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.
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.
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
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
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.
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.
(This article and the manuscript were submitted by the research team and may be updated in the future)
Education has always been a “primary commodity” in the Philippines. With the implementation of the Universal Access to Quality Tertiary Education Act (Republic Act 10931), State Universities and Colleges (SUC) in the country are now mandated to provide free education to all tertiary students enrolled in their programs. Because of this, about 3.2 million college students were reported to enroll in the year 2018 alone [1] and this number is expected to double due to the implementation of the said law.
The Effect of COVID-19 Pandemic to Tertiary Education
The current COVID-19 has crippled the delivery of tertiary education in the country. Nationwide suspension of classes from all levels was hence declared as a mitigation measure to control and contain the spread of COVID-19 across all regions in the country. As a result, a temporary academic freeze has been widely observed from March 2020 until July 2020. This has been the case since various SUCs in the country are still addressing the unresolved dilemma of balancing safety and delivery of quality education to all SUC stakeholders upon resumption of classes in August 2020.
The COVID-19 Challenge to Resumption of Classes
With the sense of urgency to resume all classes despite the COVID-19 situation in the country, it has been widely suggested that face-to-face classes be shifted to online modes of learning this August 2020 [2]. This proposed transition, however, has been met with a huge resistance by various faculty, administrative staff, and college students. In the banner “#NoStudentLeftBehind”, online classes have been dubbed as “anti-poor” and “education solely for the privileged” [3].
As recent facts stated, only 17% of college students have been reported to have the capacity to connect to the internet wherein only 5% of such students have stable internet connectivity at home [3]. With these cited facts, it is expected that enrollment to SUCs this academic year would plunge to at least 70% [4]. Shifting then to purely online modes of learning this August 2020, hence, may not be feasible given the present situation of college students in the country.
Readiness of College Students for Online Learning – The Case of Bicol Region
Through the research grant given by Layertech Software Labs, Inc. and Hivos – People Unlimited, a group of faculty researchers from Bicol University College of Engineering (BUCENG) conducted a feasibility study solely focusing on this present dilemma. The capacity of SUCs and their students, hence, to undertake this proposed transition to online classes this August 2020 were thus reported to be comprehensively studied. In a pilot study conducted in the nine (9) SUCs in Region V, 160 (about 60%) of the 242 college students who willingly participated in a survey conducted from June-July 2020 were reported to have a monthly household income below PHP25,000. Even prior to the pandemic, about 60% of these students largely rely on cellular phones to accomplish academic tasks given to them and this represented a recurring monthly expense of PHP1,000 on cellular data alone. It was also reported that this observed expense is expected to at least double when online classes are implemented this August 2020. With these facts, it is without a doubt that these less privileged college students will have the most disadvantage if a purely online mode of learning is implemented upon the resumption of classes this August 2020.
Assessment of SUC EATing patterns – The Case of Bicol Region
With these described evidences, enabling college students to undertake the proposed online transition would then largely rely on the capacity of SUCs to deliver quality education through the said modes of learning this August 2020.
With the goal of assessing the nine (9) SUCs in the Bicol Region within the context of Education Access in Tenders (EAT), the same group of researchers from BUCENG looked closely into the information technology (IT) related procurement activities of such SUCs from the period 2016-2020. Upon a comprehensive evaluation of the collected contracts, these researchers reported two categories classifying the capacity of SUCs in Bicol Region to successfully implement the proposed online transition, namely “fully capable” and “partially capable”. “Fully capable” SUCs were reported to have largely invested on computer servers, internet coverage and bandwidth, library and learning managements systems, subscription to online databases, and acquisition of software for research and instructional use. These capabilities, as reported by these researchers, corresponded to an equivalent investment amounting to PHP241.19 million.
In contrast, while “partially capable” SUCs were reported to be to financially secure such investments, no relevant awarded IT tenders from 2016-2020 necessary to ensure effective implementation of the proposed online transition were found for such SUCs.
Collectively, seven (7) of the nine (9) SUCs in Bicol Region were seen to be “fully capable” of implementing online classes this August 2020. Though these reported findings implied that the Bicol Region as a whole is seen to effectively implement the proposed online transition, the EATing patterns of the remaining two (2) SUCs which cater to the majority of at least 3000 enrolled college students in the region indicated that much still needs to be done to ensure all college students, regardless of privilege, be given a fair and equal access to quality tertiary education. The researchers then strongly recommended that SUCs classified as “partially capable” benchmark on the IT related procurement strategies that of “fully capable” SUCs.
