Creating Sustainability-Intelligent Companies (Post 2): Data for Reporting part 1

Introduction

When discussing data for sustainability, the focus often turns to carbon accounting software, reporting and supply chain management. Typically companies starting on the sustainability reporting journey will engage consultants to do a first one off calculation of carbon footprint, identify key areas of reductions and set targets. Then they will on-board a software solution, engage their suppliers via that software’s survey module, and hope they will be done. 

However, relying solely on specialized software isn't enough to address the complexities of sustainability data, as the many re-statements and data quality issues experienced in the industry attest to. To bridge this gap, integrating data best practices from other disciplines is crucial. 

In this post I will outline some best practices to up data trustworthiness and scalability. Basically spreadsheets, or even sustainability-specific software alone, cannot solve this. But they can in conjunction with data best practices and tools that are already used for more mature data use cases (e.g. in marketing and product).

Before diving into this I want to remind us all that, ultimately, the goal should be action, not ‘just’ reporting. Reporting remains useful though because the published data enables others to act: investors, customers and employees. 

Best Practice 1: Design for an outcome 

Here, you might say, I just need to comply with the regulation. But is that it? Some will definitely only want to avoid the risk of non-compliance. But some will want to be seen as leaders, even differentiated by the granularity and trustworthiness of the data they share. So they may have a reputation objective. Or an objective to truly guide investor capital allocation decisions.

In most cases, these objectives translate into a need for trustworthy data. Increasingly, given the amount of data points required by a regulation like CSRD, there will be a need for data to be produced at scale in an automated way to avoid the massive inefficiencies and lack of auditability that come with spreadsheets and emails alone. And by that we don’t just mean inputting data into a software, but actually automating a data flow to a centralized repository, whether in a specialized software or somewhere in your existing data stack.

To be a good actor in this system you also need to share enough data with your clients, especially any B2B clients, to enable them to do their own reporting, while not compromising any competitive information. We will dig into data sharing further in our ‘BP5’. But in this early phase the critical point is to clarify your goals and the outcomes you are designing for.

The chart below illustrates the chain of decisions (orange arrows) that can be made by different actors in response to information being shared (purple arrows).

Chart 2: Macro impact of sustainability data

Best Practice 2: Foster Data Education and Literacy

Building data literacy across your organization is a key element of successful ESG reporting. By this we mean familiarity with the concepts, terms and data sources used. This includes key terms definitions, worked out with stakeholders, as well as intuition about units & scales. You want to encourage discussions, comparisons, and benchmarks related to ESG units and quantities. Education can take various forms, from regular discussions to highlighting relevant resources or formal training. By instilling a sense of data fluency at all levels, you empower your organization to engage more effectively with ESG data and spot mistakes.

In one organization I have worked with, a mistake slipped in the carbon footprint calculation, treating a monthly number as an annual number, leading to a 12x re-statement. This would never happen with £ or $, or other units your business is highly familiar with. The same goes here. Everyone should get a sense of what the footprint or carbon intensity of a typical individual or activity is and be able to apply basic rules of thumb to sanity check numbers they come across. Metaphors can also be useful to gain an intuitive sense of scales. For example, on warming, I like to compare earth temperature to the body temperature. Suddenly 1.5 degrees of warming and 3 degrees (and that trip to the emergency room) do seem very different!

Best Practice 3: Establish Data Governance Early On 

One fundamental step in enhancing data-driven sustainability reporting is the early establishment of a robust data governance process. Ensure that both internal and external data sources are included in this process. While Chief Data Officers (CDOs) often oversee sensitive business data, sustainability data may not always fall within their purview. For example, a delivery company I spoke with reported that, while they usually dealt with direct business performance drivers, the systematic use of gender data from HR systems was newly spurred by their sustainability initiative. They had to get their heads around this data - and apply some simple governance rules - to guarantee its integrity. The same happened to an automotive company setting out to systematically use some of their workshop data for the first time.

Collaborate with your Data team to advocate for the inclusion of relevant sustainability datasets in the governance process. This entails a shift in the mindset, recognizing that data quality isn't a given but a continuous effort. Involve data creators as "data citizens," fostering a culture of data ownership and quality standards.