Manufacturers tend to encounter ESG reporting in one of two ways: a regulatory obligation arriving with a deadline, or a large customer sending a questionnaire with a two-week turnaround. Either way, the constraint is the same — you can only report what you’ve been recording, and historical data cannot be created retrospectively.
That’s the argument for starting collection before you’re required to report. The reporting framework can be chosen later; the data has to exist first.
Environmental Data
Energy consumption by source and by site, ideally at a granularity that lets you attribute it to production rather than treating the site as one meter.
Water withdrawal and discharge where your processes use it materially.
Waste by stream and disposal route — recycled, recovered, landfilled — with quantities rather than costs.
Material purchases in physical quantities, not just spend. This is the foundation of upstream emissions calculation and the item most often missing, because procurement records are built around money rather than mass.
Freight by mode, distance, and weight for both inbound and outbound.
Refrigerant and process gas usage where applicable, which is small in volume and disproportionate in impact.
Social Data
Workforce composition and turnover. Health and safety incidents with severity classification. Training hours. Supplier assessments covering labour practices, with coverage recorded as a percentage of spend rather than a count of suppliers — assessing fifty small suppliers means less than assessing your three largest.
Governance And Supply Chain Data
Supplier locations to the site level rather than the head office, which is what actually matters for risk. Sub-tier visibility for high-risk materials. Certifications held by suppliers with expiry dates. Country of origin for materials, and any conflict-mineral or restricted-substance declarations that apply to your product categories.
Collect it Where the Transaction Happens
This is the practical point that determines whether the programme survives. Data gathered through an annual questionnaire campaign is expensive, incomplete, and stale by the time it’s assembled.
Data captured as part of routine operations — material quantities on receipt, waste on collection, supplier attributes at onboarding, freight details on shipment — costs almost nothing extra and is always current. Building capture into existing processes is a far smaller project than building a reporting function, and it produces better data.
Requirements Are in Flux
Disclosure rules differ by jurisdiction and company size, and several major frameworks have been revised or rescoped recently. Rather than designing to a specific standard, collect the underlying operational data — quantities, sources, destinations — which nearly every framework builds on. Then confirm current obligations for your markets and size before committing to a reporting format.
Customer requirements frequently arrive ahead of regulatory ones, particularly if you supply larger businesses. Being able to answer a customer questionnaire quickly is a commercial advantage well before it’s a compliance one.
ticktick.ai captures material quantities, freight detail, waste, and supplier attributes as part of routine transactions, so reporting draws on operational records rather than a data-gathering exercise.
