Return with me for a moment to those thrilling days of
yesteryear. We love machines. They are the primary metaphor that we use for
And why not? Machines, starting with the Newcomen engine, were what made the
Industrial Revolution possible. By 1850 or so we’d moved to the second stage
where those machines drove railroads. By 1893 we were showing off machines at
the Columbian Exposition. In 1908 Ford created the first industrial assembly
line. In 1912, Frederick Winslow Taylor published Scientific Management based on
his studies at Midvale Steel.
For the last century and a bit more, we’ve made progress by applying
engineering techniques, like quantitative analysis, to organizational processes.
And we’ve thought of our organizations as machines.
The thing about machines is that they’re not natural. You design them. The
parts of a machine don’t act independently. They follow the plan. And you judge
success by how well the results conform to the plan.
That has worked well until very recently. It works well if the environment is
stable or changes slowly. It works well if work can be specified in detail in
advance and then measured accurately. It works well, in other words, if you can
get a better outcome from planning and controlling, then you can by just letting
things run or by applying less direction and control.
In the 21st Century, adaptability in the face of competitive pressures and
rapid change will be important. That requires a different model for our
organizations and organizational strategy. We need a model that’s adaptive.
Good news. Nature has a lot of them. We call them “complex adaptive systems.”
Complex systems are different from complicated systems. And not all complex
systems are adaptive.
The difference between complex systems and complicated systems is that you
can, potentially, at least, know in advance how a complicated system achieves
results. You can only understand how a complex system gets results after the
The Apollo Moon Missions were complicated endeavors. Every part involved
things we could know in advance. Building a skyscraper is a complicated
endeavor, too. We know how to do all the individual things. Doing them well and
coordinating them are the challenges.
Raising a child is a complex endeavor. You don’t plan a complex endeavor. You
apply some simple rules, hopefully consistently.
Complex adaptive systems are a special case of complex systems. In a complex
adaptive system there are independent actors whose actions, taken together,
create an effect.
That effect is called an “emergent property.” It doesn’t exist before the
actors do their thing. It’s not planned. It emerges from the actions.
The actors follow a few simple rules. A wheeling flock of birds is an example
of an emergent property.
The movement isn’t planned. There’s no central authority calling the turns.
Instead, each individual bird keeps a precise distance away from and stays
aligned with the nearest neighbors, avoids predators, and follows some other
A chess game is an emergent phenomenon. Chess does not have many rules, only
a couple of dozen. Yet, an infinite number of combinations come from a few
simple actions and constraints.
Complex adaptive systems adapt to the environment so the system and the
environment both change. There is no central control. There are some simple
rules. And the outcomes are not predictable in advance.
In business, a culture is an emergent property of the work environment. But
that culture is, at the same time, a driver of productivity and morale. You
can’t plan for it, design it, or predict it in detail. It’s emergent.
Boss’s Bottom Line
Your team is a complex adaptive system. We are just now learning what that
means, but it surely means that your job will change so that there will be less
planning and more allowing.
Note: Special thanks to Dan Rockwell. A
conversation with Dan a few months ago sparked the original version of this