ESG Data Strategy Guide: How Salesforce integrates ESG data with Net Zero Cloud

Historically, carbon accounting and environmental, social, and governance (ESG) data management have been crucial but tedious processes. Sustainability teams are often challenged by unstandardized data, months of manual collection, and reconciliation processes. By the time the data is collected, standardized, verified, and reported, it’s already stale and the next reporting cycle begins again, leaving little to no bandwidth to take meaningful action.

In recent years, we’ve seen countless carbon accounting and ESG point solutions come to market, but the real breakthrough comes with the speed, scale, and flexibility of a platform. The ability to connect data via integrations and direct application program interfaces (APIs) provides a live view of ESG metrics and unlocks secure ways to share data insights, automate tasks, and take action across the company.

This shift from manual, once-a-year data capture in spreadsheets to real-time, automated flows creates numerous efficiencies: enhanced data quality and consistency, and faster, more reliable reporting and decision-making with live dashboards. It transforms static snapshots into continuous insights, while also supporting advanced AI and machine learning models- which perform best with database-driven data rather than static spreadsheets.

At Salesforce, we faced similar challenges with our own carbon accounting and data management, until we embarked on our journey as the first customer, or “customer zero,” of Net Zero Cloud — our ESG management platform.

In this article, we’ll dive into Salesforce’s journey with Net Zero Cloud and the 8 steps we took to achieve seamless ESG data integration. By overcoming our initial integration challenges, we’re now well-prepared for expanded ESG reporting and regulations like the Corporate Sustainability Reporting Directive (CSRD).

By sharing our experience and lessons learned, we aim to help other sustainability professionals enhance their carbon accounting and ESG data management. This can lead to significant improvements: better data accuracy, reduced reporting burdens, and more time to focus on what matters most—developing and implementing carbon reduction strategies.

Table of Contents:

• Salesforce's Journey with Net Zero Cloud
• 8 Steps to ESG Data Integration with Net Zero Cloud
• A Solid ESG Data Foundation for What’s Ahead

At Salesforce, our own experiences managing ESG data inspired discussions on how new tools could streamline processes and break free from the repetitive, stale carbon accounting cycle. We faced numerous challenges, including:

1. Unstandardized data formats
2. Disparate data sources
3. Manual data collection
4. High data volume
5. Manual data validation and reconciliation
6. Delayed reporting for decision-making

The sheer volume of data from our global value chain operations, coupled with the complexity of emissions calculations, made it clear that we needed a better solution. Recognizing the power of our own technology, we decided to leverage the Salesforce Platform as the foundation for improving our tracking and calculation of carbon and other ESG metrics. This led to the development of what was initially called the Sustainability App, which eventually evolved into a complete ESG management platform: Net Zero Cloud.

To tackle implementation barriers, we adopted an intentional, multi-phased strategy. This involved hiring in-house technical resources, securing sufficient budget, leveraging MuleSoft for data integrations, and engaging system integration partners.

Since then, we’ve successfully conducted scope 1, 2, and 3 carbon accounting, assurance, and reporting all within Net Zero Cloud. What once took months of manual work can now be accomplished in a fraction of the time. Net Zero Cloud has become a space for collaboration, allowing stakeholders across the business to leverage the data they need to drive initiatives within their own organizations.

Our journey from facing data challenges to successfully implementing Net Zero Cloud marked a significant improvement in our processes. Let’s take a closer look at the path we took to get here.

Before diving into the technical work, we brought a technical expert with knowledge of the Salesforce Platform and data strategy onto our sustainability team. This decision proved invaluable as we navigated the complex landscape of data integration and automation. We quickly realized this wasn’t a one-time task, but an ongoing journey of continuous improvement and progress.

Here are the 8 key steps we followed to seamless data integration, incorporating lessons learned from our annual assurance cycle:

1. Create a comprehensive ESG data strategy
Develop a strategic approach that prioritizes and right-sizes efforts. Identifying the right data, timing, team, and actions ensures a successful integration and maximizes the effectiveness of your ESG data strategy.

