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Analyze your impact with the explanatory factors

The explanatory factors allow you to take your impact analysis a step further. On this page, you will find a number of options that will help you to see the entity’s hotspots and how the impacts are distributed across your product’s various flow.

The Explanatory factors page is divided in two parts.

“Explorer”, the first one contains:

“Grouping”, the second one contains:

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How to analyze your impacts with the explanatory factors?

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Consult the products hotspots

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This first part provides an overview of the different impact flows according to the scale of their impact.

You can :

<aside> ℹ️ Some of the impacts could be negative, but this is not a mistake, it's the fact that the end-of-life process adds value to the product.

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Example of hotspots

Example of hotspots

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Navigate throught the Sankey diagram

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The second part displays a Sankey diagram.

<aside> 📌 The Sankey diagram associated with environmental footprinting is a visual representation of product life-cycle impacts, in which the width of components or raw materials is proportional to the environmental impact of the associated phase. From left to right, the impact is broken down from the finished product to the raw material or process data set.

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You can open it in full screen mode to navigate through it and change the number of levels you want to display in the graph.

Navigate through the impact of your products, either by clicking directly on the graph, level by level, or in the “Life cycle sub-stages” window.

The “Activity data related to this life cycle sub-stage” section allows you to see the various activity data related to the impact of the sub-stage you are currently in.

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The diagram can be exported in TSV format for copying and pasting into an Excel file.

When you reach the last impact node, you will see which dataset has been used.

<aside> 👉 You can deepen your analysis thanks to the raw dataset and have more detailed information on the data used to evaluate your product (UUID used to identify the data, technology and validity for the detail the data have been developed, version and so on

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Other interesting tips

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