Picture the scene: You are called into a company to improve a particular business process that they are having trouble with (imagine it's your area of expertise). You're told that what's currently in place simply isn't getting the job done - that you should add to it and make it more sophisticated.
After extensive examination, you find that the system is so convoluted and inefficient that far from adding anything, your recommendation should be to subtract unnecessary processes. At the same time, the company has been on a run of acquisitions over the last several years, adding components to its business that it's struggling to make profitable and that has moved it away from its core focus and capabilities. Selling off these other businesses would allow it to rid itself of these distractions and free up additional capital, both human and financial, to invest in what it does best and what made it a success in the first place.
These are two examples among many of how companies and systems designers must learn by default to first add value through subtraction. Here we can learn a great deal by examining and understanding the evolution of systems that have evolved over thousands of millions of years: namely, biological systems.
In one of the more fascinating pieces of recent research, and published in the journal Evolutionary Biology, Daniel McShea (Associate Professor of biology at Duke University) and Wim Hordijk (computer scientist), argue that what we see as naturally evolved complex systems, may have in fact been overly complex structures that were in time simplified. In contrast to the superfluous complexity often introduced into artificial systems, these lead to the more efficient and effective designs that we find in nature today.
"Here we show how complexity could arise, not by incremental addition but by incremental subtraction. We offer an evolutionary logic in which function arises in structures that are already complex, sometimes more complex than they need to be. Natural selection then favors a reduction in the complexity of these structures. They lose parts, to produce structures that are still functional, sometimes improvements, and often still sporting considerable residual complexity."
A very interesting point that the authors make, is that complexity in itself is not an indication of sophistication:
"Complexity is easy. It is spontaneous. No special mechanism beyond the simple tendency for parts to become different from each other is needed to account for it."
They argue that following a rapid initial rise in the complexity of these systems, evolution began to favour simplification and the removal of unnecessary parts in order to improve function.
"What there is evidence for, and what we draw attention to, is the reduction in complexity that followed, apparently from selection for improved function, which in turn seems to have required simplification. The resulting structure still has considerable residual complexity. But that complexity was arrived at not by accumulation, not by a build-up from a simple starting condition, not by addition. Rather it was produced by reduction, by building down from an even more complex starting condition, by subtraction."
Using a computational example, they provide evidence in support of their 'complexity by subtraction' theory, demonstrating selective pressure for reduced complexity.
"Not only can we point to ways in which the complexity of particles hindered their ability to perform the tasks, density classification and global synchronization, but we know that selection was present and that the task did not change. Thus, the ancestral more-complex particles were less fit than the less-complex derived ones...We have a system evolving to perform a particular task and in doing so its trajectory spontaneously took it from high complexity to low, which at least raises the possibility that such a trajectory might be available to any selection-driven evolutionary system, including biological systems."
Of particular note here are the words "any selection-driven evolutionary system". Evolution, of course, is not exclusive to biology, making this study relevant to systems in all disciplines. Before going over this point again though, they use a further example, this time of a biological system. Looking at skull structures they find a trend towards a fewer number of skull bones in the evolutionary transitions from fish to amphibian to reptile to mammal.
"It could be that the late-Paleozoic tetrapod skull was optimal for tetrapods needs at the time and those needs happened to require more part types than skulls in later contexts. In that case, we cannot say that the original complexity was excessive. On the other hand, part-type counts do offer the best estimate currently available of skull complexity, and they clearly indicate a decrease in skull complexity."
They go on to argue that complexity initially sees a rapid rise at the outset of a system's birth, but this must then be simplified for it to succeed. In a very compelling example in support of their case, they talk about the process of how a pile of stones can be transformed into an arch, simply by removing the unnecessary stones.
The engineer?s job, then, is not to build an arch out of stones but to remove the excess, the stones that do not participate in the already existing arch (and perhaps to reshape the remaining stones). The resulting structure is still complex, although obviously reduced from what might be called the "excessive complexity" of the structure it arose from.
Once again they emphasise that:
"...what is favored is streamlined simplicity. If functional structures are complex, it may be in part because they start that way, because initial complexity is easy."
Of course, what should draw all of us to this study is its wider implications, and the researchers conclude by emphasising this very point:
The questions we raise have to do with the generality of the route we propose. First, there is the question of how commonly it occurs in evolution, and then, whether and how commonly it occurs in non-biological systems. Do machines typically evolve along similar lines, starting with excess complexity and becoming simpler as they are improved? Do languages start complex and become more streamlined over time, under pressure perhaps for fast and efficient communication? How about the complexity of human institutions, such as businesses, that experience pressures at least analogous to natural selection for improved functionality? Do they follow a similar trajectory? As in the evolutionary case, a case-study approach of the sort we attempt here would be useful as a first step. What is needed then?for the evolutionary case as well?is a broader and more systematic study, to discover whether or the extent to which complexity by-subtraction occurs generally.
As well as providing a great deal of food for thought, the implications are clear - if indeed evolutionary biology does indicate, through thousands of millions of years, that simplicity is favoured for "fitness", then all other systems may potentially adhere to this law. Of course, without further and wider examination of the evolution of systems in different contexts, we can't say for sure that this theory stands, but it does mean that if true, a continued projection towards complexity will in fact leave that system less fit for purpose. In biological systems, being unsuitable for your environment usually places you on a gradual trajectory towards dying out, therefore when designing all other systems, it would almost certainly be wise for us to practice caution in first simplifying and making complex only when absolutely necessary.