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PRISM Product Requirements Document

Vision

PRISM (Program Rating & Improvement System for Maturity) provides a unified framework for measuring and improving organizational maturity across multiple domains: Security, Operations, Quality, and Product.

Problem Statement

Organizations struggle to:

  1. Measure maturity consistently - Different teams use different metrics and definitions
  2. Map to compliance frameworks - NIST, SOC 2, FedRAMP requirements are tracked separately
  3. Track improvement over time - No unified view of progress across domains
  4. Communicate to stakeholders - Technical metrics don't translate to executive dashboards

Solution

PRISM provides:

  1. Unified maturity model - 5-level (M1-M5) scale applicable to all domains
  2. SLI/SLO-backed levels - Each level defined by measurable criteria, not vague requirements
  3. Framework mappings - Built-in support for NIST CSF, NIST 800-53, FedRAMP, SOC 2, DORA, SRE
  4. Machine-readable specs - JSON/YAML specs that generate reports, dashboards, presentations
  5. Export formats - Markdown, XLSX, Marp slides for different audiences

Key Design Decisions

SLI vs SLO Separation

Decision: Define metrics (SLIs) separately from level-specific targets (Criteria/SLOs).

Rationale:

  • Framework mappings defined once per metric, not repeated per level
  • Cleaner exports with consistent metadata
  • Enables SLI Catalog for quick metric reference

Quantitative + Qualitative SLOs

Decision: Support both numeric thresholds and binary state tracking.

Rationale:

  • Quantitative: "MTTR ≤ 7 days" - measurable outcomes
  • Qualitative: "Encryption enabled" - binary compliance states
  • Both are valid maturity indicators

Domain-Centric Organization

Decision: Organize by domain (Security, Operations, Quality) rather than team or technology.

Rationale:

  • Domains align with organizational concerns
  • Cross-cutting view of capability
  • Easier to map to compliance frameworks

Domains

Domain Description Example Metrics
Security Application and infrastructure security SAST coverage, MTTR, secret detection
Operations Reliability, efficiency, deployment Availability, change failure rate, lead time
Quality Code quality, test coverage Test coverage, defect density, code review
Product Feature delivery, customer outcomes Cycle time, feature adoption

Maturity Levels

Level Name Description
M1 Reactive Ad-hoc processes, firefighting mode
M2 Basic Basic controls in place, some documentation
M3 Defined Standardized processes, consistent execution
M4 Managed Data-driven, measured and controlled
M5 Optimizing Continuous improvement, proactive automation

Framework Support

PRISM maps criteria to industry standards:

  • NIST CSF 2.0 - Cybersecurity Framework
  • NIST SP 800-53 - Security and Privacy Controls
  • FedRAMP - Federal Risk and Authorization Management
  • SOC 2 - Service Organization Controls
  • ISO 27001 - Information Security Management
  • DORA - Digital Operational Resilience Act
  • CIS Controls - Center for Internet Security
  • SRE - Site Reliability Engineering practices

Quality Model Alignment

PRISM quality metrics align with ISO/IEC 25010:

ISO 25010 Characteristic PRISM Category Example Metrics
Functional Suitability quality Test coverage, requirement coverage
Reliability reliability Availability, MTBF, error rate
Performance Efficiency efficiency Latency, throughput, resource usage
Security security Vulnerability count, SAST coverage
Maintainability quality Code complexity, documentation
Portability operations Deployment frequency, containerization

Export Formats

Format Use Case Command
Markdown Documentation sites, GitHub prism maturity report spec.json -o report.md
XLSX Executive dashboards, compliance prism maturity xlsx spec.json -o report.xlsx
JSON API integration, automation prism maturity report spec.json -f json
Marp Presentations prism export marp spec.json -o slides.md

Success Metrics

  1. Adoption - Teams using PRISM for maturity tracking
  2. Coverage - Percentage of services with defined maturity levels
  3. Accuracy - Automated vs manual assessment correlation
  4. Time savings - Reduction in compliance reporting effort

Future Directions

  1. Automated data collection - Pull metrics from observability platforms
  2. Trend analysis - Historical tracking with improvement visualization
  3. Benchmark data - Anonymous industry comparisons
  4. AI recommendations - Suggested enablers based on gaps

References