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Knowledge A Detailed Explanation of the Importance and Benefits of Using IT for Carbon Neutrality(2/4)~Limitations of Traditional Legacy Operations~


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Achieving carbon neutrality requires visualizing CO2 emissions. However, many global companies face challenges specific to their overseas operations when calculating and disclosing emissions throughout the supply chain. Company personnel in charge of such efforts often complain that they don’t know how to calculate CO2 emissions, or don’t know where to start. In addition to the lack of skilled local staff, another issue is the prevalent use of Excel for data management.

This article explains the importance and benefits of using IT for carbon neutrality as a solution to these challenges in four parts. It provides a clear introduction to carbon neutrality approaches, especially for those who are new to the field or looking for ways to improve efficiency.

2. Limitations of Traditional Legacy Operations

Many companies manage their CO2 emissions using Excel. However, such legacy operations face several issues:

Traditional Legacy Operations

Problems with Data Collection and Input

Manually collecting and entering CO2 emission data increases the likelihood of errors and omissions. Mistakes with numbers or units, as well as missing entries, can significantly impact overall calculation results. Inaccurate data means that the calculated emissions will not reflect the actual situation, potentially leading to inappropriate planning and reporting for reduction measures.

While some companies have automated the data entry process, real-time updating across multiple locations can still be challenging and can delay decision-making.

Problems with Data Management and Aggregation

When data from various locations or suppliers is provided in different formats or units, it must be converted and standardized before aggregation. Creating a unified data format often requires a great deal of time and effort.

Even if aggregation is automated, missing entries or errors in the calculation logic can necessitate manual review and correction. This undermines the efficiency of operations, especially when handling complex and large volumes of data, such as those involved in Scope 3.

Problems with Data Quality

Emission factors used to calculate emissions vary depending on the energy source and region, and they must be updated regularly. In Excel, these updates must be performed manually, which increases the risk of omissions.

Excel cannot directly import real-time primary data from sensors and other systems. This limitation makes it difficult to perform up-to-date analyses, increasing the risk that decisions based on outdated or inaccurate data may lead to errors.