The science behind Agile: Part 2

Jan Železný
ableneo People
Published in
4 min readFeb 27, 2020


Hi, this is Jan from and this is the second part to our series about systems we live (and develop products) in.

Without further ado, let´s get started. Today we look at machine and living systems and we touch the topic of systemics. In the end, we foreshadow the connection to Agile that we properly explore it in the last two-part that are to come.

Humanity has come up with several major system theories. The ones we explore today are Mr. Newton´s theory of machine systems and Mr. Luhmann´s theory of living systems.

Machine Systems

Newton´s Machine System. Notice that the system stays the same in the course of the time. Except for the erosion of materials, of course.

Machine systems are fixed, rigid systems that cannot change out of their own will. Just like an IKEA chair is not going to reassemble itself into something else.

A chair can definitely erode and fall apart, but that would not be the will of the chair, merely an effect of conditions affecting its state.

Likewise, if an element in a machine system is broken, we basically have to take out the clockwork wheel and put a new one in its place. Then, the system will run again — it cannot choose to “not run anymore” if we properly fix the faulty parts.

The relationships between elements in machine systems do not change — that would require the laws of nature to change.

By relationships in machine systems we do not mean nails and screws, but the physical laws that allow the screw to stay in place and nails to not just pull themselves out of the wall.


The science dealing with the living systems is called systemics and it has been with us for over 50 years now. Why have you never heard of it? Well, it is not really taught in school but is vastly used in helping professions, e.g. therapy and coaching. A very well known application of systemics is “constellations”, which is a practice that enables social systems like teams or families to experience the actual complexity of the system and re-frame their role as an observer and playing other roles. But that would be a topic of its own.

Living Systems

So what are the living systems and what are some of their characteristics?

Examples of living systems are a cell, a tree, an animal, a human, a team, a family, … From our perspective, we want to stress social systems.

Unlike a machine system, a living system decides for itself how it is going to react to stimuli affecting it.

Depending on the system´s complexity, the range of decisions and activities are varying. A human would have a different scale of independent decision making than a cat or a plant.

The living systems have an innate ability to change on their own during the course of time.

As we explored in the previous part of the series, what really changes the shape of the system is the relationship between the elements of the system. Have a look at the following picture and follow this little story:

Luhmann´s Living System. Notice, it changes drastically in a relatively short period of time.

A — Wife, B — Husband, C — Mother-in-Law (wife´s mother), D — Teenage daughter

Day 7 —a family just living their lives, all members (elements of the system) are somewhat close to each other (through relationships between the elements), some may be closer than others, but it´s a tight system.

Day 8 —a mistress calls. She tells the wife that she has been having an affair with the husband for months now. And she supports it with some evidence to make it veritable.

Day 9 — the well-arranged social system (family members and their relationships) undergoes an upheaval. The husband (B) has been pushed away. The wife (A) is now much closer to her mom now, talking about how she should have known and should have seen the signs. The mother-in-law (C) is helping the wife overcome the situation and is now closely tied to her. The daughter (D) is now spending her time locked away in her room blasting music or at her best friend´s place, where the world is still ok.

All it took was one call. One day to turn it all around.

We humans, and our social system are fragile and difficult to predict.

We can only guess what will be people´s reactions and actions. We try to establish patterns and use big data, advanced prediction models and even cookies to increase the chances of a successful prediction. However, that is all it is, our best guess.

Looking at it from the company perspective, it is naive to think that a well-thought-out org-chart or framework will work just because we enforce it or it is “reasonable”.

Agile is about humans delivering relevant value in an ever-changing rapid world. To succeed in your Agile efforts, take into account that it will be humans (living systems) delivering the value, not machine systems. It might save you some money and stress.

Thank you for being with us and stay tuned as in the third part, we will explore the organization as a system. Meanwhile, do not hesitate to drop me a question in a comment here or message on LinkedIn and I will definitely get back to you.

Until next time, this has been


In case you missed the first part of series Science behind Agile -> read here.