When running a company that is aligned with sustainability goals, sourcing high-quality data is one of the biggest challenges faced by all industries. This article will overview some lessons learned as a user experience designer creating applications to import data to a sustainability monitoring system.

Sustainability is a new topic, and many teams still struggle to implement data collection procedures in their organizations. However, it is well-established to invite specialists to run a materiality assessment to define what data a company must track depending on the industry, sustainability standards, and the necessity to comply with regulations.

In the sustainability monitoring process, data related to metrics in the Environmental, Social, and Governance (ESG) framework are the most important. In finance, it is called business activity data, in other words, all information a company creates periodically related to its operations. Some examples of sustainability metrics for which data must be provided are greenhouse gas (GHG) emissions and water usage (environmental); workplace injury rates and diversity (social); and board gender diversity and business ethics (governance).

When setting up a sustainability monitoring and reporting system, the company’s master data is needed. It defines which values and value types are acceptable for each data dimension, for instance, the master data dimension “business location” can support the name of the cities where the company has buildings, such as Munich, Bangalore, and São Paulo.

The corporate sustainability team and the company’s leadership must agree on metric targets to steer the company towards its sustainability goals. Target data must be imported into the system to enable KPI monitoring. By setting up targets for sustainability metrics, companies can understand how well they are performing.

Design Challenges

When designing for sustainability data management, the biggest challenge is to consider all uncertainties related to the evolving sustainability market, with local and regional regulations coming to action as the impacts of global warming turn more visible, and a common language on sustainability is still being defined (for example, by regulation such as the EU taxonomy).

The scope and place of sustainability data collection also vary depending on the company’s size and industry. Although most companies have central sustainability teams responsible for creating an internal corporate sustainability strategy and reporting, data collection can occur locally, regionally, or globally, depending on the metric.

Users involved in the data collection process can also vary from sustainability experts to domain experts. Moreover, different metrics need different data update cycles, ranging from monthly to annually.

Learnings

In my work as a UX designer, combining multiple user profiles and system usage patterns significantly impacts user flow choices. As the design must fulfill the needs of sustainability experts and domain experts, e.g. an HR employee responsible for the metric “employee diversity and inclusion”, the system must be designed to prevent errors, the language used in the application must be easy to understand for lay users, and there might be clear and easy ways to recover from mistakes.

Because different user profiles must use the system in different periodicity, it is important that the time investment in learning to use the application is low, what can be achieved with internally consistent terminology and flows, visible actions instead of hidden functionalities, and appropriate user feedback in form of process status and messaging, so that users can understand the consequence of their actions.

Designing for the evolving sustainability field also means designing with scalability in mind. An application can be designed to enable reporting for different standards, so that the same data can be reused, and new metrics can be created as the regulations evolve. The system can also be designed to enable future data sourcing integrations, considering that some data is already available in databases, finance and HR applications, and GHG calculation systems.

Key Takeaways

Sustainability data management is a complex topic because it comprehends designing for different user profiles, usage periodicity, and field uncertainties, such as evolving regulations, and new data sources. It is important to account for system flexibility and scalability to decrease the necessity of rework.