Don’t Step into the Three Traps of the Newtonian Mindset
In my article, Breaking with the Path of Taylorism, I wrote that, from a perspective of leadership and organizational design, we are stuck with the ideas of Taylorism. I wrote that this development began in the early 20th century. Well, I was a bit sloppy at that point. As linear thinking is the basis of Taylorism the story started way earlier.
One critical juncture that pushed linear thinking was when Sir Isaac Newton formulated his ideas. As a physicist of the 17th and 18th centuries, Newton’s theories mainly relied on linear causalities, like his three laws of motion. It means he believed in a clear relationship between cause and effect.
Because Newton’s ideas were groundbreaking at his time, his influence coined a whole mindset. The so-called Newtonian Mindset lasted for many generations after Newton — and it still lasts. Accordingly, Taylorism is a continuation of the Newtonian Mindset of linear causalities. Therefore, the basic assumption behind Taylor’s management theory is that everything can be planned upfront and controlled to increase efficiency.
However, since the times of Taylorism in the early 20th century, the world has changed. Today’s dense and globalized markets with their thirst for innovativeness force corporations to operate in complex domains instead of complicated ones. Upfront planning and controlling top-down management often became inappropriate.
To understand what that means, we need to understand the difference between complicatedness and complexity.
Relationship Status: It’s Complicated
The large circle in the above image represents a large, complicated problem. With sufficient knowledge, complicated problems can be decomposed into smaller sub-problems until every sub-problem is simple to solve. The solutions to the minor problems can then be aggregated to a solution for the large problem. It means you solve the large problem by simply solving all small problems.
This approach is known as divide and conquer — divide et impera — and it’s a form of control. It means when you can decompose a problem, you can plan. When you can plan, you have control. And control means that it’s manageable.
Accordingly, the so-called Cynefin Framework tells us that upfront planning is only possible in what the framework calls simple domains and complicated domains. There, cause and effect are clear if knowledge is available sufficiently. However, the Cynefin Framework names complex domains as well.
Complexity: Probe — Sense — Respond
When complexity kicks in, you are not able to plan and control. The following picture illustrates the idea behind it.
The large circle in the middle is a complex problem. The sub-problems cannot be arranged and decomposed in a hierarchical order. Instead, new (sub-)problems may emerge, and all problems are interdependent. Meaning the way you are solving one of the (sub-)problems changes the characteristics of the depending problems or even creates new problems.
That is what makes upfront planning impossible for complex domains. You don’t know which problems will emerge, and you cannot foresee how the dependent problems will change based on your previously made decisions and actions.
Therefore, instead of upfront long-term planning, it requires a trial and error approach with short feedback cycles. One may take the Deming Circle as an example, better known as PDCA or Plan-Do-Check-Act. Again, this aligns with the Cynefin Framework, where the wording is probe, sense, and respond. In Agile, it’s called inspect and adapt.
However, because we tend towards linear thinking, we often ignore that we are moving in a complex domain. Accordingly, we apply strategies that work for complicated domains but not complex ones. Thus, I will show you an example that demonstrates such a misconception.
Human versus Elevator
One of the skyscrapers I worked at has 31 floors served by twelve elevators. The skyscraper is divided into two sections, north and south, where the six southern elevators serve floor zero to 17, and the six elevators in the northern section serve floor zero to three and 17 to 31.
The third floor contains the staff canteen, and the 17th floor is used to connect both elevator systems. For completeness, floors 32 to 36 are only reachable via stairs and contain building services.
However, I worked on the 26th floor, meaning I didn’t want to use the stairs each time I had to go up or down. So I used the elevators. And quite often, these elevators were annoying because of a particular feature.
That particular feature aims at minimizing the waiting times. There is a number pad installed in front of the elevators on each level. On these number pads, you have to type in the floor number of your destination. Meaning, that each person that wants to use an elevator always has to type in the floor number upfront.
Then, an algorithm allocates you to one of the elevators based on all other elevators' location, utilization, and destination. In that way, the use of the resources time and electricity is efficiently managed.
According to a mindset of linear causalities, one may recognize that the algorithm is implemented in a deterministic way with the best intentions. And we can assume that Frederick Winslow Taylor would have been proud of this system.
