Issue Focus

BIM is a core digital technology for integrating data throughout the entire lifecycle before construction, but in April of this year, the government officially declared that realizing the roadmap for the “full-scale adoption of BIM by 2030” is virtually impossible.

- This is seen as the result of merely prioritizing the mandatory implementation schedule without fully establishing the core elements of a data-linked foundation, such as revising the ▲ pricing standards, ▲ administrative systems, ▲ professional workforce development, and ▲ standardization.

- Due to insufficient data standards based on usability and inconsistencies with administrative and internal systems, BIM data, regardless of whether it is public or private, remains confined to design-stage deliverables and fails to connect to the construction and maintenance stages, revealing a structural limitation

It is being faced with, and this is ultimately leading to BIM data being shelved (dead-locked) as a one-time deliverable for the client’s submission.

This study structured the factors hindering the promotion of BIM into four major domains and 16 detailed sub-factors, and conducted an AHP analysis with experts. As a result, the economic incentive factor (50.5%) ranked first, and among individual detailed factors

“ROI uncertainty” (17.6%) was identified as first place.

- This demonstrates that the essence of failure in BIM data linkage lies not in a lack of technology, but in a structural contradiction in which the party that generates the BIM data and the party that benefits from and utilizes it are not aligned.

- In particular, the fact that ROI ranked first among all categories goes beyond simply indicating a lack of return; it reveals the fundamental problem that the usefulness of BIM data is not felt by users. Even if users utilize BIM, they directly realize its benefits

As long as it is not felt, no compensation can fundamentally improve ROI awareness.

Accordingly, this study goes beyond the conventional flat conclusion of “compensation for prior research, legislative revision, and workforce development” and repositions BIM policy toward a four-dimensional framework based on four pillars: “tangible utilization → system structuring → easing entry barriers → ecosystem self-sustainability.”

Present a concrete path for a paradigm shift.

- (축 1: ROI Visualization Based on Perceived Utilization) Providing a ‘standard KPI for BIM utilization’ for public procurement, linking it to project-specific application and actual utilization through ‘quality and utilization-linked incentive allocation,’ and establishing a ‘benefit-sharing contract’ where the client and contractor share the benefits of BIM

Through standardization, establish a new compensation structure that goes beyond simply raising fees.

- (축 2: Structuring data flow through systemic restructuring) The master plan for gradually transitioning Seumteo’s bidding, permits, approvals, and completion registrations to a single BIM channel, and through the legal principle of “BIM priority and 2D annexation,” does not rely on the user’s initiative

Without doing so, structurally unify the data flow into a single unit.

- (축 3: Customized entry barrier reduction) Under the understanding that not everyone needs to be a BIM expert, the standardization of a job-specific “Role-Based BIM Usage Guide” and a natural language- and voice-based “AI-assisted interface” enable users to themselves

Even after mastering only the necessary level for work, enable them to enjoy the value of BIM data.

- (Chuk 4: Support for Small-scale R&D for Ecosystem Self-sustenance) Breaking away from traditional large-scale R&D, the “BIM Micro R&D Voucher” offers projects ranging from 50 million to 300 million won, and through the opening of KBIMS and CDE open APIs, small and medium-sized BIM solution companies and

Foster a decentralized ecosystem centered on startups.

In the future, BIM policy must achieve a fundamental paradigm shift from “mandatory submission of BIM models” to “creating an industrial structure where data flows.”