studies/202602_AmazonConnect -> studies/202602_TEI_Amazon_Connect, rebuilt as pattern Variant 4 (TEI composite reproduction): - teicalc/ self-contained engine (stdlib-only): Forrester's tables as the never-edited verbatim anchor, NPV/ROI/payback + risk adjustment transplanted from core/calculations, ClientDrivers overlay (contacts/ agents/fixed driver map, growth re-base, identity at composite scale), scenario stress with core-identical semantics - one deliverable notebook (business_case.ipynb): widget-pair sidebar drivers, published-vs-overlay KPI columns, cash-flow/waterfall/scenario charts, verification gate, backstage JSON data appendix - gate + tests reproduce the published totals within PDF rounding: NPV $78.7M / ROI 342% / payback <6 months (engine $78,713,492 / 342.48% / 0.7 months); 27 study tests, headless nbconvert green, stage simulation leak-free, exports carry the appendix - old Athena workflow (00_provision..04_export, config.py, seed_data.py) deleted; git history preserves it; root test fixture repointed to teicalc.anchor - docs: study README rewritten; root README points new studies at template/MercuryNotebook; pattern doc stale ctm-token-calculator paths now cite studies/202607_CTM_GenesysCX; Variant 4 cites this study as its realized reference Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
98 lines
3.9 KiB
Markdown
98 lines
3.9 KiB
Markdown
# 202602 — Amazon Connect TEI
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Self-contained reproduction of the Forrester *Total Economic Impact™ Of
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Amazon Connect* study (February 2026, commissioned by AWS), built on the
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[Mercury Notebook Deliverable Pattern](../../docs/Mercury_Notebook_Pattern_V1-00.md)
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as **Variant 4 — TEI composite reproduction**: Forrester's composite
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organization is the never-edited verbatim anchor, the in-notebook gate
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proves the engine reproduces the published totals, and 🟡 client drivers
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rescale the composite live.
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## Source
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The full Forrester study is at
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[`docs/202602_TEI Report Amazon Connect.pdf`](docs/202602_TEI%20Report%20Amazon%20Connect.pdf).
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Published composite totals (3-yr risk-adjusted PV @ 10%), reproduced by
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`teicalc` to within the PDF's own table rounding (benefits PV lands $223
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low; costs PV $0.22 low):
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| Metric | Published | Engine |
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|---|---|---|
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| Benefits PV | **$101,696,791** | $101,696,568 |
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| Costs PV | **$22,983,076** | $22,983,076 |
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| NPV | **$78,713,715** | $78,713,492 |
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| ROI | **342%** | 342.48% |
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| Payback | **<6 months** | 0.7 months |
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## Composite organization (the verbatim anchor 🟢)
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* Global B2C, ~$10B revenue (Y1), 30% YoY growth
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* 2,000 contact-center agents, 200 supervisors
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* 20M annual contacts (75% calls, 25% chat)
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* 10-min average handle time
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## Client overlay (🟡)
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A first-order linear rescale — "the composite at your size", not "your
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TEI". Each published row scales with the driver that dominates its PDF
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derivation:
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| Row | Driver | Confidence |
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| AI contact resolution · content/sentiment | contacts | 🟡 |
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| Forecasting/supervision · legacy savings | agents | 🟡 |
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| Data-driven profit lift | contacts | 🔴 proxy (revenue-driven in the PDF) |
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| Amazon Connect usage | contacts | 🟡 |
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| Implementation · ongoing management | fixed | 🟡 project-based |
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The client growth rate re-bases the composite's Y1→Y3 trajectory (which
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embeds 30% YoY). At composite scale the overlay is the identity — the
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gate asserts it.
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## Layout
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```
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202602_TEI_Amazon_Connect/
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├── teicalc/ ← ALL math (stdlib-only) — notebooks hold none
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│ ├── anchor.py ← Forrester's tables, VERBATIM, never edited
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│ ├── model.py ← NPV/ROI/payback, risk adjustment, compute_summary
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│ ├── overlay.py ← ClientDrivers + driver map + overlay_rows
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│ ├── scenarios.py ← conservative / moderate / aggressive
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│ └── staging.py ← on_stage()/backstage() (Mercury vs nbconvert)
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├── notebooks/business_case.ipynb ← THE deliverable
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├── scripts/export_report.py
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├── tests/ ← hand-checked pinned acceptance numbers
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├── config.toml ← Mercury theme (NTT DATA brand)
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├── pyproject.toml ← full toolchain as core deps — no requirements.txt
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├── docs/ ← the Forrester PDF
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└── exports/ ← generated .html/.md; gitignored
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```
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## Run
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```bash
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python -m venv .venv && source .venv/bin/activate
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pip install -e ".[dev]"
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```
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| Task | Command |
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| Tests | `pytest` |
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| Serve (the stage) | `mercury --working-dir notebooks/` (run from this project root so `config.toml` loads) |
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| Analyst view (backstage) | `jupyter lab` |
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| Headless check | `jupyter nbconvert --to notebook --execute --inplace notebooks/business_case.ipynb` |
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| Export for LLMs | `python scripts/export_report.py` |
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The data appendix (markdown tables + JSON model state) rides inside
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`exports/business_case.md` — it replaces the retired `exports/export.json`
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pipeline and is the payload for the Athena study-repository roadmap.
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## History
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This study previously ran on the shared `core/` package with an
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Athena-workflow notebook chain (provision → push → calculate → export).
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That workflow was retired when the study migrated to the pattern
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(git history preserves it); the engine reproduces the same published
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totals locally, pinned in `tests/`.
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