Tackling Data Collection Challenges in Carbon Footprint Calculation
As sustainability reporting becomes a business imperative, accurate carbon footprint calculation is at the heart of credible climate action. However, the challenge often lies in gathering the right data. Here’s a look at the most common data collection challenges and practical ways to overcome them.
Why Data Collection Is So Challenging
- Data Is Scattered Across Systems
Information needed for carbon footprint calculation—such as energy bills, travel expenses, procurement records, and waste data—often resides in multiple systems and formats (Excel, PDFs, paper invoices, surveys, etc.). This fragmentation makes it time-consuming to gather and consolidate the necessary data. - Incomplete or Missing Data
Suppliers may not provide the required emissions data, or the organization may not have collected it at the right level of detail. This is especially true for Scope 3 emissions, which cover the entire value chain and are often the largest and most complex category. - Manual Workload
Data collection frequently involves manual work across several departments. This not only increases the risk of errors but also consumes significant resources. - Data Quality and Consistency
Even when data is available, it may be inconsistent, outdated, or in the wrong format. Ensuring data quality is essential for reliable calculations.
Practical Solutions for Better Data Collection
To overcome these challenges, organizations should start by developing clear internal processes. It is recommended to begin gathering data even before the actual calculation process starts. Organizations are encouraged to create processes and systems that allow suppliers to provide necessary information, such as material recycling rates, and to make use of existing databases and industry-specific registers.
Automation and digital tools are also key. Integrating systems—such as ERP, procurement, and travel management—enables automatic data transfer and reduces manual work. APIs can be used to pull data directly from energy providers or logistics partners, while automated validation routines can flag anomalies or missing information early in the process.
Engaging suppliers and stakeholders is essential, especially for Scope 3 data. Targeted surveys that focus only on the data required for calculations can improve response rates. Sharing results and feedback with suppliers encourages better data quality in the future. When supplier-specific data is unavailable, industry databases and benchmarks can provide useful estimates.
Thorough documentation and traceability are also stressed. Every data source and calculation method should be documented, not only to support credibility and compliance but also to make future calculations easier and more transparent.
The Role of Automation and AI
Modern carbon footprint calculation increasingly relies on automation and artificial intelligence to:
- Extract and structure data from invoices and reports
- Categorize data into the correct emissions scopes and categories
- Identify gaps and estimate missing values based on historical trends or industry averages
This not only reduces manual workload but also improves data accuracy and enables more frequent reporting.
Want to learn more?
For a deeper dive into carbon footprint calculation—including real-world examples and expert insights—check out our recent webinar recording.
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Team Leader, LCA