Using Data Analytics in Public Procurement Operational Options and a Guiding Framework - World Bank (Washington, DC, 2022)
The world spent $11 trillion on public procurement in 2018, amounting to 12 percent of global GDP (Bosio et al. 2022). Given these substantial volumes, public procurement can contribute to several objectives: savings, integrity, economic growth, inclusiveness, and sustainability. Procurement Data Analytics (PDA) can contribute to the achievement of these objectives. It refers to the use of data to generate actionable insights and evidence to monitor outcomes, inform the policy dialogue, guide reform efforts, and assess the impact of reforms and strategies in public procurement. Despite a growing academic literature and impact evaluations on public procurement, the existing body of evidence is still scarce and limited to a few countries. This impedes drawing generalizable lessons on optimal policies and strategies to achieve the multi-layered objectives of the public procurement function, therefore highlighting the need for a larger adoption of data analytics tools in this area. With the increasing adoption of electronic government procurement (eGP) systems and the corresponding digitization of transaction records, public procurement has enormous untapped potential for the application of data analytics tools. This paper highlights the successful approaches and good practices of previous PDA work and provide useful resources to World Bank teams with country engagements relating to public procurement. Possibly interesting to a broader audience, an analytical framework is also discussed to guide the application of data analytics tools in public procurement, data sources, the open government agenda, and data standards.