feat: add GenesysCX study and fix Streamlit chart key collisions
- Add 202512_GenesysCX TEI study (config, seed data, notebooks, README) with NPV $10.8M / ROI 266% including AI-token cost line - Add explicit `key` parameter to all chart wrappers in app/components to prevent StreamlitDuplicateElementId errors when the same figure type renders across Summary/Benefits/Costs tabs - Render benefits bar and cost pie charts on their respective tabs - Add benefits_vs_costs_by_year chart wrapper
This commit is contained in:
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studies/202512_GenesysCX/notebooks/00_provision.ipynb
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929
studies/202512_GenesysCX/notebooks/00_provision.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "41520e77",
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"metadata": {},
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"source": [
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"# 00 · Provision — Genesys CX Cloud TEI in Athena\n",
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"\n",
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"Source study: Forrester, *The Total Economic Impact™ Of CX Cloud* (Genesys +\n",
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"Salesforce, December 2025). Published headline: **NPV \\$10.78M · ROI 266%**.\n",
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"\n",
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"This notebook creates everything the study needs in the Athena sandbox:\n",
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"\n",
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"1. **Report template** *CX Cloud (Genesys + Salesforce) 2025* + **field definitions** — 4 benefits, 3 published costs, **plus the `genesys_ai_tokens` consumption line the published study omits**\n",
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"2. **Client selection** from the CRM (profile pulled, no re-entry)\n",
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"3. **Attachment** to a Proposal or Engagement\n",
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"4. **Seed values** + server-side **calculation**\n",
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"5. **Two-tier verification**: exact match vs Athena-methodology expectations, then reconciliation to the published totals (explained Year-0 discounting delta)\n",
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"6. Persists study-scoped IDs (`PALLADIUM_GENESYSCX_*`) to `.env`\n",
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"\n",
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"Safe to re-run — every step finds existing objects before creating new ones."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "1b6f1117",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"✅ Athena connected — https://athena.ouranos.helu.ca (1 report templates visible)\n",
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"📁 Study: 202512_GenesysCX\n"
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]
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}
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],
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"source": [
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"import sys, pathlib # path shim: works on a fresh kernel\n",
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"for _p in [pathlib.Path.cwd(), *pathlib.Path.cwd().parents]:\n",
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" if (_p / \"pyproject.toml\").exists():\n",
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" sys.path.insert(0, str(_p)); break\n",
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"\n",
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"import pandas as pd\n",
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"from core.bootstrap import init, update_env\n",
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"\n",
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"pal = init(study=\"202512_GenesysCX\")\n",
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"client, seed, config = pal.client, pal.seed_data, pal.config\n",
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"assert pal.connection.get(\"status\") == \"ok\", \"Fix the connection first → 00_setup.ipynb\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "c1f8b6bd",
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"metadata": {},
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"source": [
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"## 1 · Report template (find or create)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "cc81e408",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Created report template UCb2hSJprSBx\n"
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]
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}
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],
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"source": [
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"REPORT_NAME, VENDOR = \"CX Cloud (Genesys + Salesforce) 2025\", \"Genesys\"\n",
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"\n",
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"report = next(\n",
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" (r for r in client.list_reports()\n",
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" if r.get(\"name\") == REPORT_NAME and r.get(\"vendor\") == VENDOR),\n",
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" None,\n",
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")\n",
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"if report is None:\n",
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" report = client.create_report(\n",
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" name=REPORT_NAME,\n",
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" vendor=VENDOR,\n",
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" version=\"1.0\",\n",
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" description=(\n",
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" \"Forrester TEI of CX Cloud (Genesys + Salesforce), Dec 2025. \"\n",
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" \"Includes Palladium's genesys_ai_tokens consumption line, \"\n",
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" \"which the published study omits.\"\n",
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" ),\n",
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" analysis_period_years=seed.ASSUMPTIONS[\"analysis_years\"],\n",
