Sustainability Measurement & AI Expert | Advancing Health, Equity & Climate-Resilient Systems | Driving Measurable Impact
Data is fundamental for decision-making, especially in sustainability, where it underpins efforts from measuring project impacts to evaluating policy effectiveness. However, in our rush to gather data, we often overlook a crucial question: is the information we need already available? Many times, organizations jump to new data collection projects without first examining existing resources, leading to unnecessary costs, wasted effort, and environmental impact. Building large analytics teams, purchasing third-party data, and conducting extensive surveys are standard practices, but failing to leverage existing datasets can contradict the core principles of sustainability. In my 15 years of experience working in the sustainability field, I have observed that many organizations don’t make the best use of available data. Too often, the first response to a data need is to collect fresh data, even when high-quality datasets already exist. This results in redundant data collection efforts, with multiple surveys and analyses producing similar findings. For example, in one project, a detailed city transportation survey conducted by another team provided data on vehicle composition and age. Through an analysis of existing data sources, we achieved nearly identical results, showing that sustainable data use is achievable. This experience inspired me to look more critically at how data can be used effectively. In my recent analysis, I estimated Vehicle Kilometers Traveled (VKT) per day by car in different Indian cities using available car sales data and existing datasets. This approach allowed me to produce results that were comparable to findings from previous primary surveys, which typically involve extensive fieldwork and resource investments. Additionally, using existing data enabled me to go further by obtaining detailed breakdowns by car type, engine type, transmission type, and providing estimates across a larger number of cities than would have been possible with a single primary survey. The chart below visualizes the VKT estimates across different cities, illustrating how leveraging existing data can yield reliable results that align closely with other studies. This example underscores that sustainable data practices aren’t just about reducing costs; they’re also about minimizing environmental impact and making efficient use of existing resources. By strategically using what is already available, we conserve time, money, and energy. Effective data use in sustainability starts with clear objectives and a careful evaluation of existing resources. Before new data collection, we should ask: Why do we need this data? What level of uncertainty is acceptable? Can available data meet our needs? Sustainable data practices help save costs, reduce environmental impact, and improve efficiency by repurposing existing datasets instead of conducting costly and redundant surveys.