NAVETRA™ Model & Methodology

Every output traces to two foundations: peer-reviewed and published industry research, and a proprietary quantification methodology developed by JTS Inc.

The underlying research base includes longitudinal organizational health studies, global workforce engagement surveys, labour market data from government statistical agencies, and sector-specific benchmarking from recognized industry analysts.

Our calibration rates are deliberately conservative — set at a fraction of published research ceilings. We would rather produce a defensible lower-bound estimate than an inflated figure that undermines trust.

The model is calibrated against findings from 21 primary sources across six categories:

• Organizational health: Longitudinal studies covering thousands of companies globally, demonstrating measurable financial differentials between aligned and misaligned organizations.
• Workforce economics: Large-scale surveys quantifying the productivity, profitability, and retention costs of disengagement.
• Labour market data: Government agencies publishing hiring costs, replacement costs, and turnover by sector.
• Knowledge management: Research quantifying institutional knowledge loss during employee transitions.
• Project delivery: Multi-decade data on project cost overruns and the organizational factors that drive them.
• Revenue alignment: Research quantifying the revenue impact of go-to-market misalignment.

A detailed bibliography with specific citations is available to qualified clients under confidentiality agreement.

We are transparent about the calibration stage:

Current state: All outputs fall within ranges predicted by published research for comparable company profiles.

In progress: Design-partner engagements with tracked outcomes at 3 and 6-month intervals.

Target state: After 50+ tracked outcomes, empirically fitted parameters. After 200+, per-industry calibration with statistical confidence intervals.

The engine uses a proprietary quantification methodology structured around five principles:

• Dual-anchor architecture: Revenue-generating levers are anchored to top-line revenue. Operational efficiency levers are anchored to gross margin — reflecting distinct economic mechanisms.
• Concentration-adjusted calibration: Single-project companies and diversified enterprises receive different calibrations — because risk economics differ fundamentally with revenue concentration.
• Nonlinear gap modelling: Low scores create disproportionately higher drag because systemic failures cascade across multiple levers simultaneously.
• Multi-source confidence weighting: Confidence adjusts based on respondent count, diversity, connected data, and cross-lever patterns.
• Probability-based outputs: Every estimate includes multiple scenarios rather than a single number.

Specific calibration parameters and algorithmic implementation are proprietary to JTS Inc.

Each base rate is a conservative fraction of the documented research ceiling. Published research establishes the upper boundary; our calibration sets the rate well below it.

Every output represents a minimum defensible estimate, not a worst-case projection.

The exact calibration mapping is proprietary and available under NDA for enterprise clients and institutional investors.

Every output is a range, never a single number:

• High confidence: Multiple respondents, connected system data — narrow range.
• Moderate confidence: Limited respondents, some anomalous patterns — medium range.
• Low confidence: Single respondent, multiple anomalies — wide range with advisory labels.

Proprietary overconfidence detection identifies score uniformity, structural contradictions, and single-source bias. When detected, ranges widen and follow-up recommendations are generated.

This metric quantifies how much of the full evaluation supports the numbers. It combines respondent coverage, connected system data, lever coverage, and cross-lever correlation.

• Below 25%: "Directional"
• 25–60%: "Preliminary"
• Above 60%: "Substantiated"

Always displayed prominently. We never hide what we don't know.

Traceability: Every dollar maps to a specific lever, research-backed calibration, and documented calculation. Auditable.

Concentration awareness: Standard diagnostics don't adjust for revenue concentration. NAVETRA does.

Compounding accuracy: Each tracked outcome improves the model for all future users.

Scoring frameworks produce benchmarks and rankings. NAVETRA produces dollar-denominated execution risk estimates tied to your specific financial profile.

We reference published research as calibration inputs. We do not replicate or compete with any third-party methodology. NAVETRA's contribution is the financial quantification layer.

Phase 1 (current): Calibrated from published research.

Phase 2 (50+ outcomes): Per-industry adjustment from real client data.

Phase 3 (200+ outcomes): Empirically fitted parameters. Intervention effectiveness data.

Phase 4 (ongoing): Continuous refinement. Causal modelling. Predictive risk quantification.

The architecture accepts improved parameters without redesign.