Feb 09, 2023

Making Sense of Sustainability Part Two: How to Unlock Data-Driven Sustainability

Gabriel Greening
Christian Buechel

Gabriel Greening and Christian Buechel

Making Sense of Sustainability Part Two: How to Unlock Data-Driven Sustainability

In part one of our Making Sense of Sustainability series, we highlighted the challenges facing organizations and individuals to get to net zero and our collective responsibility of limiting global warming to 1.5 degrees Celsius. We summarized how many of our clients are approaching this challenge by adopting a ‘carbon conscious’ operating model, harnessing green technology, and putting people and processes at the heart of sustainability.

Many organizations have formed sustainability agendas but have disparate data sets, with limited data and analytics capability to report, manage, and forecast carbon emissions to support day-to-day decision making. This is echoed by a recent NatWest study, which showed that 87% of SMEs are unaware of their business’s total carbon emissions.

In this blog, we explain how data and analytics plays a crucial role in helping your organization manage your environmental impact.

Headline Takeaways:

Data-driven sustainability is important because it instigates traceability, accountability, and objective decision-making.

Our top four success factors for unlocking data-driven sustainability include:

  1. Collect relevant data and ensure users can access insights.

  2. Make strategic use of sustainability data in forecasts, trend analyses, and decision-making.

  3. Engage with third parties and sustainability metrics beyond carbon emissions.

  4. Dedicate people to sustainability reporting and engage your wider stakeholder communities.

Data-Driven Sustainability

As the maxim goes, “if you can’t measure it, you can’t manage it.” This holds true for sustainability; measurements allow you to cut through the noise of having many sustainability initiatives but no tangible progress. Indeed, a data-driven approach to sustainability is critical across all levels of your organization: high-level KPIs support strategic direction, and granular reporting is crucial for encouraging the right behaviors and enabling progress from the bottom up.

So, what is data-driven sustainability, why is it needed, and what does it take to succeed? We provide insight from our client engagements below.

What is Data-Driven Sustainability?

Data-driven sustainability is an approach that creates a clear connection between the collection, reporting, and strategic use of data to make sustainability-informed decisions.

Why is Data-Driven Sustainability Needed?

A data-driven approach to sustainability brings traceability and allows your organization to track progress and make informed decisions. This helps build confidence in your sustainability initiatives by avoiding the trap of using approximated methodology to tackle sustainability.

A Credera team in the UK recently supported an integrated energy company (IEC) to transform sustainable decision making by defining sustainability KPIs, setting a carbon tracking framework, and making a platform readily accessible to track carbon emissions. As a result, our client was able to make data-led decisions based on well-defined sustainability metrics.

Here are our top success factors based on our client insight:

1. Collect relevant data and ensure users can access insights

Access to sustainability data is key. It’s important to be able to collect relevant and timely data, and then distribute it to those who can use it to make better informed decisions. To achieve this, the best place to begin is to understand what data you have access to and control over. When dealing with any gaps in the data, you can use assumptions where necessary (remembering to track these clearly), and over time build out your data model to include additional sources. As data is fed through the data pipeline and aggregated, you need to ensure it is being segmented and visualized with the end users in mind. For example, we supported our client with the collection of data from third-party suppliers on hardware recyclability, allowing us to create a circularity report that displayed sustainability properties of materials used across their IT lifecycle. The report was made readily available to IT procurement.

2. Make strategic use of sustainability data in forecasts, trend analyses, and decision-making

Data-driven sustainability, when embedded correctly in an organization, is continuous. It allows you to make improvements and track progress. However, it’s also more than a report card for past performance – the data should give you the opportunity to conduct forecast analysis and mitigate any expected bumps along the way, or discover through trend analysis the areas which may offer quick wins.

3. Engage with third parties and sustainability metrics beyond carbon emissions

Data-driven sustainability is well suited to carbon emissions, but other areas such as water usage, circularity measurements, biodiversity, and more can fit into a data-driven approach. As the scope widens, so does the need to interface with third parties who are providing goods and services to an organization. Although collecting data from these indirect sources may be more of a challenge, beginning to estimate other areas of sustainability and third-party interactions will provide long-term dividends, ensuring that you have data across the sustainability spectrum and scopes.

4. Dedicate people to sustainability reporting, and engage your wider stakeholder communities

Once set up, the data pipeline and reporting layer provides tangible metrics, but it is the people and relevant decision makers that extract the value from a data-driven approach to sustainability. Having employees understand the approach and strategic direction enables this data to be used to its full effect and will also make the data collection easier when everyone understands how their area fits into the sustainability data model. At a higher level, data governance should also be a priority to ensure there is an agreed process regarding all aspects of data management.

Making the shift to a data-driven sustainability approach can be achieved through employee engagement, clear strategic initiatives, an understanding of the data-driven approach to sustainability, and through the creation of dedicated roles to ensure sustainability is given the correct resources, support, and attention. In our client’s case, a sustainability team was created to lead collection, reporting, and employee engagement (holding company-wide, interactive sustainability talks), and this team acted as the hub for all digital sustainability within the IT delivery portfolio. As part of CredClimate, we’re setting clear Organizational Key Results (OKRs) to improve our sustainability and make data-driven decisions.

Key Takeaways for Data-Driven Sustainability

Data-driven sustainability should be at the heart of any sustainability program, but data and analytics on its own is not enough. For your organization to unlock the full potential of data and analytics, businesses need to have a ‘carbon conscious operating model’ consisting of clear business outcomes, defined roles and responsibilities, streamlined processes, and most importantly, the cultural foundations to reinforce sustainable decisions and behaviors.

Explore CredClimate to learn more, or reach out to us at if you’re interested in starting a conversation about sustainability at your organization.

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