A quick overview of each section reveals any apparent problems with the service being measured. An overall assessment can be deduced from this:
Slow but energy-efficient service
Fast but energy-hungry service
Energy-efficient but high data consumption
etc.
Analysis of the dashboard should help identify optimization levers. Two situations are possible:
Most of the steps are bad on one metric. Analysis will be simplified with a lot of problems to notice.
Some steps behave far from the average. We need to be sure that this is not a measurement error. We then need to go into a more in-depth analysis and focus on these steps.
Start analysis of the dashboard in this order:
Performance
Data
Energy
This makes it possible to construct an argument such as :
Performance analysis shows that step X is time-consuming
Data analysis associates step X with high data consumption
Energy analysis links this data consumption to high energy consumption
What the dashboard doesn't show Ecoscore calculation does not depend on the number of steps, and this can mask problems of ergonomics and journey design. A journey with many well-optimized steps will have a good Ecoscore. However, the environmental impact and duration of the journey will be poor. |