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Use (and Processing) of Sold Products : Processing Guide

Step-by-step guide for processing sold products data in Greenly: choosing the right module, running the analysis, and reviewing results.

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Written by Support

Overview

This guide covers how to process use and processing of sold products data, from choosing between the Lightweight and Advanced modules to reviewing data quality after upload.

Key use cases

  • Processing sold products data using the automated Lightweight module

  • Running a manual analysis with the Advanced module for complex product portfolios

  • Rebaselining historical data with updated emission factors

1. Align with client requirements

This module can be difficult to fill when product data is limited — estimations are acceptable for this scope, so reassure clients accordingly.
Choose the right module based on data availability:

  • Lightweight module (preferred): best when energy consumption per unit is straightforward to estimate. Allows full client autonomy from data collection to processing.

  • Advanced module: use only if the Lightweight module cannot be used (e.g., complex product portfolio, non-final products).

2. Process the data

⚠️ If working on a multi-year account, check the Rebaselining section below before starting.

Lightweight module (automatic)

No manual processing required — the module handles everything automatically.

Advanced module (manual processing)

Follow these three steps:
​Step 1 — Data collection
Use the data collection template (EN / FR) to collect for each product:

  • Product name

  • Section (optional — for qualitative analysis only)

  • Type of product: final, intermediate, component, or digital

  • Country of usage (if the product consumes electricity)

  • Annual or daily energy consumption per unit, with associated energy type and unit

  • Expected lifespan and allocation percentage (when applicable)
    The product type selected unlocks the relevant fields in the subsequent tables.
    ​Step 2 — Data analysis
    Copy the analysis template into the client's folder, then:

  1. Go to the "Calculation" tab (EN or FR, matching the data collection file language).

  2. Paste the URL of the data collection file in cell D10 and grant access to the import range formula.

  3. Select the correct version of the data collection template.
    Data is automatically imported into the raw data tab. If the template was correctly filled, the calculation is fully automated — each energy type and unit is mapped to the right emission factor. The total emissions appear in the last column.

    ⚠️ Make sure the tab names in the data collection file haven't been renamed, and that the file is saved as a Google Sheet (not.xlsx) so the sheet connection works.
    For custom use cases (non-standard units or EF types), add them in the "Database and EF IDs" tab.Step 3 — Data export 1. Go to the "To Module" tab.

  4. Download the generated table as a CSV.

  5. Upload it to the "Use of sold products" Advanced module in Greenly. All emission factors use an override under the USE_OF_SOLD_PRODUCTS purchase category, or PROCESSING_OF_SOLD_PRODUCTS for intermediate products.

    💡 If the unit gal (US) appears in the export tab (it is converted internally in the calculation tab), copy the data to another tab and replace gal (US) with l before exporting the CSV.

Rebaselining

Rebaselining applies the latest emission factors to the base year to enable year-on-year emission comparisons.
​Before starting:

  • Check if a similar analysis exists for previous years.

  • Confirm with the deal owner / client whether rebaselining is planned.

  • Ensure module consistency across years — avoid mixing Lightweight and Advanced modules for the same category between the base year and the current year.

    ⚠️ Do not proceed with rebaselining without aligning with the deal owner/client on specifics (custom EFs, EF exclusions, PC overrides, etc.)
    ​Automatic rebaselining (Lightweight module): Updating the activities is sufficient — the module handles the rest automatically.Manual rebaselining (Advanced module): Use only when the dataset to rebaseline is very small, or when the client wants to switch to a different EF database. Update the emission factor in the module or in the analysis file and rerun the analysis. Aim to harmonize categorization across years as much as possible.

3. Review the data

After uploading, go to the "2. Review" section:

  • Duplicate expenses: For sold products, no expenses should normally be flagged as duplicates.

  • Data Quality checks: Review any activity data that deviates from expectations. If no checks appear, everything is valid. Otherwise, review and correct as needed.

FAQs

The client doesn't have precise product data, what should we do?

Estimations are acceptable for this scope. Work with best-available estimates and reassure the client. If energy consumption per unit is easy to estimate, the Lightweight module is the right choice. For more complex portfolios, use the Advanced module.

When should I use the Advanced module instead of the Lightweight?

Use the Lightweight module by default. Switch to the Advanced module only when the Lightweight cannot cover the client's needs — for example, for non-final products or when specific EF requirements apply.

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