Data Centers

Tech emissions are growing at an estimated 6% year on year, and globally, data centers now consume around 3% of the world’s electricity and produce about 2% of total GHG emissions. 


In recent years, there have been substantial efficiency improvements in data centers, especially with regard to the building. Yet, at the same time, the industry faces ever-increasing demand for the computing power it provides – making the journey to net zero significantly challenging.


  • As data volumes continue to grow 30% per year, the Paris Agreement targets for the data centre industry still require significant emissions reductions of about 53% by 2030.
  • Despite substantial investments in renewable energy, the variability of wind and solar sources may not match a data centre’s demand profile, and renewable energy power purchase agreements might even be for a different grid or region.
  • The cost of carbon offsetting is rising, and whilst renewables have their place, consumption reduction and optimisation should be the priority.
  • PUE is not enough, and the new ISO30134 metrics are a welcome addition.
  • CSRD reporting will soon be required for companies of a certain profile.

The complexity of digital has presented challenges to carbon accounting, but the availability of data also offers opportunities that are not available to more traditional industries.


QiO’s Foresight Optima is uniquely placed to help data center operators on their sustainability journey with continuous efficiency improvements in energy and water consumption at multiple levels. Particular focus must be directed towards the IT stack over the coming years.

CSRD / EU Taxonomy reporting dashboard, tracking data continuously.

Monitor patterns in server power usage to automatically adjust power consumption to better match workloads while maintaining quality of service.

Extra insight into the IT estate enables reduction of the IT load energy consumption by up to 52%. 


Foresight Optima provides a suite of ready-to-deploy features with integrated algorithms that integrate with existing data centre infrastructure management (DCIM) systems to recommend and implement optimal control settings on HVAC and cooling systems as well as the CPU processors themselves, helping reduce energy and carbon emissions.

Autonomous Control

Automatically adjust performance and sleep states to match time-of-day workloads while maintaining Quality of Service. Run systems on open or closed-loop, either manually implementing suggested state changes or allowing automatic implementation. 

Energy Mix Optimisation

Use location-specific weather forecast data to accurately predict energy generation from on-site solar or wind distributed energy sources, reducing fuel consumption and grid demand during peak tariff times, resulting in reduced emissions and lower running costs.

Energy Efficiency Index

Reduce energy and water consumption and costs in real-time without spending hours analysing time-series usage and workload data. The EEI algorithm recommends fan speed, temperature and even processor power state settings based on real-time server workload, resulting in quantified cost savings and reduced carbon emissions. 

Case Study

A large data centre operator company used Foresight Optima DC+ to reduce server power consumption during idle time while maintaining service quality (QoS).

The Foresight Efficiency Index used granular telemetry data to identify opportunities for power savings and suggested actions to be taken on the platform to realise estimated power savings. The system ran in closed-loop, automatically implementing the AI-suggested actions and placing specific processors in the recommended power-saving state. This resulted in reduced CPU power consumption while maintaining application QoS results, leading to a reduced carbon footprint.


Large data centre operator

QiO is an Endorser of the EU Code of Conduct for Energy Efficient Data Centers.​