Why Commissioning Gets Messy: 7 Data Handover Failures (and How to Prevent Them)

Commissioning a data center is supposed to be the final validation step—a chance to prove everything works and hand over a fully operational site. In reality, this phase often becomes a fire drill of chasing documents, reconciling spreadsheets, and correcting last-minute surprises. Handover delays and data mix-ups are so common that they’re practically expected. One industry survey found that 76% of data center projects face construction delays, with missing handover dates becoming almost normal (www.linkedin.com). Another study of nearly 16,000 projects found only 8.5% were delivered on time and on budget, partly due to frequent changes and tools that failed to synchronize information (www.planradar.com). In short, poor data management and miscommunication make commissioning far messier than it needs to be.

Why does this keep happening, even at modern cloud infrastructure scales? The truth is that many teams still juggle a patchwork of siloed systems and manual processes. “Bad data” – inaccurate, incomplete, or inconsistent information – cost the construction industry an estimated $1.8 trillion in 2020 alone (www.constructiondive.com). And a report by Autodesk and FMI famously found that over half of all construction rework is caused by poor project data and miscommunication, representing more than $31 billion of waste per year in the U.S. (www.autodesk.com). Data centers, with their fast-track schedules and complex MEP integrations, are especially vulnerable to these failures. The good news is that they’re preventable. Below we break down 7 common data handover failures that make commissioning chaotic – and how to avoid them in your next project.

1. Siloed Systems and Disconnected Data

The failure: Data center projects involve multiple specialized tools – design models in CAD, asset details in DCIM, cable schedules in Excel, change logs in emails, and so on. When these systems don’t talk to each other, information gets trapped in silos. Each team (design, construction, operations) might maintain its own spreadsheets and databases that are out of sync. For example, the location of a server rack might be updated in a CAD floor plan but not in the Excel equipment list used by installers. This fragmented data environment leads to misunderstandings and mistakes during commissioning – teams think they’re on the same page when they’re actually working with different information.

Disconnected tools also slow everything down. On-site teams and headquarters often operate in silos using outdated tools like separate spreadsheets or even paper checklists, resulting in conflicting updates and zero transparency (www.planradar.com). One analysis pinpointed unsynchronized software and poor communication between stakeholders as key factors in why so few projects meet their targets (www.planradar.com). When essential data (like equipment specs, design revisions, or test results) lives in isolated places, the commissioning team ends up scrambling to gather and reconcile it all. It’s a recipe for errors and “I thought *you had that info”* moments.

How to prevent it: Break down the silos with integration. Make sure your critical systems can share data or feed into a central repository. This could mean using APIs to connect your Excel-based trackers with your DCIM platform, or adopting a unified data management platform that serves as a hub between design models, BOMs, and field data. For instance, ArchiLabs provides an AI-driven operating system for data center design that links your entire tech stack – connecting Excel, DCIM systems, CAD tools (like Revit), analysis software, databases, and even custom apps – into a single, always-synchronized source of truth. When one system updates (say a change in the BIM model), ArchiLabs automatically propagates that update across all other linked tools. By using a cross-stack integration platform, you ensure everyone is working off the same data, eliminating the disconnects that plague commissioning. The moment you connect those silos, you’ll see communication improve and handover tasks become far more streamlined.

2. Outdated or Inconsistent Documentation

The failure: In theory, by final commissioning, you should have a complete set of “as-built” documents that reflect exactly what was constructed. In practice, as-builts are often outdated or riddled with inconsistencies. During a fast-paced deployment, countless small changes happen on site – a contractor reroutes a cable, a different part gets substituted, equipment IDs are tweaked. These changes often aren’t captured in real-time, so the final documentation doesn’t fully match the data center as delivered (www.linkedin.com). The commissioning team might be using design drawings that don’t show that last-minute HVAC change, or an Excel list of assets that hasn’t been updated since the 90% design stage. This mismatch can cause tests to fail or get deferred while everyone figures out what’s actually installed.

Incomplete documentation is a huge risk for the operations team inheriting the site. If some field changes or deviations were “overlooked” and never documented, there will be gaps or errors in the turnover package (www.linkedin.com). Imagine trying to operate a facility when the single-line electrical diagram doesn’t match the breakers in the room, or when the equipment labels in the maintenance system don’t line up with reality. Unfortunately, this scenario is common. As one LinkedIn commentary on as-built accuracy put it, “ongoing changes… are not always captured, and the final as-built may not reflect what was constructed unless meticulously documented.” (www.linkedin.com) During commissioning, these inconsistencies surface as confusion, re-testing, and sometimes costly rework.

