Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight:
The world spent USD 11 trillion on public procurement in 2018, amounting to 12 percent of global GDP (Bosio and others 2022). Given these substantial volumes, public procurement can contribute to several objectives: savings, integrity, economic growth, inclusiveness, and sustainability. Procurement...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Washington, D.C
The World Bank
2022
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| Schriftenreihe: | Other papers
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| Online-Zugang: | kostenfrei |
| Zusammenfassung: | The world spent USD 11 trillion on public procurement in 2018, amounting to 12 percent of global GDP (Bosio and others 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 |
| Beschreibung: | 1 Online-Ressource |
| DOI: | 10.1596/37467 |
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| 520 | 3 | |a The world spent USD 11 trillion on public procurement in 2018, amounting to 12 percent of global GDP (Bosio and others 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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| spellingShingle | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight Conflict of Interest Corporate Data and Reporting Equity Governance Macroeconomics and Economic Growth Private Sector Development Public Sector Development Transparency |
| title | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_auth | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_exact_search | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_exact_search_txtP | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_full | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_fullStr | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_full_unstemmed | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_short | Using Data Analytics in Public Procurement Operational Options and a Guiding Framework Equitable Growth, Finance and Institutions Insight |
| title_sort | using data analytics in public procurement operational options and a guiding framework equitable growth finance and institutions insight |
| topic | Conflict of Interest Corporate Data and Reporting Equity Governance Macroeconomics and Economic Growth Private Sector Development Public Sector Development Transparency |
| topic_facet | Conflict of Interest Corporate Data and Reporting Equity Governance Macroeconomics and Economic Growth Private Sector Development Public Sector Development Transparency |
| url | https://doi.org/10.1596/37467 |
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