What does a high-quality carbon footprint look like?

Does your carbon inventory cover all your business activities? Does the granularity of your carbon data match the granularity of your operations? Do you have a process in place to monitor the quality of your carbon data inputs?

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To create a high-quality carbon footprint - one that goes much deeper than your headline CO₂e figure - you need a carbon footprinting process that is specific to your organisation’s nuances, and only uses high-quality carbon data. 

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Here are the four core components of a high-quality carbon footprint: 

Comprehensive carbon inventory

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According to The Greenhouse Gas Protocol, “all relevant emissions sources within the chosen inventory boundary need to be accounted for'' to compile a ‘complete’ carbon inventory. If your sustainability data doesn’t cover as many activities and entities as possible within your business then you can’t effectively manage your greenhouse gas (GHG) risk. 

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But to satisfy Scopes 1-3, you need complete accounting of your GHG emissions both internally and externally. No matter if you pursue an ‘equity share approach’ or ‘control approach’, you need to get carbon data from your suppliers, partners and customers to ensure you have a comprehensive understanding of your carbon inventory - even if this data is not 100% accurate. For example, the Body Shop struggled to disaggregate energy consumption data for stores located within shopping centres, but by estimating individual stores’ emissions based on square footage and usage hours, they were able to include these facilities in their overall carbon emissions picture (The Greenhouse Gas Protocol, Page 9). Although this example is from 2004, 20 years later this exact dynamic still persists. 

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Granular carbon data

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Most carbon footprints - no matter if they cover CO₂e for the six Kyoto-outlined greenhouse gases or the 15 Scope 3 levels - are too high-level to be useful. For a high-quality carbon footprint, you need highly granular data that captures the structure, complexity and nuances of your organisation. 

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To accurately reflect your organisation’s operations, collect emissions data from individual facilities, trucks and journeys - not just your country HQ. This level of specificity develops a rich set of metadata across your organisation - i.e. for different business units, geographies, cost centres or product lines. That way, your carbon footprint better captures your specific business activities. By ‘atomising’ your carbon data, you can also see what's really driving an increase in your carbon footprint, make specific interventions to limit emissions, and easily build data sets to prove specific compliance standards. 

Frequent and timely data collection

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Annual data collection does not deliver a high-quality carbon footprint. Without insights into how your sites and activities vary month by month, even week by week, you can’t truly understand what is causing carbon emissions or how to reduce them. You also need a short turnaround time for data collection to ensure your data is recent (capturing monthly data is futile if you have to wait six months to get it). 

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For example – one of our customers was having monthly meetings to review their metrics, but realised that they were relying on data that was quarterly. Meeting around data that was sometimes 3 months out of date meant they were unable to set appropriate targets based on those metrics and it led to inefficiency and frustration internally, leading them to seek help via external software. If you are going to review metrics, the metrics need to be refreshed on a cadence that matches. 

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To produce a high-quality carbon footprint, you want at least monthly footprinting where there's a week (or even zero) lag time. This timely data enables you to more effectively manage behaviours, incentives and operational KPIs - just as frequent and timely revenue data enables you to make good management decisions and improve your cash flow. If you want to create a high-quality carbon footprint and take meaningful mitigation actions, treat your emissions data on an equal footing with financial data. 

Optimised and verified data inputs 

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There’s a known quality hierarchy with carbon data inputs: with direct activity data at the top, followed by spend data (i.e. working out electricity consumption based on bills) then non-specific data, such as benchmarks and industry averages. The key to creating a high-quality carbon footprint is not only using as much primary data as possible, but having a streamlined process in place to monitor, verify and approve these data inputs. 

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The data flow in your organisation directly impacts the quality of your carbon footprint. As some data inputs are more reliable (i.e. from a smart meter) than others (i.e. typing up figures in PDFs), input data must always be sense-checked for irregularities or errors to ensure it aligns with expectations for that activity at that location at that time. This data must then be approved by an internal sustainability manager, in the same way that a finance manager would review employee expenses. The best carbon footprinting softwares use automated systems to reduce human error where possible and have an end-to-end audit log that shows where the data came from, who inputted the data and when the data was reviewed and by whom. This not only embeds trust in the numbers you produce, but ensures your headline carbon footprint figure hasn’t been skewed by a mistyped zero.

High-quality data improves decarbonisation efforts

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Ultimately, the equation is simple: high-quality carbon data = high-quality carbon footprint = high-quality carbon mitigation. 

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With today’s range of carbon accounting applications and emissions calculators, it’s increasingly easy to create a basic one-off carbon footprint for your business. But carbon footprints are of little value unless they’re derived from high-quality carbon data and are in a structure that is replicable over time. 

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To truly understand your actual carbon footprint and produce an impactful decarbonisation roadmap, look for carbon accounting software that incorporates these core elements and delivers high-quality carbon data. 

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