The Red Queen Trap is to be found in the famous Red Queen paradox from Lewis Carroll’s Through the Looking Glass. In this story, a sequel to Alice’s Adventures in Wonderland, Alice climbs into a mirror and enters a world in which everything is reversed. There, she encounters the Red Queen who explains to her the rules of the world resembling a game of chess. Among other things, the Red Queen tells Alice:
It takes all the running you can do, to keep in the same place.
On the face of it, this is an absurd paradox, but it reveals an important insight about a critical point in the life of every system. Let me explain.
Every system, be that a single entity or a large organization must perform itself into existence from moment to moment. If it stops doing that it succumbs to entropy and falls apart. Spoiler alert, in the long run, entropy always wins.
To perform itself into existence every system must expend a certain amount of energy, which is a function of the relationship between its internal state and the external conditions it operates in. In other words, it must expend some energy on keeping its internals working smoothly together, and then expand some energy on resisting and adapting to adverse external conditions.
The better adapted a system’s internal state is to its external conditions, the less energy it must dedicate to perform itself into existence, and the larger the potential energy surplus it can use to grow, expand, or replicate itself.
However, external reality is complicated [not to be confused with complex] and changes dynamically in ways that cannot be modeled over the long term and require constant adjustments by the systems [organisms, humans, organizations] operating within it. In other words, an external state observable at time A is no longer present at time B.
This is a problem for all systems because it requires them to change how they operate.
It is a small problem for simple systems which are usually internally homogeneous and highly distributed. Their homogeneity means they don’t need to spend much energy to maintain their internal state, and their distributed topology means they make decisions and react very fast.
It is a serious problem for complex systems [large organizations] which are usually rather centralized and heterogeneous. Their heterogeneity means they must expend a lot of energy to maintain a coherent internal state consisting of various qualitatively different elements, and their centralized topology means they react and make decisions rather slow.
It is a profound problem for complex hierarchical systems [large organizations with vertically integrated decision making] which consist of multiple heterogeneous elements stacked along one or more vertical axes. Vertical integration means that each successive layer going up is further removed from direct exposure to external conditions and is, therefore, slower in adjusting to them.
A system might be quite successful in adjusting its internal state to external conditions at time A, but a later time B might present a different configuration of conditions to which the internal state of the system at time A is profoundly inadequate. The more complex the system, the more energy it must expend in adjusting to changes in external conditions from time A to time B.
Complex hierarchical systems have the hardest time in making these adjustments because key strategic elements of their internal state [i.e. decision-making centers high in the hierarchy] are far removed from direct contact with external conditions. To orient themselves and perform the system’s OODA loop they rely on communication about external conditions reaching them from the periphery of the system, while orders on necessary adjustments must travel the other way, from center to periphery. This takes time, and the more layers the signal communicated from the periphery must pass through on its way to the center the more abstracted it becomes from external conditions. In other words, the center receives a highly imperfect version of the external conditions about which it must make adaptive decisions.
Over time, this generates a growing number of errors in the internal state of the system, requiring more and more energy to be routed to internal maintenance [i.e. bureaucratic paperwork], leaving less and less surplus energy for adaptation, growth, and expansion. Eventually, and this stage can arrive very fast, the system reaches a state of pseudo-equilibrium in which all energy it can produce goes towards internal maintenance and there is zero surplus energy left. This is where the Red Queen Trap kicks in:
The system does all the running it can do, to keep in the same place.
How does the trap work? First, from the inside everything in the system still seems to be operating smoothly and things are humming along following external conditions at present time A. However, this is a false perception of equilibrium, because when external conditions invariably change in future time B the system will have no surplus energy reserves to adjust to the new conditions.
The more imperfect the version of external conditions reaching the center of decision-making, the more pronounced the system’s inertia in this state of pseudo-equilibrium, and the deeper it goes into the Red Queen Trap.
Second, having eventually discovered there are no more surplus energy reserves left, the system must now make a choice. In the absence of surplus energy and provided there is no energy transfer from the outside, it must somehow free up energy from within its internal state to adapt. The question is, which internal elements should be sacrificed to free up that energy? This is where the Red Queen Trap’s simple elegance is fully revealed.
Essentially, there are two options – a seductively easy one and an unthinkable one. The seductively easy option is to sacrifice the periphery, or elements of it, and preserve the decision-making center. It is an easy choice for the center to make because it naturally sees itself as the key element of the system and this choice allows it to remain intact. It is a seductive choice because the center suddenly finds itself with a flush of spare energy which it can use to maintain the pseudo-equilibrium and often even to grow itself at the cost of the periphery. Alas, the elegance of the trap is in the fact that the seductively easy option removes the center even further from external conditions; less periphery equals fewer opportunities to observe and react quickly to external reality, thereby further magnifying the initial conditions that brought the system to this state in the first place. By making that choice the center sinks further into the trap.
By contrast, the unthinkable option is to sacrifice the center and preserve the periphery, thereby flattening the internal structure of the system into a less hierarchical form. It is an unthinkable option for the center to make because, as pointed out above, it naturally sees itself as the key element of the system, and this choice forces it to sacrifice itself. It is also unthinkable because it involves a thorough rethinking of the internal structure of the system, which until that moment was organized entirely around vertically integrated decision making, with little to no autonomy in the periphery. The center must not only sacrifice some of itself but also reorganize the periphery in a way allowing it to perform those functions in place of the center. This would allow the system to free itself from the trap.
Most systems choose the seductively easy option and the Red Queen Trap eventually grinds them into oblivion. Those few systems that go for the unthinkable option escape the trap and, if they remain persistent in their application of the unthinkable, learn how to go different places with running to spare.