TLRI 10Q Methodology Framework

What is TLRI 10Q?

TLRI 10Q — TalentivaLabs Labor Risk Index — is a labor risk quantification framework developed to translate Indonesian regulatory exposure into financial metrics suitable for executive decision-making and investment analysis.

In many organizations, labor risk exists as a hidden balance sheet risk — remaining invisible in financial statements until it manifests as disputes, severance liabilities, or operational disruptions. TLRI 10Q is designed to make these liabilities visible, measurable, and actionable before formal escalation occurs.

Legal Framework

TLRI 10Q covers ten primary dimensions of Indonesian labor law compliance. Each question is calibrated against regulations in force in 2026, including post-Omnibus Law amendments and relevant Constitutional Court rulings.

Four-Layer Quantification Model

The methodological architecture of TLRI 10Q consists of four analytical layers operating sequentially — from signal detection to financial translation.

Weighted Scoring & Penalty Model

TLRI 10Q utilizes a penalty-based scoring system. Each question has three response options, each carrying a penalty weight calibrated to that area's financial impact band. The total score represents accumulated exposure — the higher the score, the greater the liability.

Penalty weights are differentiated by the financial impact band of each question rather than uniform weighting. This reflects the reality that an administrative flaw in a fixed-term contract (Q03) can trigger liabilities 10–20x larger than the lack of a formal organizational chart (Q01).

Critical Hit Mechanism

Q03 (PKWT), Q06 (BPJS), and Q08 (Termination) are designated as Critical Questions. A non-Yes answer to any of these triggers a Critical Hit flag, forcing a minimum verdict of ELEVATED — regardless of the total aggregate score.

Six-Tier Risk Band

Scores are mapped to a six-tier Risk Band classification. Each tier features a distinct Severity Class, verdict interpretation, and action implications.

Escalation Probability Model

Escalation Probability estimates the likelihood that identified compliance gaps will lead to formal regulatory enforcement, labor disputes, or litigation if left unaddressed. Expressed as a percentage (3%–97%).

The model simultaneously considers three components: the proportion of the overall score, the number of active critical gaps (Q03/Q06/Q08), and the level of unverified exposure from "Do Not Understand" answers. Values are capped at 97% to reflect that even the most severe exposure profiles retain a marginal chance of avoiding escalation.

Financial Exposure Estimation Model

TLRI 10Q translates compliance gaps into indicative financial exposure ranges per area. This estimation is designed for executive-level decision framing — answering: "What is the order-of-magnitude of financial risk?"

Ranges are constructed from four inputs:

• Regulatory Floor Minimum payments or fines mandated by current regulations — such as severance multipliers, 2% monthly BPJS late fees, or PDP Law administrative sanctions.
• Liability Cluster Adjustment Non-compliance in one area often creates cascade liabilities in related areas. Ranges reflect this clustering effect at the upper bound.
• Workforce Scaling Factor Ranges assume a baseline of 20–50 employees. Per-employee liability items (severance, overtime claims) adjust proportionally for larger workforces.
• Scenario-Based Projection Ranges cover scenarios from a single controlled incident (minimum) to systemic or mass-claim scenarios (maximum).

The model produces estimated ranges, not a single deterministic figure. Two compliance areas (Q06 and Q09) have maximum exposures proportional to revenue — which cannot be stated as fixed IDR amounts — and are displayed separately in Pro Reports.

Structural Risk Classification

The TLRI 10Q model is built upon six risk categories reflecting common exposure patterns in the Indonesian employment landscape:

• Structural Employment Risk Risks arising from the design of employment relationships and contractual structures — including the use of PKWT for permanent roles.
• Compliance Exposure Risk Administrative or regulatory non-conformities potentially triggering obligations — including BPJS registration failures and lack of valid Company Regulations.
• Compensation & Severance Liability Risk Exposure to severance pay, long-service pay, and other compensation claims — including retrospective overtime liabilities.
• Contractual Ambiguity Risk Unclear clauses or documentation increasing the potential for interpretation disputes at the Labor Court (PHI).
• Workforce Status Misclassification Risk Risk from workforce classifications that do not align with actual practices — the primary trigger for automatic contract conversion.
• Governance & Documentation Risk Weaknesses in internal policy documentation, disciplinary procedures, or oversight controls that weaken the company's legal standing during disputes.

TLRI 10Q Output Structure

TLRI 10Q generates two levels of output using identical scoring engines — differing only in the depth of information provided.

Download sample → TLRI 10Q Pro Report Preview

Limitations & Appropriate Use

Understanding the limitations of TLRI 10Q is essential for proper interpretation of its output.

• Input Dependency All output is a direct function of the answers provided. The model cannot independently verify answer accuracy. TLRI 10Q is most valuable when completed by respondents with direct knowledge of the company's compliance status.
• Scoped Coverage TLRI 10Q covers ten primary dimensions of labor compliance. It does not cover every possible area of exposure, including sector-specific regulations, specific PKB details, or international labor compliance.
• Indicative Estimation Financial ranges are based on categorical projections, not actuarial calculations. Actual liabilities may be higher or lower depending on specific facts.
• Continuous Calibration The framework is calibrated periodically as regulations, court rulings, and dispute patterns evolve. The version and effective date are recorded in every report's metadata.