Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Apply the three-level framework of digital transformation — Digitization, Digitalization, and Digital Transformation — to diagnose and plan organizational change enabled by digital technologies. Use this skill when the user needs to assess an organization's digital maturity, distinguish between automating processes versus transforming business models, plan a DX roadmap, or when they ask 'where are we on digital transformation', 'is this digitization or real transformation', or 'how do we build a
.claude/skills/asgard-ai-platform-grad-digital-transformation/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-15 | ✗→✓ | ▲ Improved | 9% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 74% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 27% | 0% |
Digital transformation operates at three distinct levels. Digitization converts analog information to digital format. Digitalization leverages digital technologies to improve existing business processes. Digital Transformation (DX) fundamentally reshapes business models, value creation logic, and organizational identity through digital technologies. Conflating these levels leads to strategic misdirection — most organizations that claim transformation are merely digitizing.
IRON LAW: Digital transformation is an ORGANIZATIONAL change enabled by
technology — technology alone does NOT transform; without strategy and
culture change, it is merely digitization.Key assumptions:
Classify the organization's current digital initiatives across the three levels:
| Level | Definition | Example | Value Impact | |-------|-----------|---------|-------------| | Digitization | Analog to digital conversion | Paper forms to PDF, scanning records | Efficiency of storage/retrieval | | Digitalization | Process improvement via digital tech | Workflow automation, CRM deployment | Operational efficiency | | Digital Transformation | Business model and value logic change | Platform business, data-driven services | Strategic differentiation |
Evaluate organizational readiness across four dimensions:
Define the target state and intermediate milestones. Identify which initiatives are truly transformational (changing what value is created and for whom) versus digitalizing (improving how existing value is delivered).
Establish DX governance that is cross-functional (not IT-only). Define metrics at each level: efficiency gains (digitization), process KPIs (digitalization), new revenue streams and business model metrics (transformation).
markdown## Digital Transformation Assessment: [Organization] ### Current State Diagnosis | Initiative | Level | Evidence | Gap to Next Level | |-----------|-------|----------|-------------------| | | | | | ### Enabler Assessment | Dimension | Maturity (1-5) | Key Strength | Key Gap | |-----------|---------------|-------------|---------| | Digital Strategy | | | | | Leadership | | | | | Culture | | | | | Capabilities | | | | ### Transformation Roadmap - Phase 1 (Digitization): ... - Phase 2 (Digitalization): ... - Phase 3 (Transformation): ... ### Governance & Metrics | Level | Metric Type | Specific Metrics | |-------|-----------|-----------------| | Digitization | Efficiency | | | Digitalization | Process KPI | | | Transformation | Business model | | ### Strategic Recommendations 1. ... 2. ...
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-15 | fail→pass | 28,484 | 19,109 | -33% | 1 | 1 | 0% | 3,730 | 4,052 | +9% | 0 | 0 | — |
case-01 | pass→pass | 37,021 | 24,519 | -34% | 1 | 1 | 0% | 5,159 | 4,599 | -11% | 0 | 0 | — |
case-02 | pass→pass | 35,741 | 25,048 | -30% | 1 | 1 | 0% | 5,424 | 4,668 | -14% | 0 | 0 | — |
case-03 | pass→pass | 52,587 | 27,910 | -47% | 1 | 1 | 0% | 7,504 | 4,801 | -36% | 0 | 0 | — |
case-04 | pass→pass | 20,490 | 20,887 | +2% | 1 | 1 | 0% | 3,450 | 4,451 | +29% | 0 | 0 | — |
case-05 | pass→pass | 33,309 | 27,863 | -16% | 1 | 1 | 0% | 4,543 | 4,451 | -2% | 0 | 0 | — |
case-06 | pass→pass | 47,693 | 40,783 | -14% | 1 | 1 | 0% | 8,237 | 8,109 | -2% | 0 | 0 | — |
case-07 | pass→pass | 23,142 | 22,102 | -4% | 1 | 1 | 0% | 3,155 | 4,049 | +28% | 0 | 0 | — |
case-08 | fail→pass | 24,491 | 22,593 | -8% | 1 | 1 | 0% | 3,204 | 3,857 | +20% | 0 | 0 | — |
case-09 | fail→pass | 18,039 | 15,912 | -12% | 1 | 1 | 0% | 2,894 | 3,737 | +29% | 0 | 0 | — |
case-10 | pass→pass | 22,247 | 15,753 | -29% | 1 | 1 | 0% | 2,658 | 3,652 | +37% | 0 | 0 | — |
case-11 | pass→pass | 22,203 | 18,013 | -19% | 1 | 1 | 0% | 3,694 | 4,165 | +13% | 0 | 0 | — |
case-12 | fail→pass | 13,505 | 19,293 | +43% | 1 | 1 | 0% | 2,088 | 3,641 | +74% | 0 | 0 | — |
case-13 | fail→pass | 21,392 | 34,306 | +60% | 1 | 1 | 0% | 3,358 | 4,270 | +27% | 0 | 0 | — |
case-14 | fail→pass | 19,900 | 16,309 | -18% | 1 | 1 | 0% | 2,636 | 3,776 | +43% | 0 | 0 | — |
case-16 | pass→pass | 14,795 | 22,970 | +55% | 1 | 1 | 0% | 2,160 | 4,076 | +89% | 0 | 0 | — |
case-17 | fail→pass | 13,155 | 19,937 | +52% | 1 | 1 | 0% | 1,945 | 4,276 | +120% | 0 | 0 | — |
case-18 | fail→pass | 17,968 | 20,718 | +15% | 1 | 1 | 0% | 2,781 | 3,828 | +38% | 0 | 0 | — |
case-19 | fail→pass | 16,771 | 18,837 | +12% | 1 | 1 | 0% | 2,470 | 4,104 | +66% | 0 | 0 | — |
case-20 | pass→pass | 16,894 | 14,562 | -14% | 1 | 1 | 0% | 2,095 | 3,510 | +68% | 0 | 0 | — |
case-21 | pass→pass | 19,006 | 22,343 | +18% | 1 | 1 | 0% | 2,704 | 3,920 | +45% | 0 | 0 | — |
case-22 | fail→pass | 49,876 | 19,229 | -61% | 1 | 1 | 0% | 3,966 | 4,166 | +5% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +45 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.