Both of our organizations wanted to find more ways to use data to reduce the team's emissions. And so, the next stage of the journey began: to create a carbon-emissions calculator that could help the team make more informed and environmentally sustainable travel choices.
The calculator gathered data such as the distance between two locations and used a machine-learning model to predict what the journey would involve and gave the team travel recommendations based on carbon output. Each user could see just how big or small their footprint would be when traveling between races or for business meetings.
The calculator helped the company make decisions between journey time and carbon use. And the additional visibility helped with resource planning and deciding who would go to a race or whether a meeting could be held virtually.
Each season, the team sets a carbon-reduction target. Employees could use the calculator to contribute to the goal.