How to Handle Missing Sustainability Data Without Breaking Your Report

No sustainability report is based on perfectly complete data. An invoice arrives late. A site manager doesn’t submit meter readings for two months. A utility transitions to smart metering mid-year and the data format changes. A data source simply doesn’t exist for a new acquisition.

Missing data is not a crisis — it’s an expected condition of sustainability reporting. What matters is how you handle it.

The wrong approaches

Omitting the gap entirely. Reporting only the periods or sites where you have data produces an understated emissions figure. If your assurance provider identifies a gap that isn’t flagged, they’ll have concerns about the completeness of your methodology.

Filling the gap with a round number. Inserting an estimate without documenting the basis produces a number that can’t be verified or reproduced. It may happen to be close to correct, but an assurance provider can’t assess it.

Carrying forward the prior-period figure. Using last month’s number for a missing month is a common shortcut that introduces distortion, particularly when consumption varies seasonally.

The right approach: document and estimate

The standard approach in greenhouse gas accounting for handling missing data is to estimate the missing value using the best available basis, and to clearly document:

1. That the period or data point is missing
2. The estimation method used
3. The estimated value
4. The assessed materiality of the gap

This applies whether the gap is one invoice for one site, or an entire data source for the first six months of a new acquisition.

Estimation methods (in order of preference)

1. Use actual data from a comparable period

If you’re missing Q3 electricity for a site, use the Q3 figure from the prior year and adjust for known differences (a site expansion, a shutdown period). This is the most defensible basis when seasonal patterns are consistent.

2. Use average of adjacent periods

Average the periods immediately before and after the gap. For a missing October, average September and November. This works well when consumption is relatively flat.

3. Use an industry or asset-based estimate

If you have no comparable period data, use a published benchmark or asset-based estimate. For example: an office building of 5,000 sqm in Victoria, using a NABERS or industry average kWh per sqm figure. Document the benchmark source.

4. Extrapolate from sub-metering or partial data

If you have partial data (data for some weeks, or data from a sub-meter covering part of the site), extrapolate to the full period or full site. Document the extrapolation factor.

Materiality: assess and document the impact

Not all gaps are equally important. A missing invoice for a small remote office is a much smaller issue than three months of missing data for your largest manufacturing facility.

For each gap, assess:

• What is the estimated magnitude of the missing data (as a percentage of your total)?
• Is this above your materiality threshold?
• Does omitting this data change any material disclosure (e.g., crossing a threshold, affecting a trend)?

Most sustainability reporting frameworks define materiality at 5% of the relevant total. A gap that contributes less than 5% of your Scope 1 total can typically be estimated with less rigour than a larger gap.

What to disclose

In your sustainability report (or in the underlying data package provided to your assurance provider), disclose:

• The total estimated percentage of your emissions figures that is based on estimation rather than measured data
• The primary gaps and their estimated impact
• The estimation method used for material gaps

You do not need to disclose every minor gap in the public report. But the methodology notes in your internal documentation should capture each one.

Practical systems for tracking gaps

Build a data register that lists every expected data source for every site and period. Mark each as:

• Received — actual data obtained
• Estimated — gap filled with an estimate (with method noted)
• Missing / under investigation — not yet resolved

This register is your control mechanism. Running it against your submitted data tells you immediately where gaps remain and what proportion of your figures are estimated.

The register also serves as a checklist for the sustainability lead before sign-off: “Have we accounted for every expected source?”

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Ayika maintains a data register by site and period, flagging missing or estimated values and tracking their status through to the final report. See how data quality management works in the platform.