Ludwig von Bertalanffy introduced the idea of a General System Theory in 1969. He understood such a theory as a unifying theory of science, as certain systemic effects or patterns could be found in a number of sciences.
“We need a simpler, more unified approach to scientific problems, we need men who practice science—not a particular science, in a word, we need scientific generalists”
and
“Unity of Science is granted, not by a utopian reduction of all sciences to physics and chemistry, but by the structural uniformities of the different levels of reality.”
A recurring systemic pattern that I have found to occur in a number of different sciences and domains can be explained by a hysteresis curve.
 |
| Illustration of a hysteresis curve for three different applications |
This type of pattern can be found in physics, biology, organisation theory, media theory / psychology and others. For instance in biology: Martin Scheffer et al discuss Catastrophic Regime Shifts in Ecosystems (Nature 2001):
“External conditions to ecosystems such as climate, inputs of nutrients or toxic chemicals, groundwater reduction, habitat fragmentation, harvest or loss of species diversity often change gradually, even linearly, with time. The state of some ecosystems may respond in a smooth, continuous way to such trends. Others may be quite inert over certain ranges of conditions, responding more strongly when conditions approach a certain critical level.”
(highlights added) and
“Because of hysteresis in their response and the invisibility of resilience itself, these systems typically lack early-warning signals of massive change.”
Constant increase in phosphorous influx into a lake can create an effect similar to curve (1) in the illustration. For a time, the system shows only little ecological effects until a tipping point is reached and the system deteriorates sharply. In some cases the original “healthy” state can be regained by removing the negative effect (Phosphorous in that case). However, as indicated with curve (2), the system has to be reversed significantly beyond the collapsing tipping point until gradual “healing” is made possible.
This hysteresis effect seems to be observable in a number of different domains. Some examples:
Physics: there are many examples in physics, such as: elastic hysteresis, adsorption hysteresis, magnetic hysteresis, electrical hysteresis etc.
 |
| Elastic hysteresis of an (idealised) rubber band (Wikimedia Commons) |
Organisational capability: Organisations initially show a certain resilience (observable from the outside) when the capability of the organisation is decreasing, for instance due to poor management, loss of key staff, etc. The observable performance / output initially seem to be little impacted by declining internal quality. Competent staff take over more responsibility, more external resources are utilised, and generally adjustments are made to compensate for lost capacity and capabilities. Over time however, the organisation is hollowed out, organisational (or technical) debt accumulates and then the external performance drops significantly and rapidly.
Once this drop has occurred, it is hard and takes much time and determination to regain the original capability (2).
Trust in media, business partners, organisations, etc: A similar pattern can be observed in all trust based relations. We experience a fairly quick drop in trust, once we feel betrayed or scammed, and it takes much more effort and time to regain trust than it took to lose it.
The last example also indicates that while the general pattern is the same, the resilience (the duration of negative effect until tipping point) seems to be quite different: in the example of trust there appears to be a larger asymmetry, i.e. people tend to lose trust rather quickly. Hardly anyone will continue to trust a business partner after being scammed. Regaining trust is takes much more effort.
Also, should the regaining phase (2) be interrupted by more negative impact (e.g. lack of determination of management, rebounds, violation of trust) the curve might spiral down even more sharply and the return path could take much more effort.
