# 202602 — Amazon Connect TEI

Self-contained reproduction of the Forrester *Total Economic Impact™ Of
Amazon Connect* study (February 2026, commissioned by AWS), built on the
[Mercury Notebook Deliverable Pattern](../../docs/Mercury_Notebook_Pattern_V1-00.md)
as **Variant 4 — TEI composite reproduction**: Forrester's composite
organization is the never-edited verbatim anchor, the in-notebook gate
proves the engine reproduces the published totals, and 🟡 client drivers
rescale the composite live.

## Source

The full Forrester study is at
[`docs/202602_TEI Report Amazon Connect.pdf`](docs/202602_TEI%20Report%20Amazon%20Connect.pdf).

Published composite totals (3-yr risk-adjusted PV @ 10%), reproduced by
`teicalc` to within the PDF's own table rounding (benefits PV lands $223
low; costs PV $0.22 low):

| Metric | Published | Engine |
|---|---|---|
| Benefits PV | **$101,696,791** | $101,696,568 |
| Costs PV | **$22,983,076** | $22,983,076 |
| NPV | **$78,713,715** | $78,713,492 |
| ROI | **342%** | 342.48% |
| Payback | **<6 months** | 0.7 months |

## Composite organization (the verbatim anchor 🟢)

* Global B2C, ~$10B revenue (Y1), 30% YoY growth
* 2,000 contact-center agents, 200 supervisors
* 20M annual contacts (75% calls, 25% chat)
* 10-min average handle time

## Client overlay (🟡)

A first-order linear rescale — "the composite at your size", not "your
TEI". Each published row scales with the driver that dominates its PDF
derivation:

| Row | Driver | Confidence |
|---|---|---|
| AI contact resolution · content/sentiment | contacts | 🟡 |
| Forecasting/supervision · legacy savings | agents | 🟡 |
| Data-driven profit lift | contacts | 🔴 proxy (revenue-driven in the PDF) |
| Amazon Connect usage | contacts | 🟡 |
| Implementation · ongoing management | fixed | 🟡 project-based |

The client growth rate re-bases the composite's Y1→Y3 trajectory (which
embeds 30% YoY). At composite scale the overlay is the identity — the
gate asserts it.

## Layout

```
202602_TEI_Amazon_Connect/
├── teicalc/               ← ALL math (stdlib-only) — notebooks hold none
│   ├── anchor.py          ← Forrester's tables, VERBATIM, never edited
│   ├── model.py           ← NPV/ROI/payback, risk adjustment, compute_summary
│   ├── overlay.py         ← ClientDrivers + driver map + overlay_rows
│   ├── scenarios.py       ← conservative / moderate / aggressive
│   └── staging.py         ← on_stage()/backstage() (Mercury vs nbconvert)
├── notebooks/business_case.ipynb   ← THE deliverable
├── scripts/export_report.py
├── tests/                 ← hand-checked pinned acceptance numbers
├── config.toml            ← Mercury theme (NTT DATA brand)
├── pyproject.toml         ← full toolchain as core deps — no requirements.txt
├── docs/                  ← the Forrester PDF
└── exports/               ← generated .html/.md; gitignored
```

## Run

```bash
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
```

| Task | Command |
|---|---|
| Tests | `pytest` |
| Serve (the stage) | `mercury --working-dir notebooks/` (run from this project root so `config.toml` loads) |
| Analyst view (backstage) | `jupyter lab` |
| Headless check | `jupyter nbconvert --to notebook --execute --inplace notebooks/business_case.ipynb` |
| Export for LLMs | `python scripts/export_report.py` |

The data appendix (markdown tables + JSON model state) rides inside
`exports/business_case.md` — it replaces the retired `exports/export.json`
pipeline and is the payload for the Athena study-repository roadmap.

## History

This study previously ran on the shared `core/` package with an
Athena-workflow notebook chain (provision → push → calculate → export).
That workflow was retired when the study migrated to the pattern
(git history preserves it); the engine reproduces the same published
totals locally, pinned in `tests/`.
