8 min read

Data as a key driver for sustainability

Read about how we use generative AI and spreadsheets to drive data-driven sustainability, empowering businesses to make eco-conscious choices without compromising efficiency. We aim to democratize advanced data management and analytics for a sustainable future.
Written by
Published on
October 13, 2023

In an era of growing environmental concerns, improving supply chain sustainability is paramount. Businesses recognize the financial and ecological benefits of sustainability, but the missing link is data. The inability to access and utilize relevant data hinders progress. Talonic.ai emerges as a solution, harnessing generative AI and spreadsheets to provide data-driven insights, empowering individuals to enhance efficiency and reduce environmental impact. This data-driven approach enables businesses to make more sustainable choices while maintaining cost-effectiveness, ushering in a significant shift in global operations. By offering a simplified example, the article illustrates the power of data-driven decision-making, from procurement to logistics, stock management, and vendor assessment. Talonic.ai aims to make cutting-edge data management and analytics accessible to all, revolutionizing sustainability practices.‍

As the world grapples with pressing environmental concerns, the importance of improving the sustainability of our supply chains has become more critical than ever. After all, they are the main causative agent to greenhouse gas emissions and social labour issues. And as businesses are increasingly recognize that sustainable practices not only benefit the planet but also yield financial advantages through efficiency improvements and enhanced  reputations, the stakeholders seem aligned. But why do businesses struggle so much with identifying and carrying out the necessary change?

The reason is missing data. In my MBA Dissertation at Warwick I spoke with over two dozen high tier managers from large businesses, and since we’ve founded Talonic I have spoken to many more. The problem seems universal across industries and company divisions: everyone knows about the pressing sustainability issues, everyone wants to do something about it, but no one knows how to. The individuals who could make an impact simply don’t know how, simply miss the data on it to inform their decision-making. It sounds trivial, but it isn’t: if you don’t know the impact of your decisions on the environment and humans beyond the abstract, how can you make better decisions?

In this context, Talonic.ai emerges as a powerful tool to enable data driven businesses, enabling individuals to boost their organization’s efficiency and trimming down their environmental footprint in the process. We just leverage a tool literally every professional already works with: spreadsheets.

By consolidating all your data to these spreadsheets, generative AI can understand the context of your work and use data analytics out of the box to better inform your decisions. This is the first step for a more comprehensive view of your business, building over time, until our AI has understood enough about your operations that additional insights and data about sustainability can be funneled right into your viewpoint. This is Phase 2 of Talonic.

It seems marginal, but it isn’t. A whopping 100% of the managers I’ve spoken to have told me that they will always prefer the more sustainable option of many if they have a lower environmental impact and come at the same costs. Over three third told me that they’d be willing to overcome internal politics to chose the environmentally friendlier option if it comes at slightly higher cost. And that is already all we need to achieve a significant improvement on global operations.

To put this in practical context, imagine someone in procurement selecting a supplier to order a component they need for manufacturing. Normally, they have always ordered at the same place — it’s just convenient. But this time, when the decision is made, the manager is informed that another option at the same cost will cause 30% less carbon emissions and has no risk for forced labour, compared to the routine supplier. They might as well put in the effort to break their routine and try their other option.

This is a very simplified example and only one of many use cases: from improved logistics, better stock management to save on overproduction, to better vendor assessment: data is always at the core of it. So stay tuned for our vision of making state-of-the-art data management and analytics accessible to everyone.

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