When presented with the goal of making a change in a complex system (human), we have to consider where in the system we can intervene to promote the desired change.
There are two types of feedback loops that are important to consider: Balancing feedback loops and reinforcing feedback loops.
Balancing feedback loops are self-correcting. For our purposes, think homeostasis and allostatic mechanisms.
Baroreceptor reflexes regulating blood pressure, maintenance of substrate concentrations in the intracellular and extracellular fluid in our filtering systems, maintaining body temperature via vasodilation or sweating, and regulation of gas concentration in the blood via respiration are all balancing feedback loops.
The more intensive the training, the harder our allostatic mechanisms need to be able to work to meet the imposed demands. This represents the variability of the system.
Reinforcing loops are self-reinforcing. This is the training effect. These loops promote a growth of the system in a very specific manner. This is an important point to remember.
The more I use it (specificity) or the harder I push it (intensity), the stronger it gets but in return, I narrow the scope of adaptability.
There are certainly situations where this is ideal for growth and performance purposes as long as we accept the trade-off of reduced system variability. It is also important to understand that left unchecked, reinforcing feedback loops will eventually destroy the system. Balancing feedback loops have limits.
In training, this may be represented by the onset of injury or illness.
While trying to enhance the balancing feedback loops through restorative means (cryo, compression, manual therapies, physical agents, nutrition, sleep, etc.) may be beneficial in the short-term, the limits of the balancing loops will eventually fail.
The better strategy is to “slow cook” them to borrow a phrase from Buddy Morris. Intentionally reduce the gain from the reinforcing feedback loop is the better strategy to stay within the limits of the balancing feedback loops.
If you set a PR in training, it’s probably best to shut it down for the day and redirect the remainder of your training for that day to less intensive means. Your system has no experience at that level of performance, and you have no idea whether it has the capacity to restore within the typically allotted time frame.
There are certainly other strategies that can be implemented to keep reinforcing feedback loops in check, but this may be the most important. Complex systems (humans) are inherently unpredictable. Small changes in inputs can result in massive impact, little impact, or no impact. The same input on one day may have a different result on another day.
It is best to “slow cook ‘em.”
Resource: Thinking in Systems by Donella H. Meadows