ESG has quickly grown out of investment philosophies into a broader set of core strategic positioning for businesses. In this shift from meaningful change to measurable value, the biggest challenge for businesses is to have standardized and consistent data from a variety of sources, structured or unstructured keeping in mind the regulatory frameworks. 

‍

With the ESG data still being very thin (almost non-existent for private companies) and frameworks and standards still being defined, businesses are looking for efficient ways to build the most complex part of the ESG data asset - their Supply Chain. 

‍

SPAR (Sustainability, Predict, Assess & Refine) is an innovative, AI-powered verticalized solution. It is created in collaboration with leading sustainability industry experts to address this increasingly prevalent and complex challenge faced by organizations globally. Other than businesses with complex supply chains, this solution will be equally relevant for asset managers, their portfolio constituents and their respective supply chain - one of the driving forces to build the most comprehensive ESG data asset.

‍

The solution  will not only enable businesses to simplify and efficiently identify their supply chain’s exposure to sustainability-related risks; but also seamlessly manage and mitigate those risks in a timely and cost-effective manner.

‍

SPAR is able to simplify the supply chain sustainability risk management process by automating relevant ESG data point aggregation, as well as information capture from supplier documents, then processing both through a purpose-built scoring algorithm and finally delivering clear and concise output and guidance to the user.

‍

With SPAR, businesses  can now truly transform and manage their supply chain's sustainability in just seconds. 

‍

Refer to the video below for more details.

‍

‍