Supply Chain Sustainability Reporting with Python 🌲

4 steps to build an ESG reporting focusing on CO2 emissions of your Distribution Network

Supply Chain Sustainability Reporting

The demand for transparency in sustainable development from investors and customers has grown over the years.

Investors have placed greater emphasis on business sustainability when assessing an organisation's value and resilience.

Therefore, more organisations are investing resources to build capabilities for sustainability reporting and determine the best strategies for a sustainable supply chain.

Youtube Video

Click on the GIF below to access a short explainer video to understand the concept behind this solution

Article

In this Article, we will introduce a simple methodology to report the CO2 emissions of your Distribution Network using Python and PowerBI.

Definition

Based on the GHG Protocol corporate standard (Link), greenhouse gas emissions are classified into three scopes:

• Scope 1: direct emissions released to the atmosphere because of the company’s activities (Company’s facilities like manufacturing plant/warehouses, company’s vehicles)
• Scope 2: indirect emissions from the generation of purchased energy (purchased electricity, gas,...)
• Scope 3: all indirect emissions (out of scope 2) occurring in the value chain of the company (Transportation, Waste of Operations, Business Travels, …)

In this article, we focus on Scope 3 calculations for downstream transportation. What is the environmental impact of your distribution network?

Formula

Following the protocol of the French Environmental Agency Ademe, the formula to estimate the CO2 emissions of transportation is:

Formula using Emission Factor

Objective

1. Based on this formula, we collect and process data to calculate the emissions.

Data to be Collected

2. We calculate the unit of measure conversions considering the shipped handling units.

Handling Units

3. We add distances by mode and compute the CO2 emissions by order

Emission by transportation mode

Exemples of visuals using PowerBI

Bubble map with size = f(CO2 Total)

Bubble Map

Visual Insights

You can observe where you have the majority of CO2 emissions (large bubbles) with a colour coding by transportation mode.

Split by Country Destination and Item Code

Bar Chart

Product Portfolio Insights For each market, which item has the highest environmental impact?

Product Portfolio Insights

For each market, which item has the highest environmental impact?

CO2 = f(Turnover) by City Destination

Scatter Plot

Financial Insights

The impact of your future CO2 emission-reduction efforts on profitability will be greater for customers in PEINE-WOLTORF.

Code

In this repository, you will find all the code used to explain the concepts presented in the article.

Files

• Transportation CO2 Emissions Reporting.ipynb - Jupyter notebook with step-by-step analysis
• co2_emissions_reporting.py - Standalone Python script
• data/ - Folder containing input CSV files (order_lines.csv, distances.csv, etc.)

Getting Started

pip install -r requirements.txt
python co2_emissions_reporting.py

Dependencies

• pandas

About me 🤓

Senior Supply Chain and Data Science consultant with international experience working on Logistics and Transportation operations.
For consulting or advising on analytics and sustainable supply chain transformation, feel free to contact me via Logigreen Consulting.
For more case studies, check my Personal Website.