Abductive Reasoning, abstract thinking, antifragility, Art, business schools, Categorization, complexity, Daniel Pink, Dave Snowden, hierarchy, integrative thinking, management consulting, Management Theory, mental models, Nassim Taleb, right brain thinking, Roger Martin, Sense Making, statistical analysis, strategy, weak-signals
As I have recently argued, the world’s top strategists agree that strategy in complex, cause-and-effect blurred environments requires a unique mindset.
According to Snowden and others, in complex environments cause and effect relationships do not repeat and a categorization mindset where data is fit to preconceived notions about reality (i.e. models, frameworks, etc.) is ineffective. This by the way rules out most of the consultants who provide precisely this: prescription style, a-la-carte frameworks and models. What works are sense-making models (to understand the distinction between categorization and sense-making in the words of the world’s top strategists, see my related blog). Categorization models are fast and efficient, but may miss so called “weak signals”, comparatively insignificant data points that are simply part of the average in normal situations, but which can be the source of new emergent patterns in complex circumstances – fat tails and Black Swans respectively in Nassim Taleb parlance.
And so, strategy in complex (i.e. turbulent, uncertain, etc.) environments is about sensing emerging patterns from weak signals, hopefully before they become obvious if they are to be of any use as competitive advantages. This is not a guaranteed approach, but neither is it chaotic and happenstance: it can be best described as an educated trial-and-error heuristic.
Now let me focus on what I mean by educated trial-and-error, because this is where the human element comes in. It takes a mind to filter emergent patterns. And no, I am not referring to “filter” in the statistical sense, where computers can better humans. Statistics and pattern recognition are two very different things. Statistical analysis of the kind invoked by Big Data is about deducing patterns by fitting data to existing models, while pattern recognition is a heuristic that humans apply to infer their own models from data. I hope you can see by now that pattern recognition fits with sense making models, at which humans are very adept. It is also what Roger Martin calls abductive reasoning, i.e. inferring an explanation for a newly observed phenomenon even invoking paradox as necessary.
Let me get into controversial territory and claim that different individuals have varying abilities when it comes to strategy in the pattern-fitting sense. What may appear to one mind as noise, can be an important hint to another.
Now one might argue this is quite often the case if we take a horizontal look across professions: a manager will stare blindly at few white dots on an x-ray while a doctor may see an intriguing new pattern. But let me actually propose that we stay within one profession, and claim an uncomfortable truth you already knew: that some doctors are better at diagnosing elusive diseases than others (remember the Dr. House show?), just as some mangers are better at strategy than others. Let me further the controversy and claim that a few years past apprenticeship, age or level of experience, or title, or trophies and accolades may have little to do with the qualitative difference in sensing patterns, or in management parlance, with being a great strategist. And so, while accumulating more knowledge with time may help to some extent, it does not guarantee a corresponding qualitative improvement in sense making. You knew this one too, since lots of billionaire entrepreneurs are very young, even as our society, and particularly the public sector, insists on a pay scale commensurate with years of experience. Many of these entrepreneurs have actually gotten to billionaire status precisely by sensing an emerging pattern before everyone else (operating systems, social networks, and the like), and then orchestrating its coming into general acceptance.
So if it isn’t about age and amount of knowledge accumulated, how can a mind be better than another at seeing patterns? Let me introduce a key distinction at this point between perspective and abstraction.
Perspective is a matter of “horizontal” familiarity with a particular field or another, with a particular set of experiences or another, etc. Public relations experts and politicians are well aware of this and try to keep messages as simple as possible, to avoid the issue of perspective relativity and get their points across. And indeed, in the doctor and manager example above, signal sensing doesn’t work well across professional divides.
Abstraction by contrast is “vertical” and it is the more interesting aspect to focus on when elucidating effective strategy in complex environments. More powerful strategists and pattern fitters have (through both talent and/or training) attained a higher power of mental abstraction in my opinion.
Imagine reality as a series of stacked abstractions. Let’s use an example: there is a factory floor level view of an assembly line with real parts and real workers, then there can be a process monitoring software abstraction of the same reality running on an operator’s computer screen, and then there can be a higher abstraction yet in the COO’s office where measurements from the real time process control software are aggregated. Because the COO is looking from a higher plane of abstraction, he or she is likely to focus on weak signals that would only look like noise for the floor factory worker. Now I used a process control software analogy, but the same can be said about the mind. Some minds are sensitive to higher degrees of abstraction, and the more complex the environment, the higher the abstraction mental plane required. Let me make one more point on abstraction and weak signals: the higher the abstraction, the weaker the signal! That is because higher abstractions operate at lower energy levels. In the factory floor example, it takes a lot less energy to run the software abstraction of the assembly line than the assembly line itself, and so, the higher abstraction means less brute force, more subtlety and thus less obvious signals.
This view of reality as a vertical series of stacked abstractions fits beautifully with the complexity which our brains and the world they function in share. Emergence, the key ingredient of complexity, is precisely the mechanism that enables upward abstraction. Einstein’s famous we “cannot solve the problem with the thinking used to create it” makes the powerful case for abstraction, if it is taken to mean not only new thinking, but higher level (i.e. abstract) thinking. Staying in physics, how else did Maxwell solve the paradox of electricity and magnetism if not by rising to a higher level of abstraction where the two apparently contradicting concepts become facets of a single unified construct, electro-magnetism?
Having made the case for abstraction as a key ingredient of pattern sensing, and the case for strategy in complex environments being about sense making, is the world promoting abstraction? And can we train minds for abstraction? The answer is: possibly.
To date, our society has had limited success assessing mental abstraction capacity (there were a few lone attempts such as Elliott Jaques). More generally speaking, we are not so good at assessing right brain thinking. According to Daniel Pink and others, this is the realm of artists, and while we can appreciate great works of art, it is much harder to apply a GRE or GMAT like test to reliably filter great artists. And so, great strategists like great artists end up being judged by the greatness of their outcomes, rather than by their a-priori potential. No matter how much our higher education institutions and corporate establishments insist that their “enlightened curricula” and “tested processes” can deliver great strategists en masse, the individuality characteristic of the particular mind (i.e. the “maverick factor”) will remain the dominant ingredient of effective strategy in complex environments for the foreseeable future.
If and when (if ever) we do develop explicit methods for exercising abstraction, we may get to an age where all of us are better strategists comfortable with and even welcoming complexity as a source of “antifragility” to paraphrase Nassim Taleb. We could start with Daniel Pink’s six senses for stimulating right brain thinking where pattern-fitting abilities reside: design, story, symphony, empathy, play and meaning. As you can see, none of these six have anything to do with categorization and process, but at least a few may have very much to do with abstraction.