From Chaos to Clarity: Fixing Broken Workflows 

Picture this: three weeks into a complex facility design, the owner sends updated equipment specifications for the third time. Hundreds of data points and Revit families across multiple models need adjustment, MEP calculations must be reviewed for increased equipment loads, and the deadline hasn’t moved. How can the team adapt? 

If this scenario sounds familiar, you’re experiencing what I call data chaos. 

In my last post, I explored how automation is changing the landscape of A/E project delivery, examining the mounting pressures of project complexity, fragmented tools, and growing owner expectations. But identifying automation’s potential is only half the story. To understand why automated solutions matter, we need to focus on the root issue many teams face: data chaos. 

Defining Data Chaos 

Data chaos in A/E occurs when critical project information is scattered across multiple places, formats, and versions—with no single source of truth. It’s the gap between the data we have and the data we can actually use when making decisions. 

This stands in stark contrast to other industries. In manufacturing, digital twins synchronize specifications across design to production. In automotive, connected platforms enable real-time collaboration from shared datasets. Meanwhile, A/E firms still rely on static 2D drawings, with BIM data trapped behind a ‘Print to PDF’ bottleneck.” 

The Cost of Data Chaos 

Tech Debt: 

Quick fixes compound like financial debt. Hastily modeled elements and temporary solutions become permanent, leading to costly mistakes and rework. 

Reinventing the Wheel: 

Teams recreate custom solutions for each new project instead of building reusable, scalable tools. Lessons learned and design decisions are quickly lost in the fray of new deadlines and information, leaving staff with no choice but to start over from scratch once again. 

Information Silos: 

Critical project data gets trapped in isolated systems and programs when different disciplines or project stages use tools that can’t natively communicate. It is not uncommon to see the same data managed separately in any number of places – Revit, Excel, or a PDF buried on the network. When updates are shared, even the slightest hiccup in communication with any necessary party can lead to poorly coordinated deliverables or design solutions that miss the mark entirely. 

Turning Chaos Into Clarity: A Case Study 

To understand how custom automation solutions can cut through data chaos, let’s examine a recent challenge SMRT faced in our Science, Technology, and Manufacturing (STM) practice. 

The Challenge 

On a compressed timeline for a confidential STM facility, we managed hundreds of complex pieces of equipment, each with dozens of critical data points. 

The traditional approach of juggling individual equipment cut sheets, manually creating BIM families, and hand entering data would have consumed weeks of team capacity that we simply did not have. With constant scope updates, any manual process would create a perpetual game of catch-up, introducing dozens of potential error points every time data changed hands. 

The Solution – A Two-Part System 

I worked with our project team to develop a seamless two-part solution that transformed how we handle complex equipment data. 

Step 1: Centralized Data Management 

To make our project data work for us, we needed it all to live in one central “database” – our source of truth. Here, Excel provided the perfect balance of functionality and accessibility. The resulting tool matrix contained 400+ rows of equipment across 93 columns of data. 

Built-in pivot table functionality allowed our engineers to quickly tabulate and sort through the data, analyzing mechanical and electrical loads by building area for immediate quality control and design verification. 

Step 2: Automated BIM Integration 

Once the data was clean and centralized, we needed to connect it to our design tool, Revit. Using Python to interface with Revit’s application programming interface (API), it took two weeks to develop a custom add-in that transformed what would have been a weeks-long manual process into a simple 10-minute automated workflow. 

The tool can: 

• Read directly from the latest tool matrix 
• Automatically create Revit families for each unique piece of equipment 
• Populate all associated parameters with owner-provided data 
• Update, add, and remove families and data as the tool matrix evolves 
• Complete the entire data transfer process with as few as three clicks 

The Impact 

The two-week development effort led to immense project savings on initial model setup alone, plus ongoing savings as the matrix was continuously updated throughout the design phase. More importantly, we significantly reduced the error-prone manual data transfer process entirely. 

The efficiency of this process was measured on two fronts: 

Data Management:  

For data management tasks, including Excel matrix data entry, validation, and cleanup, we estimate an efficiency gain of 60 to 70 percent by providing a single, multi-user entry point that rejects incorrect formatting and data types. 

Revit Tasks:  

When looking at the Revit tasks associated with tool management, the automation provided an astounding estimated 2900% efficiency gain when compared to manual processes. 

On average, creation of a new Revit family with proper construction, parameter creation, naming, and insertion of graphics would take > 5 minutes per family (not including open and save times). With automation, this work is done in roughly 10 seconds per family. 

More importantly, this initial project served as a test case – now, this automation is in the process of being adapted to a reusable framework and standard operating procedure that our teams can easily adapt for future projects of any scale – 10 tools or 10,000. This is automation solving data chaos in action: it takes information trapped in traditional documents and integrates it intelligently with our design process in real time. This ability to quickly adapt our custom automations to unforeseen changes provides a highly valuable in-house capability. 

This equipment management breakthrough represents just one example of what becomes possible when firms approach automation strategically. By freeing designers from the distracting work of data management and allowing them to focus on the primary goal of better design, we turn data chaos into a competitive advantage. 

Creating custom solutions that solve real problems requires more than just technical skills.  

In my next post, I’ll dive into SMRT’s approach to developing automations that teams embrace rather than resist.