Tag Archives: procurement

Home › procurement

Uncovering the Most Vulnerable in Times of Crisis: Analyzing Procurement Capacity Index with Multi-Criteria Decision-Analysis

Comment

Featuring a published paper by one of OCDex’ fellows, Engr. John Raymond Barajas of Bicol University College of Engineering

Abstract:

This paper presents a multi-criterion decision analysis approach to developing a procurement capacity index for local government units (LGUs) in the Philippines. The index serves to assess the resilience of LGUs in times of crisis, particularly in the context of the COVID-19 pandemic. This study utilized two open datasets published by the Philippine government from January to June 2020, and identified five criteria for the procurement capacity index: total approved budget of the contract, internal revenue allotment, number of awarded tenders, number of tenders posted, and fund utilization rate. This study then employed the criterion impact loss (CILOS) method to determine the weight vectors of the identified set of criteria, and calculate the index as a weighted sum based on these vectors. This study found that the fund utilization rate and internal revenue allotment are the two most important criteria for determining the capacity of an LGU to secure goods or services during a crisis such as the pandemic. This insight is consistent with observations drawn from use cases in the US, UK, and Canada as revealed in reviewed literature. Results also revealed that LGUs can be categorized into three clusters based on their procurement capacities: low, medium, and high. Moreover, the developed index facilitated the ranking of LGUs according to their procurement capacity, revealing that LGUs located in Regions II, III, VI, VII, VIII, and X have insufficient budget allocation, thus strongly suggesting urgent intervention from the national government. Overall, the developed index can serve as a valuable decision aid tool to assist the government in identifying LGUs that need additional support to procure resources or services required to mitigate the consequences of a crisis.

Reach out to the author (or to us) for the full paper: https://ieeexplore.ieee.org/document/10137798

Public Data Analytics: Community Problem Solving

VOLUME 2 of the OCDex Public Data Analytics Series

Data science and analytics has demonstrated its power in informing decision-making and problem-solving. Data can reveal trends and insights that would have otherwise been obscured. It can give decision-makers key information needed to craft effective and optimal solutions to organizational problems. It can help predict potential bottlenecks and challenges, so that organizations may come prepared when it happens. Data science and analytics is a sought out
skill in the digital age.

The Covid-19 pandemic and its resulting limitations on mobility has forced many transactions and communications to migrate from the physical space to the digital space. This sudden global digitalization resulted in an increase in data produced and a subsequent increase in the potential game-changing insights that these data may be hiding.


While many in the private sector have been seen leveraging the power of data for business insights and maximization of revenue, the public sector is yet to catch up in terms of digitalization and data utilization, especially in developing countries. The power of data would especially help communities and local governments in coming up with efficient, effective, and inclusive policies and solutions to problems.


The aim of the 2022 OCDex project run is to bring data scientists and analysts together, and demonstrate how analysis of government data can be used to help solve problems in local communities. The project aims to demonstrate how it can help inform local policymaking and project planning, and how citizens and researchers can participate and help their respective local government units in overcoming community challenges hand-in-hand. This handbook hopes to convince local governments and authorities to invest in good data housekeeping and integrate data science and analytics into their decision-making.


This handbook features how academics and data enthusiasts used public data to help inform solutions to various community problems such as healthcare, inclusivity, and accessibility for persons with disabilities, fairness, and transparency in public procurement, and ensuring enough supply of utilities. Lastly, this handbook presents a replicable model of cooperation between local governments and their local researchers and data enthusiasts toward the effective use of data science and analytics for community building.

Loader Loading…
EAD Logo Taking too long?

Reload Reload document
| Open Open in new tab

For more information, questions, suggestions, and submissions, please e-mail learning@layertechlab.com

Reflections: How analysis of government data can help LGUs, NGAs, and local communities

Comment

Author: Roben A. Juanatas (CCIT – National University)

Analysis of government data, in my opinion, has the ability to bring about considerable change for the LGU or community. Local governments are particularly enthusiastic about promoting this new approach to community engagement. Many local governments have begun to see the value of analyzing government data for more open and transparent operations. The study of government data can assist the LGU in staying connected, informed, and up-to-date with their community’s day-to-day operations. 

Furthermore, this trend may aid the LGU in continuing to deliver and make decisions that are in the best interests of the community. It also opens up new possibilities for local government applications, boosts community interest, and can lay the groundwork for new technology innovation and economic progress. Furthermore, data analysis can provide relevant facts, which can serve to bring a community together and empower them to create the future.  

Finally, it is not simply the simplification of the community’s operations and proving progress toward strategic priorities that fosters community confidence through data analysis. It is important in a variety of government areas, including education, employment, manufacturing, agriculture, and criminality, to name a few. The information gathered in LGU can be used to develop strategic policies and provide insights to make better judgments. 

