Procurement Diagnostics Hub (PH0073)

Brief Description of the Commitment

The Procurement Diagnostics Hub houses the analytics and diagnostics on public procurement. Such initiative will enable participatory procurement through public monitoring of the use of public funds in the procurement process and in the implementation of contracts with the end in view of ensuring the prudent and judicious use of government resources.

Problem Definition

1. What problem does the commitment aim to address? The commitment proposal aims to address the problem of disintegration of procurement data in the government sector which affects the timely and effective delivery of GPPB-TSO mandate. Disintegration of data poses a threat for the GPPB-TSO in recommending sound procurement policies to the Board, designing responsive capacity development programs for public procurement practitioners, suppliers and manufacturers, Civil Society Organizations, and other stakeholders, and providing effective feedback on the public procurement health of the Philippines. As the only procurement policy Office in the country, the delivery of these services influences the decision- making process of policy makers, utilization of public funds as a result from public procurement and recipients of the same, relationship between public and private sectors, and national strategies on greening the economy, among others.

2. What are the causes of the problem? Problems with the disintegration of data in the government sector occur due to lack of standardization, silos and bureaucracy, legacy systems, data security concerns, lack of resources, resistance to change, complex regulations, inconsistent data quality, limited interoperability, and lack of clear strategy. Hence, to address these issues, the government sector needs to prioritize data governance, establish standardized formats and protocols, invest in modern technology, and promote a culture of collaboration and data sharing among Offices. Effective data management practices and a clear commitment to integration can help overcome these challenges and lead to more streamlined and efficient government operations.

Commitment description

1. What has been done so far to solve the problem? The said problem was early on identified in October 2018. Hence, the Office tapped low-lying fruits as an effort to help resolve the issue. Beginning 2019, the GPPB-TSO with the technical assistance of the United Nations Development Programme ventured on data analytics using the procurement data submitted by pilot agencies covering the years 2018 and 2019. The following year, the Office was able to generate data analytics of the buying patterns of pilot Procuring Entities, volume and amounts of awarded contracts, average procurement periods and timelines, basic gender profile of procurement officers, risk registry, level of compliance, and the overall public procurement health from the GPPB Procurement Dashboard. The successful launch of the dashboard in February 2020 was particularly timely since the Office was able to easily anticipate pain points in the procurement process in light of the pandemic restrictions imposed. Hence, the Office was able to recommend immediate procurement policy amendments to the GPPB early on that aimed to simplify, streamline, and innovate specific areas in procurement planning and its conduct. The GPPB Procurement Dashboard then became the jumping board for the Interim Review of Procurement Performance (IRPP) initiated in the same year where the Office used procurement monitoring reports submitted to the GPPB and applied the learnings from the dashboard project. The IRPP is a tool that diagnoses the procurement health of the agency in the interim and determines courses of actions to improve or sustain the performance of an agency towards the end of year. As the Office was honing its skills in data analytics, they went ahead and reviewed the existing procurement reports in the year 2020; and recalibrated its content, presentation and overall design with the technical assistance of United Nations Office on Drugs and Crime (UNODC), and Open Contracting Partnership aimed to effectively transform all these reports as planning tools instead of reporting documents that are regularly submitted out of compliance. Instead, the Office looks forward to a shift in mindset and employ these reports as planning tools to guide public procurement practitioners better achieve value for money through the procurement activities they undertake. The revision of these reports has an immediate efficiency impact on time savings with the revised Procurement Monitoring Report (PMR) form. For instance, having only 27% of the columns need to be filled out manually; 20% with drop down options; 23% auto-generated while the 30% with possible combination of manual and autogenerated. These revised forms are the foundation of the ongoing automation project where the Office with the technical assistance of the UNODC is developing a web-based system where all public procurement practitioners can access and prepare their Project Procurement Management Plan, which shall automatically generate the Annual Procurement Plan, PMR, and ultimately the Agency Procurement Compliance and Performance reports. When completed, there will no longer be a clamor on submission deadlines as the system will auto-generate most of the reports and would need just a few added information from and validation with public procurement practitioners. The Office will then simply process these reports real-time based on what has been encoded by public procurement practitioners as well as those recorded in the Modernized Philippine Government Electronic Procurement System eBidding facility.

2. What solution are you proposing? The automation journey as detailed above will give birth to the development of a Procurement Diagnostics Hub which houses the analytics, diagnostics, and data-storytelling on public procurement consistent with Open Contracting Data Standards. By centralizing procurement information that is easy-to-understand and readily available for access and download, the initiative will help enable participatory procurement through public monitoring of the use of public funds in the procurement process and in the implementation of contracts with the end in view of ensuring the prudent and judicious use of government resources.

3. What results do we want to achieve by implementing this commitment? The Hub is meant to create an avenue that provides access to procurement information, fosters public participation, and encourages greater accountability among public procurement practitioners and suppliers.

Commitment Analysis

1. How will the commitment promote transparency? The Hub will be able to promote transparency by way of centralizing data analytics and diagnostics on public procurement. At the same time, anyone from the public can easily access and download procurement information without the need for registration. There will also be a communication feature installed so anyone from the public can easily communicate their queries or clarification.

2. How will the commitment help foster accountability? Meanwhile, the Hub will help foster accountability since procurement information from the national lens down to procurement process lens are showcased and dissected for better understanding of the public procurement health. This way, the Hub will be able to highlight Procuring Entities practices and be accountable for their actions.

3. How will the commitment improve citizen participation in defining, implementing, and monitoring solutions? Because the Hub is open and downloadable, the initiative will be able to better inform the public on the public procurement health in terms of what it is, how it is so, and why it would be. Complemented with its communication feature, the public will easily be able to throw in their perspectives, comments, and suggestions on the public procurement health which will then be packaged by the Office with other stakeholder perspectives in strengthening the Philippine Public Procurement System.

See action plan for commitment milestones and expected outputs.