The Philippine Statistics Authority Davao Occidental Provincial Statistics Office conducted a municipal level training, coordination and field visit on Philippine Standard Industrial Classification (PSIC) and Philippine Standard Geographic Code (PSGC) to the Municipality of Don Marcelino.

The coordination and briefing was held on the 10th day of May 2024 at SB Hall, inside the Municipal Hall of Don Marcelino. The activity were attended by Ms. Girlyn P. Leopoldo and Mr. Raymart U. Silao from Municipal Planning and Development Office (MPDO), Ms. Deniza P. Dangawon from the Municipal Treasurer’s Office (MTO) and LGU Don Marcelino Business Process and Licensing Officer (BPLO) Mr. Benjamin M. Sabid. Senior Statistical Specialist Rodon S. Tahil and COSW-Statistical Analyst Mae Leonacor C. Sibla served as resource persons during the field visit and briefing.

The objective on the conduct of the municipal-level training, coordination, and field visits and assessment of LGUs on the adoption of PSIC and PSGC is in light of capacitating LGUs in using standard classification, strengthening partnership, data sharing, and strategic generation of quality, timely, and comparable industrial statistics at the national and local levels.

Specifically, the training, coordination, and field visits aim to orient LGUs on the importance of PSIC and PSGC, look into challenges encountered in the adoption of PSIC, discuss data sharing, and harmonize the LGU Business Register from i-BPLS/e- BPLS in terms of statistical classification systems with PSA establishment and industrial data.

The activity is also part of the Nationwide Assessment of LGUs on the Adoption of PSIC since it recognizes the importance of LGU business registers in coming up with a total picture of socio-economic development in the country for more informed decisions and more efficient delivery of government services.

It is hoped that this activity will strengthen LGU’s knowledge in using PSIC and PSGC as well as ensuring uniformity and comparability of data produced which will be used as aggregated data useful for local planners and policy makers.

APPROVED FOR RELEASE:

JESSIE A. MADULIN
Chief Statistical Specialist