The Naïve Dream of Systemic Maps

Unseen Risks in Complex Environments

This quote, once seen in a 1981 publication from Narcotics Anonymous, is often attributed to Albert Einstein. Not only is that attribution wrong, but in an evolving environment, the statement itself is also wrong.

At one of the biweekly improvement sessions, a team member mentioned that there’s a problem with frequent late arrivals at the daily sync meetings. Late arrivals also lower the willingness of the more disciplined to arrive on time. As a consequence, they also start to arrive late. All the team members agreed that from then on, late arrivers would have to pay a penalty fee, which would be collected in a jar and donated to charity.

For the first week, it worked well. More often was it full attendance by the time the sync meetings started. However, in the second week, one of the team’s most highly valued members was late one day and was then punished in accordance with this very strict rule. She felt unfairly treated and resigned from the company. Could anyone have predicted this loss? In retrospect, it is easy to connect the dots. But in advance, there were too many unknown unknowns to even calculate the risk of losing this beloved colleague. That risk was not even on the map.

Causal Loop Diagrams

When seeking improvement, merely optimizing the parts of the system is not enough. This tautology was popularized in the 1990s. Management teams were asked to think systemically: consider the whole and the interactions between its parts, especially in terms of cause and effect. For example: Albert is angry at Bohr, which makes Bohr angry at Albert, which makes Albert even angrier at Bohr, which makes Bohr even… — in an endless causal loop.

Consultants have since facilitated an impressive number of workshops for these enterprise leaders, where the intention is to map the entire system of their business — all the parts and how they influenced each other — in causal loop diagrams. (The uncrowned king of this practice was Peter Senge, who, in his bestseller , managed to squeeze in almost sixty causal loop diagrams, using them to describe everything from the US–Soviet balance of terror to homemade theories of corporate growth and underinvestment.) But what if cause and effect happen to have a stormy — even everchanging — relationship?

When Cause and Effect Won’t Walk Hand in Hand

Creating systemic maps of all parts is a terrific idea. Unfortunately, however, the complexities of our reality might soon render it useless. Here, new parts are constantly being born, and old ones are dying as we speak. New interactions are established between the parts, and others suddenly disappear. In addition to this constant state of change, the number of parts and interactions is vastly greater than any human, or even a computer system, can keep track of. And frosting on the cake: other “wholes” are penetrating, and thus changing, our “whole” in a coevolution process.

Rather than a simplistic causal loop diagram, our reality may be thought of as a continuous flow of dispositions. Each new disposition is different from all those that have existed in the past. History doesn’t repeat itself. It just looks like something that once was — until it doesn’t. One way to think of this is that events happen for the first time, and their impact can never be undone.

When Julius Cesar crossed the Rubicon River in January 49 BC, things changed irreversibly. This ultimately led to Julius becoming dictator perpetuo — a dictator for life. His term as governor in the north had ended, and the Senate had ordered him to disband his army and return to Rome. By crossing Rubicon toward the south, he broke the law, which disallowed bringing armies into Italy. Before staging this declaration of war against the Roman state, Julius used an apt metaphor, saying that the die now had been cast. Never again could things be the same. Any systemic mappings carefully crafted before that moment found themselves tossed immediately into the wastebin.

There Are Better Ways

You may already know that the recent twenty years has given us a body of new methods for working in such complex environments. These methods affirm, for instance, diversity rather than specialization, guiding principles rather than strict rules, parallel contradictory theories rather than premature alignment, and direction rather than goals. In fact, these are all based on the lesson we may learn from this very article: Doing the same thing twice might give us two different outcomes. Or as a Albert perhaps would have phrased it: “Insanity is doing the same thing over and over and always expecting identical results.”

Staffan Nöteberg is the author of published by The Pragmatic Bookshelf and most recently with Simon & Schuster.

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