The BIM Paradox: It’s about data, not just drawings

Today’s BIM paradox stems from the fact that we have digitized our tools, but not our way of thinking. A recent comment on The ZIGURAT Summit sparked a necessary and urgent conversation within the architecture, engineering, and construction (AEC) community, uncovering an uncomfortable truth: without an intelligent data strategy, BIM risks becoming merely an expensive digital drafting method.

For over a decade, we have been implementing software, training teams, and adapting our workflows to this methodology that promised to revolutionize everything. We have created 3D models of astonishing complexity and beauty, capable of detecting clashes with millimeter precision. And yet, have we truly changed the way we conceive and manage project information? Or have we simply found a more sophisticated way of doing the same thing we did with CAD?

This is the paradox of BIM today. We invest in cutting-edge technology to solve a problem, but often, we are focusing the technology on the wrong problem. The real challenge lies not in modeling a beam or a wall in greater detail, but in understanding and structuring the information that element represents. The reflection is clear: “It’s not about better modeling software or faster machines; it’s about a better data architecture.”

Analog bias in a digital world

Let’s think for a moment about our traditional processes. A project was a collection of documents: blueprints, reports, bills of quantities, specifications. Each lived in its own silo. A change on a floor plan required a manual update to the elevations, sections, measurements… a slow and error-prone process.

BIM promised to solve this by creating a single source of truth. But have we achieved it? The “files and folders” mentality inherited from the analog world and early computer systems remains deeply ingrained. We organize our models, our families, and our data as if they were static documents. We export and import files, create countless versions, and ultimately, we are still managing containers of information instead of the information itself.

The question we must ask ourselves is: are we thinking in terms of relationships and dependencies? When we model a structural column, does our system only understand that it is “a 40×40 cm column made of HA-30 concrete”—an object with a geometry and a material name? Or is it capable of interpreting that this column supports a specific load dependent on the five floors above it, that its steel reinforcement corresponds to a precise calculation, that its 28-day curing time is a critical milestone that defines the project’s progress, that its embodied carbon is a key metric for the building’s sustainability certification, and that its exact position forces the rerouting of three main HVAC ducts in the false ceiling?

When the model only answers the first question, we have digital drafting. When it can answer the second, we begin to talk about true Building Information Modeling.

The project’s nervous system

This is where the concept of “data architecture” ceases to be an abstraction and becomes the fundamental pillar of effective BIM. Imagine data architecture not as a digital filing cabinet, but as a living system, a nervous system for our project. In this system, every piece of data has relationships, dependencies, and evolving requirements throughout the building’s life cycle.

Designing this architecture means asking ourselves strategic questions before even drawing the first line of the model: What information is critical for each project phase? Who generates it? Who needs it, and in what format? How is its quality validated? How do we ensure that a change in one piece of data (like the fire rating of a panel) propagates automatically and reliably to all other dependent data (cost, weight, acoustic specifications, etc.)?

This approach shifts the center of gravity from “what we model” to “why we model.” The goal is no longer to have a perfect 3D model, but a robust and reliable information ecosystem that supports decision-making, from conceptual design to the operation and maintenance of the asset.

The Lesson from Manufacturing

The manufacturing industry, faced with similar logistical and production complexity, solved this problem decades ago. No one in a car factory conceives of the chassis, the engine, and the electronics as separate files that are “coordinated” at the end. They work with an integrated Bill of Materials (BOM), a data system where every component, from the smallest screw to the engine block, has a clear identity, relationships, and dependencies that affect the supply chain, assembly, and quality control.

Why in construction, where mistakes cost millions and safety is paramount, do we continue to accept fragmented information management? What would a building project look like if we adopted a similar mindset, where our BIM model was the source of a living, connected “bill of materials and data”?

Questions We Should Be Asking

The way out of the expensive digital drafting paradox is not to buy new software or a more powerful computer. It is a cultural and strategic shift. It requires project leaders to stop delegating “the BIM stuff” to a specialist and get involved in the fundamental question: what do we want our data to do for us?

It means ceasing to measure BIM’s success by the level of detail in a model and starting to measure it by the quality and intelligence of the information it contains. A model can be visually simple but immensely rich in data that can automate calculations, validate compliance, optimize planning, and facilitate the future management of the building.

The next time you start a project, perhaps the first meeting should revolve around questions that force us to rethink our methodology: What key question about the building’s operation and maintenance are we not asking our model today? What would our design process look like if we started by defining the data architecture before the physical architecture? What single piece of information, if connected to the entire project, would transform the way we work?

And the final question, the one that initial reflection poses directly to us: For you, what does quality data really look like?

The answer to that question will define whether we continue to be digital drafters or if we finally become true information architects.