Fair, transparent, and efficient government procurement benefits the public. In this information age, where insight generation from big data has proven to be powerful, using the tools of Data Analytics can help ensure integrity and transparency in public procurement.
From years 2018 to 2020, Layertech has worked under the support and grant of Hivos’ Open Contracting programme on improving government procurement data use and disclosure. Layertech worked with the Local Government Unit (LGU) Legazpi city, academic institutions such as Bicol University and Southern Luzon Technological College, individual business owners and business organizations such as the Albay Chamber of Commerce and Industry, and Civil Society Organizations (CSO) such as Gayon Bicol LGBTQI organization and their regional network.
This compilation was produced to share experiences and methodologies of Layertech and partners, in mining government procurement data to answer advocacy-related questions of CSOs; to generate business insights; to help suppliers and procuring entities identify bottlenecks and inefficiencies in various procurement stages; and, to uncover trends and red flags in the procurement process.
Target readers of this handbook are assumed to have basic working competency in mathematics, statistics, and basic data manipulation. Working knowledge in coding such as in R and Python, would allow the reader to better appreciate the use-cases and replicate them.
Please NOTE that this handbook focuses on the data sources, filtering, and modelling methods used. Links to the papers (published AND manuscripts) are provided at the end of every use-case, and it is encouraged that the reader visit the links to view the full papers and studies. Some of the papers featured in this handbook may be updated, supplemented, and improved in the future.
You are free to use the contents of this document in any way permitted by the copyright and related legislation that applies to your use. No permission is required from the rights-holders for non-commercial use. Please credit and/or link to www.OCDEX.tech and Layertech Labs.
Attribution and USE of Handbook
Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.
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