I’m a lucky guy. Nearly every day I walk between home and office along the Hudson River, just north of where it widens out into New York Harbor. As an amateur photographer, I have begun to pay closer attention to — and often photograph — the scene (as below).
Each day the sky as the sun sets over New Jersey is different. Sometime clear, sometimes cloudy, often mixed — with many variations in cloud types, formations, heights, and so on. Each day the river water is different — sometimes calm and almost glassy, sometimes choppy and almost ocean-like, with thousands of variations in between.
The tides create a 4-5 foot variation in river height on a typical day, as well as variation in the direction and interactions of the channel flow and the surface texture. Sometimes the air is still, sometimes pleasantly breezy, sometimes downright windy. Each day of the year, the sun sets in a slightly different place.
In the five years I’ve been doing this, I do not recall seeing the identical sky-water combination more than once. There are simply too many factors that change over too wide a range, and that interact in complex ways to see much repetition. The building and piers are the only relative constants — and sometimes those change too.
New York Harbor is an open, dynamic, complex system, with an innumerable number of factors interacting continually.
This reminds me of the pre-Socratic Greek philosopher Heraclitus’ concept of flux — most famously depicted by the realization that you can never step in exactly the same river twice. By the time you try to, it has already changed.
To me, it also stands as a useful metaphor for our economy. With economic affairs, we are always in flux. In my strategy and intelligence work, I remind my clients that their ‘economic universe’ today at 4pm is not the same as it was yesterday at 4pm, or the day previous. Things have changed — possibly in imperceptible ways — but possibly in ways that over the long run will have a noticeable impact on their organization’s performance and even viability.
Perhaps even more importantly, at 4pm tomorrow, and the day following that, the same will be true — the world will be different — perhaps just slightly so, but different. It’s tempting to say change is the only constant in our economic universe — but even change itself changes continually — in speed, quantity, and characteristics.
Our whole system of economic thought is built largely on principles borrowed from ‘classical’ physics called Newtonian mechanics. As many of us know it: for every action, where is an equal and opposite reaction. Gravity. Equilibrium. Deterministic models that predict that when X happens (you throw a ball, for example), Y follows as a consequence (it travels some distance, then hits the ground and bounces).
The physics of the 20th century disrupted that Newtonian model when Einstein, Bohr, and others introduced quantum mechanics — such that extremely small objects like electrons were no longer seen as fixed in space, but rather as positioned probabilisticly within a range. And always in flux.
It’s possible that our economic modes of thinking are stuck in the 18th century and have not yet been re-calibrated to include 20th century insights like quantum theory. And perhaps they don’t really even include 6th century BC concepts like flux.
Certainly this is the case in competitive analysis. In a recent LinkedIn discussion on models of strategic analysis, I argued that ‘industry analysis’ based models (like Porter’s ‘Five Forces’) tend to be static and to underweight dynamic considerations in the economic environment. My view is that the reason some people are now reacting against these models (Columbia professor Rita McGrath, for example) is that we are now confronted with continual and undeniable change and volatility in nearly aspect of our economic lives.
Major financial crises occur once or twice per decade. The average stock is now held by institutions for four months — in 1960, the average was eight years. Instead of equilibrium, in effect we now have cascading disequilibria — such that no sooner do we adjust to a ‘new normal’, than it’s displaced by an ‘even newer normal’.
Organizational strategists seek ‘models’ that closely track reality, such that they can be used to forecast what might lie ahead. To extent these models are consistent with the underlying reality, they are deemed valid and useful. To the extent they differ from reality — either at the outset, or over time as the represented reality continues to evolve away from them — they are decreasingly useful.
Many of our strategic models still used today were created in the period 1965-1985. This was during the Cold War, when nuclear standoffs were the ‘game theoretic’ endpoints discussed by strategists like Thomas Schelling and Herman Kahn.
This period was also pre-Internet, when industry boundaries seems less fluid, people’s buying habits seemed more stable — and everything just seemed to move more slowly and predictably.
Our strategic models now seem like ‘messages in a bottle’ from a competitive world significantly different from our own. There is growing and justifiable concern that they have outlived their relevance and usefulness.
We need ways to monitor and measure the continual changes in the ‘economic universe’ of an entity (a company, for example) over a period of time, so that we can forecast — or at least make educated guesses about — the direction and magnitude of those changes in the future. So as not to inundate us with more data, this requires knowing which of these factors are most important.
I am not advocating a macro-futures scenario development exercise a là Naisbitt’s Megatrends or Gore’s The Future — though these have their place. What I’m proposing would focus on micro-futures — movements in more local drivers that together create significant impacts on the entity being modeled. It would be easily communicated to, and digested by, decision-makers whose job it is to produce value and results using the output.
This will enable us to finally drag strategy into the 21st century — from the Newtonian era to the quantum era. Quantum strategy is real-time, evidence-based, algorithmic, and probabilistic.
Is strategy in your organization based on outdated models? Is it a once-a-year ordeal, the results of which are obsolete almost as soon as it’s finished? Strategy should be a management tool for making decisions and guiding actions in a competitively dynamic world.