As the world continues to rely even more on data centers and cloud infrastructure, energy efficiency has become a much more important concern for data centers all around the world.

There were over 2600 data centers in the United States in 2020. By 2026, there will be over 5,400 total facilities, including those under development in the USA, and there are over 10,506 data centers in the world presently..)

Recently (2025–2026), the data center industry is under pressure to move from voluntary green initiatives to strict, mandatory compliance, particularly around AI-driven growth.

The European Union’s Energy Efficiency Directive (EED) mandates that data centers above 500kW must report on energy performance, water usage, and heat reuse. The data reported is published in a public EU database. While in Germany, the Energy Efficiency Act forces data centers with more than 300 kW capacity to meet strict PUE (Power Usage Effectiveness Targets). Existing data centers operational before July 2026 must achieve a PUE of less than 1.5, while newer facilities must meet a PUE of 1.2.

To keep up with comparative benchmarks and energy efficiency targets, data centers use standard metrics like power usage efficiency (PUE) and DCiE in order to measure how well operations are performing in terms of energy efficiency.

This article explores what data center infrastructure efficiency is and the best practices to achieve it.

What is Data Center Infrastructure Efficiency?

Data Center Infrastructure Efficiency is a standard performance improvement metric used by data centers to calculate energy efficiency. Simply put, DCiE answers one question:

How much of your energy is actually doing useful computing work?

Data Center Infrastructure (DCiE) was developed by the Green Grid, an open industry consortium founded in 207 which is dedicated to improving energy efficiency, sustainability, and resource management in data centers and IT ecosystems.

How Can DCiE Be Calculated?

DCiE is calculated to determine the amount of energy consumed by IT equipment in a data center. It is expressed as a percentage, and it is calculated by dividing the IT equipment power by the total facility power.

The DCiE formula is written simply as:

DCiE = IT Equipment Power ÷ Total Facility Power * 100

Where:

• IT Equipment Power = energy consumed by servers, storage, and networking systems
• Total Facility Power = energy consumed by the entire facility, including cooling, lighting, power distribution, and other supporting infrastructure

Example

If a data center consumes 1,000 kW in total and 700 kW powers IT equipment:

DCiE = (700 ÷ 1,000) × 100 = 70%

This means 70% of the energy is doing productive computing work, while 30% supports overhead systems.

What is a Good DCiE Score?

A higher DCiE indicates better efficiency because more energy goes directly to IT workloads rather than overhead.

- 50–60%: Inefficient or legacy facilities

- 60–75%: Average performance

- 75–85%: Efficient modern facilities

- 85%+: Highly optimized data centers

Although the theoretical ideal DCiE percentage is 100%, it is practically unattainable because some overhead (cooling, lighting, power conversion) is always going to be needed.

How To Measure For DCiE

To accurately measure for DCiE, proper monitoring is non-negotiable as well as reliable instrumentation. Key steps to help measure accurately for DCiE include:

1. Installing Power Meters

Make sure to install power meters at critical points where measurement needs to take place, such as the utility or main incoming supply, UPS output, Power Distribution Units (PDUs), and IT load panels.

2. Separating IT VS Facility Loads

Ensure IT equipment consumption is measured independently from cooling and mechanical systems. This makes it more convenient to measure and calculate for DCiE when power loads are not measured separately; it becomes harder to calculate for DCiE, and results may be warped.

3. Use Pai Enterprise for Real-Time  Monitoring

To measure for DCiE, it is very important to collect energy data continuously. Continuous or real-time monitoring helps provide more trusted insights than periodic manual readings and helps identify inefficiencies in real time. Intelligent Energy management software like Pai Enterprise can be used to collect real-time energy data in your data center, using smart IoT sensors.

4.  Track Trends Over Time

Compare DCiE monthly or quarterly to evaluate the impact of upgrades or operational changes. On Pai Enterprise, you can easily see the trend tables of your consumption by cooling equipment and IT equipment in real time and over any preferred period of time in less than three clicks.

Why DCiE is Important

Cost Reduction

Energy is one of the largest operating expenses for data centers. Higher energy efficiency can help reduce energy costs.

Sustainability Goals

Improving DCiE aids the reduction of carbon emissions and supports ESG and regulatory compliance targets.

Capacity Optimization

Efficient facilities are able to support more IT workloads without increasing infrastructure size or power draw.

Performance Benchmarking

The DCiE metric allows data center operators to benchmark against industry standards and justify investments in efficiency improvements.

Best Practices To Achieve Good Data Center Infrastructure Efficiency

To manage your data center infrastructure efficiently, intentionality and well-organized measures are required. It is important to implement and adopt useful and appropriate tools as well.  Improving DCiE doesn’t always require massive upgrades. Small, consistent operational improvements often deliver the biggest gains. Here are concise, high-impact practices to achieve good DCiE:

Optimize Cooling Systems

To optimize cooling systems, use hot/cold aisle containment, free cooling, and variable speed fans to reduce HVAC energy use.

Utilize or Refix the Facility For Better Airflow

Install blanking panels, seal floor gaps, and remove unused hardware to prevent air leakage and hotspots.

Adopt or Deploy Efficient Power Systems

Adopt or deploy high-efficiency UPS units and minimize power conversion stages so you can cut electrical losses at your data center facility.

Consolidate Servers

Virtualize workloads and retire underutilized servers to reduce unnecessary power draw.

Implement the Right Sizing for Your Data Center’s Capacity

This is one bit that can be a little tricky. Avoid overprovisioning infrastructure, scale equipment based on actual demand. Pai Enterprise's sizing optimization feature can help data centers determine the optimal combination of energy assets to aid efficient operations.

Practice Preventive Maintenance

Do not wait until there are serious complications or total breakdowns; schedule regular servicing of cooling and electrical systems to ensure that peak efficiency is guaranteed always.

Monitor Energy Usage In Your Data Center In Real Time

Monitor energy usage in your data center in real time with intelligent energy management systems like Pai Enterprise. With Pai Enterprise, you can get granular data on energy costs, consumption, and even power output from various sources. In a few clicks,s you can access accurate DCiE metrics in real time. You can also detect anomalies instantly with Pai Enterprise, like energy cost or use anomalies, so you can access and solve problems just as they happen, instead of racking up unnecessary expenses.

With these measures, you can easily upgrade your DCiE metrics and ensure that your data center runs efficiently. DCiE solutions to consider include renewable energy integration, AI-driven cooling optimization systems, DCIM (Data Center Infrastructure Management) tools, and Energy intelligence and monitoring platforms.

Manage Data Center Infrastructure Efficiently With Pai Enterprise

Pai Enterprise is an intelligent energy management system that is designed to give operators full visibility into energy usage across their facilities.

With real-time monitoring, granular device-level insights, and automated analytics, data center operation teams can:

1. Track IT and facility power separately

2. Derive DCiE and other efficiency metrics instantly

3. Detect energy waste easily and early

4. Make data-backed decisions to optimize cooling and power systems

5. Make data-driven operational decisions

This level of visibility helps data centers move from reactive troubleshooting to proactive optimization. Ready to improve your data center infrastructure efficiency or manage it better? Contact the team at Pai Enterprise to book a free walk-through demo and a call with an energy management expert.