Kodiak Rating: Blockchain-Based Tool For Transparent Supply Chains
Reference number | |
Coordinator | CSV Rating AB |
Funding from Vinnova | SEK 800 415 |
Project duration | May 2018 - September 2019 |
Status | Completed |
Important results from the project
The prototyped tool enables sharing of sensitive data in a safe manner between a buyer and supplier, inherently increasing the transparency, insight and trust between supplier and buyer, encompassing a wide scope of performance criteria - including ESG/ social and environmental impact performance. Through this we have further the SRM solution space, enabling pairing advanced business intelligence analytics, with blockchain technology, creating a blueprint of how companies can be transparent, and collaborate to drive sustainability improvements in all parts of the value chain.
Expected long term effects
The prototyped tool will be an innate part of the next-generation Supplier-Buyer Relationship Management. It will be easier and safer to share data, measure, evaluate and analyze and thus to reward the suppliers who can show that they improve their performance in areas such as ESG compliance, social responsibility, CO2 footprint and environmental impact. The fact that a customers and buyers can evaluate a supplier based on reliable data within a large number of performance areas, will increase transparency and accelerate positive changes at every stage of a value chain.
Approach and implementation
The project has been implemented in four phases; WP1 - Market study; WP2 - Technical Study, WP3 - Development of Prototype and WP4 - User study together with customers. Blockchain as a means to enable easy access to supplier data beyond what is presently available, will enable companies to engage in responsible sourcing. The insights in 1&2 led to the prototype enabling data to be collected in a simple and safe manner, providing analytics that could be compared across organizations, industries and geographical areas, built in a way that it would cater for future application of ML & AI.