ESG software: Top 5 providers at a glance

For many companies, Excel is the first step toward ESG reporting. Existing data is consolidated in spreadsheets, initial key figures are calculated, and simple analyses are created. Especially for mid-sized companies, this approach may seem reasonable at first: the tools are already available, employees are familiar with them, and additional investments can be avoided.

Excel can also be a pragmatic solution in the early stages, particularly when only a limited number of data points need to be collected and requirements are still manageable. This allows companies to gain initial insights into their ESG data and create a foundation for the next steps.

However, as ESG topics become more relevant, the situation changes. Requirements from regulations, supply chains, and financing increase; data needs to be collected more regularly and prepared more consistently. At the same time, more departments and locations become involved.

This is exactly where it becomes clear: Excel is a good starting point, but not a scalable solution.

ESG reporting with Excel: where the limitations become clear

The limitations of Excel in an ESG context mainly arise from the growing complexity of requirements. While simple data collections can still be managed effectively, manual solutions quickly reach structural limits.

Typical day-to-day challenges include:

No central data foundation: ESG data is spread across multiple files, versions, and departments. A consistent “single source of truth” is missing.
High manual effort: Data is requested by email, transferred into Excel, and consolidated manually. Recurring processes are time-consuming and prone to errors.
Lack of traceability: Changes, calculations, and data sources are often not clearly documented – creating risks during audits.
Limited scalability: As the number of locations, data points, or requirements increases, Excel quickly becomes difficult to manage.
No clear workflows: Responsibilities and approval processes are not mapped within the system and must be organized manually.

Why ESG data management with Excel does not work in the long term

ESG data differs from traditional business metrics in several ways. It is generated across different areas of the company, needs to be updated regularly, and is increasingly subject to regulatory requirements.

In addition, ESG data is not used for just one purpose. It is needed in parallel for reporting, supply chain requirements, internal management, and financing processes.

Excel, however, is not designed to map these requirements in a structured way. In practice, this leads to:

Inconsistent data versions
High coordination effort
Increased risk of errors
Limited audit readiness

This is exactly where specialized ESG data management tools come in.

ESG software as an alternative: what changes in practice

Using ESG software changes the way companies handle ESG data as a whole. Unlike Excel, data is no longer collected in isolation, but captured, processed, and made available for different use cases in a structured way.

The most important changes include:

Centralized data storage instead of distributed files: All ESG data is captured and consolidated in one place.
Automated processes instead of manual work: data collection, calculations, and reports can be standardized and partly automated.
Clear workflows and responsibilities: Tasks, approvals, and responsibilities are defined within the system.
Traceability and audit readiness: Data sources and calculation logic are documented transparently.
Scalability as requirements grow: New locations, data points, or regulatory requirements can be integrated in a structured way.

Excel vs. ESG software: a direct comparison

The differences between Excel and specialized ESG software become especially clear in day-to-day use. While Excel is primarily designed as a flexible tool for individual use cases, ESG software solutions from various providers map structured processes and requirements directly within the system.

As data volumes grow, regulatory requirements increase, and more departments become involved, it becomes clear that the challenge is not only about collecting data, but also about processing it consistently, ensuring traceability, and making it usable.

The following comparison highlights the key differences in handling ESG data and shows why many companies move from Excel to specialized ESG data management tools as complexity increases:

Area	Excel	ESG software
Data storage	ESG data is often stored across multiple files and versions, which can lead to inconsistencies.	ESG data is captured centrally and consolidated in a uniform structure, creating a consistent data foundation.
Data collection	Data is usually collected manually via emails or individual templates, resulting in a high level of coordination effort.	Data is collected in a structured way through standardized inputs and can be partly automated.
Data quality	Data quality is often affected by manual entries and a lack of validation.	Standardized processes and validation mechanisms help ensure high and consistent data quality.
Processes & workflows	Processes, tasks, and approvals must be organized and coordinated manually.	Processes, responsibilities, and approvals are defined within the system and clearly structured.
Reporting	Reports are created manually and need to be adjusted with every update, which is time-consuming.	Reports can be created automatically, adapted, and reused for different requirements.
Traceability	Changes and calculations are often difficult to trace and only documented to a limited extent.	Data sources, calculations, and changes are fully documented and remain traceable at all times.
Scalability	As data volumes, the number of locations, or complexity of requirements increase, Excel quickly becomes difficult to manage.	The software can easily scale with growing data volumes, additional locations, and new requirements.
Integration	Integration with existing systems is usually limited or requires a high level of manual effort.	Interfaces with ERP, finance, and other systems enable automated and consistent data exchange.
Collaboration	Collaboration is often more difficult because teams work with different versions and coordination has to be handled manually.	Collaboration takes place centrally via one platform with clear roles, permissions, and coordinated processes.
Regulatory requirements	Regulatory requirements must be interpreted and implemented manually, creating additional effort.	Relevant standards and requirements are supported within the system and mapped in a structured way.

When companies should move from Excel to ESG software

In practice, the move from Excel to specialized ESG software is rarely triggered by a single reason. Instead, it usually develops gradually. As ESG topics become more relevant, data volumes, complexity, and requirements increase – and with them, the limitations of manual solutions. Moving from Excel to ESG software becomes particularly useful when:

ESG data is collected and updated regularly: As soon as data is no longer collected once, but needs to be captured and maintained at fixed intervals, the effort required for manual processes increases significantly.
Several departments or locations are involved: When ESG data from different areas or entities needs to be consolidated, coordination in Excel quickly becomes confusing and prone to errors.
Requirements from regulation, supply chains, or financing are increasing: Requirements such as CSRD, customer requests, or expectations from banks call for structured, consistent, and traceable data.
Reports need to be created on a recurring basis: When ESG reports need to be created, adapted, and used for different purposes on a regular basis, manual effort quickly becomes a bottleneck.
External reviews or audits are upcoming: As soon as ESG data needs to be reviewed, traceability becomes essential. Excel often does not provide sufficient transparency and documentation for this.

In these situations at the latest, Excel shifts from being a pragmatic starting point to becoming a structural weakness. ESG software creates the necessary foundation to manage data efficiently, standardize processes, and meet requirements reliably.

Conclusion: Excel is a starting point, but not a long-term solution

Excel can be a practical and sensible solution for getting started with ESG reporting. Especially in the early stages, when data volumes are limited and only a few stakeholders are involved, initial structures can be built quickly and without additional tools.

As requirements increase, however, the situation changes fundamentally. ESG data needs to be collected regularly, consolidated, and used for different purposes, whether for regulatory requirements, customer requests, financing, or internal management. At the same time, the number of departments, data sources, and processes involved continues to grow.

At this point, Excel reaches its structural limits. Manual processes become time-consuming, data becomes inconsistent, and traceability decreases. The effort required for coordination, maintenance, and reporting grows continuously – often without being fully visible at first.

ESG software addresses exactly these challenges and creates a central foundation for handling ESG data. Through structured data collection, standardized processes, and clear workflows, many of the typical challenges can be solved. At the same time, ESG data can not only be captured, but also systematically analyzed and incorporated into business decisions.

Tip: Companies should regularly assess how much manual effort their ESG processes require and how much coordination is needed. As soon as ESG data is collected on a recurring basis and used for multiple purposes, it is worth comparing ESG software solutions.