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" discount_rate=seed.ASSUMPTIONS[\"discount_rate\"],\n",
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" status=\"draft\",\n",
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" )\n",
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" print(f\"Created report template {report['id']}\")\n",
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"else:\n",
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" print(f\"Found existing report template {report['id']} (status: {report.get('status')})\")\n",
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"\n",
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"REPORT_ID = report[\"id\"]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e31bbd8b",
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"metadata": {},
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"source": [
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"## 2 · Field definitions\n",
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"\n",
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"Same Palladium conventions as the Amazon Connect study: benefit risk\n",
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"adjustments live on the field; cost values get pushed pre-multiplied by\n",
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"`(1 + risk_adj)`; Year-0 amounts use companion `*_initial` fields.\n",
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"The `genesys_ai_tokens` line is seeded \\$0 (reproduces the published study) —\n",
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"the annual cost gets entered per deal, from the Genesys quote, in\n",
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"`01_business_case.ipynb`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "55e69828",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"12 fields created, 0 already existed.\n",
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"Report template activated.\n"
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]
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}
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],
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"source": [
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"def field_defs():\n",
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" defs, sort = [], 0\n",
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" for b in seed.BENEFITS:\n",
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" sort += 1\n",
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" defs.append({\n",
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" \"table\": \"benefits\",\n",
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" \"field_key\": b[\"field_key\"],\n",
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" \"label\": b[\"label\"],\n",
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" \"description\": b[\"notes\"][:200],\n",
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" \"field_type\": \"currency\",\n",
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" \"category\": b[\"category\"],\n",
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" \"is_annual\": True,\n",
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" \"risk_adjustment\": str(b[\"risk_adjustment\"]),\n",
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" \"sort_order\": sort,\n",
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" \"is_required\": True,\n",
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" \"source_notes\": b[\"notes\"],\n",
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" })\n",
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" for c in seed.COSTS:\n",
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" sort += 1\n",
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" defs.append({\n",
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" \"table\": \"costs\",\n",
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" \"field_key\": c[\"field_key\"],\n",
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" \"label\": c[\"label\"],\n",
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" \"description\": c[\"notes\"][:200],\n",
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" \"field_type\": \"currency\",\n",
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" \"category\": c[\"category\"],\n",
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" \"is_annual\": True,\n",
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" \"risk_adjustment\": \"0\", # cost risk adj applied client-side\n",
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" \"sort_order\": sort,\n",
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" \"is_required\": False,\n",
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" \"source_notes\": c[\"notes\"],\n",
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" })\n",
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" sort += 1\n",
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" defs.append({\n",
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" \"table\": \"costs\",\n",
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" \"field_key\": f\"{c['field_key']}_initial\",\n",
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" \"label\": f\"{c['label']} — initial (Year 0)\",\n",
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" \"description\": \"One-time Year-0 amount (companion field).\",\n",
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" \"field_type\": \"currency\",\n",
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" \"category\": c[\"category\"],\n",
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" \"is_annual\": False,\n",
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" \"risk_adjustment\": \"0\",\n",
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" \"sort_order\": sort,\n",
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" \"is_required\": False,\n",
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" \"source_notes\": \"Year-0 lump sum; Athena treats non-annual values as Year 1.\",\n",
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" })\n",
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" return defs\n",
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"\n",
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"existing = {f[\"field_key\"] for f in client.list_fields(REPORT_ID)}\n",
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"created = 0\n",
