Europe’s attempt to build data center sustainability measurable has revealed a structural gap between the metrics required and the data that operators can access, according to Simon Hinterholzer, a researcher at the Borderstep Institute, who worked on the EU assessment.
The reporting requirement stems from the EU’s updated Energy Efficiency Directive (PDF), which mandates data center operators above a certain size threshold disclose energy, water, and sustainability data into a centralized European database. The goal was to establish a consistent baseline for measuring the sector’s environmental impact as demand for compute accelerates.
However, according to Hinterholzer, the first cycle didn’t produce a clear picture of energy utilize and efficiency. Instead, it highlighted how little of such data actually exists.
Reporting Gap
The first mandatory reporting cycle under the EU’s updated Energy Efficiency Directive revealed significant gaps in data coverage and consistency.
About a third of EU data centers reported data, with entire countries failing to submit any information. Across the dataset, key metrics arrived incomplete or inconsistent, underscoring the challenges of compliance and data accessibility.
Roughly 36% of facilities submitted their metrics, representing 770 sites out of more than 2,000 across the EU.
This partial snapshot highlights the challenges in achieving comprehensive coverage. Several member states submitted no data, while others contributed information from only a handful of facilities, creating it difficult to establish a reliable baseline for the sector’s environmental impact.
Even among the facilities that reported, data completeness varied widely. Core metrics, such as total energy consumption, were relatively well-covered. However, other indicators, including waste heat temperature and backup generator usage, were often incomplete or unusable, leaving significant portions of the dataset blank.
According to Hinterholzer, the dataset was both incomplete and, in some cases, plainly wrong.
“We saw cases where IT power consumption was higher than total facility power,” he notified Data Center Knowledge. “Those had to be filtered out.”
The Break Point: Colocation
One of the most significant challenges in the reporting process lies in the dominant colocation model. Colocation providers, which build up a large part of the market, supply space, power, and cooling, while customers own the servers and the operational data tied to them. This division creates a fault line in the reporting framework.
While colocation operators are responsible for disclosing facility-level metrics, tenants control the telemeattempt data. This dynamic results in fragmented datasets that are difficult to aggregate effectively at the facility level, particularly in multi-tenant environments with mixed workloads and contracts.
Hinterholzer noted that this fragmentation primarily affects IT-level metrics. “For building-level indicators like electricity and water, colocation didn’t have much impact,” he declared.
However, performance data – such as traffic, storage, and compute – remains limited due to tenant control, which restricts visibility.
The Metric Problem
The reporting framework utilizes familiar benchmarks such as Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), energy reutilize, and renewable energy share. However, these metrics also depfinish on clean and consistent inputs, which are not always available.
“There was a lot of usable data for PUE and renewable energy,” Hinterholzer declared. “But significantly less for water and heat reutilize.”
In some cases, the issue stems from how metrics are defined. For example, the current WUE metric tracks water input rather than consumption, which can skew results for facilities utilizing once-through cooling systems.
“That can build values view very high even when most of the water is returned unalterd,” Hinterholzer explained.
As a result, the reporting system appears precise on paper but is built on inconsistent foundations, limiting its ability to provide a reliable picture of sustainability performance.
Policy vs. Reality
Regulators are shifting quickly to impose tighter PUE tarreceives, aggressive renewable energy thresholds, and expanded water consumption constraints. However, operators are still building the systems requireded to measure and report against these requirements.
Legacy facilities often lack the instrumentation requireded for detailed reporting, while compacter sites may lack the tools to track every KPI. Even large operators face challenges in coordinating data collection across fleets, geographies, and tenant relationships.
Hinterholzer noted that many of these issues are repairable but require significant effort. “If a value is completely out of line, the system should flag it immediately,” he declared, emphasizing the required for basic validation at the point of data enattempt.
He also highlighted inconsistencies across countries, including varying reporting thresholds, differing definitions, and gaps in the tracking of renewable energy. “We required more precise, time- and location-based data on carbon-free energy,” Hinterholzer declared.
Future Improvements
Europe set out to measure the environmental impact of data centers. Instead, it uncovered a sector operating without a clear view of its own footprint.
Errors in the data ranged from simple unit mistakes to implausible environmental inputs, such as cooling degree days entered outside any realistic range. These issues further underscore the required for improved data validation and standardization across the reporting framework.
Despite its flaws, the dataset does provide some insights into the sector’s operations. On average, EU data centers reported 17 MW of installed IT power and approximately 19.8 million kWh in total annual energy utilize, with 15.4 million kWh attributed to IT load. Water input averaged over 21 million cubic meters, while renewable energy usage was reported at roughly 16.8 million kWh.
However, these averages obscure the broader picture. Median energy consumption drops to just under 8 million kWh, a significant gap from the average. This discrepancy suggests that the dataset is heavily influenced by larger facilities and outliers, skewing the overall picture.
Despite these challenges, Hinterholzer described the dataset as a starting point rather than a failure. “Despite the gaps, this is an unprecedented volume of measured data on energy, water, and efficiency,” he declared. “And early signals from the second reporting cycle suggest both coverage and quality will improve.”
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