This study demonstrates three metrics for measuring the performance of the Philippine scientific enterprise system. The system consists primarily of institutions, agencies, and organizations in the country that are directly involved in the generation of new scientific knowledge and in the training of future Filipino scientists and researchers in science, technology, engineering, and mathematics (STEM). The national budget in 2014 was 1.59 times larger than that in 2009 consistent with the steady growth of the gross domestic product during said period. Consequently, the budgets for the state universities and colleges (SUCs) and the Department of Science and Technology (DOST) also grew by 61.53 percent and 115.11 percent, respectively. The DOST is a major source of research and development (R&D) grants and scholarships for STEM students, while the country's higher education institutions (HEIs) form the backbone of the enterprise system. Peer-reviewed technical publications and PhD graduates are considered to be tangible outputs of an institution that is engaged in scientific R&D activities.
The performance indices are: Academic Productivity Index (API), Science Productivity Index (SPI), and the PhD Production Efficiency Index (PPEI). The API score of an HEI is given by the ratio of the (geometric) product of the number of SCOPUS publications and PhD graduates produced in a given year, and that of its corresponding budget allocation and number of faculty members. The SPI score is computed as the ratio of the product of the number of SCOPUS publications and PhD graduates, and that of the number of faculty members and their time to do research. A PhD program gets a high PPEI score if it graduates many PhD students within the shortest possible completion time. An institution gets a zero API or SPI score if it does not produce a PhD graduate even if its faculty members are publishing. Two or more units perform uniformly well when their corresponding index scores are comparatively high. The geometric product places equal importance to the institutional output (PhD graduates) and the individual accomplishment (peer-reviewed publications). Because the possible outputs are calibrated to the inputs, an index score would track the response (absorption capacity) of an institution or program to temporal variations in resources invested in it.
The use of scientific measures that align institutional output with individual performance is recommended in faculty and staff promotion and in the selection of administrators, as well as in assessing the possible impact and long-term consequences of programs and administrative policies. Prudent application of data-driven analytics promotes transparency, predictability, fairness, and meritocracy in the scientific enterprise system. It motivates stakeholders to work together for a common purpose that is larger than the sum of their own individual aspirations.