Public Sector · Government
GL measures how well a public system actually delivers.
A single metric for system delivery performance.
No internal access · No installation · Works with public or table-based data
GL Framework — What It Is
A practical introduction to how GL Framework diagnoses process load — and where intervention actually changes outcomes.
Government & Public Sector
Request a Diagnostic Brief
We provide a non-attributable process diagnostic using public or shared data.
No system access required. No installation.
No system access required. No installation.
This is not a purchase. This is a starting point.
Thank you.
We will prepare a preliminary diagnostic outline focused on where process load may be accumulating.
If appropriate, we will reach out to schedule a short discussion.
No payment required · No system access · Response within 2 business days
01
Compare delivery performance
See how similar public processes perform across programs, units, or jurisdictions.
02
See friction without system exposure
Start with public data, table exports, or manually assembled operating figures.
03
Support leadership discussion
Discuss delay, burden, rework, and process design risk with a common metric.
Law, regulation, and execution
Different systems. Same gap.
IV&V requirements under 45 CFR § 95.626 establish independent verification during system development. However, in practice, these requirements are not consistently extended into outcome-based verification once systems are in operation.
This creates a misalignment between regulatory intent — ensuring effective system delivery — and operational reality, where post-deployment outcomes are not always systematically demonstrated.
Across different legal systems, oversight mechanisms vary in form but share a common limitation. Whether through audit-driven accountability in common law systems or rule-based administrative control in civil law systems, verification frameworks are primarily designed to confirm compliance and completion, rather than continuously demonstrate outcome improvement.
The result is a shared structural gap between implementation assurance and demonstrated improvement in public service delivery.
Why this matters for procurement
Public acceptance confirms completion. Public accountability requires outcome visibility.
Public procurement often assumes that successful implementation implies successful delivery. In reality, system acceptance confirms that a system was built — not that it works effectively for citizens.
Without a mechanism to verify post-deployment outcomes, governments carry hidden risk: projects may be formally completed while delivery performance remains unchanged. Accountability stops at acceptance, while public impact remains unverified.
Use this directly
Insert this language into your next digital transformation contract.
“Within 90 days of system go-live, an independent outcome verification review shall confirm whether intended service delivery outcomes improved. The review shall rely solely on external or publicly available data. No internal system access is required.”
“Final acceptance or performance evaluation may incorporate outcome-based verification results where applicable.”
This does not add technology burden. It adds a post-deployment proof layer.
It does not replace implementation acceptance. It completes the accountability structure.
It does not replace implementation acceptance. It completes the accountability structure.
System already deployed?
We can run a post-implementation Delivery Assurance Review now. No system access required. External data only. Delivered in 5–10 business days.
✓ Registered Vendor · Commonwealth of Massachusetts CommBuys · Supplier ID 00085149
Why it matters
Public delivery problems are often structural before they are political.
A program can be well-funded and well-intended and still underperform because the path through the process is too slow, too layered, or too difficult to complete.
Start with one program, one workflow, or one operating unit.
GL is designed to help public leaders discuss delivery performance with more clarity before the problem becomes normalized as routine backlog.
Request a Diagnostic Brief →
Publications
Selected public administration writing
Research and commentary focused on administrative friction, policy delivery, and system design.
PA Times · Published
The Denominator Problem: How Administrative Friction Derails Policy
Introduces the implementation burden lens behind GL and explains why delay and process drag weaken outcomes even in well-funded programs.
Read Article →PA Times · Apr 3, 2026
Proportional Sequencing in Long-Term Care
Examines how process ordering affects access and why safeguards do not need to be removed in order to reduce delay.
Read Article →PA Times · Apr 24, 2026
What Global Benefit Systems Reveal About Policy Delivery
Looks at how administrative design shapes outcomes across national systems.
Read Article →PA Times · May 1, 2026
Forthcoming
When AI Is Placed Wrong: Front-End Automation and the Amplification of Public Sector Error
Examines why deploying AI at the intake stage amplifies error rather than reducing it.
PA Times · May 22, 2026
Forthcoming
What One-Stop Service Reveals About the Delivery Problem
Shows why coordination burden should sit with systems rather than citizens.
SSRN Publications
Selected working papers
Published on SSRN · American Society for Public Administration · PA Times
SSRN · 6642280 · 2026
The Missing Layer in Public Procurement
Outcome verification after deployment. Structural gap in procurement frameworks. April 2026.
Read on SSRN →
SSRN · 6372460 · 2026
The Denominator Problem
How administrative friction derails policy. PA Times March 2026.
Read on SSRN →
SSRN · 6372358 · 2026
Proportional Sequencing in Long-Term Care
A process design approach for U.S. HCBS. PA Times April 2026.
Read on SSRN →
SSRN · 6343198 · 2026
GL Framework: Measuring Administrative Friction as Governance Failure
Cross-jurisdictional comparative analysis.
Read on SSRN →
SSRN · 6242658 · 2026
Administrative Friction in the Age of Automation
Empirical validation of governance fluency measurement.
Read on SSRN →
SSRN · 6178024 · 2026
Quantifying Administrative Friction
A diagnostic ratio model for policy implementation efficiency. GL = (Fs × Vn) ÷ (Pd × Cf).
Read on SSRN →
SSRN · 6343960 · 2026
GL Framework Technical White Paper
Institutional efficiency and delivery loss in public systems.
Read on SSRN →
GL Diagnostic Reports — Sample Cases
Four systems, four diagnoses
Each report uses only public administrative data. No internal access required. These are sample diagnostics illustrating the GL Framework's analytical depth and output format.
United States · Massachusetts
Department of Unemployment Assistance
0.059
Flow Collapse
For every $1 of policy intent, less than 6 cents reaches eligible claimants as timely benefits.
GL = (0.44 × 1.2) / (3.0 × 3.0) = 0.059
Download ReportUnited Kingdom
Department for Work and Pensions
0.074
Structural Failure
Project controls existed, but outcome verification did not continue into live claimant experience.
GL = (0.48 × 1.3) / (2.8 × 3.0) = 0.074
Download ReportTaiwan
Long-Term Care Plan 3.0
0.148
Structural Failure
Budget expansion did not by itself resolve front-loaded process burden in service activation.
GL = (0.54 × 1.35) / (2.5 × 2.7) = 0.148
Download ReportUnited States · Iowa
Medicaid Eligibility System
0.082
Structural Failure
System acceptance did not prevent high downstream loss through procedural disenrollment.
GL = (0.46 × 1.4) / (2.6 × 3.0) = 0.082
Download ReportAll diagnostics use public data only · No internal system access required · Delivery timeline: about 2 weeks per report
Cross-System GL Analysis
GL scores across selected policy systems
Illustrative values calculated using public administrative data.
| Jurisdiction | Policy / System | GL Score | Rating | Source |
|---|---|---|---|---|
| U.S. | Student Loan Forgiveness | 0.006 | Policy Violence | Book analysis |
| UK | Universal Credit | 0.06 | Policy Violence | Book analysis |
| Taiwan | Vaccine Booking Platform | 1.50 | Moderate | Case study |
| India | Demonetization | 0.023 | Policy Violence | Case study |
| EU | GDPR | 0.40 | Policy Violence | Case study |
| South Africa | Social Grant System | 2.14 | Good | Case study |
| Finland | Education System | 3.13 | Excellent | Case study |
| Estonia | Digital Governance | 10.54 | Outstanding | Case study |
Values are illustrative estimates derived from public data and used to compare relative delivery load across systems.