How to prevent it: Treat documentation as a living process throughout the project. Don’t wait until the very end to start updating drawings and databases – enforce changes to be logged as they happen. Implement a standard workflow where any site change (RFI, field markup, etc.) is systematically recorded and reflected in the master documents within days, not weeks. Digitize this process with tools that allow field teams to mark up digital plans that sync back to designers in real time. Using a common data environment (CDE) or a platform like ArchiLabs helps here. In ArchiLabs, for example, design models, cable schedules, and asset lists all live in one connected workspace; when a field engineer updates a value (say a serial number or a cable route) using a tablet on site, that change can automatically update the central model and all related documentation. By turnover time, your “as-builts” are truly accurate – because they’ve been continuously built and verified throughout construction. This proactive approach eliminates the scramble to patch drawings last-minute and ensures the operations team gets a clean, reliable dataset.

3. Manual Data Entry & Duplication Errors

The failure: A surprising amount of data handover work still happens via manual effort. Think of all the times someone copies equipment data from one spreadsheet into another, or retypes test results from paper forms into a report. Every manual handoff is a chance for human error to creep in. A technician might transpose two digits of a breaker setting, or an engineer might mis-key a rack number. These small mistakes can have outsized consequences during commissioning – an incorrect setting could trigger a false alarm, or a mislabeled asset might get skipped in testing. Moreover, manual data handling is painfully slow. Commissioning teams often burn days consolidating various Excel sheets, writing up test forms, and double-checking entries. It’s grunt work that delays the actual validating of systems.

It’s well known that humans make mistakes when inputting data – even careful professionals. In fact, studies have found that the typical error rate for manual data entry is around 1% (blog.beamex.com). That may sound low, but consider a data center with tens of thousands of individual data points (assets, serial numbers, test readings): 1% of that is hundreds of potential errors introduced just from typing. Compound this with duplication as data gets handed from one format to another (Excel to DCIM, DCIM to checklist, etc.), and you can see why by the time commissioning is underway, there are discrepancies everywhere. Bad data snowballs – a single wrong entry can propagate across multiple documents if everything is being copied over by hand.

How to prevent it: Automate the tedious stuff. Wherever possible, eliminate manual re-entry by using integrations or scripts to transfer data between systems. If you have to update a value, update it once in a primary system and let automation push it to other places that need it. Many modern DCIM and BIM tools have import/export capabilities or APIs – leverage them so that, for example, your equipment inventory in Excel can be imported programmatically into a commissioning management software without retyping. Use data validation rules to catch outliers (did someone enter a power reading of 5000 kW instead of 500 kW by accident?). Even better, adopt a platform that unifies data across applications so manual transfer isn’t needed at all. ArchiLabs, for example, was built to connect disparate tools and keep data consistent; it can read and write data to CAD models, spreadsheets, databases, and more, meaning you enter information once and it’s correctly reflected everywhere. By automating repetitive workflows and using smart integrations, you not only speed things up, you also drastically cut down on transposition errors and “oops” moments. The result is a cleaner handover package and a smoother commissioning process with far fewer frustrations.

4. Missing or Lost Commissioning Records

The failure: Commissioning generates a ton of data – checklists, test results, calibration settings, performance readings, issues found and fixed, sign-off sheets, you name it. Often this information is recorded in disparate ways: some in commissioning management software or spreadsheets, some on paper forms clipped to clipboards, some via emails or even text messages between on-site engineers. Without a centralized approach, critical records inevitably go missing or slip through the cracks. Perhaps a subcontractor performed a test and recorded the results on a sheet of paper that never made it into the final report, or a series of emails about a failed generator test didn’t get logged anywhere official. By the end of commissioning, it’s chaos trying to assemble the final binders or digital folders of results – and gaps in that record can delay handover or leave serious doubts about whether everything was properly tested.

The use of ad-hoc documentation methods makes this problem worse. Shockingly, over 70% of construction firms still rely on paper documents or even WhatsApp messages for project communication and documentation exchange (www.planradar.com). When commissioning info is shared through non-formal channels like text messages or handwritten notes, it’s extremely easy for it to never be captured in the permanent record. One missed step or a lost page can mean a piece of equipment wasn’t verified, or an entire functional test has no documented proof. Not only does this jeopardize the project sign-off, it robs the operations team of valuable insight (like knowing that UPS #2 failed a test initially but was fixed – something you’d want to track for future maintenance).

