Enhancing HIV Procurement Efficiency in Bicol Region

1. USE CASES FOR OCDex.techOPEN CONTRACTING DATA ANALYTICS PORTAL PREPROCESSING OF HIV-RELATED PROCUREMENT DATASETSof DEPARTMENT OF HEALTH Philippines - Region 5 LAYERTECH SOFTWARE LABSREV: June 2019 THIS PRESENTATION IS CREATED by LAYERTECH SOFTWARE LABS and MAY NOT BE REPRODUCED WITHOUT WRITTEN CONSENT OF LAYERTECH.

2. NOTE: This research was conducted with the support of Hivos under the open up contracting programme. The purpose of this research is to create a sample use-case on how analyzing procurement data can help both CSOs and Government Agencies streamline procurement activities to ensure that both government end-users and the public receive quality goods and services. Layertech is not giving any conclusive statements about the agencies and organizations mentioned in this report. We highly encourage that additional research and validation be conducted when using the information stated in this report.PRINCIPAL RESEARCHERSSangil, Frei and Maceda, Lany

3. “You cannot improve what you cannot measure”

4. Open Contracting Data Standard Use Case The success of implementing the Open Contracting Data Standard (OCDS) should not be measured by compliance but by how much data is being used. The data standard was designed to help people make sure contracting information achieves: Better value for money; Fairness of accessing the market of public tenders; Detection of corruption; and Monitoring on effectiveness of delivery. Source: OCP-OCDS Documentation Website

5. Prescribed Use Case Methodology

6. Brief Background – Why HIV? MEDIAN AGE of DIAGNOSIS: 28 YEARS OLD In October 201829% of cases were among youth 15-24 years old

7. Brief Background

8. CIVIL SOCIETY ORGANIZATION GAYON BICOL Inc. Identify stakeholder groups • LGBT Organization - Based in Albay, Bicol Region, PH • Conducts COMMUNITY-BASED Screening for HIV (since November 2018) • Conducts HIV-related Advocacy Activities (Screening, Training, Awareness Campaigns)

9. Issues faced by Gayon Bicol • Figure out what they want • Not enough HIV Testing kits, condoms, lubes, etc. upon request. • Problems in crafting proposals for HIV-advocacy projects (what is allowed, what is not allowed) • Finding the perfect “timing” to request for test kits, and other advocacy materials. • Ensuring that HIV trainings delivered are not cut short (e.g. 4 day training – 2 days only) • Ensuring quality of trainings (e.g. conducive training location, etc.) Figure out what they want

10. Primary source: PHILGEPS • Map Supply of Data with Demand • “Lowest-hanging fruit” with machine-readable datasets (in relational database structure) with 40 columns. • Other sources are DOH websites and eFOI portal (but are majority in non-machine readable formats, or release of requested documents via the eFOI portal takes 15 days or more) • FDPP portal is down • Hard-copies posted are not suitable for data analysis, unless manually encoded to machine-readable formats.

11. Research team will initiate use of procurement data • Document Use and Impact Layertech (Intermediary) – Help Gayon visualize and analyze datasets, Document Use and Impact to their experience Bicol University (Intermediary) – Research partner to ensure scientific accuracy Gayon Bicol (and LGBT network) – Representative of Target User group.

12. RESEARCH and DEVELOPMENT Layertech and Research Partners

13. PROBLEM STATEMENT Primary: How can visualization and analysis of HIV-related procurement datasets of Department of Health Region 5, help the Civil Society Organization, Gayon Bicol, to receive good-quality services and goods for their advocacy against HIV? Secondary: How can the insights drawn from addressing the first problem statement be used by DOH, to help in their procurement planning activities?

14. Methodology PRIMARY INFORMATION SOURCES: • PHILGEPS • DOH RO5/MAIN Website and Documents (APP, projects, etc.) • Accounts and other info from Partner CSO

15. General Initial Observations on Data Sources • PhilGEPS files are in EXCEL format (not CSV) • Agency names inconsistent, especially in years 2016 and 2017 (e.g. DOH Regional Office 5, DOH CHD BICOL, DOH MAIN, DOH NCR, DOH NC, etc. some with spaces, some without ) • Documents uploaded in Agency Websites are in PDF/SCANNED PDF file format. Clearly NOT machine-readable and needs to be digitized. • Details in datasets: Contract duration for 3-4 day trainings is “0” days • Notice to Proceed is issued AFTER contract end date(?) and the like.

16. We are interested in the following: HIV-related rows: • HIV Test kits • Condoms • Antiretroviral Drugs • HIV/STI trainings • HIV/STI IEC Materials • Others Trends and Visualization: • Timelines – Start, Bid, Close, Award • Contract amounts and top contractors • Contract Delivery days • Others

17. PhilGEPS Columns:

18. VISUALIZATIONS For Year 2018 (soon, from 2016-2018) – 3 years

19. DOH RO5 – Rows Scraped Why do we need to visualize the DOH Region 5 procurement? Why not visualize the HIV rows only?We want to see the procurement activity of the office as a whole. And from there, we can compare the difference of the procurement activity for HIV rows versus other procurements made by the office.

20. Initial Visualization (General)

21. Area of Delivery by Frequency Where are these delivered? We don’t know.

22. Area of Delivery by Contract Amount Where are these delivered?This is around 10 million pesos contract amount.

23. Business Category versus total Contract Amount: • Highest amount is on Construction Projects on 2016 and 2017, followed by Services on 2016.

