Inside the Audit: A Closer Look at BIM Data Consistency – Part 1

Introduction

From BIM standards implementation through to project handover, Summit BIM’s goal during the design phase has always been clear — to deliver a robust design intent dataset that accurately represents the proposed facility. Our audits play a key role in this process, ensuring that the design data is consistent, reliable, and ready to support future operations.  Ideally, the combined deliverables, consisting of accurate design models enriched with reliable data, alongside traditional drawing and document sets, should serve as the foundation of a true digital twin — a virtual representation that mirrors every critical detail of the physical facility.

In one of our recent healthcare projects, we encountered several challenges with the design data, particularly related to the tracked assets. While data issues are not uncommon in BIM projects, they remain among the most complex to resolve — often surfacing only after models are well advanced and teams are under pressure to meet deadlines.

Why Does It Matter?

At Summit BIM, our focus is on serving the building owner — ensuring that the final deliverables hold long-term value beyond design and construction. In many BIM projects, emphasis is placed primarily on geometric accuracy. While valuable to designers and contractors, this focus can leave owners with deliverables that do not take full advantage of the rich data environment inherent in BIM.

Our goal is to change that. By setting, auditing, and enforcing robust data standards from the beginning, Summit BIM helps owners unlock the full potential of BIM — transforming it from a design coordination tool into a powerful foundation for operations, maintenance, and lifecycle management.

Issue #1: BEP Audit

During the project audit, our team identified a few recurring challenges. The project faced several issues, including delays in developing the BIM Execution Plan (BEP) and ambiguous strategies for assigning unique identifiers, such as equipment tags used for future on-site maintenance.

Ideally, strategies for identifiers should be established early in the design phase to guide consistent data entry and model organization. However, in this case, the tagging approach had not been sufficiently well defined during early design development. Compounding the issue, significant updates to the BEP only began around the 50% Construction Document (CD) stage — precisely when tracked assets were just beginning to be populated within the model datasets, including their basic geometry, identification details such as family name and type, and unique identifiers for tagging.

Impacts

As the models evolved rapidly and were frequently updated, the BEP struggled to keep pace. Without a clearly defined and actively maintained BEP, inconsistencies emerged between the intended tagging strategy and the actual design data being produced.

Over time, these discrepancies compounded. As the project advanced, designers faced mounting workloads and limited time to correct data issues. What began as minor misalignments eventually snowballed into larger challenges, many of which surfaced too late to be corrected efficiently. The result: additional time and effort were required late in the project to reconcile design data with the expected standards.

Lessons Learned

Given the realities of how BIM projects typically unfold across the construction industry, encountering data challenges of this nature is often inevitable — but their impact can be greatly reduced through proactive planning and consistent communication.

The key lessons learned from this audit were clear:

Establish standards early. Identifier and tagging strategies should be clearly defined in the early design phase, before data begins to populate the models.

Flag issues early and often. Continuous auditing helps identify inconsistencies while they are still manageable.

Treat the BEP as a living document. The BEP should evolve alongside the project, guiding data structure and coordination throughout every stage of design and construction.

Ultimately, a well-maintained BEP not only prevents costly rework but also ensures that the final dataset provides long-term value to owners — enabling a smoother transition from construction to operations and setting the foundation for a true digital twin.

Closing Thoughts

In our next blog, we’ll take a deeper look at the data issues uncovered throughout the design, and data collection phase — exploring how they emerged, what impact they had, and the lessons learned along the way. If you’re new to Summit BIM and would like to understand more about the services we provide, stay tuned. The second part of this series will also showcase examples of how we transform complex design data into organized, actionable information — empowering owners to streamline data collection and enhance facilities maintenance and operations.

If you are interested in learning more about how to get started and our process, please reach out. We would love to help you.

We are here to help!