Philippines staffing research ·
Can a State Model Reduce Payroll Input False Clears?
A blinded synthetic review of missing, pending, conflicting, late, and accepted input states.
Research question: Does a defined state model reduce false clearance compared with a binary received or missing tracker?
Methodology and scope: Generate seventy-two synthetic requirements across time, leave, worker changes, allowances, deductions, starters, leavers, and provider responses. Seed accepted, absent, unapproved, conflicting, late, and unreadable cases without real employee data.
Protocol and measures: Compare a binary tracker reviewer with a reviewer using explicit states. Both classify release-ready or hold and give a reason. Report false clears, unnecessary holds, reason accuracy, and median review time.
Scope boundary: The unit is one input requirement for one period. The study does not calculate wages, taxes, entitlements, exchange rates, or provider results and releases no funds.
Inference boundaries: Better classification would support further testing, not payroll correctness, legal compliance, or population completeness. Payroll and employment owners retain treatment, cutoff, approval, correction, and release decisions.
Limitations: The answer key simplifies ambiguity, time excludes follow-up, and finite states may train reviewers. Live use needs approved definitions, restricted-data handling, dual control where required, and result reconciliation.
References: National Institute of Standards and Technology, Cybersecurity Framework 2.0 (https://doi.org/10.6028/NIST.CSWP.29); National Institute of Standards and Technology, Privacy Framework 1.0 (https://doi.org/10.6028/NIST.CSWP.01162020); U.S. Government Accountability Office, Standards for Internal Control in the Federal Government, GAO-14-704G (https://www.gao.gov/products/gao-14-704g); Philippine Statistics Authority, Annual Survey of Philippine Business and Industry (https://psa.gov.ph/statistics/annual-survey-philippine-business-and-industry). These primary publications supply control, privacy, evidence, and sector context. None evaluates Outsourced Employment or the synthetic cases proposed here.