How to Build a Sustainability Data Collection Process Before Reporting Season

The difference between a sustainability team that breezes through assurance and one that spends six weeks scrambling before the report is due usually comes down to one thing: whether they built their data collection process before reporting season, or tried to collect data after the period had closed.

Here’s how to build a process that runs reliably throughout the year, so reporting season is a collation exercise rather than a data hunt.

Step 1: Map every expected data source

Start by listing every data source that will contribute to your Scope 1 and Scope 2 figures:

• Which sites are in scope?
• What energy and fuel types does each site use?
• Who provides each utility (retailer, network operator, bulk supplier)?
• What format does the data arrive in (invoice PDF, CSV export, API, manual read)?

This map is your data register. It defines what you expect to receive and from whom. Every row in the register should have an expected frequency (monthly invoice, quarterly tank dip, annual meter read) and a responsible person.

Step 2: Establish the collection workflow for each source type

For utility invoices (electricity, gas, water):

• Set up a forwarding process so invoices reach the sustainability team — not just accounts payable — at the time of receipt
• Assign someone to process each invoice into the data register within a defined timeframe (e.g., within 5 business days of receipt)
• Flag invoices with estimated reads for follow-up when the actual read arrives

For fuel records:

• Arrange for monthly fuel card statements to be forwarded to the sustainability team
• Set up a process for bulk delivery dockets to be collected and filed at each site
• Require monthly tank stock counts (opening and closing dips) at sites with bulk storage

For meter readings:

• Assign site managers a monthly task to photograph and submit meter readings
• Provide a standardised form (even a simple one) with fields for site code, meter ID, reading, date, and units
• Set up a reminder or workflow to chase missing submissions by a fixed date each month

Step 3: Build the quality check into the monthly cycle

Don’t wait until reporting season to check for data quality issues. Build a monthly review into the process:

• Completeness check: Are all expected sources represented for the month? Which are missing?
• Anomaly check: Are any consumption figures implausibly high or low compared to the prior month or prior year same month?
• Estimate flag: Are any invoices for estimated reads? If so, is the actual read expected next month?

A one-hour monthly data review catches most issues when they’re easy to fix. The same issue found six months later during assurance preparation is far more difficult to resolve.

Step 4: Maintain the source document library

Every data point should be traceable to a source document. Maintain a structured folder or document library organised by:

• Site
• Data type (electricity, gas, fuel, water)
• Period

Naming convention matters: SiteA_Electricity_2025-06.pdf is retrievable in 12 months. Invoice.pdf (1).pdf is not.

Step 5: Define sign-off responsibilities

Before any data enters an emissions calculation, it should be reviewed by someone who can identify errors — not just the person who collected it.

Define:

• Who reviews each data type before it goes into calculations?
• What does the review cover (completeness, anomaly check, format consistency)?
• How is the review recorded?

Even a simple sign-off log — date, reviewer name, period covered, any issues found — is evidence of a quality-controlled process when the assurance provider asks.

Step 6: Lock in your factor references at the start of the year

At the start of each reporting year, confirm:

• Which version of the NGA Factors applies to this period
• The specific factors you’ll use for each emission category (electricity by state, fuel by type and combustion category)
• Whether any sites have GreenPower or PPA instruments that affect market-based Scope 2

Record these in a factors reference document that all calculations in the period will use. This prevents mid-year divergence where different team members apply different factor versions.

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Ayika is designed to run this process continuously throughout the year — not just at reporting season. Book a demo to see how ongoing data collection works.