(This article and the manuscript were submitted by the research team and may be updated in the future)
As of July 22, 2020, a total of 72,269 total COVID-19 cases has been reported, of which 46,803 are still classified as active cases [1]. With this continual rise of COVID-19 cases, it is estimated that this would cost about PHP2.2 trillion economic losses and is equivalent to at least a 2% contraction in the nominal gross domestic product (GDP) of the country [2]. As a consequence of this economic loss, about 26% of businesses operating in the country have already closed [3] resulting to about 100,000 Filipinos losing their jobs in the 1st half of 2020 [4] Indeed, there is an immediate need to control the spread of COVID-19 in the country to further mitigate the impact of the said disease to the Filipino people.
Fastracking the Public Procurement Process
The COVID-19 crisis in the country is a race against time. As seen from the success stories of our neighboring ASEAN countries, fast, efficient, and integral procurement played a crucial role in securing a “COVID-free” nationwide status. In response to this sense of urgency brought about the by the COVID-19 pandemic, the Government Procurement Policy Board (GPPB) recently issued a series of resolutions to shift current publicly held procurement related to COVID-19 into negotiated procurement (emergency cases) and relax existing guidelines on the submission of vital bid documents [5]-[8]. For instance, expired business or mayor permits and unnotarized bid documents submitted by eligible bidders could already be accepted under these new GPPB issuances.
Challenge on Procurement Integrity and Transparency
While it is necessary to fastrack public procurement in response to the COVID-19 pandemic, it is equally important to ensure integral and transparent implemented procurement processes to protect the interest of the Filipino people. Considered as one of the most vulnerable to corruption especially in this time of an emerging health crisis, relaxation of the imposed regulations is seen to compromise the overall integrity of the present public bidding processes. The acceptance of unnotarized bid documents, for instance, could promulgate misrepresentation on the capacity of an eligible bidder to faithfully undertake any contractual obligations if such barriers are removed.
REACT Risk Indexing System
Through a research grant given by Layertech Software Labs, Inc. and Hivos – People Unlimited, a group of faculty researchers from Bicol University College of Engineering looked closely into this present dilemma. Considering that shortening the time needed in awarding government contracts is of utmost priority, a rapid evaluator and assessor of contractor traits (REACT) risk indexing system was proposed and investigated as an intervening and supplemental tool to aid in upholding the integrity of the presently changed public procurement process on construction and infrastructure tenders related to the COVID-19 pandemic.
Using historical data periodically published by GPPB, assessment of an eligibility of a contractor based on its previous performance was further simplified by these researchers. Through REACT, three general classification of contractors were reported namely, “low risk”, “moderate risk”, and “high risk”. Contractors that were classified as “low risk” in the proposed risk indexing system were found to be the most eligible as these contractors were reported to have at most an average negative slippage of 7.5%. In accordance to the findings reported by these researchers, it was further suggested that necessary precautions and scrutiny be exercised to those contractors that would be classified as “moderate risk” and “high risk” contractors since these contractors were found to have an average negative slippage of at least 24.9% which is well beyond the acceptable negative slippage of 15%.
Indeed, as presented in the case study of the proposed REACT risk indexing system to the publicly available historical data of contractors in Region V, the applicability of the proposed system to preserve integrity of the presently relaxed public procurement process has been validated.
With the validation of the efficacy of the proof of concept as reported by the researchers, the proposed REACT risk indexing system is seen to be a plausible data-driven solution in light of the challenges in the public procurement process amidst the COVID-19 pandemic.
(This article is submitted by the research team and may be updated in the future.)
The COVID-19 pandemic has largely affected local government units (LGU) in the Philippines, guven the continuous rise of confirmed COVID-19 cases within their respective areas of jurisdiction. In mid-June 2020 alone for example, a spike in the COVID-19 cases was observed across all regions in the country.
As of July 22, 2020, a total of 72,269 confirmed COVID-19 cases has been reported, of which 46,803 cases are classified as active [1]. It is therefore imperative for the LGUs to immediately contain this spike in confirmed COVID-19 cases to prevent further spread of infection in their areas.
Possible Cause of Recent Spike in COVID-19 Cases
With the sudden implementation of a nationwide lockdown across all provinces in the Philippines, about 84,000 individuals remained stranded in Metro Manila for the duration of the imposed mitigation measures in the country [2]. In this case, a humanitarian effort to send these locally stranded individuals (LSI) to their respective home provinces was launched.
As the COVID-19 data published daily by the Department of Health indicated [1], the recent spike in confirmed COVID-19 cases mid-June 2020 could be linked to the return of LSIs to their respective home provinces.
