As building information modeling (BIM) continues to evolve, BIM data is produced and consumed in many ways, using many different applications and processes. There really is no limit to how BIM data can be consumed throughout the building lifecycle from design through construction and even during post-occupancy. With recent improvements to technology in the AEC space, it is becoming more and more common to see practices that leverage data such as computational design, point clouds, and artificial intelligence. With all of these new use-cases for data, it is up to us as an industry to continue to find new ways to manipulate and analyze that data.
In this post, I’ll share a few examples of how BIM data is commonly used as well as a few ideas on how we can start to look at more progressive ways to leverage this valuable information.
Common Uses for BIM Data in the Design Phase
There are quite a few ways that BIM data is both created and consumed during the design phase of a project. For example, during the design phase, an engineer can use data to better understand the requirements for the spaces and rooms in a building by reading some basic architectural room data such as location, area, and occupancy type. An architect can design a more efficient building using data gathered from the geographic location of the building or historic weather data. Contractors can even begin to use BIM data during the design phase to help ensure the project stays on budget during these critical stages of a building.
BIM Data Helps with Accurate Documentation
But regardless of who’s consuming this design data, I think we can all agree that one of the most common advantages in using BIM data is to help us generate accurate drawings and documentation efficiently. As I’m sure you’re all aware, drawings are still the contract documents on most projects, so in today’s projects this set of drawings is often considered more valuable than the models.
However, before BIM, drawings within a single drawing set have been often decoupled from one another because much of the drafting and design was handled manually, which has the risk of expensive errors, especially due to the iterative nature of the design phases of a project. Not only was the information across multiple drawings in the same discipline at risk of being uncoordinated, but coordinating information across multiple disciplines was even harder to maintain.
Today, by using building information modeling, we can use a single data set to generate a significant amount of our set of drawings. For example, both floor plans and schedules can be produced from BIM data, so a drawing set has a much higher chance of being fully coordinated, even through the several iterations in the design phase, because as the floor plans are revised, the schedules are updated automatically to reflect any of those changes.
In addition to the concept of floor plans and schedules being generated from BIM data, another common use for BIM data is engineering calculations.
Thinking back to my first job in this industry as a fire alarm designer, years and years ago, I remember having to print hardcopy floor plans only to physically highlight every single symbol to count the fire alarm devices on each circuit. I also had to measure the wire runs of each circuit. I used these numbers to calculate the voltage drop per circuit. The good news is I eventually translated that to structured data I used an Excel spreadsheet to handle all of the formulas for the calculations, but there was still a lot of risk for error.
Using BIM data, you can mitigate much of that risk because you can create a “virtual circuit” (for lack of a better term), meaning you can now have your panel schedules calculate your electrical loads for you. In addition, these calculations will automatically update as you iterate your design throughout design and construction phases.
BIM Data for Project Managers
I like to refer to the critical team members on project who are somewhat disconnected from BIM workflows as “Non-BIM stakeholders” (e.g., senior engineers, project managers, or project executives). Due to the rapid pace that technology is changing, they’re becoming further and further removed from design and construction processes that influence their projects within a BIM model. Here at Unifi, we consider this issue, Dark BIM. These crucial players are surrounded by data-rich models, but they’re stuck without a guiding light. They have no visibility into the models and often rely on their more tech-savvy team members to validate the data within these models.
Project managers are a great example of some of the non-BIM stakeholders in a project. They are most likely less interested in BIM data that helps with design and construction workflows because they are more focused on the progress and success of their projects. However, that doesn’t mean that BIM data can’t be useful for them.
With the right tools, there is an opportunity to leverage BIM data for such things as identifying changes to engineers’ designs. And because many firms can be on the hook for multiple disciplines, a change to one discipline’s design can impact several other members of their team. This exposes new risk of uncoordinated drawings. Again, since the drawings are the contract documents, these issues can end up being extremely costly, and even worse, tarnish a firm’s reputation.
Considering the fact that drawings are typically generated from BIM Data these days, it really makes more sense for a PM to monitor the model data for changes, rather than drawings; BIM data is live and a set of drawings is static. In other words, the moment drawings are exported from a model, they are decoupled from the live model and can are typically immediately outdated.
UNIFI Project Analytics for Project Managers
The good news is, Project Analytics can help project managers because it gives them visibility of model data without having to open the model. Although typically viewed as a tool to help BIM managers, it can also give project managers new light when trying to keep an eye on changes to models, which again, reflects on their team’s drawings and ultimately affects coordination of a multi-disciplinary project.
Project Analytics: Compare Changes
In Project Analytics, we have a feature that allows these non-BIM stakeholders to review changes to models. In the image above, you can see that an air handling unit was swapped out for a larger unit, which ultimately can affect all MEP disciplines. For example, the electrical load could have increased resulting in a need for a larger panel. The piping for the drain could have increased in size or shifted in location which would affect spatial coordination in the ceiling space below.
These types of changes are conventionally difficult to track without the ability to compare changes of model elements, but with the help of our Project Analytics solution, we’re giving PMs the ability to see those types of changes whenever the models are synchronized, meaning it is truly live Revit model data.
This an example of how Unifi can help project managers transition from a workflow reviewing unstructured data on drawings, to reviewing structured data which is produced directly from the live model.
Project Analytics: Revisions
Another feature of project analytics that Project Managers might be interested in, is the ability to see the contents within a live model. Again, this information is updated whenever any user syncs.
One piece of content that we surface here is the Revisions within a Revit model. Here in Project Analytics, PMs have access to the live information in the model, so they’ll at anytime be able to open their web portal and review all of the revisions and RFIs that and their current status as defined in the Revit model.
How Are You Using BIM Data?
I hope this has helped you see some of the benefits of BIM data. What are some other ways you’re using BIM data? Have your non-BIM stakeholders gotten involved with leveraging this data? Please share your experiences with us in the comments below.