Doxel at DICE Pacific Northwest
Where Speed Meets Precision in Data Center Construction
The pace of data center construction has changed.
Schedules are tighter. Labor is harder to find. And the tolerance for error is almost zero. Owners and builders are being asked to deliver faster than ever, often on projects where even a small delay can cascade into millions in lost revenue.
That’s exactly why Doxel is heading to the DICE Pacific Northwest Data Center Investment Conference & Expo. This event brings together the investors, developers, contractors, and technology leaders shaping the next generation of digital infrastructure. And this year, one topic is rising above the rest: How do you build faster without losing control?
Why This Conversation Matters Now
The demand for data centers continues to surge, but the industry’s ability to deliver them has not kept pace.
Global construction productivity has barely moved over the last two decades, increasing just 0.4% annually, even as project complexity has grown dramatically
At the same time:
- Labor shortages continue to constrain output
- Projects are becoming more complex and interdependent
- The cost of delays is rising, especially in mission-critical environments like data centers
The result is a widening gap between what needs to be built and what can be delivered.
To close that gap, leading teams are rethinking how projects are executed. They are combining modular construction strategies with real-time, objective visibility into progress.
Featured Session: Speed Meets Precision
Speaker: John Rewolinski, PSP, Head of Scheduling Analytics, Doxel
Session Title: Speed Meets Precision: How Modular Delivery and Construction Tech Are Redefining Data Center Execution
This session focuses on a simple but critical challenge: Speed alone is not enough. Precision is what keeps speed from turning into rework.
Attendees will learn:
- How modular delivery accelerates schedules while introducing new coordination risks
- Why traditional schedule tracking fails on fast-moving, high-density builds
- How leading teams use AI-driven progress tracking to validate work in place
- What it takes to align BIM, schedule, and field conditions in real time
The Problem With Traditional Progress Tracking
Most construction teams still rely on a familiar process:
- Walk the site
- Ask trade partners for updates
- Compare notes against the schedule
The issue is not effort. It’s timing. By the time a deviation shows up in a report, it’s often weeks old. On a data center project, that delay can mean:
- Missed handoffs between trades
- Out-of-sequence work
- Rework that compounds across systems
Doxel changes that dynamic by delivering objective, automated progress tracking that compares actual site conditions directly to the BIM model and schedule. Instead of asking what’s happening, teams can see it.
What Doxel Brings to Data Center Construction
Doxel was built for complex, fast-paced projects where precision matters.
With Doxel, teams can:
- Track progress automatically across all visible trades and construction stages
- Detect deviations early, before they impact downstream work
- Align teams around objective data, reducing disputes and guesswork
- Make faster decisions with real-time, visual insights
This approach eliminates manual reporting gaps and gives teams a consistent, accurate view of the jobsite.
The impact is clear:
- Earlier risk detection
- Fewer surprises
- More predictable outcomes
Deliver Faster. With Confidence.
Construction is not getting simpler. But it is becoming more measurable.
With the right combination of modular delivery, AI-driven insights, and objective progress tracking, teams can finally deliver projects at the speed the market demands without sacrificing quality or control. Doxel is helping lead that shift. See Doxel today.
The Quality Control Use Case Nobody Planned For
When the scan says "not installed," and the trade says "we did it," the answer might be a quality problem, not a data error.
A Disagreement That Turned Into a Discovery
Doxel's system was designed to track progress, but on a hyperscale data center project with DPR Construction, it caught something that no daily report, RFI, or schedule update had flagged, and the lesson changed how the team interpreted data discrepancies entirely.
The story starts with a flag. Doxel's AI detected uninstalled security components near certain doors. The electrical trade partner pushed back hard, claiming they had roughed in all the security to those doors. In their estimation, the work was done.
After further investigation, the team found the truth: the security boxes had been installed. Three feet to the right of where they were supposed to be.
Wrong Location. Not Flagged Anywhere.
The components had been physically installed, but they were mislocated relative to the BIM. When comparing the 360° site photos against the model, Doxel’s AI correctly identified them as not installed in the designated location.
"If something's showing as not installed and the trade partner says it's installed, we probably have a quality control problem. Not the intended use case — but awesome to see."
— Mike Miller, Superintendent, DPR Construction
The team had stumbled onto a new interpretive principle. When Doxel flags something as missing and the trade says it's done, don't default to assuming the data is wrong. Investigate. The discrepancy might not be a tracking error; it might be a quality flag.
The Cost of Dismissing the Signal
REWORK WARNING: Dismissing data because it contradicts expectation is how quality issues get buried. The cost of investigation is almost always lower than the cost of rework — especially once walls are closed.
This is not an abstract lean principle. It played out on a real job, on real infrastructure, with real rework costs. The lesson is practical: when scan data and field reports disagree, treat the disagreement as information, not noise.
What This Means for Quality Management on Complex Projects
Construction quality management has traditionally relied on scheduled inspections, trade self-reporting, and periodic walkthroughs. These methods work reasonably well for obvious defects. They are poor at catching components that are physically present, but are installed in the wrong place relative to the design.
Computer vision can fill this gap by comparing what is physically present against the BIM at the component level across all visible trades every week. Mislocations look identical to missing components from the system's perspective, because in both cases, the component is not where it should be.
The practical recommendation is to establish a protocol for investigating discrepancies rather than defaulting to dismissal. When a trade reports complete and the system reports incomplete, send someone to review the discrepancy. It only takes minutes, but it can prevent weeks of rework.
Beyond Rework: The Documentation Value
There is a secondary benefit this story highlights: objective, time-stamped documentation of installation location for every component. On a complex facility like a data center, where systems are dense, and modifications may be needed years later, having a record of where things were actually installed, not just where they were designed to go, has ongoing operational value.