The dashboard is a functional journey analysis tool. The main objective is to provide a higher-level analysis than the results displayed on the Workshop, with a notion of journey. We detail here :

Calculation method

Global Ecoscore

The Ecoscore is a score out of 100 with a dual purpose:

• Represent the quality of a functional journey in terms of performance, data and energy

• Compare with other functional journeys

The overall Ecoscore is the average of the 3 metrics analyzed:

• Performance

• Data consumption

• Energy consumption

It is used to award a Greenspector eco-design label level:

• Gold level - 100 à 90

• ​ Silver level - 90 à 70

• Bronze level - 70 à 50

Critical and non critical steps

Critical stages are entry points to functional domains with a theoretically higher number of visits than other steps. This makes it possible to assess whether or not the quality of the path is strongly impacted by bad critical steps.

The overall score for a metric is the result of a weighted average:

• 0.7 for the score of critical steps

• 0.3 for the score of non-critical steps

Metric calculation

Example of performance calculation:

• Each step of a user journey is analyzed for each metric: performance, data, energy, etc.

• A specific threshold per type of step is applied to obtain a score out of 5

• A weighted average is used to obtain an overall score

On some metrics, there are unmonitored steps:

In fact, pauses are not taken into account in performance.

This gives us an indicator that is representative of the quality of a functional journey, regardless of its length. It does not depend on the estimated environmental impact.

Dashboard sections

Header

List of fields and their correspondences in the definition file :

Synthesis

This section gives an overview of the results. It gives a good idea of the quality of a functional journey, without necessarily going into detail.

1. Total number of steps measured without reference. Check that this corresponds to the number of steps defined in the definition.yml.

2. Ecoscore previously described

3. Main performance, data and energy metrics. We find :

   • The total value of the metric for the journey :

     • Time in seconds for performance, action and loading steps only.

     • Consumption in MB for data

     • Consumption in mAh for energy

     • Unlike the scores, these values depend on the length of the course and are given as an indication.

   • The evolution when comparing several versions, in the unity of the metric :

     • Decrease above 10%

     • Stable evolution

     • Increae above 10%

   • Overall metric score for the service tested

4. Details of critical and non-critical step scores.

Notes by step

This graph represents the scores for each step along the journey. Line-by-line analysis is not necessary, but the graph gives a good overview of the trend. We will concentrate instead on analyzing the last steps, which are the worst and those to be treated in priority.

Metric detail

1. Metric of the section

2. Analysis of all types of steps. It allows you to identify common tendencies between different types of step.

3. Main analysis :

   • Performance : load steps

   • Data : load steps

   • Energy : load, action, scroll steps

4. Secondary analysis :

   • Performance : action, scroll steps

   • Data : pause, action, scroll steps

   • Energy : pause steps

5. Analysis by functional domains in definition.yml, parameter domain. It highlights the functional domains with the strongest impact for each metric.

Example of performance load steps:

• The title reminds us of the metric and the steps analyzed.

• The blocks set the number of steps per threshold according to the type of step.

• The graph displays the colors associated with each step's score.

Specificity of energy

In order to harmonize consumption between terminals, the threshold used is a multiplier of the reference consumption of the phone in inactivity. The energy rating of the steps is based on the ratio of the step's energy discharge speed to the reference.

The unit used is the microampere per second, µAh/s, which represents the instantaneous discharge speed of the battery and is independent of time.

In this example :

• 1 step consumes less than 1.05 times the reference

• 6 steps consume between 1.05 and 1.5 times the reference

• 2 steps consume between 1.5 and 2 times the reference

• 1 step consumes between 2 and 3 times the reference

As the unit used is unusual, additional graphs in milliampere hours, mAh, are available:

• All steps combined

• Loading, action and scroll steps

• Pause steps

We use the following equation:

This graph offers a new analysis perspective:

• CHRGT_product is not the step which have the highest instantaneous consumption (µAh/s).

• But it's a long step, and its total energy consumption (mAh) is the highest.

• The reference, at the bottom, puts each charging step into perspective: CHRGT_product consumes almost twice as much energy as the device at no activity for 30s.

In this graph :

• Height corresponds to instantaneous discharge speed in µAh/s

• Column width corresponds to step duration

• The area of the column therefore represents energy consumption.

This graph can be used to highlight steps that are abnormally long, or steps that consume abnormally high amounts of energy, even though they are short.

Environmental impact

You can directly visualize the environmental impact of a functional journey by completing the section environmentalinput in the file definition.yml.

1. The environmental impact of a complete journey is calculated on three metrics:

   • Greenhouse gas emissions

   • Water use

   • Land surface use

2. The calculation date can be used to check the version of the environmental impact API.

3. Distribution of greenhouse gas metric by origin, with projection uncertainty. More precisely :

   • Terminal depends on energy metric

   • Network depends on data metric

   • Servers depends on the number of requests specified with the parameter reqnetwork

The impact of the terminal is generally the most important, especially for mobile applications with few network exchanges.