Embrace Complexity to Find Simplicity

My previous article focused on the topic of the multiple technological and business/market factors for ‘successful innovation’, but there is another dimension to the problem that relates to the process by which key decisions are made. Now, I am not referring to the mandated, rigid corporate processes which all of us find frustrating and seemingly arbitrary in many cases. I am talking about a higher-order intellectual process that should be adopted for all complex decisions in order both to maximize the probability that the optimal path is selected initially, as well as to allow adaptation of that path as needed when the critical variables change.

It is simply this: you have to understand the problem in real depth and only then try to reduce it to its simplest form or barest essence. In short, you have to embrace complexity to find simplicity. 

It is clearly desirable to find simple solutions to problems, but simplicity alone is not sufficient as a test of the ‘goodness’ of a solution – one has to fully explore the problem space across the multitude of facets and factors, and then eliminate all the irrelevant or immaterial elements and variables, leaving the simplest solution comprised only of the critical factors that must be retained and resolved. 

And I am not alone in this view; many eminent people from both science and the arts have espoused similar views with quintessentially pithy quotes:

“Any intelligent fool can make things bigger and more complex…it takes a touch of genius and a lot of courage to move in the opposite direction”. Albert Einstein

“Out of clutter, find simplicity”. Albert Einstein (again)

“Simplicity is complexity resolved”. Constantin Brancusin (sculptor)

“Simplicity is the ultimate sophistication”. Leonardo Da Vinci

But the most insightful quote is from the US Supreme Court Justice, Oliver Wendell Holmes, as follows:

“I would not give a fig for the simplicity this side of complexity, but I would give my life for the simplicity on the other side of complexity”. 

This accurately describes the trap that must be avoided at all costs – the na?ve assumption that finding simplicity before consideration of all the complex factors is equivalent to the finding simplicity after full consideration of these factors. 

This is schematically depicted in the figure below, which can be described as follows; all analyses follow the initial ‘analysis vector’, with increasing time required as the full complexity of the problem becomes apparent. After some time, a point is reached where one of three things happens:

1)    Analysis fatigue (or simply impatience) sets in and summary conclusions are drawn prematurely, with the resultant solutions suffering from ‘Excessive Simplicity’ in the worst case. Note: the analysis vector is truncated relative to the two other solutions described below, resulting in premature conclusions being drawn

2)    Analysis paralysis occurs when the appropriate amount of analysis is initially performed but ever more complex analyses are then undertaken, resulting in the inability to define solutions that will improve upon the current situation as they suffer from ‘Excessive Complexity’

3)    Analysis perfectus is the idealized outcome, resulting from sufficiently complete analysis that eliminates complexity by a deeper understanding, resulting in solutions that possess ‘Essential Simplicity’ and that have the potential to reinvent the space in which they operate.

Clearly, Wendell Holmes saw the folly of 1) and the nirvana represented by 3) very clearly. And 2) didn’t merit any mention.

This would perhaps seem to be a statement of the obvious, but I think in the modern business climate it is all too common for 1) and 2) to prevail over 3). For example, the prevalence of ‘100 days’ as the time period for all new strategies, transformations or initiatives to be defined and implemented lends itself to solutions that exhibit Excessive Simplicity, due to the abbreviated analysis period. Conversely, the fondness for the formation of large cross-organizational teams with representation from all functions typically leads to Excessive Complexity, as the relevance or importance of various factors becomes difficult to discern or ‘impolitic’ to do so. So, time eventually runs out, triggering the (lengthy) production of a complex recommendation document.

In many ways, the primary advantage of smaller, more agile companies and organizations is not their technical ability or portfolio, it is that they are forced to find solutions that have Essential Simplicity, in part because the intrinsic complexity of their world/space is less, and in part because they don’t have throngs of people with different goals and intents; they are singularly focused on a common goal.

And, for this reason alone, sometimes great companies, full of great people and talent, can fail, because they cannot ‘see the wood for the trees’ and do not embrace complexity to find simplicity.