Using Data Analytics in Public Procurement Operational Options and a Guiding Framework
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,...
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Format: | Report |
Language: | English |
Published: |
Washington, DC
2022
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Online Access: | http://documents.worldbank.org/curated/en/099030105172217504/P1750330d968020ee0b60d01ec17bb14115 http://hdl.handle.net/10986/37467 |
Summary: | 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. |
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