Working at Bit as a researcher, we married mixing qualitative and quantitative methods in researching variables that could be affected (relatively) easily and would have a positive impact on CO2 emissions.
The brief
Working as a design researcher at Bit, we worked together with a European airline company to explore if and how data and machine learning could help them minimize CO2 emissions.
The approach
Mixing qualitative and quantitative methods, we worked closely together with designers, researchers, data scientist, and ML engineers. The qualitative approach included interviews with pilots, stewards, planners, management, and other staff. We translated our insights into hypotheses the data team could seek to (dis)confirm in their data exploration. Overlaying our qualitative insights with the sample dataset provided by the client, we were able to find a handful of variables that could be affected (relatively) easily and would have a positive impact on CO2 emissions.
The deliverable
We presented the qualitative and quantitative insights and next steps. The data team went on to build a predictive model that could simulate the impact of the variables thus informing stakeholders how to plan/fly/organize the flights to minimize CO2 emissions.
The team
I was a researcher on the project responsible for co-designing and conducting the research, synthesizing insights, and help present the final results to the client team.
About Bit
Bit is a research and prototyping studio run by 50 young tech talents, on a mission to fast-forward the impact of emerging tech.
