Everyone is aware of the increasing obligations for reporting carbon emissions. It’s a planetary movement.
98% of companies have at least begun the work of assigning ownership of carbon accounting duties and putting tracking systems in place.
By now, you may be running into issues around data quality.
You may not be referring these issues as “data quality”, but, as you’ll find in this article, this is in fact an appropriate label.
In this article, you’ll learn:
- What we mean by “data quality” when it comes to carbon accounting
- Why data quality is important to carbon reporting
- Challenges to maintaining data quality in carbon accounting
- Best practices for maintaining data quality
For a more comprehensive view of carbon accounting in manufacturing, see the Complete Guide to Sustainability and Carbon Accounting in Manufacturing.
What do we mean by Data Quality (When talking about Carbon Accounting)
When it comes to carbon accounting, there are 3 types of “data quality”:
- Coverage: Are you tracking all carbon emissions across your entire operation?
- Accuracy: Are your reported emissions an accurate reflection of your true carbon emissions?
- Consistency: When aggregating emissions from different sources, are you making sure to add apples to apples?
Why is Data Quality in Carbon Accounting Important?
Data quality in carbon accounting is vital for two main reasons: For making good decisions, and for keeping your promises regarding sustainability.
Data Quality and Decision-Making
To make good decisions, you need good information.
We all want to make data-driven decisions. But if the data you’re relying on is inaccurate, your decision-making will suffer.
All of us are working to reduce our carbon footprint. But reducing emissions requires a keen understanding of which actions will bear fruit – and how much of an impact you can expect to make.
High-quality data in your carbon accounting processes will help you identify your biggest sources of emissions – whether they be from upstream purchased goods or from your operation’s direct emissions. Data quality can help you focus on prioritising actions you can take to reduce emissions, and will help you have confidence in the decisions you make.
Data Quality in Carbon Accounting – Your Public will Hold you Accountable
According to KPMG,85% of consumers are looking to sustainability as a factor when making purchase decisions. Companies are recognising the increasing importance of sustainability. Fully half of the world’s largest companies have pledged to get to net-zero.
These pledges can drive business success. But the public – and investors – will hold you accountable.
Asda, Asos, and Boohoo all faced backlash – as well as fines – for making misleading claims about their progress towards sustainability.
You cannot hope to make progress against your sustainability targets if the data quality of your carbon accounting is poor.
What are some of the Challenges to Data Quality in Carbon Reporting?
Coverage – Multiple Sites, Multiple Activities, and Scope 3
Today’s manufacturers can be global operations – with sites sprawling across different time zones and industries.
Even smaller manufacturing operations still have dozens or hundreds of suppliers.
Whatever the size of your manufacturing operation, ensuring you are tracking and reporting all your carbon emissions sources will be a challenge.
Different Reporting Standards for Different Countries or Industries
There are at least five different reporting standards or frameworks for carbon accounting: the International Sustainability Standards Board (ISSB), the Global Reporting Initiative (GRI), the Task Force on Climate-related Financial Disclosures (TCFD), the Greenhouse Gas Protocol (GHG Protocol), and the European Sustainability Reporting Standards (ESRS).
Each of these standards offers a unique focus and methodology for collecting and reporting on carbon emissions, often complementing each other in the broader context of sustainability and financial disclosures.
The manufacturing world has yet to settle on a “gold standard” for emissions reporting, and different companies use different frameworks for reporting their carbon emissions.
In fact, Deloitte found that some companies employ more than one of these standards – utilising different standards at different sites, and even within sites.
There is nothing wrong, per se, with using different standards – as they are, in general, complementary rather than conflicting.
However – the presence of multiple reporting standards can present confusion and cognitive burden.
Different Methods for Measuring Emissions
As you roll out carbon emissions tracking throughout your manufacturing operation, you have many different methods to choose from for estimating carbon emissions. Some methods are more accurate, others are more quick-and-dirty.