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"for d in field_defs():\n",
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" if d[\"field_key\"] not in existing:\n",
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" client.create_field(REPORT_ID, d)\n",
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" created += 1\n",
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"print(f\"{created} fields created, {len(existing)} already existed.\")\n",
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"\n",
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"if report.get(\"status\") == \"draft\":\n",
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" client.update_report(REPORT_ID, status=\"active\")\n",
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" print(\"Report template activated.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "96b360d3",
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"metadata": {},
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"source": [
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"## 3 · Select the client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "5a0a701f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>name</th>\n",
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" <th>vertical</th>\n",
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" <th>client_type</th>\n",
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" <th>employee_count</th>\n",
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" <th>contact_center_agent_count</th>\n",
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" <th>supervisor_count</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>2</td>\n",
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" <td>Global Guardian Insurance</td>\n",
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" <td>None</td>\n",
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" <td>For-Profit</td>\n",
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" <td>12000</td>\n",
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" <td>2500</td>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>3</td>\n",
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" <td>Eudaimonix</td>\n",
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" <td>None</td>\n",
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" <td>For-Profit</td>\n",
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" <td>1500</td>\n",
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" <td>300</td>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>4</td>\n",
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" <td>Aetherium Forge</td>\n",
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" <td>None</td>\n",
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" <td>For-Profit</td>\n",
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" <td>500</td>\n",
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" <td>42</td>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" id name vertical client_type employee_count \\\n",
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"0 2 Global Guardian Insurance None For-Profit 12000 \n",
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"1 3 Eudaimonix None For-Profit 1500 \n",
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"2 4 Aetherium Forge None For-Profit 500 \n",
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"\n",
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" contact_center_agent_count supervisor_count \n",
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"0 2500 None \n",
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"1 300 None \n",
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"2 42 None "
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"CLIENT_SEARCH = \"\" # e.g. \"Acme\" — empty lists everyone\n",
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"\n",
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"clients = client.list_clients(search=CLIENT_SEARCH or None)\n",
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"if clients:\n",
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" display(pd.DataFrame(clients)[\n",
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" [c for c in (\"id\", \"name\", \"vertical\", \"client_type\", \"employee_count\",\n",
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" \"contact_center_agent_count\", \"supervisor_count\")\n",
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" if c in clients[0]]\n",
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" ])\n",
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"else:\n",
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" print(\"No clients found — create one in the Athena UI (Orbit → Clients) and re-run.\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "1e375b54",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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||||
" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Global Guardian Insurance</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>id</th>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>name</th>\n",
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" <td>Global Guardian Insurance</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>abbreviated_name</th>\n",
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" <td>GGI</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>vertical</th>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>client_type</th>\n",
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" <td>For-Profit</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>employee_count</th>\n",
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" <td>12000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>revenue</th>\n",
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" <td>4500000000.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>contact_center_agent_count</th>\n",
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" <td>2500</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>service_desk_agent_count</th>\n",
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" <td>300</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>supervisor_count</th>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>location_count</th>\n",
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" <td>120</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Global Guardian Insurance\n",
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"id 2\n",
