Climate Data: How to Overcome Collection and Analysis Challenges
“You can’t manage what you don’t measure” may be an oversimplification. But it’s also a pithy expression of an important management principle. That principle extends to the management of sustainability, climate, and equity initiatives. Unfortunately, acquiring, curating, and analyzing data in this domain is uniquely challenging. Those data obstacles can put organizations at greater risk of falling short of their climate and business goals and their regulatory obligations.
Effective Climate Strategies Depend on Good Data
Data is critical for setting climate strategy; developing plans; tracking progress; and making public disclosures. Many different types of data are relevant for these purposes. For instance, data on the greenhouse gas emissions associated with energy consumption, transportation, or production of goods is needed to calculate an organization’s carbon footprint, set carbon reduction goals, and prioritize emissions reductions efforts. Climate data, such as the climate conditions faced by a given operational site, can help companies assess operational and infrastructure risk and inform mitigation and adaptation strategies. Data on other corporations’ emissions, climate goals, and progress toward achieving those goals helps companies benchmark their own goals and progress.
It’s not just data about the natural environment or our impact on it that is important. Data on clean energy and technologies that can help reduce greenhouse case emissions — also known as climate tech — such as emissions abatement potential, cost, and maturity, can help organizations prioritize hundreds of alternative paths to net zero. And demographic and social data, including information on employment, can help inform socially aware company initiatives such as siting and community engagement.
The most robust climate strategies incorporate data like this in integrated assessment models that reflect the interactions among the system of systems that comprise our global economy and the context in which all organizations operate.1
Why Is Climate Data Such a Challenge?
Data has long played an important role in how companies make strategic and operational decisions. In recent years, companies have tended to make growing use of external sources of data for these purposes. This practice can help reveal risks and opportunities that might be missed if analysis were limited to data generated by internal operations, customers, and first-tier suppliers. However, making effective use of external data can challenge even sophisticated data teams.
The challenges can be even greater when it comes to climate and sustainability data. For example, a recent survey of financial firm executives by the Institute of International Finance found that only 5% of 130 surveyed firms think the data they use to measure, track, and achieve their net zero objective is fully accurate or complete.
As we have noted, the climate and sustainability data ecosystem comprises an extraordinarily diverse variety of sources and types of data, from bills of materials in material requirements planning systems to crumpled hardcopy invoices reflecting purchases of fuel oil. And the ecosystem is less mature than those many data professionals are accustomed to working with: Among other things, there are fewer (or too many) standards, less consistency, and a higher incidence of “missing,” yet critical data. Some data sets, like those generated by climate models, require special training to work with. And some of the important data providers are non-profit organizations that are unaccustomed to licensing their data for commercial purposes, complicating even the acquisition of data.
Risks of Climate Data Misuse and Mismanagement
The risk of errors in analysis can increase as the diversity and number of data sources involved increase. Our system structure is trained to handle the technical challenges of integrating data in diverse formats such as unstructured text, delimited excel files, and more. But climate-related data often ranges from the highly granular to the high level. Blending different levels of measurement can reduce analytical certainty and introduce the potential risk of bias. For instance, integrating social equity considerations into climate analysis can entail judgements about the use of quantitative indicators of socioeconomic status and vulnerability.
To help ensure consistent and repeatable analysis, organizations need to follow standards where available to weight those factors appropriately. And they need a firm grasp on the provenance and governance of the data they use to help ensure results can stand up to external scrutiny.
The Bar for Climate Data Quality is Rising — that’s Good for Business
The market is demanding ever better data on climate and sustainability. Rough emissions estimates used to suffice, but the trend has shifted toward ever greater data quality and specificity. For instance, many companies estimate their Scope 3 emissions by using rough estimates of emissions associated with broad categories of goods and services and then multiplying those emissions factors by spend data to estimate emissions. But leading companies track emissions by specific suppliers in specific locations and sometimes by specific products.
The demands for greater data granularity and accuracy are making the management of climate data ever more challenging. But in the medium term, businesses have no choice; it will be required by regulators and customers. And companies will need precise data to make wise carbon abatement investment decisions and to get credit for — and to monetize — the carbon abatement they achieve.
Imperatives for Data Leaders
Drawing on our experience and lessons learned from developing an AI-enabled, end-to-end emissions measurement and net zero strategy-setting platform, leaders responsible for organization data collection and management should consider the following steps to help ensure the organization has the capability to measure and manage climate-related data:
Develop or acquire a climate-ready data capability. A data system like Saastain built specifically for climate measurement should be able to aggregate climate-related data from hundreds of data points. Our carbon accounting and data analysis platform should be able to streamline access to vetted, curated, and current data critical for crafting climate strategies and road maps, monitoring and evaluating sustainability initiatives, and making accurate public climate disclosures.
Modernize your data team. Climate initiatives require first-rate data governance and management. And, as described above, they entail the use of highly diverse data sets generated by the organization or by others in its value chain. Some of this data requires special skills to manage and analyze. Unfortunately, those skills are generally not found today in one organization in one company. Data leaders will need to review the skills across their organization and fill critical gaps by hiring, partnering, or training.
Collaborate to explore the art of the possible. Effective leaders know that success requires alignment with the business, knowledge of its challenges, and a deep understanding of the opportunities it is pursuing. But it would be a mistake to wait for the business to lay out its requirements. These days, technology and data is used not just to solve problems, but to create opportunities. What the business may not have considered — or thought possible — could evolve into a key capability or differentiator for the business.
Manage and Measure
Today, organizations — and the tech and data teams that support them — are increasingly being evaluated on how they manage data on sustainability, climate, and equity. Companies will be expected to manage carbon as an asset and a business advantage. Good strategy and operations coupled with good data will make outstanding decarbonization performance a differentiator and make it possible to monetize carbon reductions — through price premiums, share price growth, offsets, and tax incentives. Data is the key to addressing the social and environmental responsibilities that organizations should consider commiting to advance.
