Why it’s critical to get data collection right, and how to make it easier

Data collection is a crucial part of a company's climate journey. Nonetheless, it can be challenging and time-consuming to get it right. Sonya Samson and Matt Sprague, our experts in the Climate Strategies team, share their suggestions for transforming your data collection process from burden into opportunity.

Whether you're just starting out, or expanding on your value chain emissions, developing a greenhouse gas (GHG) emissions inventory is an important part of your company's climate journey. Collecting data is always the first step in this process.

Carbon footprints are used to identify business risks and opportunities, set decarbonisation targets and support investor relations and market positioning. A credible carbon footprint depends on the quality of the underlying data and the transparent communication of its limitations. Having inefficient data collection processes is detrimental not only to your sustainability team, but also to the broader company and your stakeholders.

Why is data collection so challenging?

The key challenges we see when working with clients include:

Data volume and quality

It's just a lot of data! This is due to the varied inputs required. For complex companies, this can take two to three months for a resource-constrained team.

Data gaps will be identified during this process with alternative data sources required. This means that teams need to understand the shortcomings and uncertainties associated with different data types.

Multiple data sources and owners

Data is needed across sources, including waste, water, energy, business travel and company purchases. Such information often sits with many different "data owners". For some applications, forward-looking data is required, needing input from the business.

Supplier or customer data is often not uniform or readily available. Companies may need to make assumptions developing the footprint.

Finally, the information may not have been stored with carbon footprinting in mind. Data owners need to consolidate or manipulate data, and address data gaps.

A dynamic space

The fundamentals of carbon footprinting are well-established; however, reporting requirements are constantly shifting. Conditions set by different disclosure schemes, government programmes or internal decision-makers are often improved and expanded. It is important to have robust processes in place to meet these changing requirements.

Understanding the reputational and compliance risks of a shifting landscape, and what is – and what is not – accepted by auditors, investors and the media is critical to ensuring that any climate claims are credible.

So, what can be done?

Data collection is a means to an end. As a company, you need to use your GHG information to support real climate action, not spend your time collecting data and reporting. So, how can this part of the process be improved?

1. Understand why you want to collect the data, what it will be used for and then you can build the internal business case. Consider the opportunities that a good understanding of the data may bring across engagement, target-setting and innovation. Data collection cannot be the job alone of the sustainability team, so this step is useful for increasing the level of engagement across different teams, who can start to understand their role in the company's climate journey. This forms the basis of your data management plan.
2. Identify major emission sources, key data points and data owners and document this information. Record who provided data and where it was stored or sourced from. This will provide a valuable record for repeating and improving on the process.
3. Consider taking a hybrid approach to data collection where you collect primary (volumetric) data for the material emissions and secondary (sector average, spend based) data for the lower impact emission sources to streamline the initial data collection effort. Consider reaching out to industry bodies for data on common emission sources and streamlining internal requests. When collecting data, always bear the overall intent of the exercise in mind – this will help guide your data quality requirements. Complete but low-quality data, for example, may make tracking progress against an emissions reduction target difficult.
4. Identify gaps, assumptions and improvement opportunities. Start with material emission sources first and look to improve your process in future reporting cycles. Spend the most time on the most significant emission sources or where the data is the most poorly understood.
5. Embed data collection in internal business processes. Decide on the “source of truth" and the format for data collection, then document this in internal operating procedures. Identify a central location for data, potentially using data portals or data collection software systems. Finally, discuss the format, quality and regularity of reports with suppliers. Getting the right data in the right format saves a lot of time.
6. Assign data owners and hold people accountable. It is very important to make sure that appropriate training and tools are provided to these individuals to ensure that they are empowered in their role. You should also decide who is accountable for the tracking and improvement of the overall data management plan.
7. Reflect on the process. Look for good practices that can be adopted across the organisation, identify what took the longest and where improvements could be made. Ensure that this information is shared with the relevant teams. Starting is the most important step.

Increasing efficiency with software

There are a lot of software solutions available that can streamline the process of calculating your carbon footprint. These solutions range from individual estimates for household emissions, all the way through to enterprise data and emissions management platforms.

Software solutions can help by:

1. Providing data connections to link energy, procurement and other activities to the carbon management solution.
2. Allowing several users to upload activity data as well as supporting evidence within a single interface; this improves version control and avoids email chains.
3. Enabling you to delegate, track, approve and set reminders for data collection, and
4. Automating warnings for large variances in data relative to the last entry.

Software is only as good as the data you provide

However, while it's an important tool, software should only form part of your overall solution: your team still needs to understand the inputs, methodology and results. Software and technology should form part of your processes, but you should make sure they are fit for purpose and that the outputs are actionable, insightful and can inform more than just reporting.

When selecting a software solution, it is important to consider the data points that should be collected, the completeness of the carbon data reporting (can it report on scope 1, scope 2 and all 15 scope 3 categories?), the transparency of the outputs and your overall reporting or decision-making requirements. During the footprinting process, bear in mind that software is only as good as the data you provide. If you cannot interrogate the data, or do not understand the underlying assumptions, it can be difficult to trust the software report, or make strategic decisions.

It is worth considering doing the carbon accounting manually the first time. While this is time-consuming, it will provide a sense check of the software output, and also streamlines the software implementation as you already know the data sources and formats.

Do it right so you can focus on action

If data collection is done well, you can expend effort on using the data to improve business sustainability outcomes, which is where the power of the data lies. Being able to make business decisions, set credible climate targets and decarbonise are the real goals – not the reports!