However, there is some cynicism going on about the elevator system. It’s because waiting times are not low. They are often high, especially in times of high elevator usage. And this has something to do with what I call The Human Factor. To put it more clearly, let me tell you about some observations I made when using the elevators by myself.
Observation #1: The group that only typed in one number
A group of five people wants to use the elevator to go from ground level to floor 28. Only one person in that group types in the destination floor number because the others are too lazy. The system tells this person which elevator to take, and all five people enter the same elevator.
We must keep in mind that if every single person in this group had typed in the destination number, the algorithm may have distributed them to different elevators. But the group decided not to split because they wanted to stay as a group. The thing is that the deterministic algorithm still assumes that only one person entered the elevator that arrived.
Observation #2: The group that decided against the split
On level 17, a group of three people wants to go to floor 31. Each of them typed in the destination number, and each of them got allocated to a different elevator. But same as the group in situation one, they also don’t like the idea of getting split. So they decided to join the first elevator that arrived. This elevator was already overcrowded, but the three managed to get into it.
You will recognize that the algorithm assumes two people are still waiting for an elevator. Meaning, that besides the first elevator that arrived, two additional elevators will stop on level 17, and both will drive to floor 31. While the first elevator that came was heavily overcrowded, the remaining two elevators transported one person less than assumed by the algorithm.
Observation #3: Not enough space
Six people want to go from floor 18 to floor 29—only one person types in the destination number.
An already crowded elevator arrives.
Because the eight people do not fit in as a group, they decide to skip the elevator.
Again, only one person types in the destination number. The next elevator arrives, but yet there are already people in the arriving elevator. This process repeats several times. The algorithm still assumes for all elevators that arrive, that there are people inside who want to go from floor 18 to floor 29, which is obviously not the case.
Human 3:0 Elevator
Each observation on its own does not seem too bad. But assume that it’s rush hour at lunchtime. Everyone wants to go to either the third floor where the restaurant is located or the ground floor to get lunch outside. At lunchtime, mostly groups of people use elevators instead of single individuals.
To be concrete, I once waited eleven minutes until the first elevator stopped to bring me from the 26th floor to ground level. In such stressful situations, the elevator system produces waiting times that grow exponentially rather than linear.
However, we see that the algorithm has been implemented to solve a complicated problem. It has been broken down into solvable sub-problems where the solution is that every person does what the system asks them to do: everyone types in a number. Everyone goes to the elevator they got allocated. And that’s it: the large problem is solved!
My observations demonstrate that as soon as human beings come into play, the probability is very high that a situation becomes complex. As I already said, I call it The Human Factor because human decision-making relies on many criteria we cannot evaluate upfront. In this case, complexity emerged because we do not know how many people want to use the elevator and how strong their need is to stay as a group.
Because I often experience that people rely on linear thinking even if a situation is obviously complex, I formulated the following three traps. I call them The Three Traps of the Newtonian Mindset.
Trap #1: Determinism
The Trap of Determinism is the basis for the two following traps. It is precisely what is described with the term undercomplex. When you rely on linear thinking in a complex domain, you have already stepped into the trap.
The designers of the elevator system did so. They created a solution that may look good on paper or a PowerPoint presentation, but it’s inappropriate as soon as the complex behavior of human beings is taken into account.
To step out of the Trap of Determinism, we must accept the fact that every effect in one direction has an effect in the opposite direction. You can say that everything is cause and effect at the same time.
Trap #2: Directing people
The elevator system tried to direct people. The assumption is that the people are doing what they have been asked for. But systems theory tells us that every communication sent into a system gets transformed by the system according to the existing patterns.
And that is what’s happening here. The expected behavior of the elevator system is not in line with the prevailing behavioral patterns.
However, suppose people see the purpose, or let’s say personal value, of typing in a number to call for an elevator. In that case, there is a chance that they might be intrinsically motivated to show disciplined behaviors, also known as Organizational Citizenship Behavior. This might lead to a behavior that gets in a direction that you expected.
