Data is the new oil — like oil, data is extracted, refined, stored, and transported to help people work smarter and live better. With rapid advancements in technology and the rise of AI, datacenters are in demand more than ever.
This creates a self-fulfilling prophecy within the construction industry: The more we use data to build, the faster, better, and more cost-effectively datacenters can be delivered.
Drawing on MCA, Inc.’s experience supporting the planning, measurement, and tracking of more than a dozen datacenter projects since 2005, this article outlines data management strategies that can enable successful datacenter construction.
Why Datacenters Require a Unique Approach
Ask a contractor how to accelerate a project, and they’ll say, “Add more labor.” Ask a trade contractor how to improve quality, and they’ll say, “Give me more time.” But neither approach reduces cost.
Instead, success in datacenter construction hinges on the synchronized management of work, effort, and time1 — across and within trades — to meet aggressive, customer-driven timelines.
After studying construction productivity trends for over two decades, Dr. Perry Daneshgari recognized that tracking work, effort, and time is convoluted in daily operations. To clarify their individual impact, he has advocated for tracking them separately, as each has distinct units of measurement.
Time Is a Feature of the Product
While technology companies continue to demand more datacenters, the time-to-market of the infrastructure is as critical as its technical complexity. Ongoing changes in datacenter technology cause these megaprojects to start and stop, placing significant pressure on schedules and labor.
When projects pause but end dates remain fixed, teams are forced to complete more work in less time — driving up the demand for labor. At the same time, supply chain issues and design changes complicate material and equipment procurement, adding further challenges to already compressed schedules.
Schedule Management & Externalizing Work
Given these pressures, schedule management becomes essential — not only to define the project timeline, but to also allocate labor and materials effectively. A datacenter may require hundreds of electricians at peak, but with proper modeling and Externalizing Work®, at least half of the scope can be completed offsite, where productivity is typically higher and scheduling constraints are reduced.
With persistent labor shortages, sourcing skilled local labor is increasingly difficult. As a result, datacenter projects often rely on traveling labor — crews who may be unfamiliar with local conditions or company practices — leading to reduced productivity and heightened risk.
What Data Is Needed
Datacenters must be approached as standalone ecosystems. While strong financial controls, planning, and tracking are foundational, the scale and complexity of these builds require more effort than the average project.
The process begins before the job is awarded — during estimating — and includes monitoring the project’s impact on backlog. For many contractors, a single datacenter can represent more than half of their annual volume, requiring planning months in advance for the management of labor, material, and cash flow.
Without clear visibility into the pipeline and backlog (Exhibit 1), planning is often reactive — jeopardizing the company’s ability to deliver on time and within budget.
Planning With Work Breakdown Structures
Knowing what lies ahead allows participating contractors to plan, acknowledge, and manage the large amount of ambiguity associated with the constant changes in design and contracts for these large jobs.
A work breakdown structure (WBS) is an essential planning process for datacenter projects. Structuring the work and deliverables is more complicated than it may be for most projects, especially when multiple contractors are working together within the same trade. Attention is needed at both the top layers of the WBS to plan the structure and at the bottom layer, where the work and activities are identified.
Very often, the work itself is repeatable across various data halls or colocation centers, but the effort involved in each one could be slightly different. Importantly, the WBS is developed independently from the estimate, as the plan for the work needs to represent the knowledge and experience of the foreperson/field lead responsible for the build.2
Contractors should expect that a qualified field lead may spend several days — or even weeks — developing the WBS. According to MCA, Inc.’s data, every hour spent planning can yield up to 17 hours saved in the field, assuming the plan is followed.3
Using the WBS & Scheduling for Labor Planning
With the WBS complete, work and effort can be planned and linked with the overall project schedule to see how this work fits in with respect to time and resources. Many contractors develop a “resource loading plan” based on input from the field team — often relying on gut feel rather than actual data.
By integrating the WBS with the schedule, contractors can generate a labor projection based on network logic — grounded in data rather than assumptions. The projection should also be studied to flatten the labor curve by Externalizing Work®, using prefabrication and vendor support for logistics and material handling.
Conflicts in the schedule should be raised to the GC or other contractors; for example, if the schedule shows sequencing that will lead to trade stacking or peak labor that is simply not available, it’s best to raise these concerns early and discuss alternatives.
Baselines & Productivity Measurement
Once work, effort, and time are planned, this “expectation” is locked in as a baseline for measurement. In the schedule, the baseline must be set to measure changes and their impacts on time and resources.
For the work and effort, a labor productivity reference point is set, against which progress and changes are measured. Contractors should apply ASTM E2691, the Job Productivity Measurement standard, to track productivity and identify obstacles.4
This is done for each contractor and can be rolled up across multiple contractors for visibility on the entire job’s progress.
Logistics & Labor Challenges
Labor is the biggest variable for trade contractors, especially with the transient workforce typically required for projects of this scale. While monitoring their productivity, progress, and obstacles happens using ASTM E2691, a plan for material logistics is also essential on datacenter projects.
With an already tight window for procurement (driven by ongoing changes and late decisions in equipment requirements), the plan for work, effort, and time should incorporate how material and equipment will get to the install location.
A comprehensive material logistics strategy should be integrated into both the project schedule and progress tracking systems.5