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

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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.

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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

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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

Data Analytics a way to solve the crisis in education: A local setting approach

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Author: Ramon L. Rodriguez (National University – Manila)

The current pandemic highlights further the problem in the educational sector in the country. Even before the pandemic, the World Bank conducted an assessment of the country’s education system and found that a crisis in education existed. As we know, education is one of the foundations for the success of every community. Can we develop strategies to address this crisis using data analytics in the local settings? The LGU should explore this strategy to develop a concrete solution based on data. Decisions of developing new programs should be data-driven, especially in the local government settings.

If data-driven decisions are highly utilized, many improvements can be made to every LGU, including fiscal adequacy. Suppose the LGU has updated data on the profile of students, households, and problems encountered by every student. In that case, it can be a basis for a new strategy for addressing issues in education. Say, for instance, what support is needed by certain schools and what resources. The data may be available, but it is important to structure it and become ready for analysis. At this point, data analytics plays a significant role.

On the other hand, data analytics can also be used to match the needs of every LGU in terms of job availability on a local and global scale. The matching gap in skills needed in the industry has been highlighted for years, but actions to address this are still not concrete. However, different agencies have undertaken several initiatives but not enough to solve the problem. Almost every LGU in the Philippines has community colleges where locals can enroll. The intention of establishing community colleges is anchored on the principle that education is one of the backbones of community development. Having a community college is a great idea, but we have to make sure the programs offered are sustainable and benefit the family. We also want to avoid underemployment scenarios wherein graduates are employed not in their respective specialization. If we have data on the graduates and the skills needed in the local, national and global, then it is easy for us to match and decide what programs can be offered by schools. The budget for education is allocated per LGU. At the national level, almost 16% of the national budget is for education, but still, we have a crisis in education. The need to use data analytics in addressing issues in the education sector is a must.

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: rlrodriguez@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: Data to help Cities and Municipalities

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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

e-Participation: A Road to Strategic Decision-Making Using Data-Driven Approach

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Author: Lany L. Maceda (Bicol University)

Data has a very powerful role to play. Analyzing data is very important nowadays. We are no longer in the era of simply digitization, it now allows any government agencies both at the local and national levels to get more data to have an evidence-gathering basis. A data-driven approach could mean that the organization uses facts and metrics as its basis in forecasting, in aid of legislation or policymaking. A strategic decision based on data analysis could result in a decision that is in consonance with the organizational initiatives and objectives with an end goal of better serving the community.

When the Local Government Units/National Government Agencies realize the importance of data, this denotes that they empowered the community members for better decision making, every day. A data-driven decision is objective and rational since it undergoes systematic and scientific analysis of data.

e-Participation fosters civic engagement and open participatory governance with the use of Information and Communication Technologies (ICTs). This means that data-driven citizen feedback could be greatly needed improve the basic services of the government agencies. The said approach could address issues like Anti Red-Tape Authority (ARTA), transparency, and corruption in the bureaucracy, local and national levels.

his 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: llmaceda@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: How do you think data and analytics can help your LGU, NGAs, and/or community and how do you propose ways to do it?

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Author: Gabriel Avelino Sampedro (National University)

In the age of digitalization, everything is done online. Most of the data collected from people are stored in the cloud entities, and the amount of data stored there exponentially increases daily. It can be challenging to organize, manage, and obtain insights from various sizes and varieties of data. One solution for managing massive amounts of data is implementing self-serving, automated solutions to daily operations such as data input and reporting, which can improve efficiency and increase the efficacy of the mission. Data analytics plays a significant role in obtaining insights from our data in managing data. Data analysis is the process of studying data by using analytical or statistical methods in order to discover important information. The goal of this process is to conclude the data. The data analytics process helps us develop a clearer picture of the current situation for decision-makers to provide data-driven solutions to problems. The conclusive findings may come in a summary or an image, like a chart or graph. Showing data visually, which makes the job simpler, is known as data visualization. Data analysis may be done using various methods, including data mining, text analytics, and business intelligence. Data analysts use charts and graphs rather than tables or databases to convey data. It simplifies complex facts and makes it easier for the eyes to take in the information. Furthermore, data analytics may even assist in preventing fraud, waste, and abuse and helping with staffing shortages.

Using the knowledge obtained from the OCDex training, one possible application of using data analytics is for predicting arrival times of mass transportation systems. One of the significant issues in the country is the poor transportation system we have. Train stations encounter very long lines, and not everyone in line will immediately be served. One of the main issues in the system is the uncertainty of arrival times. People would go to train stations randomly, hoping to ride the train. The long wait can be pretty frustrating, and plans made throughout the day can be ruined. Although it will not entirely solve the whole issue, one way to solve this is to develop a system for predicting the arrival times of trains. In addition, providing people with data on the number of people on the platform (through the data from gate entries) can help people make data-driven decisions about their travel. The purpose of the system is to decongest some modes of transport and allow people to consider other options. The solution would use data from the station platform and logs of train operators to develop a machine learning-based model to improve this process.

