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NTT Data

2 cohorts  ·  0 feedback entries  ·  0 open actions
Programme record · NTT Data

Quantitative data from post-programme surveys. NPS, participation, and benchmark against programme average across all cohorts attended.

Pooled NPS
too few to report
n=3 D2 · need ≥20
Cohorts attended
2
CohortCityDatesD1 nD2 nNPSProg avgGapP/Pa/D
C6LondonMay 18–19, 202632+100+43+57
P 100%/Pa 0%/D 0%
C27LondonJuly 29–30, 202641+0+43-43
P 0%/Pa 100%/D 0%
Capability Profile
Persona mix
Developer 29%Architect 57%T.Lead 14%
AI proficiency
Learning 14%Applying 29%Independent 14%Frontier 43%
Seniority mix
Sr Prac 67%Mgr 33%
Content depth
Too basic 29%About right 71%
Pace
Well paced 100%
Relevance (mean)
4.8 / 5
D1 confidence (mean)
4.3 / 5
Confidence Δ (D1→D2)
n=3 · too few
Confidence growth by domain
Build Δ
n=3 · too few
Design Δ
n=3 · too few
Commercial Δ
n=3 · too few
Satisfaction by Persona
Developer
n=1 · too few
Architect
n=2 · too few
Strategic Insights
Advanced readiness: 43% at Frontier level — partner is ready for complex implementation engagements
Feedback log · NTT Data

Anecdotal feedback from partner reps, stakeholders, and other sources. Each entry is sourced and benchmarked against survey data where available. Hearsay entries are flagged — weight accordingly.

No feedback logged yet. Run org_intake.py to add entries.
Action items · NTT Data

Org-specific actions arising from survey data and feedback. Programme-wide actions are tracked separately in programme-actions.yaml.

No open action items.