How to prevent it: Establish a single, digital commissioning log that everyone uses. All test procedures, results, and issue logs should funnel into one system of record – ideally a cloud-based commissioning management tool accessible to all stakeholders (owner, GC, Cx agents, subs). Ditch the paper and use tablets or laptops in the field to record data directly into this system in real time. Even if you still like paper checklists for on-site convenience, have a process to promptly input those results into the central database each day. The key is that by project end, nothing only lives on a piece of paper or someone’s inbox. Modern solutions can aid this: for example, ArchiLabs can automate large parts of the commissioning process by generating test procedures, capturing and validating results on the fly, and tracking all of it in one unified dashboard. A commissioning agent can run through automated test sequences (say for a generator load test) where the system records readings directly (via IoT integrations or manual input on a tablet) and flags any out-of-spec results immediately. All data gets consolidated, time-stamped, and linked to equipment records. By the time you’re producing the final commissioning report, it’s essentially already compiled itself – with every check accounted for. Not only do you prevent data loss, but you dramatically speed up the handover package preparation. Plus, the operations team can trust that if it’s not in the system, it didn’t happen – no more second-guessing whether some unlogged issue is lurking out there.

5. No Single Source of Truth

The failure: Perhaps the most fundamental problem underlying all the above is the absence of a single source of truth for project data. When there isn’t one authoritative place to find “the latest” information, everyone ends up working from their own sources (and hoping it’s up to date). During commissioning, this manifests as confusion over which data set is correct. Is the Excel equipment schedule that the commissioning team has the final word, or is the DCIM database on the operations side more accurate? What about the Revit model – has it been updated to reflect all field changes, or is it now out of sync? Without a single source of truth, disputes and discrepancies are common. We’ve seen scenarios where three different lists of assets (from design, construction, and operations) all have slightly different counts or naming conventions – and no one knows which to believe. This not only delays testing and verification, it erodes confidence in the entire handover. Teams waste time in meetings reconciling data instead of actually executing the commissioning plan.

Operating without a single source of truth also means any post-handover updates might not get propagated to all stakeholders. Data center teams might inadvertently create multiple “sources of truth” – for example, facilities keeping their own spreadsheets because they don’t fully trust the turnover documentation. This splintering of data will continue to cause inefficiencies long after commissioning, as there’s no reference point that everyone treats as gospel. It’s the classic “multiple versions of the truth” problem that plagues many enterprises – and it’s especially dangerous in complex infrastructure projects where mistakes are costly.

How to prevent it: Commit to a single source of truth philosophy from day one. This means designating one platform or repository as the place where current project data resides, and enforcing its use. Many organizations use a Building Information Model (BIM) as the core, with everything linked to it. Others use a centralized database or a tool like a DCIM as the master and integrate others around it. The approach can vary, but the goal is the same: everyone references the same data source for decision-making. A cross-stack platform like ArchiLabs is designed for this purpose. ArchiLabs essentially creates an always-in-sync knowledge base for your data center – linking your BIM/CAD models, spreadsheets, DCIM, and other apps so that they behave like one unified system. For example, if a cooling unit’s specification is updated in an Excel sheet by a designer, that change can automatically flow into the Revit model parameters, the procurement database, and the commissioning checklist. All users see the latest info, no matter which interface they’re using. By having this single source of truth, you prevent the divergence of data. Commissioning teams can trust that the list of equipment they’re verifying is complete and current. Any discrepancies discovered in the field are addressed in one place (and thereby updated everywhere). This approach requires discipline and the right integration tools, but once in place, it dramatically reduces confusion and the potential for error. It means fewer meetings to reconcile lists, and more time to focus on actual testing and problem-solving.

6. Poor Change Management and Version Control

The failure: Changes are inevitable in any data center project – designs evolve, equipment gets swapped, setpoints are tweaked during commissioning. The failure here is not the changes themselves, but how they’re managed (or not managed). Many teams lack a robust version control process for their documents and data. Instead, they rely on ad-hoc methods: emailing revised spreadsheets around, saving files as “_final_final_v2.xlsx”, or keeping personal notes of changes. This leads to multiple conflicting versions floating around. During commissioning, uncontrolled changes create havoc. You might have one version of the network diagram used by the IT team, while the facilities team is working off another version that doesn’t include a late-breaking change. Without clear version control, it’s easy to test against outdated criteria or miss re-testing something that changed.

Another aspect is change approval and communication. If the commissioning team isn’t looped in when, say, a firmware update is applied to a UPS mid-commissioning, they might be operating on wrong assumptions. We’ve also seen instances where lack of standardized workflows and non-standardized communication exacerbates change-related issues (www.planradar.com) (www.planradar.com) – essentially, if one hand doesn’t know what the other is doing, a small change can snowball into a big problem. The result is often last-minute surprises at handover: “When did that get changed? Why isn’t it in the report?” A lack of proper change logs and version history means troubleshooting is harder too, because you can’t easily trace what changed when.

How to prevent it: Implement a formal change management and version control process for all project data and documents. This includes using a revision control system for drawings and models (e.g., a BIM collaboration tool or a source control repository for code/configs), and maintaining a change log for key data like setpoints or configuration files. Every change during commissioning should go through a quick review and get documented. It helps to nominate a “configuration manager” or data custodian role on the project who ensures that no change goes untracked. Use software that supports multi-user collaboration with audit trails – for example, many teams use platforms like Autodesk BIM 360 or similar for versioning design files, and something like a ticketing system to track change requests in commissioning.