Everyone of us had that moment where we think “if just everyone would follow what is best, the overall situation would be way better”. The climate change is a prominent example. Well, we are still driving with our cars and we still consume too much. Any advice, appeal or recommendation, however well-intentioned, gets almost absorbed by the system and people just don’t care.
In short: if you have children, I am pretty sure that you have already experienced The Trap of Directing People.
Trap #3: Punctuation
According to Paul Watzlawick and his theory of Radical Constructivism, the nature of a relationship is dependent on the punctuation of the partners’ communication procedures. It means that we always create our version of what we observe and experience. It causes us to finger point at each other when problems occur because we tend to see the root cause for problems in external events or other people rather than ourselves.
Bringing it in context to the elevator example, I wrote that there is some cynicism regarding the elevator system. This cynicism means that people have already stepped into The Trap of Punctuation because they blame the elevator system instead of questioning their own behavior. Because their own behavior is part of the problem.
Of course, one can still say that the elevator system is inappropriately designed because it does not address The Human Factor. Consequently, the overall question is: where to start? And the answer to that question can only be: with ourselves. Because it’s ourselves where we have the power to initiate immediate change. Otherwise, asking others or the system to change, we would consequently step into
- The Trap of Directing People, for the case that we try to change the behavior of other people or
- The Trap of Determinism, for the case that we ask to change the surrounding system.
Keep Your Eyes Open
I like the idea of these three traps because they are easy to understand. You don’t need to deep dive into systems theory to get it. Thus it’s more digestible and especially when you are in a leadership position, it is important to be aware of the negative effects of linear thinking.
However, be aware of the Human Factor and the Trap of Directing People — whenever you try to change things in your organization by convincing people of your ideas, they will interpret them by themselves. And you cannot predict the outcome of this process.
Thus I would leave it to the following advice: look at yourself and next time you come to a situation where things do not work out as expected, you may remember the three traps I presented in this article. Then, take a step back and reflect on the situation and your behavior. In the end, adjust your behavior accordingly and try again.
 Learn about Newton’s laws of motion at Wikipedia.
 Learn about divide and conquer or divide and rule at Wikipedia.
 Learn about the Cynefin framework at Wikipedia.
 Learn about the Deming Circle, also called PDCA, at Wikipedia.
 However, some brilliant people avoid using the default elevator system by using the emergency elevator instead. It goes from ground level up to floor 34.
 Sure, one can solve the elevator problem with many sensors around and inside the elevators and extensive use of statistics. But I think such a solution is a bit over the top.
 Learn about John Kotter’s 8-Step Process for Leading Change at Wikipedia.
 Learn about Organizational Citizenship Behavior at Wikipedia.
 Learn about McGregor’s Theory X and Theory Y at Wikipedia.
 Learn about Bass’ Full Range of Leadership Model, Transactional Leadership, and Transformational Leadership at Wikipedia. You may also read my first article, Leadership: History Matters.
 Learn about Constructivism at Wikipedia.
 Learn about Psychological Resilience at Wikipedia.
 For example, see Organizational Cynicism: Bases and Consequences by Rebecca Abraham (2000) or search Google Scholar. Find a short note about Social Cynicism at Wikipedia.
The Principles of Scientific Management
Frederick W. Taylor
Bernard M. Bass (†), Ronald E. Riggio
The Responsibility Process: Unlocking Your Natural Ability to Live and Lead with Power
Denkwerkzeuge der Höchstleister: Warum dynamikrobuste Unternehmen Marktdruck erzeugen
Gerhard Wohland, Matthias Wiemeyer
Leadership Without Easy Answers
Ronald A. Heifetz
Leadership and the New Science: Discovering Order in a Chaotic World
Margaret J. Wheatley
Thinking in Systems: a Primer
Complexity and Management: Fad or Radical Challenge to Systems Thinking
Ralph D. Stacey, Douglas Griffin, Patricia Shaw
Pragmatics of Human Communication: A Study of Interactional Patterns, Pathologies, and Paradoxes
Paul Watzlawick, Janet Beavin Bavelas, Don D. Jackson
Einführung in die Systemtheorie
How Real is Real?
Many thanks go to LDX#40, who reviewed this article for me.