Making fast decisions doesn’t mean deciding blindly: the real role of data

Written by

Juan Cruz Mesigos

Updated

February 6th, 2026

3 min read

In sectors such as real estate, workspaces or hospitality, decisions rarely come with all the answers on the table. Context shifts, demand moves, and usage patterns evolve faster than reports can be finalised.

Still, making fast decisions does not mean making decisions without information.

The difference is not having all the data, but knowing which data matters when time is limited.

The trap of waiting for perfect data

One of the most common blocks in decision-making is the belief that clarity must come first. More metrics, more time, more validation. In reality, that clarity often arrives too late.

Data is always partial. It comes with a delay, reflects the past, and rarely captures the full context. When used as a reason to postpone decisions, data stops being a tool and becomes an obstacle.

Waiting for perfect data is often more expensive than deciding with incomplete but relevant information.

What data actually helps when decisions must be made quickly

Not all data supports fast decisions. In moments of pressure, value does not come from volume, but from direction.

The data that truly helps usually shares three characteristics:

It’s actionable, not merely descriptive
It can be interpreted quickly
It reflects real usage, not theoretical assumptions

In the case of space, for example, knowing total square metres available is far less useful than understanding when peak usage occurs, where friction appears, or how operational bottlenecks form.

The most valuable data does not explain everything. It helps reduce uncertainty.

Data and judgment are inseparable

Data alone does not make decisions. It requires judgment. A framework that allows information to be interpreted without falling into analysis paralysis.

This is where many organisations struggle. Some rely too heavily on intuition. Others defer decisions to dashboards that no one feels responsible for challenging. In both cases, accountability is lost.

Good decision-making combines sufficient information with clear principles. It means knowing which metrics to prioritise, which to ignore, and when to accept that data will not resolve the question, but can still limit downside risk.

Data does not replace judgment. It sharpens it.

Using data in changing environments

In environments where usage is uneven and demand fluctuates, data works best as a signal rather than a certainty. It helps detect early patterns, validate intuition and adjust decisions over time.

The goal is not to be right every time, but to build a system that allows for fast correction. When data is chosen well, even decisions that fall short generate valuable insight for the next move.