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7 data considerations to underpin your decarbonization journey

Sponsored: Achieving net-zero requires reliable and robust GHG emissions data. Follow these data practices to establish financial-grade emissions data for net-zero.


Pathway to Net Zero. Source: Envizi.

This article is sponsored by Envizi.

If 2020 has taught us anything, it’s that the unprecedented can happen, and preparation matters. After COVID-19, our next great crisis is climate change, and many organizations are heeding the lessons learned in 2020 and planning actions now to reduce their long-term climate impact. A key part of this journey is a commitment to decarbonize.

While emission reduction tactics may vary by industry and organization, many organizations are following an increasingly popular pathway to carbon reduction that typically involves a combination of operational energy efficiency initiatives, building retrofits, on-site or off-site renewable energy and carbon offsets to negate unavoidable emissions.

Emissions reduction strategies require two essential ingredients: a verifiable and robust data foundation and a financial-grade greenhouse gas (GHG) emissions accounting process.

In over a decade of supporting organizations along their decarbonization journey, I am constantly reminded that data capture and management present a challenge for many. While sustainability performance is increasingly being used to assess organizational performance in a manner akin to the way investors use financial data, the deeply embedded and highly developed structures and processes for capturing and managing financial data do not always exist for sustainability and energy data.

So how can organizations prepare their data to accelerate their emission reduction goals? This article outlines tried and tested guidelines for establishing a financial-grade, best practice sustainability data foundation.

1. Create a robust and flexible data structure 

Your data must be structured in a way that best supports the decarbonization target you have set in place. Consider which types of data your organization needs to capture and how the data should be tagged and aggregated. Your sustainability data management software should support tagging of data at the account or meter level, which can be aggregated to locations and further aggregated to groups. 


  • Review the detailed reporting requirements of pledges or commitments you have made, and ensure your team understands what data it needs to support them.
  • Regularly check and maintain metadata (tags, labels, opening/closing dates, etc.)
  • Set minimum key performance indicators for the data management process to define thresholds such as "data completeness," and document the decisions.

2. Review data accessibility and evaluate options for data capture 

The data required for setting and implementing decarbonization strategies is often scattered across various internal systems throughout the organization, many of which may be incompatible, or the data may be held by suppliers that do not have systems and processes in place to share it. To complete your data foundation, your team needs to determine how it will source the data it needs on an ongoing basis.


  • Consider outsourcing the data capture process to a specialist service provider.
  • Get as close to the original data source as you can.
  • Aim for automated data transfer wherever possible. Minimize human intervention: Files touched by people prior to data collection are more prone to failure to load, precision loss and metric confusion.
  • Consider how you will store and manage the data on an ongoing basis. A cloud-based enterprise software platform is infinitely superior to spreadsheets for this task.

3. Work with your utility providers

Consumption data informs decarbonization strategies, and sourcing this data from utility providers via utility meters is the gold standard. 

This seems straightforward until you consider that there are thousands of utility providers with different rules and processes for data provision. This creates variability in each utilities’ willingness and ability to provide data, which creates difficulties, particularly for organizations with multiple facilities in different geographic locations.

Tips to address this challenge: 

  • Contact your utility provider and explore data sharing options. The preference should be an automated data provision via either an online portal or via an application programming interface that allows data exchange.
  • Consider working with a specialist partner to automate the data capture process.
  • Include a data provision clause in all new energy procurement contracts. 

4. Develop processes for data management and assign ownership

Data-driven decision-making is only valuable if the data is accurate, complete and up-to-date. Effective data management requires dedicated attention to detail, ownership and diligence.


  • Create an accountability matrix for data management and assign responsibilities to staff. This matrix should set out a regular schedule to review data completeness to catch errors in time to address them.
  • Keep a close eye on data flowing in. Set up inactivity alerts against each data source to identify data gaps early on.
  • Institute a process to reconfigure formatting updates from utility supplier updates. A small change such as which column a data is located on within a bill can prevent your data from loading properly.
  • Follow up promptly with parties that have not fulfilled data provision commitments.

5. Create a single, trusted source to store and share your data 

Data is an increasingly valuable resource for guiding business decisions, so it should be made accessible to both internal and external stakeholders.

If this process is outsourced, remember that this data poses as much of a business risk as financial data and the governance structure to protect it should be similar.


  • Use cloud-based storage to provide password-protected access for all stakeholders
  • Ensure supplier contracts are worded to ensure data ownership rests with your organization. 

6. Align your data capture and management plan with audit requirements

The audit process is a critical step to validating reported progress. While the outcome is important to the organization’s governance, the steps to achieve audit-ready, traceable data can be challenging. 


  • Consult with your auditor up front, understand their requirements and ensure your policies for data retention and tagging are aligned.
  • Leverage a cloud-based single system of record that includes change tracking and document storage, and that can easily be configured to provide access to external parties as required.

7. Engage your teams early in the process

The responsibility for energy and sustainability data management cannot fall solely on the sustainability team. There is much to be learned from organizations that have successfully tackled this particular challenge. GPT, one of Australia’s leading REITs, successfully introduced policies and procedures to drive company-wide engagement in data capture and management. 


  • Elevate the importance of GHG data capture and storage within the organization to senior level management to encourage participation and support.
  • Consider internal reporting tools to provide transparency and drive accountability for data capture and storage.


As is the case for all strategic decision making, data must lie at the heart of any effective emissions reduction strategy — to inform strategy and tactics, and to deliver robust and verifiable reporting.

Investors are including sustainability outcomes in their evaluation of organizational performance. Therefore, processes and tools to capture and manage emissions data must meet the same robust requirements applied to financial data.

However, there are challenges associated with capturing and managing the data required to support decarbonization. Each challenge is addressable with forward planning and focused effort. Based on over a decade supporting organizations in managing and reporting on sustainability and energy performance, Envizi has found that the areas where many organizations see challenges are: 

  • data accessibility and capture (particularly from utility providers);
  • effective data management (including the way data is structured and accessed);
  • data ownership; and
  • preparedness for audit and team engagement. 

Sustainability and energy teams willing to tackle these challenges will reap the benefits of a financial-grade data foundation to underpin their decarbonization efforts.

If you’d like to learn more about using data and technology to streamline and accelerate decarbonization, read our Pathway to Low-Carbon Guide.

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