INNOPAS D9 Framework
INNOPAS D9 is a comprehensive, leadership-ready maturity assessment framework that evaluates digital, data, analytics, and AI capabilities across nine critical dimensions. It goes beyond traditional maturity models by translating raw scores into precise, actionable decisions—identifying exactly what to stabilise first, where to enforce standards, and when your organisation is ready to scale advanced analytics or responsibly deploy AI. Designed specifically for executive reviews, D9 provides a shared language and visual tools (like one-page heatmaps) that align business and technology leaders on priorities, risks, and investment sequencing.
Whether you’re running a single transformation program, managing a portfolio of schemes, or preparing for enterprise-wide AI adoption, D9 ensures efforts target the true binding constraints rather than symptoms or siloed initiatives.
Why D9? Solving real transformation challenges
Many organizations invest heavily in digital tools, data platforms, and AI pilots only to see limited impact due to underlying gaps in governance, data trust, or decision adoption. D9 addresses this by combining end-to-end coverage (nine interconnected dimensions) with a diagnostic “Tri-Lens” method that reveals why maturity is stalled, not just what the score is.
The result? Clear portfolio-level prioritization, reduced risk of premature scaling, and a repeatable system for tracking progress across business units, functions, or schemes. Leaders use D9 in governance forums to answer: “Where are we leaking value today? Which gaps block AI? What should we fund next?”
The nine D9 dimensions: Complete transformation coverage
D9™ assesses maturity holistically across the full digital value chain, ensuring no critical gaps are overlooked
D1: Strategy & Governance
From ad-hoc ownership to predictive, outcome-driven governance
D2: Process Digitisation
From manual workflows to self-optimising, exception-managed processes.
D3: Data Availability
From silos to real-time, interoperable data ecosystems.
D4: Data Quality & Trust
From low-confidence data to predictive anomaly detection
D5: Platform & Interoperability
From point solutions to optimised, shared service ecosystems.
D6: Analytics & Insights
From static reports to AI-assisted decisioning.
D7: Stakeholder Experience
From unmanaged pain points to proactive, inclusive design.
D8: Security & Compliance
From weak controls to security-by-design with continuous monitoring.
D9: AI Adoption Readiness
From no governance to trusted, auditable AI at scale
All these methodologies have a focus on process. At its most basic level Process Excellence is not about any methodology but about improving the way businesses create and deliver value to customers.
The 5-level maturity model: Executive-readable and comparable
Every D9 dimension follows a consistent 5-level scale, described in plain language for quick leadership interpretation:
| Maturity Level | Description | Focus Areas |
|---|---|---|
|
Level 1: Initial |
Fragmented, ad-hoc practices with heavy manual dependency, low trust, and weak controls. |
High leakage and operational risk |
|
Level 2: Basic |
Partially defined capabilities with inconsistent outcomes and basic checks |
Weak accountability and unreliable execution. |
|
Level 3: Defined |
Documented, repeatable processes with end-to-end coverage and periodic reviews |
Stable but plateaued; ready for enforcement. |
|
Level 4: Managed |
Automated, SLA-driven execution with active monitoring and exception handling |
Reliable and scalable; under-utilised potential. |
|
Level 5: Optimised |
Predictive, self-improving systems with AI-assisted decisioning and continuous assurance |
Innovation-ready; focus on scaling best practices. |
These levels enable apples-to-apples comparisons across schemes, functions, or competitors, turning assessments into strategic discussions.
Tri-Lens method:
Diagnose the why behind every score
D9s breakthrough is the Tri-Lens approach, which breaks each dimension into three interdependent factors. The “limiting lens”—the lowest score—becomes the binding constraint dictating action priority.
Lens 1: Capability
Does the operational ability exist, scale reliably, and perform without heavy manual workarounds? (E.g., end-to-end digitized workflows vs. point solutions
Lens 2: Control
Does the operational ability exist, scale reliably, and perform without heavy manual workarounds? (E.g., end-to-end digitized workflows vs. point solutions
Lens 3: Outcome Linkage
Does the operational ability exist, scale reliably, and perform without heavy manual workarounds? (E.g., end-to-end digitized workflows vs. point solutions
Action Decision Matrix: Scores → Investments → Results
D9 maps every dimension score directly to risks, action types, and interventions making it a practical tool for budget and roadmap decisions
| Score | Maturity | Primary Risk | Action Type | Typical Interventions |
|---|---|---|---|---|
|
1 |
Initial/Fragmented |
High leakage, manual dependency |
Stabilise & Standardise |
Basic digitisation, ownership definition, minimum controls. |
|
2 |
Basic/Partially Defined |
Inconsistent outcomes |
Strengthen Foundations |
Workflow standardisation, DQ rules, KPI redesign. |
|
3 |
Defined |
Performance plateau |
Enforce & Integrate |
SLA enforcement, API integrations, action tracking. |
|
4 |
Managed |
Under-utilised potential |
Optimise & Predict |
Advanced analytics, early-warning systems. |
|
5 |
Optimised |
Missed innovation |
Innovate & Scale |
AI decision support, continuous optimisation |
Leadership guidance: Always fix the limiting lens first, then sequence investments top-down by risk.
AI Adoption Readiness Gate: Scale AI responsibly
D9 enforces a strict pre-condition gate before AI deployment, protecting against common pitfalls like “AI on untrustworthy data
| Pre-Condition Dimension | Minimum Score | If Not Met |
|---|---|---|
|
D4: Data Quality & Trust |
≥ 3 |
Do not introduce AI (low data confidence) |
|
D6: Analytics & Insights |
≥ 3 |
Restrict to reporting (insights not actioned) |
|
D8: Security & Compliance |
≥ 3 |
Block AI deployment (misuse/breach risk). |
Only when these gates pass can you proceed to controlled pilots, then trusted, auditable AI at scale
Portfolio Prioritization Heatmap: Enterprise-scale decisions
Organizations are continuously looking at ways to improve their business outcomes by adopting various approaches to improve their Customer Experience and Quality by adopting Industry standards and Models like Total Quality Management, Business Process Reengineering, Lean Six Sigma.
Multiple dims ≤2
Pause expansion; fund foundations.
Strong capability, weak outcomes:
Redirect to decision workflows.
Weak D4/D8:
Block AI; automate trust first.
Plateau at 3
Prioritize integration over new tools.
Ready core, weak D9
Approve human-in-loop AI pilots.
This turns scattershot investments into a sequenced roadmap.
One-page maturity heatmaps
Limiting lens diagnostics,
AI-gated roadmaps, and
Portfolio prioritization. Clients get a living decision system—not a static report for quarterly governance reviews
How Innopas delivers D9 assessments
We run rapid D9 assessments to produce
Get started with your D9 assessment
Share your key processes, data landscape, or AI ambitions, and we’ll scope a tailored D9 review (domain-specific, portfolio-wide, or AI-readiness focused). Contact us to eliminate transformation guesswork.