With big®, model checking becomes a transparent, structured, and fully integrated process.
Models are automatically combined into a shared coordination model — without any manual preparation or complex setup. This allows the team to start checking immediately and see at a glance where issues arise. Automated rules detect clashes, missing information, or structural deviations, while the integrated issue function captures these points as model-based tasks and tracks them transparently. The result is a clear, end-to-end review and approval process that improves planning quality, makes risks visible early, and sustainably enhances collaboration among all stakeholders.
Systematic checking — not shotgun-style, with targeted model validation instead of a flood of collisions
Automated checking rules make it quick and reliable to identify clashes and conflicts — both between entire models and individual elements. Tolerances can be set flexibly, and targeted filters ensure the review remains focused and phase-appropriate. All detected deviations can be highlighted in the overall model and examined in context or individually, ensuring maximum transparency and full traceability.
From review to resolution — model-based and structured
All detected issues can be recorded directly as model-based tasks and managed in a structured way via the integrated issue management. By clustering clashes and assigning them to responsible roles, a transparent and efficient process is created that supports planning and enhances model and design quality.
Data validation for consistent and reliable models
During data validation, big® analyzes all information at both type and instance levels, automatically detecting deviations or missing values. Exceptions are clearly highlighted, making inconsistencies immediately visible and easy to resolve. The result is significantly higher data quality, reliably supporting planning as well as downstream processes such as cost management, operations, or ESG reporting.
