Why plans are useless but planning indispensable

“Plans are worthless, but planning is everything”
-Dwight D. Eisenhower

“Failure to plan is planning to fail”
-Benjamin Franklin

We all have the fantasy of the perfect plan that goes without a hitch. Heist movies, like Ocean’s Eleven (Twelve and Thirteen), The Italian Job, The Bank Job, etc. all fuel that fantasy that you can be a mastermind capable of seeing all the angles, predicting everyone’s behavior several moves ahead, getting the timing right down to the second and achieving your goal exactly as you planned. In the real world however this is rarely the case. Why?

We live in a complex, interconnected world. Every action we take can cause ripples of unpredictability in the system. Complex systems are by their very nature unpredictable because there are no universal laws that govern them. Even if every agent in the system were to have simple rules by which they make decisions, the overall system behavior that emerges is unpredictable.

To account for all the possible scenarios quickly exceeds the capacity of even the most powerful of today’s computers. Just look at the weather patterns. Despite all the advances in computational power and simulation capabilities, we still can only forecast the weather with any level of accuracy a few days in advance. The complex behavior of the water molecules, the air temperature, atmospheric pressure, initial conditions and other factors make it nearly impossible to analyze and predict what will happen.

There are however systems which are highly predictable even if they seem very complex. A computer program’s behavior for example is very predictable (most of the time anyway) A car’s various systems: the engine, transmission, brakes, electrical systems, etc. are also very predictable even if they are interconnected and interdependent.

So what’s the difference?

David Snowden’s Cynefin framework (pronounced kun-ev-in) recognizes three types of systems: Ordered, Complex and Chaotic. The difference between them is the level of constraint in each system.

Ordered systems are highly constrained and as such their behavior is very deterministic and predictable. You can easily determine cause and effect and the patterns you find are very likely to repeat in the future. Ordered systems are further divided into Simple and Complicated. A highly structured business process for example (like getting a loan) is a Simple system. It’s highly constrained and relatively easy to fix or optimize. Cause and effect relationships are clearly visible and you can predict with very high accuracy what will happen.

A car is an example of a Complicated system. It’s still Ordered because it’s highly constrained (there’s little to no variation beyond what’s been specified by the system designer) but the level of detail in the design makes it much harder to understand and notice cause and effect relationships. This is why you need highly trained professionals (experts) to analyze the system and figure out cause and effect relationships.

Complex systems on the other hand are only partially constrained. Complexity science is still actively being studied and discovered but we do know a few things that can help us understand how these systems work. Complex systems are made up of agents that interact with each other and with the system based on their own rules and strategies and the constraints imposed by the system.

In the example above we saw that cars were Ordered systems because of the high level of constraint in every aspect of their design; traffic on the other hand is only partially constrained and as such it’s a Complex system. There are rules in the form of laws and guidelines such as speed limits, traffic signs, traffic lights, highways, ramps, paved roads, direction of driving, etc. but these rules do not fully constrain driving. You can choose to dive fast or slow, change lanes frequently or not at all, slow down or speed up, turn left or right, etc.

This creates unpredictable emergent patterns such as accidents, traffic jams, traffic congestion or sparsity, etc. On top of that, the traffic patterns from moment to moment, from day to day are completely novel and unique. There’s no way to know for sure when an accident will occur or when the traffic will become congested. Even though you may know exactly why an accident happened, it doesn’t help you fully predict future accidents.

Chaotic systems are highly unconstrained. Imagine for a second that one day none of the rules of driving applied. You could drive in the middle of the road if you wanted, drive backwards, go through red lights and stop signs, drive on the opposite side of the road, cut through lanes at will, make sudden u-turns, break and accelerate as you wished, etc. What would happen? Complete and utter chaos. It would be impossible to predict anything.

Side Note: Temporarily removing constrains in a system is an excellent way to unclog bureaucratic gridlock in an organization and spur innovation. Dave Snowden calls this “shallow dive into chaos” but that’s a topic for another day.

So how does this relate to planning?

Most planning is done under the assumption of Ordered systems. We assume that the future is predictable from past events so making plans is easy. Planning comes naturally to us as our brains function like cybernetic (goal seeking) systems. We set a goal and immediately our brain provides ways to achieve it.

Now if the system you’re dealing with is highly constrained, these plans are very likely to succeed. For example if you wanted to buy a house you’d need a bank loan and since getting a loan is an Ordered system, given certain criteria, you can predict with very high accuracy if you will succeed or fail.

If we’re dealing with a complex system however, or a chaotic system, we would be unable to account for all the possible future scenarios and contingencies and our plans would be at best incomplete. Before the advent of GPS and turn-by-turn navigation systems with up the the minute traffic data, it was impossible to plan a route down to the minute and be very confident you would arrive at a particular time.

So the reason why plans are useless is that more often than not they are incomplete and don’t account for all the possible contingencies in the complexity of today’s systems.

Why then is planning indispensable?

The process of planning gets us to think through many of the possible futures and scenarios that can unfold and help us be better prepared if any of those futures scenarios were to happen by creating contingencies. Of course we can’t cover every single scenario and we need to be agile and capable of course correction. The measure of true agility is the ability to ditch your plans halfway through when the situation has changed and made your plans obsolete even if the sunk cost might be high.