Energy Intelligence — Data-Driven Decision Making | EC.DATA

Energy Intelligence — Data-Driven Decisions

Using energy data for intelligent facility management: KPI dashboards, benchmarking, and reporting.

Energy Intelligence Framework

• KPI dashboards — kWh/m², kWh/degree-day, kWh/unit of production, cost per occupant
• Benchmarking — compare buildings against portfolio averages and industry standards (ENERGY STAR, CIBSE TM46)
• Regression analysis — correlate energy consumption with weather, production, and occupancy
• CUSUM charts — cumulative sum analysis to detect sustained changes in consumption patterns
• Automated reporting — scheduled daily, weekly, and monthly energy reports

Energy Intelligence in practice

Energy intelligence is the layer above metering: weather-normalised baselines, anomaly detection, IPMVP-grade savings reports. EC.GAIA combines tariff data, weather feeds, and EMS telemetry into one analytical surface.

How EC.DATA operationalises Energy Intelligence

Energy Intelligence is a primary surface in EC.EMS — the dashboards, alerts, and reports treat it as a first-class signal. Baselines are weather-normalised in the background and savings are recomputed on every tariff change in EC.Bills, so when a customer asks "how are we tracking?" the answer is one click away.

The EC.GAIA capstone (EC.GAIA) ranks every Energy Intelligence-related opportunity across the customer's portfolio so partners can sequence the highest-impact retrofits first instead of working alphabetically through the building list.

Common pitfalls when working with Energy Intelligence

Energy management programmes stall when Energy Intelligence is treated as a one-time configuration instead of a continuous discipline.

• Setpoints drift back to defaults after BMS updates — EC.EMS audits the live setpoint against the design weekly.
• Baselines that are not weather-normalised report false savings or false losses on the first hot/cold week.
• Alert fatigue caused by under-tuned thresholds trains operators to ignore EC.Alerts; tighten thresholds gradually based on response data.

Where Energy Intelligence connects across EC.DATA

Energy Intelligence touches every layer of the EC.DATA stack: telemetry capture in EC.Node; visualisation and alerting in EC.EMS with EC.Alerts; tariff translation in EC.Bills; savings verification in EC.GAIA; and field-device fleet governance in EC.IoT. Solution work originates in EC.Solution Design Studio; partner and customer training live in EC.Academy.

Frequently asked questions about Energy Intelligence

How does EC.DATA expose Energy Intelligence to partners?

Energy Intelligence is surfaced through EC.Node telemetry capture, normalised into the EC.DATA tag schema, then made available across EC.EMS dashboards, EC.Alerts notifications, EC.Bills tariff models, and EC.GAIA savings reports — one source of truth across every module.

Do I need a separate license to access Energy Intelligence?

No. Energy Intelligence is part of the core EC.DATA platform; partners get it as part of their standard licence and white-label it under their own brand for their customers.

Where do I learn more about Energy Intelligence on EC.DATA?

Start with the EC.Academy track this page belongs to, then explore the related EC.DATA platform modules linked above. The EC.DATA changelog announces new capabilities and the EC.Academy session catalogue tracks every recorded session.

How EC.DATA applies this in production

The concepts in this lesson are not theoretical — they are operationalised every day inside the EC.DATA platform across deployments in 10+ countries on 3 continents. The module most directly tied to this track is EC.EMS, working alongside EC.GAIA and EC.Alerts to translate the underlying physics, protocols, and methodology into a working production system.

Every reading in EC.DATA flows through the same lifecycle: telemetry is captured at the meter or sensor, normalised by the EC.Node edge gateway (which speaks Modbus RTU/TCP, BACnet, OPC-UA, MQTT and pulse counting natively), buffered locally for offline resilience, then delivered to the cloud where EC.EMS stores it as 1-minute resolution time-series. From there, EC.Bills reconciles metered kWh against the utility invoice, EC.Billing allocates consumption to tenants or cost centres, EC.Alerts watches for anomalies, EC.PQ scrutinises waveform quality, and EC.GAIA applies machine learning for forecasting and root-cause analysis.

That integration is what differentiates EC.DATA from the patchwork of disconnected tools most facilities run today. Because every module shares the same data warehouse and the same role-based permission layer, a finding in one module is immediately actionable in another — a tariff change in EC.Bills can adjust demand-alert thresholds in EC.Alerts, a setpoint override in EC.BMS is automatically measured for energy impact in EC.EMS, and an IPMVP baseline is established once and reused across reports forever.

The team behind EC.DATA — described in more depth on the Who We Are page — combines former Fortune 500 energy consultants, field commissioning engineers, and software developers, with a deliberate hiring policy that requires every senior product role to have prior experience on the customer side of an energy programme. The platform is what we wish had existed when we ran those programmes ourselves; the academy is the public-domain version of the training material we built internally to bring new hires up to speed.

If you want to see the platform in action, the free assessment, the savings calculator, and the Solution Design Studio are open without an account; the partner programme is the route in for ESCOs, facility-management firms, commissioning agents, and utilities that want to deliver EC.DATA under their own brand.