GIGO to DINO: Is This Evolution? How to Make Sure Your Data Visualisation Means Something

I was chatting with a colleague today and, as often happens, the conversation drifted toward data.

Not just data collection — but what actually happens to the data once it has been collected.

One of the points we discussed was how organisations sometimes collect enormous amounts of data that never truly become information, insight, or knowledge. The data exists. The dashboards exist. The charts exist. But little understanding or meaningful action emerges from them.

And somewhere in the conversation, I heard myself say:

“Data In, Nothing Out.”

DINO.

I quickly wrote it down before I forgot it, knowing a blog article was percolating.

The Rise of the DINO-saurus

We are all familiar with the phrase “Garbage In, Garbage Out” (GIGO).

Poor-quality data inevitably leads to poor-quality outputs.

But DINO is different.

With DINO, the data itself may not even be bad. The problem is that nothing useful emerges from it. We collect it, store it, visualise it, and report it — yet still fail to create understanding.

At best, the data sits unused “just in case” someone might need it one day.

At worst, it is transformed into impressive-looking charts and slides that provide little insight and trigger no meaningful action at all.

No noise-to-signal. No learning. No change.

Just… data.

“I Plotted the Data — Look What It Shows!”

I often share with those I mentor and coach that a good visualisation should not require the author to stand beside it explaining what it means.

The chart itself should communicate the message.

If a graph only makes sense after a lengthy verbal explanation, then perhaps the visualisation has failed in its primary purpose.

In another conversation today, we reflected on an important lesson:

Visualising data alone does not automatically create information or knowledge.

A graph is not insight.

A dashboard is not understanding.

A report is not wisdom.

This brought me back to Russell Ackoff and his D-I-K-W hierarchy: Data → Information → Knowledge → Wisdom. I'll write about this next, the themes have been appearing recently in a few areas.

Data only becomes information when it answers a meaningful question.

Information only becomes knowledge when it helps us understand something well enough to act.

And wisdom? That is knowing what action actually matters.

Many organisational dashboards never move beyond the first step.

Escaping the DINO-saur Era

If we do not intentionally plan our measurement strategy as part of our aim, improvement work, or problem-solving approach, we can easily wander into DINO-saur territory.

Before collecting or presenting data, it is worth asking:

• What are we actually trying to achieve?
• What data do we genuinely need?
• If the measure is time-based, how frequently should it be collected?
• Is this the best chart type for communicating the message?
• Does every element of the visualisation add meaning?
• Will the audience immediately understand what matters?
• Does this help create knowledge — or merely display data?

Good data visualisation is not decoration.

It is communication.

Its purpose is not simply to display numbers, but to support understanding, learning, and better decisions.

Otherwise, we risk building ever larger museums with skeletons of the DINO-saurus:

Data In. Nothing Out.