From Numbers to Insights: The Power of Data Visualization in Life Cycle Assessment
Life cycle assessment (LCA) is a crucial tool for evaluating the environmental impacts of a product or process. This comprehensive method, which considers the entire life cycle of a product from its raw material extraction to its disposal, often generates a large dataset that can be complex and difficult to interpret. That's where data visualization comes in.
We asked EarthShift Global (ESG) Data Visualization Specialist, Tess Konnovitch, about her experience visualizing LCA data. She has worked on a wide variety of projects, featuring multiple clients across differing industries and strongly believes data visualization is a critical bridge between the scientific, business-oriented, and public parties interested in our work, and sustainability in general.
Q: What is data visualization and how does it contribute to understanding LCA results?
Data visualization is the graphical representation of data and information. As a data visualization specialist, I help our analysts communicate complex information in a clear and concise manner to a wide variety of audiences.
In general, data visualization is important for two primary reasons: it deepens the understanding of data for those involved, and it makes data accessible to those not involved. For those generating and working with the data, visualizations help to identify trends, patterns, and outliers that might not be evident in raw numbers. For those not working closely with the data, or those with little to no experience in math or science, visuals make that data more accessible and memorable, thus enhancing communication and understanding.
In life cycle assessment specifically, data visualization contributes to impact category comparison, stakeholder engagement, and informed decision-making. Visualizations allow for the side-by-side comparison of various impact categories, despite their different units and quantities, aiding in stakeholder understanding. Finally, and perhaps most importantly, visualizations can help decision-makers better understand the data and make informed choices that consider environmental impacts, ultimately helping to reduce their organization’s impact.
Q: Can you describe your experience working with life cycle assessment data and how you use data visualization techniques to help communicate this information to different audiences?
Life Cycle Assessment data is complex, and there are many ways to visualize LCA data. Therefore, the best technique in choosing a visualization is to start with the client or analyst, not the data. I first take the time to understand the specific goals and needs of the audience, as well as the context in which the data will be presented.
Before analyzing the data, I ask analysts and clients, “what is the message you are trying to convey?”. A good data visualization is driven by the message. It is the job of our analysts and my “scientist brain” to determine the message that the data is telling, and the job of our clients and my “artist brain” to determine how to translate this message to the relevant parties (e.g., stakeholders, the public, etc.). A technique I find particularly useful is to use various design features to establish an information hierarchy in a dashboard or figure. I do this by discussing what features are most important with our analysts and clients, and then using graphic and visual cues to encourage a reader’s eye to follow this predetermined hierarchy or story.
Q: How do you decide which techniques and tools to use for different projects?
I initially use the same technique across all projects, which is to ask the analyst or client a series of clarifying questions: “What is the end deliverable?”; “Who is the audience?”; and “When is the deadline?”. These three questions determine the entirety of my creative process, because they clarify what I am designing, for whom I am designing, and how long I get to design. Once I have clarity on these subjects, I typically consider how we handled similar projects in the past (what worked and what didn’t work) when building the bones of the design (structure, format, hierarchy), and then begin ideating new and project-specific features to focus on (e.g., individual visualizations, messages, colors, etc.).
In terms of tools, this is almost always analyst- or client-specific. Most of my work is done in Microsoft Office, as I value (as do our analyst and clients) “living” figures that are linked to data. I will either design right in Microsoft PowerPoint, or import designs from the Adobe Suite. Operating in a familiar workspace (e.g., Microsoft or Google) encourages collaboration between all parties (e.g., clients, stakeholders, analysts, designers, public).
Q: What do you see as the future of data visualization in the context of life cycle assessment, and how do you plan to stay at the forefront of this field?
I believe that data visualization will follow today’s trends of interactivity and automation. With the increasing prevalence of big data, the ability to create interactive dashboards that allow users to explore data and gain insights will become increasingly important. Interactive dashboards allow users to quickly and easily manipulate data, visualize trends, and identify patterns and outliers. This level of transparency and accessibility will enable stakeholders, with the support of our experienced analysts, to make more informed decisions about environmental impacts and sustainability.
Our team is monitoring the automation and artificial intelligence trends, especially in the context of data collection, analysis, and visualization. We anticipate that these trends and the subsequent tools could enhance efficiency, accuracy, and consistency in data collection, as well as thoroughness when identifying and comparing possible trends and patterns in data. This automation will leave more time for creative and thoughtful consideration when it comes to sharing visualizations and insights. In addition, we anticipate that artificial intelligence will assist in streamlining the process of creating visualizations with more automated tools.
We plan to stay at the forefront of this field by continuously learning and adapting to new technologies and methodologies. This includes staying up to date on the latest developments in data visualization and automation, attending conferences and workshops, and collaborating with other experts in the field. By doing so, we can help to drive innovation and ensure that our clients receive the most advanced and effective solutions for their needs.