25. VISUALIZATIONS (HIV) TARGET – 2016, 2017 and 2018 (3 years)

26. HIV Dataset Basic Information

27. Procurement Modes HIV Dataset Procurement Mode versus total Contract Amount: • Highest amount is on Public Bidding, specifically on 2017. • Direct Contracting on 2017 is 2nd highest • In 2018, highest amount is procured via Negotiated procurement – Small Value Procurement.

28. Area of Delivery by Frequency vs Amount

29. Business Category versus total Contract Amount: • Highest amount is on Laboratory Supplies and Equipment. • In 2018, highest expenditures goes to Catering Services.

30. AVERAGE COSTS per ROW DOH RO5

31. PROCUREMENT TIMELINE in DATASET

32. NOTE: The dates have different formats per row. Some have m/d/Y and some are d/m/Y. We noticed that there is more row consistency than column. Hence, we calculated the difference per row to get the number of days, before we calculated for the summation. Approximately 336 rows have their format d/m/Y and the majority being m/d/Y.

33. PROCUREMENT TIMELINE in DOH RO5 DATASET 7.43DAYS 13.75DAYS 53DAYS 51.95DAYS 52.45DAYS -27.02DAYS

34. AVERAGE DOH RO5 PROCUREMENT TIMELINE

35. PROCUREMENT TIMELINE in DOH RO5 HIV DATASET 7.4DAYS 41.9DAYS 13.67DAYS 93.11DAYS 116.81DAYS -110.17DAYS

36. AVERAGE HIV-related PROCUREMENT TIMELINE

37. SOME ROWS and OBSERVATIONS in HIV Dataset

38. Versus Annual Procurement Plan APP SOURCE: http://ro5.doh.gov.ph/ • Stakeholder cannot isolate activities/rows related to HIV • No online copy of PPMP • In non-machine readable formats (scanned PDF)

39. Versus other DOH RO5 Related Information March 14, 2019 - REQUESTED thru eFOI portal the allocation of HIV screening kits from DOH Main to DOH Region 5 from 2016-2018 March 20, 2019 – Marked‘PROCESSING’ by FOI Decision MakerApril 8, 2019 – Received Requested Information

40. Allocation of Screening Kits, ARVs and Condoms from DOH Main to DOH RO5

41. AUTOMATING THE PROCESSINGOCDex ANALYTICS FILTER BY PROJECT, PROCURING ENTITY, TAG, ETC.

42. AUTOMATING THE PROCESSINGOCDex EXPLORE PROJECTS FILTER BY PROJECT, PROCURING ENTITY, TAG, ETC. ACTUAL PROJECTS/CONTRACT DETAILS

43. AUTOMATING THE PROCESSINGOCDex EXPLORE PROJECTS – INDIVIDUAL PROJECTS ACTUAL PROJECTS/CONTRACT DETAILS PHILGEPS to JSON! And Vice Versa

44. AUTOMATING THE PROCESSINGOCDex EXPLORE PROJECTS – INDIVIDUAL PROJECTS ALL CONTRACT DETAILSIN ALL STAGES

45. AUTOMATING THE PROCESSINGOCDex OPEN DATA DOWNLOAD CLEANED/ORGANIZED DATASETS per category/sector to encourage further research and innovation

46. LGBT Network/ CSOs in Bicol Region On May 22, 2019, Layertech conducted a presentation of the research results, hands-on demonstration of OCDex, including a crash course on Data Science and how to interpret Graphs to the LGBT network of Bicol Region (6 provinces, 7 cities, 108 municipalities, 3471 villages).

47. Insights by Bicol LGBT Network • Online tools are important especially for HIV because of social stigma. It makes them more comfortable to browse HIV-related documents in private. • They can inspect every Project in Detail (e.g. see contract amount, contract period, etc.) • They can estimate when the next delivery will arrive, and how to effectively schedule their activities. • They can refer to average awarded prices in creating proposals • They can take note of potentially problematic stages in the procurement. For this case, publishing of Award Notice. • By looking at the details, they can ‘visualize’ the kind of quality of service that they should get and compare it with the quality they are getting. • They can formulate evidence-based requests, complaints and proposals to Department of Health (and in other agencies, for that matter). • They can justify the need for budget increase in procuring HIV test kits and Antiretroviral Drugs.

48. Other Insights, Recommendation by CSO • Check screening kits details thru Item Description column to ensure it adheres to WHO standards. • Some CSOs are not given HIV Screening kits and related goods and services because they don’t have programs for HIV. They should submit proposals. • It would be very helpful to put contract duration for trainings so that they can check if the hotel really is giving them the proper service they paid for. • Gayon suggested a feedback page for them to share experiences with some suppliers/venues. (We link this up to BU’s SEE LOG system)

49. CSO Experience Matches with Calculated Values Gayon Bicol’s Actual Experience and Costs (e.g. 1300 php/head training) matches the average calculated values and simulated values from the historical dataset!

50. CONCLUSION • Data, if properly visualized and presented, can help optimize and maximize advocacy activities. • Data provides a concrete basis for a complaint, a request, or a proposal. Many ‘trends’ happening can be dismissed as hearsay without proof. With Data, these trends can be given a solid foundation for further improvement/investigation/optimization. • By automating analysis (such as OCDEx) non-IT or non-Data professionals can also use the benefits of analyzing data without having to rely too much on intermediaries, or ‘single point of failure’ in the analysis ecosystem. • Making CSOs like the LGBT community aware of the power of data and how it is being used, makes it difficult for others to use data to confuse, mislead, exaggerate, or manipulate their perception on certain issues.