Find energy-consumption and utility-bill anomalies across sites
Compare made consistent consumption and tariff effects while retaining weather, occupancy, operating hours, meter changes, and billing adjustments. Start with the what one row represents and definitions, calculate only from eligible records, and check the result against the source before using it.
Clues in the source data
- The source files do not share one documented what one row represents or cutoff.
- The decision owner cannot trace the headline result to eligible source records.
- A cost spike can occur without a usage spike because of tariff, demand, tax, or correction changes; separate price and consumption effects.
Why this gets messy
Interval meter exports, bills, tariffs, weather, and occupancy use different time zones and periods. Estimated readings and billing corrections can resemble real consumption spikes.
From the field · Facilities analyst
Compare made consistent consumption and tariff effects while retaining weather, occupancy, operating hours, meter changes, and billing adjustments.
Interval meter exports, bills, tariffs, weather, and occupancy use different time zones and periods. Estimated readings and billing corrections can resemble real consumption spikes.
Columns used in the example
site_id · meter_id · interval_start · consumption_kwh · reading_type · bill_start · bill_end · tariff · cost · degree_days · occupied_hours
Follow it with your own file
- Align meter intervals, time zones, billing periods, and site-meter relationships.
- Separate actual, estimated, corrected, and missing readings before aggregation.
- Calculate consumption and cost per area, occupied hour, and weather context where appropriate.
- Investigate anomaly candidates against tariffs, equipment schedules, closures, and meter events.
Check: Interval consumption must reconcile to bill periods within known adjustments, units must be consistent, and missing intervals must remain visible.
Separate a useful answer from a fragile total
| Approach | What it answers | What remains at risk |
|---|---|---|
| Quick spreadsheet total | A narrow descriptive question | Definitions, duplicate rows, timing, and exceptions may be hidden |
| Reviewed analysis | The stated decision with reconciled evidence | Human judgment is still required for policy and action |
| Ongoing monitored workflow | The same decision across new periods | unexpected column changes and changed business rules still need review |
A method you can follow
- Define the decision: Align meter intervals, time zones, billing periods, and site-meter relationships.
- Prepare the evidence: Separate actual, estimated, corrected, and missing readings before aggregation.
- Calculate the result: Calculate consumption and cost per area, occupied hour, and weather context where appropriate.
- Review the exceptions: Investigate anomaly candidates against tariffs, equipment schedules, closures, and meter events.
The question behind the rows
Compare made consistent consumption and tariff effects while retaining weather, occupancy, operating hours, meter changes, and billing adjustments.
A boundary case worth isolating
A cost spike can occur without a usage spike because of tariff, demand, tax, or correction changes; separate price and consumption effects.
The short version
- Compare made consistent consumption and tariff effects while retaining weather, occupancy, operating hours, meter changes, and billing adjustments.
- Interval consumption must reconcile to bill periods within known adjustments, units must be consistent, and missing intervals must remain visible.
- A cost spike can occur without a usage spike because of tariff, demand, tax, or correction changes; separate price and consumption effects.
Doing these steps in Prepyr
Prepyr accepts CSV files only. Export the worksheet or table you need as a UTF-8 CSV first; workbook formulas, formatting, macros, charts, and other sheets will not be included. Describe the result you need: Analyze energy consumption and utility bill anomalies across sites. Check the columns selected, preview any proposed changes, and compare the output with the source before applying or exporting it.
Prepyr steps used here: Data Profiling · ML Anomaly Detection · Interactive Charts · What-if
Final checks before using the result
- what one row represents and eligible population documented
- Dates, units, currencies, and identifiers validated
- Interval consumption must reconcile to bill periods within known adjustments, units must be consistent, and missing intervals must remain visible.
- Exceptions retained for human review
- Published result links back to its evidence
A decision-ready result for “Analyze energy consumption and utility bill anomalies across sites,” with its assumptions, exceptions, and source totals still visible.
Questions readers usually ask next
Can this facilities analyst analysis be done in Excel?
Yes for a small, stable file. Keep the source unchanged, document formulas and exclusions, and check outputs against the source.
What should not be automated?
Do not automate the final policy or business judgment. A cost spike can occur without a usage spike because of tariff, demand, tax, or correction changes; separate price and consumption effects.