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: rajuanatas@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: Data to help Cities and Municipalities

Comment

Author: Nico O. Aspra (Bicol University)

In our generation today, technology has rapidly consumed everyone. It has rooted itself in the core foundation of modern society. With various age groups, even toddlers, access to technology is easy. As such, it has enabled agencies or companies to gather data from their users. With this accessible data, inevitably, advertisers specifically target consumers by their liking through the use of available information to gain more profit. With this in mind, this has revolutionized the advertising world from its traditional delivery to tailor-fitted advertisements. Policymakers can also utilize this strategy to tailor-fit the community’s specific needs. Local government units can benefit through data analytics by collecting and analyzing municipal- or city-wide information regarding a certain topic and thereby utilize this data to address problems or issues accordingly. Before the data even reaches the regional or national level, it can already be organized at the local level. Consequently, data will be more systematic and available at all levels of government, and if the data permits, challenges, and problems can be more easily addressed.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: nico.aspra@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: Data Analytics for Social Development

Comment

Author: Mary Joy Canon (Bicol University)

Exploiting data through machine learning and analytics has been a trend solution in helping the government and other organizations alleviate pain in terms of social and economic aspects. Tools and methodologies in data analytics are used to generate insights, to recommend actions and more importantly to assist authorities in policy-making and translating these analyses to sound programs which directly benefit the people.  Perhaps, different organizations through their projects have already contributed, through data science, to social development and welfare. Kaggle, for instance was able to predict poverty levels to identify where the highest need is for social welfare assistance. This kind of project wouldn’t have been possible without access to data.

In the Philippines, the aim of social development mandated under the Constitution is to enact measures to protect and enhance the right of the people to human dignity, reduce social and economic inequalities and remove cultural inequities. Open data and analytics offer significant contribution and opportunities for the government and other bodies to create social impact.

Humanitarian Data Exchange of OCHA publicly made available a consolidated dataset on social development from World Bank Open Data. Data covers child labor, refugees, gender issues and disparities with key topics on education, health, labor force participation and political participation. This compilation of data, once processed and analyzed can be utilized in projects for social impact. The analysis can serve as an aid to identify the social issues or concerns that need immediate action by making essential benefits and services more accessible to the people. Data scientists, government officials and social sector leaders can work together to come up with a data-driven solution to take a major step forward in providing social transformation.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: mjpcanon@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: The Importance of Analysis of Government Data

Comment

Author: Jimson Ornido (National University)

The purpose of government is to enable the people of a nation to live in safety and happiness. Government exists for the interests of the governed, not for the governors.

– Thomas Jefferson

Local government units play an essential role in the lives of their constituents and the community. In the National Capital Region alone, there are 16 cities and one municipality, consisting of 1710 barangays. Some of the functions performed by LGUs are as follows: taxation, law enforcement, administration, maintaining peace and order, providing public works, overseeing the local police force, and disaster management.

All of the mentioned functions involve a vast amount of data. Hence, data analysis is a crucial step in progressing the level of governance for LGUs. For example, disaster management will significantly benefit from the insights extracted from previous records. Contingency and emergency plans can be improved as a result.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: jvornido@national-u.edu.ph or Layertech labs support at learning@layertechlab.com


        	

        	        
        	        

    

	





    

                    
            

    	        
			
							

		            

                
        

        	

        		        	
        		
Maragondon and Ternate Tourism: Managing Riders and Businesses
        		                

        			         			Comment
        			        			        		

        		        		
        	

        	        	

        		

Author: Mark Emmanuel Malimban (National University)





Maragondon and Ternate are municipalities located in the southern part of Cavite. These rural areas are rich in history and culture: Ancestral houses, Churches, and Historical sites can be found here. Mountains and many types of bodies of water are also enjoyed by the locals and tourists.





Bikers and motorists were commonly seen roaming around the vicinity. These groups come in small to big groups mostly coming from other areas and cities. Popular destinations of these riders are the Kaybiang Tunnel and the stretch road of Maragondon-Ternate-Nasugbu with the scenic beaches; with these, a lot of businesses have sprouted in the area which helps the local and LGU.





The increase in riders in the area doesn’t only come with advantages, some unfavorable circumstances were also identified. LGU placed some necessary steps to reduce some of these inconveniences and concerns.





Data analytics can help in developing the policy for government efficiency and resiliency. Bikers’ regulations for compliance with national directives; peace and order structure for tourists especially riders; and management of businesses in terms of investment and promotion. Analysis can also be used as a reference in devising the Disaster Risk Reduction Plan and Local Risk Assessment.





Opportunities should not be wasted, they should be managed well to increase their potential. LGU Policies and regulations should be data-driven to ensure that all perspectives and opinions were considered. Managing and establishing appropriate directives for these bikers and motorists will ensure not just safety but also the progress of the community.





This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.





For more information about the article, please reach out to the author: memalimban@gmail.com or Layertech labs support at learning@layertechlab.com

        	

        	        
        	        

    

	





    

                    
            

    	        
			
							

		            

                
        

        	

        		        	
        		
Educated Spending: An Insight on SUCs Utilization of MOOE
        		                

        			         			Comment
        			        			        		

        		        		
        	

        	        	

        		

Author: Sittie NB Pasandalanb (Mindanao State University – Iligan Institute of Technology)





Despite the reality of reduced budgets of the education sector especially of state universities and colleges (SUCs), institutions of learning have a good share of the annual National Expenditure Plan of the government. Generally, appropriations of SUCs can be categorized into three: Personnel Services (PS), Capital Outlay (CO), and Maintenance and Other Operating Expenses (MOOE). Of these three categories, the MOOE should be of great interest as this gives insight to how a higher education institution (HEI) of the government utilizes government funds, ergo tax payers’ money.