• The right data: Instead of integrating all the data in one phase, consider key factors to prioritize your data integrations. We prioritized materiality to our sustainability goals, our ability to improve data quality, and our reporting needs. This ensured our ESG data strategy was built on a foundation of accurate and relevant information.
• The right timing: Determine the frequency of data collection and reporting required to drive effective decision-making. This could mean moving from annual to quarterly, monthly, or even real-time data. A well-integrated data system like MuleSoft can enable automation to ensure accuracy and efficiency, and reduce time spent manually collecting and cleaning data.
• The right team: Understand who your stakeholders are and make data actionable for those who need it the most. We involved non-sustainability teams early to understand their day-to-day operations and integrated sustainability data into existing tools and processes to accelerate adoption and impact across the organization.
• The right actions: Leverage technology such as Agentforce and automations to empower employees to take informed action without disrupting their usual routines. With Net Zero Cloud, which exists within Salesforce, our team continued using familiar systems while accessing the sustainability data they need to drive meaningful impact.

2. Build the Business Case
Secure stakeholder buy-in through a cost-benefit analysis that highlights the advantages of your integration plan. Communicate early with cross-functional teams — such as compliance, IT, and data owners — about how the integration will be executed. We learned that this transparency builds trust and ensures alignment.

3. Find the Right Moment
Align the integration with reporting and compliance deadlines, and develop a contingency plan for manual uploads in case of delays. During this phase, we considered the complexity and volume of data being uploaded into Net Zero Cloud to determine the best time for integration. Involving key stakeholders helped us avoid conflicts with other projects or processes.

4. Conduct Data Migration and Integration
Ensure smooth integration with existing systems while maintaining data quality and consistency. After determining our data strategy, we used Tableau to identify necessary data transformations. We then used MuleSoft, Data Cloud, and Snowflake to establish and bring the data into our trusted data repository, or data lake, to ensure data harmonization and manage updates. This helped us create a data architecture crucial for maintaining integrity across various systems.

5. Establish a Data Change Management Plan
Set up a process for identifying and addressing data updates or corrections, as sustainability data often requires adjustments. By collaborating with data owners, we established a shared understanding of how these changes would be managed, ensuring that the integration adapts to ongoing data corrections or updates.

6. Configure Net Zero Cloud
Tailor the platform with dashboards, report templates, workflows, and automations. Involving stakeholders throughout this phase allowed us to configure the system in a way that supports their specific needs. Knowing which data requires frequent attention helps us automate critical tasks, improving efficiency and accuracy.

7. Provide Training and Support
Develop training programs and establish support systems such as help desks and user communities. Cross-functional training is essential, especially for compliance managers and reporting teams. Ensuring these groups were comfortable with the new processes helped increase platform adoption and confidence in the system.

8. Improve and Iterate
Continuously monitor the integration, conduct regular audits and feedback loops, and update the platform to adapt to new ESG regulations. Maintaining open lines of communication with stakeholders allowed us to gather feedback from multiple departments and fine-tune our integration based on their evolving needs. Collaboration with data owners and IT helped ensure that the system remains flexible and updated as business needs change.

With our carbon accounting foundation and data architecture strategy in place, we’re now well-prepared for expanded ESG reporting and emerging regulatory requirements. As regulations like Corporate Sustainability Reporting Directive (CSRD) come into play, we’re ready to bring together even more data sources and produce comprehensive reports.

We encourage all sustainability teams to embrace the data and AI revolution and think about how they can transform their own reporting strategies. By leveraging Net Zero Cloud, MuleSoft, and Agentforce and following a strategic implementation approach, organizations can transform their reporting processes, drive more informed decision-making, and ultimately accelerate progress toward their sustainability goals.

As we look to the future, our journey with Net Zero Cloud demonstrates the power of innovative technology in advancing sustainability practices. We're eager to engage in dialogue with customers, peers, and partners to improve carbon accounting and ESG data management across industries.

Together, we can build a more sustainable future, one data point at a time.