How can you use Data Science to select the best suppliers considering indicators for sustainability and social indicators?
Sustainable sourcing is the process of integrating social, ethical and environmental performance factors when selecting suppliers.
This involves assessing and evaluating suppliers based on a set of sustainability criteria, such as labour rights, health and safety, environmental impact, human rights, and more.
The aim is to minimize the negative impacts on the environment and maximize the positive social impacts.
Once you established measurable sustainability targets, you can use data analytics to assess suppliers' performances to select the best one to optimize your objective (cost reduction, CO2 emissions) while respecting social and environmental constraints.
Use data analytics to automatically select the best supplier with a mix of economic and environmental constraints
In this article, we will discover how to use data analytics to design an optimal Supply Chain Network to minimize costs and environmental impacts.
Sustainable Sourcing KPIs
Scenario: T-shirts Suppliers
Let us take the example used in the previous articles about life cycle assessment and circular economy.
You are a logistic performance manager in an international clothing group that has stores all around the world.
The company is sourcing garments, bags and accessories from factories located in Asia.
Stores are delivered from local warehouses that are directly replenished by factories.