Cross-examination of recently published COVID-19 data on regions (i.e. Region V) reporting a significant number of arriving LSIs further supplemented this observation [3]. As a result, there have been reported instances of mismanagement on the containment protocols of possible COVID-19 positive cases due to the onset of this described occurrence [4]. Hence, there is then a need to assess the capacity of LGUs to properly manage the arrivals of possible COVID-19 positive LSIs while ensuring that the arriving individuals are not discriminated and properly received according to the required medical protocols .
Capacity of LGUs to ACT on Arriving LSIs
Through a research grant given by Layertech Software Labs, Inc. and Hivos – People Unlimited, a group of faculty researchers from Bicol University College of Engineering looked closely into this present dilemma. Using COVID-19 related procurement data and officially press released COVID-19 data for the case of Region V, a system classifying the capacity of LGUs in the said region to accommodate, contain, and treat (ACT) arriving LSIs was formulated.
Under the developed system, three general LGU classifications were then derived namely, “low”, “moderate”, and “high”.
LGUs classified under the “high” category were reported to have at least three (3) hospitals and at least 10,000 PPEs readily available for ACTing on the arrival of possible COVID-19 positive LSIs. This then implied according to the researchers that LGUs categorized as “high” are the most equipped on ACTing on arriving LSIs. On the other hand, “moderate” LGUs were reported to have 1-2 hospitals readily available and a significantly low number of active COVID-19 cases within their respective areas of jurisdiction while “low” LGUs were also reported to have 1-2 hospitals within their vicinity but their active COVID-19 cases were relatively higher than that of “moderate” and “high” LGUs. In this perspective as cited by the researchers, LGUs (i.e. Oas, Albay) classified into “moderate” or “low” categories are highly advised to exercise due scrutiny and adhere to stringent health protocols while ensuring LSIs are not discriminated upon their arrival.
With the validation studies done on the case of Region V, this developed classification system is indeed seen to be helpful in providing data-driven insights that will specifically aid decision-makers on creating policies for proper management on the arrival of such individuals.
25 students from Bicol University College of Science – Computer Science and IT Department, and students from Southern Luzon Technological College Foundation, Inc., joined the two-day Datathon on September 4-5, 2019 at Bicol University College of Science Laboratory. The event is facilitated by Layertech Labs, with the help of Bicol University CS- CSIT and SLTCFI, supported by Hivos.
In 10 hours, students learned basics of the R Environment, Basic Data Scraping and Data Analytics techniques. The students were made to form teams of 3 or 4, with a procuring entity of their choice. Using R, the students were able to scrape official Philippine procurement data from Philippine Government E-Procurement System (PhilGEPS), clean and standardize the datasets, before visualizing them into graphs.
At the end of theDatathon, the teams presented their findings before a panel of judges from: Department of ICT Luzon Cluster 3, Bicol University CS-CSIT, SLTCFI, and Gayon Bicol Civil Society Organization.
The judges declared the final winner, team “Paste Copy”, for analyzing Department of Education Region 5’s procurement efficiency, focusing on procurement of school supplies in the region’s public schools.
Supported by Hivos, Layertech lead a data scraping session using R and R Studio, using official Philippine Procurement Datasets found in Philgeps.gov.ph’s Open Data Portal.
The session attendees were faculty members of Bicol University College of Science IT Department, and faculty and graduating students of Southern Luzon Technological College Foundation, Inc.
While procurement datasets are available in open data formats, the large PhilGEPS datasets still need to be pre-processed, filtered, visualized and analyzed. Only then can researchers, advocates, and concerned citizens draw useful insights to aid them in their advocacy and decision making.
What’s the objective?
Layertech and partners advocate for #DataDrivenGovernance. We aim to encourage researchers to study and innovate on government procurement. For them to do that, they must be equipped with the necessary skills and tools to draw insights from procurement information that is available.
For this first session, the academe was specifically invited because the team also needs to get their insights, comments and suggestions about the training design, in order to improve the next tech training sessions to come.
The team and partners will soon be deploying training sessions for young researchers, students, innovators, and faculty, on various topics such as:
Data Science Data Analytics Data Visualization Python Programming Machine Learning Cybersecurity Data Privacy
What are the results?
For the first training session with R, the participants were able to publish a total of 13 datasets (downloadable HERE, in our Open Data Portal) under various categories such as Health, Local Government, and Education.
The participants also actively presented their outputs and how these cleaned datasets can help increase transparency and efficiency in public procurement in the Philippines.
Want to know more about HOW to filter Philgeps datasets? Here’s a quick, general guide HERE.
Keep on visiting our “References” section for more procurement and data scraping, visualization, and analytics guides!
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