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For general data quality help, see Data Quality FAQ.
Nectar continuously watches your utility data for unusual patterns. When something looks off — a jump in usage, an unexpected cost increase, a late fee, or billing after a site is archived — it surfaces as an anomaly for your team to review, right alongside your other data quality items.
Anomaly detection is off by default. Turn it on in Settings > Company > Data Quality > Anomaly detection. Once enabled, Nectar checks your data automatically every day, and you can run a check on demand at any time.

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What Nectar looks for

Each anomaly points you to the relevant site or account and time period, plus a commodity when applicable.

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How detection works

For usage, cost, and unit-price anomalies, Nectar compares each site against its own recent history and accounts for weather. This helps prevent normal seasonal swings from being flagged.
Weather-aware detection uses historical temperature data from Open-Meteo, licensed under CC BY 4.0. Nectar processes this data into heating and cooling degree days for each site and period.
Interest charges and bills received after a site is archived use direct billing checks rather than weather comparisons. History requirements apply to the weather-aware types. New sites, or sites with sparse data, are left alone for those types until there’s enough to compare against.

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Sensitivity

Weather-aware anomaly types have a sensitivity setting: Higher sensitivity catches more, but may include some patterns that turn out to be normal. Lower sensitivity is quieter but may miss smaller changes. Other anomaly types use settings suited to their check, such as a minimum charge amount or an archive grace period.

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Where to find anomalies

Anomalies appear in your Data Quality inbox alongside other data quality items — there’s no separate page to check. From the inbox you can:
  1. Filter to anomalies (and by type, site, or commodity) to focus your review.
  2. Open an anomaly to review its evidence. Depending on the type, this may be a trend chart, bill-cost view, or table of flagged bills.
  3. Resolve it once you’ve addressed it, or dismiss it if it isn’t a real problem.
Resolved and dismissed anomalies are kept for your records and won’t be flagged again on future checks. The Data Quality overview also rolls up your open anomalies by type and shows their estimated total dollar impact, so you can see where the biggest opportunities are at a glance.

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Getting value out of anomalies

  • Catch overspend early. Cost and unit-price anomalies highlight bills that cost more than expected — often a rate change, a billing error, or a usage problem worth chasing.
  • Stop paying avoidable fees. Interest-charge anomalies surface late fees so you can fix the underlying payment or billing issue.
  • Spot operational issues. Usage anomalies (including unexpected drops) can reveal equipment left running, meters that stopped reporting, or changes in how a building is used.

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Improving accuracy

If an anomaly’s chart shows gaps or unexpectedly low months, the underlying data may be incomplete — and incomplete history can make a normal period look unusual. Records with open data quality issues (such as unmatched accounts) are left out of the analysis. If a site has many unresolved issues, resolve them in your Data Quality inbox — the next check will use the corrected data and produce more accurate results.
See also: Glossary — Anomaly