Stop Hand-Keying — Let ERP and IoT Meters Feed Your Carbon Data Automatically
Hand-keyed data is always late, wrong and expensive — automation in carbon work is not a luxury but the only approach that scales past a few dozen sites.
The number-one pain in carbon accounting is data collection — chasing utility bills from every branch, keying receipts one by one, then reconciling everything at year-end. It is slow and error-prone.
Two automated paths
ERP push — your ERP or procurement system posts activity data straight into the carbon platform via API, supporting batches of hundreds of records with idempotency so retries never create duplicates.
IoT meters — electricity meters or gateways stream readings into the system, which rolls them up hourly or daily and computes Scope 2 near-real-time. You see energy trends without waiting for month-end.
The principle that matters more than the tech
Automated and manually entered data must flow through exactly the same calculation logic; otherwise the two channels drift apart and cannot be explained to a verifier. The pipeline should also be vendor-neutral — never locked to one hardware brand.
In GCarbon
The Ingest API lets ERPs POST activities directly (batches up to 500 records), and a meter-readings endpoint rolls IoT data up into Scope 2 automatically. Every channel shares the same calculation library as the manual entry screens — figures can never diverge by input path.
“Have as many data channels as you like — but only ever one calculation logic”
Where to start automating
The highest-payoff order in practice: begin with electricity meters at your most energy-intensive sites, since Scope 2 is usually the largest category and meters offer hourly granularity. Next, fuel procurement data from the ERP, covering most of Scope 1. These two typically cover over 80% of total emissions — then extend to HR systems (travel) and logistics.
Questions to ask before integrating
Does the receiving API support batching and idempotency (retries never duplicate)? Does automated data pass the same validation as manual entry? If a mapping is wrong, can it be corrected retroactively without losing the audit trail? And when either side goes down, where does data queue? These four answers separate production-grade systems from pretty demos.
GCarbon Team
Carbon accounting specialists
