TA Transformations
Real problems. Real systems. Real results.
Three transformations across AI rollout, global operating model, and shared services centralization.
AI Adoption Curve · 6 Months
Click a point to see what drove it
AI-native ✓
Month 4
AI became the default, not an add-on. Pipeline quality improved. Candidate experience improved. 20% faster time-to-hire — not despite the automation, because of how we built it.
40 Countries · One operating model
Drag the slider — or scroll — to watch the model take shape
Diagnosis
I didn't build three COEs from scratch — I created synergy where it was fragmented and chaotic. 40 country offices, each running their own playbook, became one operating model with three regional hubs absorbing volume hiring. Time-to-fill dropped 37%. Agency spend dropped 30%.
Before vs. After
What changed when the system was rebuilt
Before
Stuck at 13% — no visible career paths
Internal MobilityAfter
40%
3× lift after launching mobility on a real job architecture
Before
Recruiters duplicating work across 40+ brands
Hiring EfficiencyAfter
+35%
Aligned by function, not brand. Eliminated duplication.
Before
Workday misconfigured. No sourcing, no reporting.
Pipeline HealthAfter
+33%
Recruiters could finally source, track, and report.
Dotdash Meredith was mid-transformation — moving from a legacy print publisher to digital-first after acquiring Time Inc. in 2018. The business needed a TA function built to hire for that shift. What it had was the opposite.
- 40+ brands across 4 verticals (PEOPLE, InStyle, Better Homes & Gardens, Allrecipes, Health, Parents…) each running its own isolated TA process.
- Recruiter sprawl. Two recruiters often covering the same pool of jobs with no coordination. No specialization, no real expertise.
- Broken Workday. Misconfigured from day one — no sourcing, no pipeline visibility, no reporting.
- Internal mobility stuck at 13%, attrition high, pipeline health declining.