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Systems Reading

Doing good work is only part of what gets you ahead.

A lot of what determines what happens around you sits outside your job description: who has influence, how decisions really get made, what people care about, and how things get moving.

We often call this office politics. But underneath it is something more fundamental: being able to read the system you're working in.

You can't see the whole system. No one can.

The goal is to understand it well enough to know what's happening, where you have leverage, and how to use it to move your career forward.

Read

8 minutes

Pillars

Three

The central idea

A system can never be fully seen.

It can only be understood well enough, and observed closely enough, to move with it.

Here are three foundational pillars to get you started.

01Read the system 02Know your blind spots 03Adapt

Read the system

And keep reading it as it moves

To read it, we first need to understand what a system is and how it works.

01What is a system made of?

At its simplest, a system is made up of three things: its elements, the connections between them, and a real purpose (not always the stated one). Behaviours emerge from the interaction of those three.

02How do systems behave?

01

Connections Matter More Than Elements

The elements of a system are visible. The relationships between them are not, and yet that is where most of the system's behaviour comes from. Changing an element rarely changes the system. Changing a connection often does.

02

The System Never Stands Still

The system continuously generates new information, which shapes behaviour, which produces more information. Any clarity we reach begins to decay the moment we stop updating it. So we keep reading. Not to catch up, but to stay in step with the system as it moves.

03

Behaviours Reveal True Purpose

Not what it says it does. A system's true purpose is revealed by its consistent behaviour over time, not by its stated strategy or values. Before we can influence a system, we need to be honest about what it is actually optimising for.

This week, let's ask ourselves

What surprised me recently?

Take that surprise through the five steps below.

Observe→Explain with evidence→Identify patterns→Anticipate the trajectory→Ask yourself: Does it serve the system's goal?

Know your blind spots

Read yourself, too.

We don't see the whole system. We see our own version of it, filtered by where we sit, what we have experienced, and what we believe. So does everyone else in the room.

01Why do we have blind spots?

Every decision we make is shaped by a mental model: an internal map of how we believe the system works, based on assumptions we often take for granted. That map is built from experience, knowledge, and filters accumulated over time. It is never a perfect representation of reality. The gap between our map and the territory is where poor decisions are born, often with complete confidence.

Nobel Prize

Daniel Kahneman and Amos Tversky identified a cognitive trap they called the illusion of validity: we feel most confident in our judgements precisely when our mental model feels coherent and complete, regardless of whether the underlying data supports it. The more the picture hangs together in our mind, the more certain we feel, and the less likely we are to question it. Expertise does not protect against this. It often amplifies it.

Kahneman and Tversky, Judgment Under Uncertainty: Heuristics and Biases, Science (1974)

MIT Sloan

Peter Senge, Senior Lecturer at MIT Sloan, spent decades studying how organisations learn and change. In The Fifth Discipline (1990), he identified mental models as a key barrier to learning. Put simply, we often blame failure on poor strategy or execution, when the deeper issue may be the assumptions we never thought to question.

Peter Senge, MIT Sloan, The Fifth Discipline (1990), MIT Sloan Management Review (1990)

02What to do about it

01

Accept that we have incomplete information

This is not a personal weakness. It is a structural condition called bounded rationality, where actors in a system tend to make locally rational decisions based on the information available to them. Those individually rational decisions can produce collectively irrational outcomes. The person blocking an initiative is not necessarily wrong. They are optimising for what they can see.

02

Check what you can't see

Even when accurate information does reach us, our mental model filters it. So, we notice what fits, discount what does not, and often miss what would change our reading most. The result is that decisions get made on partial pictures, not because people are not trying, but because both the structure around us and the filters within us prevent the full picture from forming. Staying close to the work and to people across levels is how we keep our model closer to reality.

This week, let's ask ourselves

Whose perspective am I missing that would most change how I see this situation, and when did I last actively seek it out?

Adapt

Dance with the system.

Those who adapt best stay close enough to the system to hear what it says back. They treat every move as information and adjust their course accordingly.

01Why do we need to keep adapting?

Because the system never stops moving, our response cannot be a one-time analysis followed by execution. We act, we read what the system does in response, we update our model, and we act again. This loop, done with discipline, is our edge.

02How to adapt?

01

Treat every action as a deliberate experiment

Before we act, we name the hypothesis: if we do this, we expect the system to respond like this. Then we observe what actually happens. The gap between expectation and outcome is not a failure. It is the most precise data we will ever get about where our model needs updating.

Act→ Observe the response→ Update our model→ Act again
MIT Sloan

Senge's research at MIT distinguishes between adaptive learning, adjusting behaviour within fixed assumptions, and generative learning, where the assumptions themselves are challenged and updated. Only the second produces lasting change. The act-observe-update loop is generative learning in practice.

Peter Senge, MIT Sloan Management Review, The Leader's New Work (1990)

02

Map your stocks: what feeds them, what drains them

Many goals depend on a stock. Inflows build it; outflows drain it. Adaptation means watching those flows and adjusting accordingly. You strengthen what adds to the stock and reduce what drains it.

03

Make feedback a non-negotiable discipline

Weekly, monthly, quarterly: whatever the pace of the system demands. The goal is not a perfect model. It is a model that gets less wrong over time.

04

Do not lower the bar

A goal that shrinks to match results is not adaptation. It is drift. Each shortfall makes a smaller ambition feel reasonable.

When the system pushes back, look at what it rewards. Change the route or the incentives, not the aim.

Change the aim only when you learn it was wrong, not because it was difficult.

This week, let's ask ourselves

What am I trying to achieve (the stock)? What's feeding it (the inflows)? What's depleting it (the outflows) and how can I mitigate it?

Start

How well do you read the systems around you?

Knowing the three pillars is one thing. Knowing how well you can apply them is another.

So I've put together twelve scenarios leaders commonly face. In each one, you'll practise reading the system around you, make a call based on what you can see, and discover where you're strongest and where your blind spots may be.

Pass it on

If it was useful to you, it will probably be useful to someone you work with.

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Conceptual foundations
Donella Meadows, Thinking in Systems, Chelsea Green (2008) · Peter Senge, The Fifth Discipline, Doubleday (1990) · Russell Ackoff, Redesigning the Future, Wiley (1974) · Stafford Beer, Brain of the Firm (1972), and his later formulation that the purpose of a system is what it does (2002) · Herbert Simon, A Behavioral Model of Rational Choice, Quarterly Journal of Economics (1955)
Research and data
Peter Senge, The Leader's New Work, MIT Sloan Management Review (1990) · Kahneman and Tversky, Judgment Under Uncertainty: Heuristics and Biases, Science (1974)
Interpretation
This framework applies the work above to how leaders read the systems around them. The three pillars, and the readings they describe, are Sidrlabs' interpretation of that work, not claims made by the authors cited.
Privacy
To know whether this framework is useful, Sidrlabs counts anonymously how often it is opened and how often someone goes on to the diagnostic. There is no cookie and no identifier. Privacy policy