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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: Policymakers and informed decision-making

Author: Pee Jay N. Gealone (Bicol University)

Culturally, Philippines has been reliant to tradition in many of our practices and behavior. These traditions play vital role in how we see our world, sometimes however, these traditions are the ones that hold us back. In the advent of information technology and new technologies in general, the decision-makers are struggling how to push forward reforms that are often in contrast to the perceived norms and tradition. This is more true in a local government than in the national government because they are closer to the people. With the proper use of data, the policy makers will be able to tailor fit policies that are needed and supported by the general public.

The LGU may institutionalize the use of data to determine the right policies to be implemented in their localities. By passing resolution that institutionalizes these practices, there will be a creation of system where local policy makers can have the tool to push through programs and policies that may be in conflict with the perceived traditions and norms. I am convinced that it is now the time to bring down data-driven policies to the local level.

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

Reflections: How the Academe can Leverage Data and Analytics to Help LGUs

Author: Mia Amor C. Tinam-isan (Mindanao State University – Iligan Institute of Technology)

Data analytics has been the talk of the town. It finds its way across agencies (government or private), businesses, or various institutions in discovering valuable information about the existing and overwhelming amount of data. Data in these times exponentially increase and extracting valuable information from these data is essential. Information from the analysis can be used for decision making, coming up with a good marketing strategy, or even in establishing policies and guidelines from a broad test base. However, local government units per se in various parts of the Philippines, have not yet maximized the impact of data analytics. Varying factors might contribute to this such as unorganized data and non-computerized processes.

As part of the academic community, we can implement programs, webinars, and workshops that will empower our LGU to exploit their available data. It is imperative to partner with NGAs, and LGUs, and develop a working strategy for local government digitization. We can propose a simple initiative and start from the automation of LGU processes to organize and ensure the quality and the integrity of data for analysis. We can also venture into partnering with private agencies such as OCDex which has experienced in partnering with LGUs and had already developed numerous government data analytics applications. As of the moment, the College is continuously having a dialog with different offices of LGU-Iligan in crafting MOA for the digitization of the city government.

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: miaamor.catindig@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

Educated Spending: An Insight on SUCs Utilization of MOOE

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

Reflections: Using Data Analytics to Validate Philippines’ occupational gender segregation

Author: Christian Sy (Bicol University)

The World Economic Forum’s Global Gender Gap Report of 2021 recognized the Philippines as the best-performing country in Asia in terms of gender equality. It ranked 1st in Asia and 17th out of the 156 countries. The Global Gender Gap Index (GGGI) is a significant indicator of gender disparity worldwide. It is useful for tracking the extent of access to resources and opportunities and differences between men and women. It adopts four key dimensions that include 1. Economic Participation and Opportunity, 2. Educational Attainment, 3. Health and Survival, and 4. Political Empowerment.

The Philippines have almost closed the gender gap for educational attainment and health and survival gaps with an index score of 0.999 and 0.979, respectively out of the perfect score of 1. On the other hand, economic participation and opportunity, and political empowerment are trailing with 0.792 and 0.353 index scores. This is primarily because of the gender gap in employment opportunities for women, and statistically, there are too few seats in government-held for women.

With this, we can explore a textual analysis of multi-domain, multi-source, and multi-year articles through big data analytics to validate the Philippines’ occupational gender segregation along with the economic participation and opportunity dimension of the Global Gender Gap Index (GGGI). The result of this textual analysis may be utilized to improve institutional transformation and policy formulation for equalizing economic participation and opportunity for women.

References

[1]        M A R C H 2 0 2 1 Global Gender Gap Report The analysis presented in the Global Gender Gap Report 2021. 2021. [Online]. Available: http://reports.weforum.org/global-

[2]        R. R. Sharma, S. Chawla, C. M. Karam, “Chapter 10: Global Gender Gap Index: World Economic Forum Perspective”, 2021, DOI:88975728.00017.

[3]        T. Mehdi, “Global Gender Gap Index: A Stochastic Dominance Approach,” SSRN Electronic Journal, Sep. 2020, doi: 10.2139/ssrn.3663281.

[4]        R. E. Matland, “Women’s Representation in National Legislatures: Developed and Developing Countries,” Legislative Studies Quarterly, vol. 23, no. 1, p. 109, Feb. 1998, doi: 10.2307/440217.

[5]        C. L. Hoyt, “Women, Men, and Leadership: Exploring the Gender Gap at the Top,” Social and Personality Psychology Compass, vol. 4, no. 7, pp. 484–498, Jul. 2010, doi: 10.1111/j.1751-9004.2010.00274.x.

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: cysy@bicol-u.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:

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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.

Using Government Procurement Data to Influence Bidding Strategy of Local Contractors

Using Philippine Government E-Procurement System (PhilGEPS) data of 19 local government units from years 2016-2018, four out of six key information requirements of local contractors and bidders were answered. Reducing the cost of acquiring information led to increase in bidding confidence, and a more concrete bidding and logistics strategy.