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: garsampedro@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflection: Using Data Analytics to Gain Insights from Citizens’ Feedback

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Author: Jennifer Llovido (Bicol University)

Government data is a powerful resource that can influence public opinion, citizen services, economic development, government success, and a variety of other aspects. The government’s goal of transparency necessitates access to and management of data. Government data analysis helps both the public and private sectors acquire insights into the current situation of the state, which acts as a guideline for policymaking. The government’s adoption of technological developments in data storage and improved analytics allows for a much more comprehensive understanding of people. The potential for using data in government to provide more efficient, effective, and trustworthy public services is practically limitless.

Recognizing the importance of data as one of an organization’s most important assets, it is practically worthless without supporting technologies to mine, process, organize and analyze it. The official website of the Local Government Unit of Legazpi provides a feedback and query portal that would foster civic engagement by soliciting feedback and suggestions from the local populations as it extends the consultation processes beyond the traditional face-to-face meetings. The said portal could also be implemented at the level of the various barangays, where Legazpeños would be encouraged to give their feedback and participate in the continuous improvement of public services. It would further promote data-driven decision-making as well as result in the production of quality datasets to encourage researchers and innovators to conduct studies and provide innovative solutions that would help solve issues of the LGU Legazpi. Further, citizen feedback may be visualized into tabulations and graphs that can be used to gain insights, and detect sentiments, trends, and public opinion. The opportunity of maximizing the use of the data at hand by improving visualizations and making it more informative with the application of data analytics is recognized.

As a resident of Legazpi City and a member of the academe, I envision the possible improvement of the LGU Legazpi website with the provision of enhanced data analysis and visualizations of the feedback and query portal data by employing new methods for modeling and analyzing data, including advances in natural language processing and visualization. More meaningful visualization for each question in the portal may be developed and utilized to enhance the presentation of data and effectively share the results back to Legazpeños. The end goal of this is to encourage Legazpeños as well as visitors of the city to give unbiased and useful feedback with the use of cloud computing leading to data-driven governance in the city. This could further improve the policymaking processes as well as make government policies more relevant to citizens at the level of the local government of Legazpi City. Its benefits are intended to benefit a wide range of stakeholders, including the economically and politically disenfranchised. The results are foreseen to provide actionable insights for good decision-making and support the development of evidence-based solutions for solving community issues in Legazpi City.

his 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: jllovido@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflection: The Study of Pandemic Resilience on Impoverished Municipalities

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Author: Shehab D. Ibrahim (Mindanao State University – Iligan Institute of Technology)

Pandemic orders are declared to protect public health. However, some of these orders are more challenging to comply for impoverished or vulnerable groups. Let’s take the staying at home policy as an example. Vulnerable groups have no choice but to go out to work despite the great physical risk.

The researcher will investigate the pandemic resilience of the municipalities with high poverty incidence. Specifically, the researcher will look into the spread of the poverty index across the municipalities in the Philippines, study the correlation between pandemic resilience/ preparedness and social statistics of the municipalities, and determine the important factors (e.g. ICT and healthcare system investments) in developing pandemic resilience and provide data visualizations to aid decision-makers.  The data will be taken from the DOH public open data repository,  OpenStat database from the Philippines Statistics Authority (PSA), and other Philippines open government data repositories.

The researcher plans to create a Dynamic Poverty Heat Map through Geographical Information System (GIS) to show the poverty levels of every municipality. Spatial autocorrelation can also be performed to measure the autocorrelation of municipalities (through its polygon representations). This is to determine the pattern of the spatial position of municipalities and the poverty rate and evaluate if it is clustered, dispersed, or random. Also, the researchers will determine significant attributes from the DOH and OpenStat Database specifically related to Pandemic Resilience and Social Statistics of municipalities. A correlation heatmap can be visualized to show the relationship between these attributes. Finally, the researcher will create a model that will use the Social Statistics attributes as the features (independent variables) and the Pandemic Resilience attribute as the targeted variable (dependent variable). Models that can determine the important predictor variables, such as Lasso and Ridge regression, will be used. This will be helpful in determining the factors that may lead to developing pandemic resilience.

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: shehab.ibrahim@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: A Missing Link in Philippine Mental Health: Data Analytics

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Author: Manolito Octaviano Jr. (National University)

According to WHO, there are estimated 154 million Filipinos suffer from depression, 24 million from Alzheimer’s disease and other dementias, and 15.3 million persons with drug use disorders. Despite this, public sectors and government in the Philippines give little attention to the mental health of Filipinos, with only around 3–5% of the total health expenditures being allotted. The poor resource allocation is alarming and cannot aid many people suffering from mental disorders.

Given the identified problems in the Philippines, there is a pressing need to convince the public sector and the Philippine government to take immediate action. A way to highlight these issues to local officials is to take advantage of the existing mental health data from DOH. Then, computational approaches can be applied to gain valuable information and a comprehensive structured analysis presentation. These insights can aid policymakers in reshaping communities to support mental and social wellness.

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: mvoctavianojr@national-u.edu.ph or Layertech labs support at learning@layertechlab.com