By Prof Albert Sanchez-Graells, Professor of Economic Law (University of Bristol Law School).
While carrying out research on the impact of digital technologies for public procurement governance, I have realised that the deployment of artificial intelligence to promote sustainability through public procurement holds some promise. There are many ways in which machine learning can contribute to enhance procurement sustainability.
For example, new analytics applied to open transport data can significantly improve procurement planning to support more sustainable urban mobility strategies, as well as the emergence of new models for the procurement of mobility as a service (MaaS).* Machine learning can also be used to improve the logistics of public sector supply chains, as well as unlock new models of public ownership of eg cars. It can also support public buyers in identifying the green or sustainable public procurement criteria that will deliver the biggest improvements measured against any chosen key performance indicator, such as CO2 footprint, as well as support the development of robust methodologies for life-cycle costing.
However, it is also evident that artificial intelligence can only be effectively deployed where the public sector has an adequate data architecture.** While advances in electronic procurement and digital contract registers are capable of generating that data architecture for the future, there is a significant problem concerning the digitalisation of information on the outcomes of past procurement exercises and the current stock of assets owned and used by the public sector. In this blog, I want to raise awareness about this gap in public sector information and to advocate for the public sector to invest in learning what it already owns as a potential major contribution to sustainability in procurement, in particular given the catalyst effect this could have for a more circular procurement economy. (more…)