MOOE is funds to be used for necessities (such as electricity and water) and for activities. HEIs are institutions expected to promote conservation of energy, it is worthy to look into the electricity and water bills of HEIs as these would speak of how HEIs are walking the talk. As employees of HEIs are taxpayers themselves, spending for activities should be examined to determine judiciousness in utilizing government funds, ergo taxpayers’ money. 





There is the disconnect between spending from one’s own pocket to spending from another’s pocket. Most likely, one finds it easier to spend from another’s pocket than one’s own. This begs the question of whether employees in HEIs (taxpayers in HEIs) can connect with the funds allocated to HEIs as taxes they have paid to the government, ergo their money. 





In the case of MSU-IIT, the MOOE for 2021 amounted to Php 297,321,732.24 (from Php 222,402,237.68 in 2020). The question on how the amount was utilized and if the expenses are necessities or mere expenditures to utilize funds allocated by the government begs to be answered. 





This article is a reflection on the OCDex 2022 Fellowship Programme for Researchers





For more information about the article, please reach out to the author: sittie.pasandalan@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

        	

        	        
        	        

    

	





    

                    
            

    	        
			
							

		            

                
        

        	

        		        	
        		
Predicting Public Procurement Irregularities in the COVID-19 Response of Local Government Units (LGUs) in the Philippines
        		                

        			         			        		

        		        		
        	

        	        	

        		

Authors: Barajas, J.R., Aspra, N., Gealone, P.J., Lucero, A., Padua, O., Ramos, M.





Motivated by ensuring transparency, fairness, and efficiency in public procurement at the time of the COVID-19 pandemic,  a team of engineers and faculty from Bicol Region (Region 5) in the Philippines collected, digitized, and analyzed public procurement data to inform the COVID-19 response of select Local Governments in the country. 





Highlights of the Report:





• On average, only 2 out of 10 LGU contracts have been awarded in
2020.

• For every Php1 spent, approximately Php1 remains unspent in
the procurement of goods and services made by LGUs.

• A total of Php481 billion were distributed across all LGUs in the country
for 2020 but only 10% of this budget was allocated for the procurement
of drugs and medicines. 40% of this budget went to construction
projects.

• Excluding LGU contracts not posted in the PhilGEPS website, only Php10
billion (2.16% of the total LGU budget) was allocated for COVID-
19 related contracts.

• An equivalent amount of Php720 million was potentially lost from 786
LGU contracts flagged as irregular.

• Audit findings for LGUs were primarily centered on directing accountable
officers to comply to documentary requirements mandated by existing
circulars, memorandums, and Philippine laws.

• A logistic regression model with an accuracy of 91.29% was developed
to identify contracts that are potentially irregular.





Short Summary of the Report:





From examination of 296,220 local government unit contracts, this project was able to develop a logistic regression model capable of predicting potentially irregular LGU contracts posted on the PhilGEPS website for the fiscal year 2020 at an accuracy of 91.29%. Validation of the model using metrics derived from the confusion matrix revealed that the developed model had a recall score of 1.0 and a precision score of 0.029. While the precision of the model may be
low, the high recall score is deemed more important in this use-case since it would be more costly for an LGU to miss out on irregular contracts. Overall, the developed prediction model is seen to be highly beneficial as a decision
support tool for LGUs since this could potentially narrow down the number of awarded LGU contracts to be legally reviewed resulting in a faster turnover of review cycles conducted within a given fiscal year.





The team’s collected datasets are available for download in the OCDex open data portal, attribution to the authors and contributors is required for use.





DOWNLOAD FULL REPORT HERE:




			

				

					

						

							Loader
							Loading…
						

					

					

						

							EAD Logo
							Taking too long?
						

						

							

								Reload Reload document							

							|
							
								Open Open in new tab							
					

				

			

		




Are you interested in this report? Do reach out to us at learning@layertechlab.com so that we can directly connect you with the authors, as well as the documentations they submitted.  

        	

        	        
        	        

    

	





    

                    
            

    	        
			
				Procurement Analytics Handbook			

		            

                
        

        	

        		        	
        		
Public Procurement Analytics Handbook – Volume 1
        		                

        			         			Comment
        			        			        		

        		        		
        	

        	        	

        		

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.





DOWNLOAD THE FIRST VOLUME of the Procurement Analytics Handbook for FREE HERE:




			

				

					

						

							Loader
							Loading…
						

					

					

						

							EAD Logo
							Taking too long?
						

						

							

								Reload Reload document							

							|
							
								Open Open in new tab							
					

				

			

		
Download [14.86 MB] 




For more information, questions, suggestions, submissions, please e-mail learning@layertechlab.com