gpteal Productivity Uplift — Adopter vs Non-Adopter Throughput
Opportunity Lifecycle
★ Savings Opportunity
Description & Data Evidence
Analysts who have adopted gpteal process 9.1 cases per day on average, compared to 5.1 cases per day for the 5 non-adopters — a 78% throughput advantage. Handling time per case is similar across cohorts, suggesting the gain comes from reduced between-case friction (faster case orientation, less context-switching, AI-assisted decision support). If the 5 current non-adopters matched adopter productivity, ~3.5 hours per user per day would be freed for additional throughput. Caveat: cohort comparison is not fully controlled for case complexity and user experience — the 78% uplift is directional evidence, best validated with a controlled rollout.
Self-Evaluation Scores
The platform grades each finding on four dimensions (1–5 scale). Low scores flag findings that need more data or clearer remediation before acceptance.
Key Findings
- Adopters (9): avg 9.1 cases/day
- Non-adopters (5): avg 5.1 cases/day
- Productivity uplift: +78% for gpteal adopters
- Handling time per case is similar (~0.5 min) — gain is in throughput, not per-case speed
- Closing the gap for current non-adopters: ~4,376 hrs/yr at 17 users
- Projected at 1,000 users (assumes same adoption mix): ~312,473 hrs/yr
Case Evidence
Specific case IDs pulled from the pilot data where this pattern is most pronounced. In production, clicking a case opens its full event timeline.
| Case ID | Signal | Context |
|---|---|---|
2352839 |
28 gpteal events | 1 user(s) engaged |
2353427 |
18 gpteal events | 1 user(s) engaged |
2290475 |
18 gpteal events | 1 user(s) engaged |
2351639 |
15 gpteal events | 1 user(s) engaged |
2353957 |
14 gpteal events | 1 user(s) engaged |
Adopter vs Non-Adopter Productivity (Cases per Day)
Validation Questions
0 of 3 answeredRemediation Ideas
- Onboard the 5 non-adopters via power-user shadowing and workflow templates
- Embed gpteal prompts directly into Veeva Safety narrative and assessment sections
- Track weekly cases/day per analyst to measure adoption impact in real time
- A/B test: random 50% of new analysts onboarded with gpteal vs without, measure throughput delta at 90 days
- Expand adoption beyond narrative work — routine triage, MedDRA coding, translation verification
Implementation Roadmap
- gpteal license coverage for all analysts
- Power-user playbook + training materials
- Workflow integration with Veeva sections
- Training rollout to non-adopters (2-3 weeks)
- Workflow integration (3-4 weeks)
- Adoption measurement + iteration (ongoing)
How Risk-Adjusted Savings Is Calculated
The risk-adjusted number is the annual savings multiplied by a composite factor of four independent dimensions. Each dimension is rated High (1.0×), Medium (0.8×), or Low (0.5×). See full methodology.