How Will Data Science Accelerate the Circular Economy?
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A circular economy is a system where waste is minimized and resources are continuously reused or recycled.
As the current linear economic model reaches its limits, discussions of new circular business models become increasingly prominent.
What is holding us back?
These discussions mainly focus on
- The operational and business obstacles blocking the transition
- Alternative strategies to increase the use of recycled materials
- Rental models to reduce the environmental footprint
As a data science manager of a retail company, how can you support this transition?
We can leverage the data generated by systems to overcome these barriers by identifying opportunities to create a sustainable circular economy with Data Science.
In this article, we will assume the role of a data science manager who has been asked to support the operational transformation of a fashion retail company.
Summary
I. Transition to a Circular Economy
1. What is the environmental impact of a T-shirt?
2. Data-driven Process Design
II. Overcoming the Operational Challenges
1. The Opacity of Supply Chain Networks
2. The Low Residual Value of Used Products
III. Material Efficiency & Recycled Materials Usage
1. Raw Material Optimization with Linear Programming
2. Supply Chain Network Optimization
IV. ConclusionTransition to a Circular Economy
The evolution from a linear model to a circular economy is an ongoing process with significant business and operational implications.
This shift is not just about waste management or recycling.
It requires a holistic change in how we design, produce, sell and use goods or services.
Before implementing a circular economy, the first step is to estimate the environmental impact of our current linear model.
What is the environmental impact of a T-shirt?
Let's take the example of a T-shirt you bought in a fast-fashion store.
What is its environmental impact along its life cycle?
Life cycle assessment (LCA) is a methodology for evaluating the environmental impacts of a product or service over its entire life cycle.
- Raw materials are sourced from different suppliers that are using natural resources and energy.
- Manufacturing sites transform these materials into finished products using natural resources while emitting pollutants and CO2
- Finished products are delivered to stores and sold to final customers
- Customers are using the products until disposal
How can we support for the automation of Life Cycle Assessment?
This descriptive analytics methodology can be automated using Business Intelligence solutions implemented by our analytics team.
The challenge is to collect and process transactional data
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From different systems that may not communicate with each other Factory Management Systems vs. Warehouse Management Systems
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With different formats (Unstructured vs. Structured) Excel Utility Usage Reports vs. WMS Transactional Database(s)
