is this perceived? Does Safety mean this the absence of risk or the only the acceptance of the risk itself?

There is innumerous literature on the subject. Experts brought much light in the recent years, as great advances have been made in several disciplines. But the challenge remains: How to transfer the knowledge in its proper context, where it can be applied and ultimately save lives? To do this, we need at least a common platform and a common language.

Keep it Simple!

Fractal models describe complex shapes with simple patterns. For instance, we may approximate the shape of a cloud, a snowflake, a coastline or even the surface of a material at a microscopic level with simple mathematical algorithms based on the principle of self-similarity. Self-similarity means that a given shape is similar to itself at a smaller (or larger) scale. Similarity laws help in understanding underlying patterns in the scaling process.

As a simple rule, we could say that resilience increases safety. This is true at a Microscopic scale through the plastic zone at the tip of a crack and also true for an organization. Metaphors may also help to build bridges: For instance, we could agree that a risk is like as a needle in a bunch of hay. It may be difficult to find but it may hurt you if you sit on it.

Analogies foster Inspiration

A well-known example of transfer through similarity is the inspiration by nature (e.g. Velcro fasteners, which were inspired from burrs, that clung on the trousers).

A general procedure for transferring the knowledge by similarity may be:

  1. Find simple rules / underlying patterns
  2. Compare to other systems to find commonalities / axioms
  3. Transfer (or translate) knowledge
  4. Distillate best practices within different systems
  5. Replace in its context

To illustrate different risk patterns, lets take the example of an airline that carries passengers from A to B. First of all, the risk perceived by the passengers flying onboard that airline is influenced by, lets say, their knowledge of flying principles, their degree of information, their past experience, perceptions and so on. What happens in the heads of passengers? Are they afraid of something? What can go wrong?

Before you read further, dear reader, please remember the example of the needle in the bunch of hey. Yes, flying is very dangerous if we do not use an aircraft or anything else approved for that purpose. However, the calculated risk of a disaster in aviation in much less than that sitting on that needle: Typically less than 1 per 20 millions flights. Much less than most of the risks we experience daily [reference]. If numbers do not convince you, you may consider than describing possible failures actually increase safety, as it will prompt for adequate defenses. So more needles you find in a bunch of hey, more needles you are able to remove before you sit.

Five Safety Levels

First, failure of individual components may cause mechanical fractures affecting the aircraft structure or systems as well as physical or chemical processes generating overheating, fires etc. This occurs at the materials level where physical and chemical processes are operating. Thus we may call it materials or basic level.

Second, components are assembled to form a system (e.g. electrical system) or a structural ensemble (e.g. a wing). All have been designed, built, programmed, tested and maintained by engineers, while following customer requirements. The manufacturer translates the requirements into a product using tools and technologies. Systems can fail because individual components or the interaction between components failSystem design is often made in such a way that several elements need to fail at the same time before a total break down occurs. Hence we talk about redundant or resilient systems: Here we are at the engineering level.


Third, we as human beings not only design but also operate the systems. In our case the pilots and flight attendants reduce the overall risk, or create safety, in introducing a second layer of resilience, augmented by an intelligent decision-making. The human performance in reducing the risk is, of course, greatly enhanced by adequate training, feedback and optimum stress level. Intercultural aspects play an important role as well. However, nobody is infallible. The human level is a key level influencing all other levels.

Forth, organizations such as the airline, maintenance organization, civil aviation authority, aircraft manufacturer etc. are making flying possible and desirable. They manage risks within industrial processes, among others through Quality and Safety Management Systems. The organizational level is the last level, which can be held accountable for failures.

The fifth level (or level zero, as it also precedes the first level) is the environmental level. In our case, it may be a thunderstorm, economic pressure, unlawful interference etc. It is the level where everything started - even humans and materials have been born once upon the time out of the dust of stars. It almost permanently interacts with all other levels.

Complex Systems / Simple Rules

What we just explained here is one fractal modeling of the risk among many possibilities, which can either be repeated within itself or in another context. Hence we can reproduce the pattern to understand what would happen within the company who built, for instance, the landing gear of the aircraft) or to other stakeholders of the risk (e.g. air traffic controllers).

The purpose is to help understanding the complexity in creating an axis or point of reference where intelligence can flow… There are many other models… Maybe there is infinity of those.