Technology can make this easier: ArchiLabs and similar platforms maintain a history of all changes made to the integrated data set. In ArchiLabs, if someone modifies a parameter (like a rack’s power allocation or a cable route), the system can log who made the change, when, and what the previous value was. You can always roll back or at least have an audit trail of decisions. Moreover, changes can trigger notifications or workflows – so if a last-minute design change happens, the commissioning team gets alerted and can adapt their test plans accordingly. By enforcing disciplined version control, you ensure everyone is indeed testing against the latest design and that there’s no ambiguity about which version of a document is the right one. Clear versioning = clear accountability, and far fewer “I didn’t get that memo” moments.

7. Knowledge Silos and Poor Data Handover to Operations

The failure: Commissioning isn’t just about testing equipment – it’s also about transferring knowledge to the operations team who will run the data center. A failure in data handover often means critical knowledge stays siloed with the project team or individual experts, instead of being passed on to the people who need it day-to-day. This can happen when the turnover documentation is sparse or overly technical, or when there’s no proper training provided. If the operations team receives a pile of PDFs and spreadsheets with no context or easy way to query the data, a lot of the hard-won insights from design and commissioning get lost. In fact, a Splunk survey found that 55% of an organization’s data is “dark data” – collected but never utilized, often because it’s not accessible or understandable to those outside a small group (dxc.news). Imagine all the valuable information generated during commissioning (like lessons learned, configurations that were adjusted, performance baselines). If that lives in a closed-off system or in one person’s notebook, it’s not helping the wider team.

Another aspect is the lack of user-friendly documentation and training. Commissioning teams sometimes focus on the technical results but not on packaging the information for others. The result: the facility staff inherits a data center but doesn’t have full visibility into how it was tested or why certain decisions were made. Knowledge transfer is so important that experts consider commissioning incomplete until it’s done. As JLL notes in their commissioning best practices, ensuring long-term success requires comprehensive knowledge transfer to facility staff and detailed, user-friendly documentation for all systems (www.jll.com). When this is neglected, operators may unknowingly repeat past mistakes or miss nuances (for example, a particular routine to reset a system that the commissioning team figured out but never passed on). The handover falls short of truly empowering the operations team.

How to prevent it: Make knowledge transfer a first-class goal of commissioning. This means producing documentation that isn’t just technically complete, but also organized and accessible. Use a structured handover database or a knowledge base, rather than dumping files on a shared drive. Interactive digital manuals or a wiki-style repository can be much more navigable than a 500-page PDF. During commissioning, have operations personnel shadow the process and be involved in sign-offs – this way, they gain tribal knowledge directly. Also, consider post-handover support: set up clear communication channels between the project team and operations for the initial months of go-live, so any questions can be resolved (and documented for future reference).

From a tooling perspective, leveraging a platform like ArchiLabs can provide the operations team with a live, synched environment containing all the project data. Because ArchiLabs keeps specs, drawings, and operational documents in one place (with version control and full edit history), it serves as an ongoing single source of truth after handover. Operations can continue to use it to view the digital twin of their facility, make updates as they change things, and even run custom agents to automate routine tasks. Moreover, by using such a system, the “knowledge” isn’t trapped in the heads of a few engineers – it’s captured in the data and automation workflows. Teams can even encode standard operating procedures or troubleshooting checklists as automated agents. The bottom line: preventing knowledge silos is about both culture and tools. Foster a culture of documentation and open information sharing, and back it with tools that make it easy to centralize and retrieve that knowledge. This ensures that when the commissioning team steps away, the operations team isn’t left in the dark.

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Commissioning a data center doesn’t have to be a messy ordeal. By proactively addressing these seven failure points, teams can turn handover into a predictable, smooth process rather than a scramble. The common theme in all the solutions is integration and communication: integrating your data and toolchain, and ensuring communication of accurate information to all stakeholders. In practice, this means investing in processes and platforms that connect the full lifecycle of the project – from design and capacity planning to construction and into operations. That’s exactly the vision we embrace at ArchiLabs. We’re building an AI operating system for data center design and operations that unifies every part of your tech stack into one source of truth, and then automates the heavy lifting on top of it. Whether it’s automating a rack layout design, planning optimal cable pathways, or orchestrating an end-to-end commissioning test sequence, the goal is the same: save your team from manual drudgery and data chaos. When your Excel sheets, DCIM, Revit models, and databases are all in sync, and your routine workflows are handled by intelligent agents, commissioning stops being a frantic final exam. Instead, it becomes the straightforward confirmation it was meant to be – a handover of not just assets, but of complete, trusted data and understanding to those who will keep the digital world running.