GRC for quality-driven NPM

Peter Haenni

• 2 min read
GRC for quality-driven NPM
SIPOC map auto generated by the ProcessHorizon web app

Public contracting is the core process of value creation & risk exposure in government's New Public Management (NPM) from needs identification to procurement, delivery & post-evaluation. Historically, it suffers from fragmented accountability, poor feedback mechanisms, manual oversight and lost learning opportunities. A GRC-TQM-NPM-AI-SLA integrated management process framework aims to turn contracting into a continuous, data-driven learning cycle for evolving public service expertise.

Smart, Ethical, Learning Civil Service = f(GRC)

An AI-augmented, GRC-TQM-NPM new public management framework, transforms into self-improving governance with Continuous Quality Improvement, Performance-based Public Management, AI Copilots & SLA-driven Automation.

1. FOUNDATION PHASE: Governance & Compliance Setup Building the institutional & digital foundation for GRC & SLA management

  1. Define governance structure & oversight bodies
  2. Develop unified public procurement policy framework
  3. Design standard SLA templates (service, quality, risk)
  4. Implement legal & compliance mapping
  5. Deploy GRC platform with role-based controls

2. AUTOMATION PHASE: Digital Workflow & SLA Management Operationalizing the contract lifecycle with automation & performance data

  1. Digitize procurement lifecycle (needs > tender > execution > evaluation)
  2. Integrate SLA management into contract modules
  3. Implement automated compliance & workflow triggers
  4. Train civil servants in using the digital platform
  5. Deploy ContractCopilot & MonitoringCopilot

3. TRANSPARENCY PHASE: Data Integration & Risk Analytics Ensuring open, traceable & accountable procurement through data-driven governance

  1. Integrate procurement data across systems (finance, HR, audit)
  2. Publish open contracting data (OCDS format)
  3. Apply AI analytics for fraud detection & performance trends
  4. Generate real-time risk dashboards & reports
  5. Implement EvaluationCopilot for scoring & anomaly alerts

4. LEARNING SYSTEM PHASE: Institutional Feedback & Knowledge Capture Transforming performance data into organizational learning & quality improvement

  1. Capture lessons learned after each contract cycle
  2. Analyze performance gaps & root causes
  3. Generate AI-curated learning summaries
  4. Update best-practice repositories
  5. Develop microlearning modules for civil servants

5. OPTIMIZATION PHASE: Continuous Improvement & Adaptive Governance Institutionalizing TQM principles through adaptive, data-driven management

  1. Review & benchmark service quality performance
  2. Conduct Kaizen-style process reviews
  3. Adjust SLA templates, KPIs & governance paramneters
  4. Implement feedback into policy & training cycles
  5. Monitor improvement through predictive analytics

This is a technology-based next-generation public management model for a learning, data-driven civil service where TQM provides quality discipline, GRC provides governance integrity and NPM ensures performance & citizen value, all fused together by AI copilots & SLA-based automation.

Using the following link you can access this sandbox SIPOC model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/1aFSCieNbhYbiF3RFM9qpv1k/frontend