Data dynamics

Data is often spoken of as though it were inert: rows in a table, files in storage, numbers awaiting analysis. This framing is deeply misleading. In modern systems, data does not merely describe behaviour — it participates in it.

Data is not an artefact.
It is a behavioural trace.

Data Is Produced by Choice

Every data point is the residue of a decision:

• A user clicks, scrolls, or abandons
• A system logs, samples, or ignores
• A metric is defined, not discovered

What is recorded reflects what a system considers important. What is ignored disappears from analysis altogether. Data, therefore, is shaped by design long before it is analysed.

Measurement Changes Behaviour

Once data is measured, it begins to exert influence. Metrics create incentives. Dashboards guide attention. Models reshape options.

This reflexivity leads to well-known distortions:

• Goodhart’s Law: when a measure becomes a target, it ceases to be useful
• Gaming and metric inflation
• Behavioural convergence toward what is rewarded

In such contexts, data does not passively reflect reality. It actively reshapes it.

Why This Matters for Design

Treating data as behaviour forces a shift in responsibility. Designers and data professionals must ask:

• What behaviours does this metric encourage?
• What actions become invisible because they are unmeasured?
• How will users adapt once this data is acted upon?

Ignoring these questions leads to brittle systems that perform well on paper and poorly in practice.

Data Products as Social Systems

A recommendation engine, a performance dashboard, or an analytics platform is not merely a technical artefact. It is a social system — mediating incentives, attention, and power.

Designing such systems requires more than statistical competence. It requires:

• Behavioural insight
• Ethical awareness
• Ongoing monitoring of unintended effects

From Extraction to Participation

A mature data practice recognises that data is co-created by users, systems, and designers. The goal is not to extract ever more data, but to participate responsibly in the behaviours data makes possible.

Static thinking asks: “What does the data say?”
Dynamic thinking asks:
“What is the data doing to the system — and to us?”