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Book Demo
Energy Transparency
Compare Energy Performance Across Sites and Assets
Standardize energy-performance indicators, compare like with like, and track when a site or asset moves away from its expected range. etaONE® connects every KPI to its boundary, calculation logic, operating context, and source data so technical and management teams can work from the same evidence.
Compare consistently: Use shared KPI definitions across sites and asset groups.
Account for operating conditions: Include relevant production, weather, load, utilization, or operating modes.
Investigate performance gaps: Move from portfolio-level comparisons to the underlying system and source signals.
For energy managers, utility teams, facility engineers, and portfolio leaders who need reliable and explainable energy-performance comparisons.
Trusted by leading data centers, manufacturers, and energy innovators.
Inconsistent Comparisons
Comparable results require comparable definitions
Many organizations already calculate energy-performance indicators. The challenge is that sites and teams often use different system boundaries, formulas, time periods, units, and normalization methods. This creates rankings and reports that look precise but do not always support a fair technical comparison.
Without a consistent methodology, benchmarking can direct attention toward the wrong site or asset. Genuine performance gaps remain hidden, while normal operational differences may be treated as inefficiencies.
KPI names are shared, but calculation rules differ by site.
Baselines remain in use after major operating changes without review.
Assets are placed in the same peer group even when their technical conditions differ.
Monthly averages hide gradual performance deterioration.
Analysts spend more time reconciling definitions than investigating causes.
Comparable Performance
Build benchmarks your teams can explain
etaONE® supports the definition, calculation, comparison, and review of energy-performance indicators. The customer retains responsibility for approving system boundaries, relevant variables, peer groups, baselines, and decision rules.
Standardize KPI definitions
Define common formulas, units, aggregation periods, system boundaries, and data-quality rules.
Teams can confirm that an indicator such as kWh per unit, kWh per runtime hour, or cooling efficiency is calculated consistently across the comparison.
Establish baselines
Compare current energy performance with a defined reference period, target, or expected performance range.
This gives teams a documented point of comparison instead of relying on informal assumptions.
Normalize relevant operating conditions
Include variables such as production volume, ambient temperature, system load, utilization, runtime, or operating mode where they materially affect consumption.
This helps distinguish justified variation from genuine underperformance.
Create meaningful peer groups
Group comparable sites, systems, or asset types using defined inclusion criteria.
Comparable entities can be ranked together,while fundamentally different systems remain separate.
Track performance drift
Monitor whether an asset or site moves awayfrom its baseline, peer range, or expected operating band.
Persistent deviations become easier to identify before they are hidden inside quarterly or annual averages.
Drill down into the cause
Link KPI changes to the contributing timeseries, operating states, and asset context.
Technical teams can investigate why performance changed without rebuilding the calculation manually.
Simple Process
How it works
etalytics follows a structured three-step deployment model.
Platform integration
We connect to existing infrastructure such as SCADA, BMS, PLCs, historians, submeters, utility interfaces, weather data, and relevant tariff or market signals. The standard approach is to use existing data, sensors, meters, and control infrastructure first instead of adding new hardware.
Digital twin setup
We structure data by system, asset, and energy flow, then model the relevant physical and operational relationships. This creates transparency, identifies inefficiencies, validates optimization potential, and can provide virtual measurements such as estimated volume flows when direct measurements are not available.
AI control deployment
Based on the validated system understanding, etalytics deploy optimization logic in open-loop recommendation mode or closed-loop adaptive control. Control actions operate within defined boundaries and include transparency, manual override options, and fallback strategies for mission-critical operations.
Operational Impact
Turn energy KPIs into better operational decisions
Compare like with like
Use consistent boundaries, formulas, units, and peer-group criteria to create fair comparisons across sites, systems, and assets.
Detect performance drift earlier
Identify when efficiency gradually moves away from an approved baseline, target, or expected operating range.
Focus on the largest gaps
Prioritize persistent and operationally relevant performance differences instead of treating every short-term fluctuation as a problem.
Explain why performance differs
Move from a portfolio ranking or KPI deviation to the asset data, operating conditions, and source signals behind it.
Create consistent portfolio reviews
Give site and corporate teams a shared set of indicators for recurring energy-performance discussions.
Support continuous improvement
Use traceable benchmarks to select improvement measures, review their effect, and identify where further technical analysis is needed.
Data centers
Optimize cooling plants, free cooling, hydraulic distribution, airflow-related dependencies, and supply temperatures while protecting mission-critical uptime and stability.
Pharmaceuticals and clean environments
Improve HVAC and utility efficiency while maintaining stable environmental conditions, compliance requirements, and operational boundaries.
Manufacturing and automotive
Reduce energy waste in process cooling, ventilation, heating, and site-level energy systems with variable production schedules and operating modes.
Chemicals and industrial production
Coordinate cooling, heating, ventilation, thermal utilities, and electrical infrastructure under fluctuating production loads and changing energy prices.
Large commercial and high-load buildings
Improve performance in complex HVAC environments where demand, occupancy, weather, and operating schedules change continuously.
Proven impact
Trusted by leading operators worldwide
Equinix, Merck, and others achieve up to 50% cooling energy savings with etalytics. Explore our case studies.
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Start Here
Find out whether your sites and assets are truly comparable
A reliable benchmark starts with the right system boundaries, KPI definitions, data, and operating context. Begin with a Benchmarking Assessment to identify which comparisons are valid and where the first performance gaps can be investigated.
Trusted by operators across data centers and industry
Start with a free feasibility study
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