When I interviewed over 200 sustainability teams on their day-to-day challenges, I discovered that many teams were blocked from taking actual climate action due to unreliable data. In hindsight, this should come as no surprise. While sales teams have a plethora of dashboards and facility managers have a wealth of EHS management tools, corporate sustainability largely lacks rigorous tools to provide data and reports that executives are willing to put their money on.
In this article, we discuss the pillars of carbon accounting, why accuracy matters, and how utility data collection plays a pivotal role. Carbon accounting, the process of calculating and reporting greenhouse gas (GHG) emissions, relies on three critical steps: data collection, emissions calculation, and data reporting. Each step builds upon the previous one, making the accuracy of the initial data collection paramount.
The Pillars of Carbon Accounting
Step 1: Data Collection
Carbon accounting relies on the accurate collection of utility data. This includes gathering information on energy consumption, water usage, and waste generation from various sources within an organization, such as office buildings and manufacturing facilities. Traditionally, this data collection process consisted of manual data entry, which is fraught with the potential for human error. The advent of automation software has now revolutionized this step, enabling the seamless and consistent capture of utility data. Automation ensures that data is not only collected accurately but also directly integrated into environmental management systems without the need for manual intervention.
Note that data collection focuses on utility usage data, often called activity data. Older utility and energy management systems tend to focus on utility cost and billing data, which have struggled to support sustainability functions in collecting usage data from utility bills.
Step 2: Emissions Calculation
Once data is collected, the next step involves calculating the emissions associated with the reported utility usage. Utility data forms the backbone of scope 1 and 2 carbon emissions reporting. Scope 1 emissions consist of direct emissions primarily coming from natural gas utility usage and scope 2 emissions consist of indirect emissions primarily coming from electricity utility usage.
This calculation involves converting raw utility data into measurable GHG emissions using established conversion factors and methodologies. Any inaccuracies in the initial data collection phase can lead to substantial errors in emissions calculations, potentially skewing a company’s carbon footprint and undermining the integrity of their environmental commitments.
Step 3: Data Reporting
The final step in carbon accounting is data reporting. This involves compiling the calculated emissions data into comprehensive reports, such as those required by the CDP, to communicate a company’s environmental impact to stakeholders, regulatory bodies, and the public. Precise data is critical in this stage, as inaccuracies can lead to misinformation, a damaged reputation, and potential legal repercussions with financial regulators.
The Compounding Effect of Data Errors
An initial error in data collection, even as small as 10%, can compound through the emissions calculation and data reporting stages, resulting in significantly distorted reports. Acting on unreliable data can further lead to wasted resources invested in projects that have only marginal benefits for ESG improvement. Communicating shaky metrics to the executive team breeds distrust in the sustainability team over time. These compounded errors can misguide a company’s environmental strategies, leading to ineffective or misaligned sustainability efforts. And in the long run, they can lead to a completely dysfunctional sustainability program.
Mitigating Errors Through Utility Data Automation
To mitigate the risk of errors, businesses are increasingly turning to utility data automation. Automation software offers a robust solution by streamlining the data collection process, reducing the likelihood of human error, and ensuring consistent and accurate data input. This not only enhances the reliability of emissions calculations but also improves the credibility of the final reports.
We've researched all the possible ways of automating data collection for carbon accounting. Everything from starting an offshore team to parsing utility bills to buying software to training the entire EHS team. To read more about the alternatives, check out this article.
Conclusion
Accurate utility data collection is the cornerstone of effective carbon accounting. Today, more and more businesses are choosing to use Nectar to automatically collect, analyze, and manage their utility data.
Nectar can automatically connect to any utility account worldwide and bring the data into one centralized dashboard so that sustainability and ESG teams can accurately understand their impact. This automated service guarantees data precision, enabling more reliable emissions calculations and comprehensive environmental reports. This, in turn, empowers sustainability and ESG teams to make informed and data-driven decisions that drive sustainability efforts forward. [link]