MINT: minimizing supply chain emissions

— 3 minute read

Earlier this year I met the brother of one of my friends. After I complimented him on this great T-shirt he was wearing, he started telling me about how he was launching his own clothing brand. He shared his vision for the brand: one that embraced sustainability, high-quality materials, and enduring appeal. Beautiful of course, but also modest and basic. Items designed to not only love today, but for the years to come.

Although I don’t know a single thing about fashion, but I do know that fast fashion and the excessive consumerism surrounding it have a big environmental impact. Our conversation turned to the myriad of decisions involved and how challenging it can be to evaluate all the different options. Where should he source the materials? Where should the T-shirts be manufactured? How sustainable is a sustainable production process if it results in a significant increase in transportation distances? Where is the trade-off? What is the impact on the cost price? And which transportation modes result in the minimum emissions while still ensuring acceptable delivery times?

Making “the right decision” is far from straightforward; it is often a very complex puzzle. Luckily, there are methods to model and navigate these intricacies and find the overall best possible solution among the available choices. Once we’ve modeled our supply chain, we can instruct our model to minimize the emissions across the entire supply chain while adhering to various constraints such as meeting demand and respecting production capacities. We can hit the button and let our model, the digital representation of our supply chain, make the difficult decisions for us.

Though the concept of “supply chain digital twins” is becoming prevalent in larger companies, it’s still unknown to many small enterprises. And even if they are aware, they often do not have the financial means to adopt these tools. Although there are many excellent tools on the market, they are too expensive and their implementation is too time-consuming. For small and starting businesses like my friend’s T-shirt brand, finding a suitable supply chain optimization tool is a challenge.

And that’s a missed opportunity. To make informed decisions, we need data, facts, and numbers. So I figured I’d build him a solution myself. The outcome: MINT, short for emissions MINimitzation Tool.

MINT is a hobby project. It's not all-encompassing, not complete, nor perfect. Much more so, it is a means to showcase the potential of mathematics in solving our most pressing issues.

Curious? You can explore MINT here. Load in your supply chain data in the data template and experience it firsthand!