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Zartis

3 cohorts  ·  0 feedback entries  ·  0 open actions
Programme record · Zartis

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

Pooled NPS
too few to report
n=6 D2 · need ≥20
Cohorts attended
3
CohortCityDatesD1 nD2 nNPSProg avgGapP/Pa/D
C13LondonJune 2-3, 202622+0+40-40
P 0%/Pa 100%/D 0%
C14LondonJune 4-5, 202633+67+39+28
P 67%/Pa 33%/D 0%
C16LondonJune 15-16, 202621+100+17+83
P 100%/Pa 0%/D 0%
Capability Profile
Persona mix
Developer 86%Architect 14%
AI proficiency
Learning 14%Applying 57%Independent 29%
Seniority mix
Sr Prac 80%Mgr 20%
Content depth
Too basic 14%About right 86%
Pace
Well paced 71%Too fast 29%
Relevance (mean)
4.2 / 5
D1 confidence (mean)
3.9 / 5
Confidence Δ (D1→D2)
n=6 · too few
Confidence growth by domain
Build Δ
n=1 · too few
Design Δ
n=1 · too few
Commercial Δ
n=1 · too few
Feedback log · Zartis

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 · Zartis

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

No open action items.