The most consistently accurate method for measuring carbon emissions is direct measurement, whereby you measure the carbon or GHG emitted at source during a given process. This is typically the most expensive method, given the equipment required. The other option is emission-factor-based which is often more economically viable whilst maintaining a fair level of accuracy. The quick and dirty option would be spend based.
Whatever tracking methods you use, you’ll need to ensure that you clearly outline your methodology, assumptions and justification for your selection. And ideally you would be consistent in your application of methodology across activity types and sites.
Different Emissions Factors
Emission-factor-based accounting involves using standards and activity data for calculating emissions. You use a formula to translate energy conversion into carbon emissions.
For example – in the UK, it is estimated that 2.67kg of carbon are generated through the burning of 1 liter of diesel fuel. To estimate the emissions for transporting goods in the UK, you’d track your diesel fuel usage and then apply this factor.
However – in the US, to estimate emissions involved with transportation, you’d use an emissions factor of 22.45 pounds of CO2 for every gallon of diesel fuel.
On one hand you have a factor described in terms of kg of CO2 per liter, and on the other you have a factor in terms of pounds of CO2 per gallon. These conversion factors end up being very similar when you translate them from metric measurements to “imperial” system measurements – or vice versa. Similar – but not exact.
Translating the UK factor system for use in the US will yield incorrect results, because the factors differ slightly.
If you’re using factor-based emissions estimates, you’re going to have to maintain vigilance over the different factors used in different geographies. Manually calculating emissions using factors can be fraught with human error.
Examples of Best Practices for Data Quality in Carbon Accounting
Complying with the increasing requirements surrounding carbon reporting will be challenging.
In fact – many financial accounting companies are now offering carbon accounting services.
To meet the challenges of carbon accounting, there are best practices that you can adhere to. We discuss three of them below.
Data Quality in Carbon Accounting – Automated Data Capture
One of the best ways to reduce risk in your carbon accounting processes is to minimise your dependence on humans. An integrated automated data collection system is one way to achieve this.
One strategy for automated data capture is the use of integrated monitors. Monitors can be integrated with manufacturing machines, often in non-invasive ways. These monitors can directly capture carbon emissions in real-time, and relay data to a central software source via technologies like IoT.
Another approach to automated data capture is to leverage existing data repositories. Enterprise Resource Planning (ERP) or Supervisory Control and Data Acquisition systems (SCADA) may be used for the storage of emissions reporting. Companies that already store emissions data in ERP or SCADA systems can set up automated extraction processes to port the data into purpose-built carbon accounting solutions.
A third automated data capture solution pulls carbon emissions data from “unstructured” sources such as utility bills, emails, invoices, or spreadsheets. Technologies such as Optical Character Recognition (OCR) and AI-powered systems can pull data from these sources to be stored in purpose-built carbon reporting systems.
However you approach automated data capture, the important thing is to remove human error from the process.
Automated Reporting
Another way to reduce risk of errors and maintain data quality is through the use of automated reporting.
Robust carbon accounting software solutions can automatically account for – and translate – different factor-based emissions standards. Automating the translation of emissions factors removes human error from the process.
Similarly, carbon accounting software can be configured to provide data in compliance with different reporting standards. This means that reports are automatically generated to present emissions according to the Global Reporting Initiative (GRI), the European Sustainability Reporting Standards (ESRS), or any other standard you wish to adhere to. Once again, this reduces the risk of human error from the process.
Coverage Visibility
Manufacturers that have yet to commit to using carbon accounting software often track emissions data within spreadsheets. Using spreadsheets greatly increases the risk that you are missing data from one process or another (and thus under-reporting). Carbon reporting software can help you ensure visibility of carbon emissions throughout your operation.
Centralising your carbon tracking within carbon accounting software systems helps to ensure that you don’t have any data black holes. Carbon accounting software can help you visualise your entire operation and ensure that all divisions are tracking properly.
Contact Mavarick today to see how carbon accounting software can help you meet your reporting requirements and sustainability goals.
