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How Will Data Science Speed up the Circular Economy?

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How Will Data Science Speed up the Circular Economy?

Actionable data science suggestions to beat the operational challenges in transitioning to a circular economy

Towards Data Science
(Image by Writer)

A circular economy is an financial system where waste is minimized and resources are repeatedly reused or recycled.

Imagine a world where your waste doesn’t find yourself in landfills but relatively becomes the raw material for brand spanking new products.

The transition from our current linear economy to a more sustainable circular one is a significant topic for a lot of firms.

What’s holding us back?

As the present linear economic model reaches its limits, discussions around recent circular business models turn into increasingly more outstanding.

Advantages of a Circular Economy — (Image by Writer)

These discussions mainly concentrate on

  • The operational and business obstacles blocking the transition
  • Alternative strategies to extend the usage of recycled materials
  • Rental models to scale back the environmental footprint
Data generated by systems used to administer a supply chain network — (Image by Writer)

Because the analytics manager of a retail company, how can I support this transition?

Analytics experts can leverage the info generated by systems to beat these barriers by identifying opportunities to create a sustainable and profitable circular supply chain.

In this text, we’ll step into the shoes of an analytics manager who has been asked to support the operational transformation of a fashion retail company.

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Summary
I. Transition to a Circular Economy
1. What's the environmental impact of a T-shirt?
2. Data-driven Process Design
II. Overcoming the…

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