The paper was presented in the 2020 International Symposium on Technology and Society, hosted by the University of Arizona, Tempe, AZ, USA.

This paper explores how open government data can be used to influence suppliers and contractors to participate in public bidding, by minimizing the cost of information acquisition that influence bidding decision and strategy. The researcher conducted data scraping, pre-processing, and exploratory techniques on official procurement data of nineteen (19) Local Government Units (LGUs) in Albay, Philippines, and triangulated results with local government actors, contractors, and businessmen.

The study showed that the existing procurement data mandated by the Philippine procurement law to be released can answer 4 out of 6 key information requirements of bidders, thereby increasing overall bidding confidence. Using dashboards that regularly collate, preprocess, process, and visualize these data can help local procurement competitivenes.

For more information, the paper’s DOI is: 10.1109/ISTAS50296.2020.9462199

Automated Process Mining in Philippine Procurement Event Logs – Automated Process Flow Detection

“Process mining applies data science to discover, validate and improve workflows . By combining data mining and process analytics, organizations can mine log data from their information systems to understand the performance of their processes, revealing bottlenecks and other areas of improvement. “

(IBM, 2021).

A relatively new technology, process mining, is getting more and more popular due to increases and improvements in data production and management, and cloud technology. Companies and organization that use process mining can “see” the “current state” of their process workflow, and rapidly evaluate compliance to the “target” flows.

“Companies that adopt an incremental improvement approach, on the other hand, tend to spend too much time on analyzing the “as-is.” In addition, their current process analysis is frequently based on interviews and sticky notes, which executives sometimes regard as overly subjective and treat with justifiable skepticism. “

(Davenport and Spanyi, 2019)

Public procurement is a business process that is prone to corruption and administrative inefficiency, affecting the quality of service delivery to the public.  Using state university’s three-year procurement data as a sample, a paper published and presented by Layertech Labs in the 7th International Conference on Behavioural and Social Computing (BESC) – Bournemouth, United Kingdom, explores the use of process mining on publicly available procurement data to discover the underlying structure of procurement processes of government entities in the Philippines, check for conformance with the prescribed process in the procurement law, and identify potentially problematic nodes. 

In the paper, event logs were generated from official public procurement data and mined with heuristics-based process mining algorithm, using free, open-sourced tools. The discovered processes revealed a concept drift in publication of contract award, a point for inspection and improvement for the agencies involved.

Using the process miner, analysts were able to immediately detect and visualize drifts in the prescribed process, and pinpoint the specific process points (and actors) involved. Not only this technology will help speed up analysis, but the system will also allow LGUs, auditors, and even stakeholders to constantly monitor the state of their public procurement

To read the FULL PAPER (DOI: 10.1109/BESC51023.2020.9348306), go to IEEEExplore: https://ieeexplore.ieee.org/document/9348306

Interested to apply this tool in your business operations? Shoot us a message!
learning@layertechlab.com

Follow OCDEX for more updates about this miner!

References:

IBM (2021) What is Process Mining? Available at: https://www.ibm.com/cloud/learn/process-mining (Accessed: 25 May 2021).

Davenport and Spanyi (2019) What is Process Mining and Why Should Companies do it? Available at: https://hbr.org/2019/04/what-process-mining-is-and-why-companies-should-do-it (Accessed: 25 May 2021).

How can CSOs use Data in their Community-Based HIV/AIDS Advocacy Activities?

HIV-RELATED PROCUREMENT DATASETS PREPROCESSING TO IMPROVE HIV-RELATED ADVOCACY WORK OF CIVIL SOCIETY ORGANIZATIONS

The objective of this study is to use government procurement open data to inform Civil Society Organizations (CSOs) of the best possible strategies to optimize, and maximize their advocacy work. In this paper, Layertech conducted pre-processing of the Department of Health Region 5 procurement datasets from 2016-2018, collected from the official Philippine Government E-Procurement System (PhilGEPS) repository. The visualizations and calculations showed average prices of HIV-related commodities, procurement categories, average procurement timelines and patterns, procurement allocation per province, which CSOs, represented by Gayon Bicol, may use to improve their crafting of proposal and monitoring of service delivery in their HIV-related grassroots advocacy work in the province of Albay. The data also showed late posting of Notice of Awards in PhilGEPS by approximately -16 days for the entire Department of Health (DOH) Region 5, and -108 days on HIV-related transactions, which is not within the compliance standards as stated in the Government Procurement Reform Act (GPRA) law, thus, a point for improvement for the agencies concerned.

Download the Report:

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Procurement Analytics Handbook

Public Procurement Analytics Handbook – Volume 1

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:

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Download [14.86 MB]

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