The data that powers EnerG
EnerG runs on two data streams. Monthly utility bills drive portfolio rankings, dashboards, targets, and budgets. High-frequency interval reads support granular charts, forecasting, and meter-level modeling. A data source is any path that brings that data in, such as , CSV uploads, manual entry, or a KODE OS interval feed. A meter is the device or account boundary each stream reports against. For the full picture of streams, meters, service types, and how EnerG calendarizes bills, see Data sources and meters. Interval reads from KODE OS are cleaned through interval data normalization before charts and models use them.Trusting the numbers
is the trust signal behind every metric. Gaps and overlaps lower the score, and buildings below your threshold drop out of rankings until coverage recovers. See Data completeness for how the score works and what moves it.Comparing buildings fairly
Benchmarking normalizes usage by area so buildings of different sizes compare fairly. Energy Use Intensity (), Water Use Intensity (), and carbon intensity are the core metrics. See Benchmarking and intensity metrics for how rankings and percentiles work.Measuring change over time
A baseline is a historical reference window you measure future usage against. Weather normalization adjusts that comparison for hot and cold years using degree days, so you can separate real savings from weather swings. See Baselines and weather normalization.Verifying and forecasting savings
follows practice to confirm savings are real. Models regress energy against weather and other drivers, then project usage forward. See Energy modeling and M&V.Planning spend and reducing carbon
Energy budgets track plan against actual spend, and accruals estimate usage for months that lack final bills. Capital planning models the measures and scenarios that reshape future budgets. See Budgets and capital planning and Emissions accounting for the carbon side.Explore the concepts
Data sources and meters
Utility bills, interval reads, meters, service types, and calendarization.
Interval normalization
How irregular interval reads become clean 15-minute values.
Data completeness
How EnerG scores billed coverage and why it gates benchmarking.
Benchmarking
EUI, WUI, and GHG intensity, plus how rankings and percentiles work.
Baselines and weather
Reference windows, degree days, and weather-normalized comparisons.
Energy modeling
IPMVP options, adjusted baselines, model fit, and forecasting.
Budgets and capital
Predicted versus actual, accruals, measures, curves, and scenarios.