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"name Global Guardian Insurance\n",
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"abbreviated_name GGI\n",
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"vertical None\n",
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"client_type For-Profit\n",
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"employee_count 12000\n",
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"revenue 4500000000.0\n",
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"contact_center_agent_count 2500\n",
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"service_desk_agent_count 300\n",
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"supervisor_count None\n",
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"location_count 120"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CRM agent count: 2500 (composite: 600) — indicative scale 4.17×\n",
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"CRM revenue: $4,500,000,000 (composite: $2,500,000,000)\n"
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]
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}
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],
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"source": [
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"CLIENT_ID = 2 # ← set from the `id` column above, or leave for auto-pick\n",
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"\n",
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"if CLIENT_ID is None and len(clients) == 1:\n",
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" CLIENT_ID = clients[0][\"id\"]\n",
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" print(f\"Auto-selected the only client: {clients[0]['name']} (id={CLIENT_ID})\")\n",
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"assert CLIENT_ID is not None, \"Set CLIENT_ID from the table above and re-run this cell.\"\n",
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"\n",
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"profile = client.client_profile(CLIENT_ID)\n",
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"CLIENT_NAME = profile[\"name\"]\n",
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"display(pd.DataFrame([profile]).T.rename(columns={0: CLIENT_NAME}))\n",
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"\n",
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"# Client data → study scaling levers (no re-entry)\n",
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"CLIENT_ASSUMPTIONS = dict(seed.ASSUMPTIONS)\n",
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"if profile.get(\"contact_center_agent_count\"):\n",
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" CLIENT_ASSUMPTIONS[\"agents_fte\"] = profile[\"contact_center_agent_count\"]\n",
|
||||
" scale = CLIENT_ASSUMPTIONS[\"agents_fte\"] / seed.ASSUMPTIONS[\"agents_fte\"]\n",
|
||||
" print(f\"CRM agent count: {CLIENT_ASSUMPTIONS['agents_fte']} \"\n",
|
||||
" f\"(composite: {seed.ASSUMPTIONS['agents_fte']}) — \"\n",
|
||||
" f\"indicative scale {scale:.2f}×\")\n",
|
||||
"if profile.get(\"revenue\"):\n",
|
||||
" CLIENT_ASSUMPTIONS[\"annual_revenue\"] = float(profile[\"revenue\"])\n",
|
||||
" print(f\"CRM revenue: ${CLIENT_ASSUMPTIONS['annual_revenue']:,.0f} \"\n",
|
||||
" f\"(composite: ${seed.ASSUMPTIONS['annual_revenue']:,.0f})\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2ff83486",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## 4 · Pick the attachment — Proposal or Engagement"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "584e01dd",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Proposals for Global Guardian Insurance:\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>id</th>\n",
|
||||
" <th>name</th>\n",
|
||||
" <th>status</th>\n",
|
||||
" <th>opportunity</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Secure Cloud Infrastructure Modernization</td>\n",
|
||||
" <td>Draft</td>\n",
|
||||
" <td>Secure Cloud Infrastructure Modernization</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" id name status \\\n",
|
||||
"0 1 Secure Cloud Infrastructure Modernization Draft \n",
|
||||
"\n",
|
||||
" opportunity \n",
|
||||
"0 Secure Cloud Infrastructure Modernization "
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"proposals = client.proposals_for_client(CLIENT_ID)\n",
|
||||
"engagements = client.engagements_for_client(CLIENT_NAME)\n",
|
||||
"\n",
|
||||
"if proposals:\n",
|
||||
" print(f\"Proposals for {CLIENT_NAME}:\")\n",
|
||||
" display(pd.DataFrame([\n",
|
||||
" {\"id\": p[\"id\"], \"name\": p.get(\"name\"), \"status\": p.get(\"status\"),\n",
|
||||
" \"opportunity\": (p.get(\"opportunity\") or {}).get(\"name\")}\n",
|
||||
" for p in proposals\n",
|
||||
" ]))\n",
|
||||
"if engagements:\n",
|
||||
" print(f\"Engagements for {CLIENT_NAME}:\")\n",
|
||||
" display(pd.DataFrame([\n",
|
||||
" {\"id\": e[\"id\"], \"name\": e.get(\"name\"), \"status\": e.get(\"status\")}\n",
|
||||
" for e in engagements\n",
|
||||
" ]))\n",
|
||||
"if not proposals and not engagements:\n",
|
||||
" print(f\"{CLIENT_NAME} has no proposals or engagements yet — \"\n",
|
||||
" \"the next cell can create a sandbox opportunity + proposal.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "e04b1676",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Auto-selected proposal 1: Secure Cloud Infrastructure Modernization\n",
|
||||
"Attaching via: {'proposal': 1}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Set exactly ONE (ids from above). Leave both None to auto-pick — a single\n",
|
||||
"# existing option wins; otherwise a sandbox opportunity + proposal is created.\n",
|
||||
"PROPOSAL_ID = config.PROPOSAL_ID # or e.g. 42\n",
|
||||
"ENGAGEMENT_ID = config.ENGAGEMENT_ID # or e.g. 7\n",
|
||||
"\n",
|
||||
"if PROPOSAL_ID is None and ENGAGEMENT_ID is None:\n",
|
||||
" if len(proposals) == 1 and not engagements:\n",
|
||||
" PROPOSAL_ID = proposals[0][\"id\"]\n",
|
||||
" print(f\"Auto-selected proposal {PROPOSAL_ID}: {proposals[0].get('name')}\")\n",
|
||||
" elif len(engagements) == 1 and not proposals:\n",
|
||||
" ENGAGEMENT_ID = engagements[0][\"id\"]\n",
|
||||
" print(f\"Auto-selected engagement {ENGAGEMENT_ID}: {engagements[0].get('name')}\")\n",
|
||||
" elif not proposals and not engagements:\n",
|
||||
" opp = client.create_opportunity(\n",
|
||||
" name=f\"{CLIENT_NAME} — CX Cloud Modernization (sandbox)\",\n",
|
||||
" client_id=CLIENT_ID,\n",
|
||||
" description=\"Created by Palladium 00_provision for the Genesys CX Cloud TEI.\",\n",
|
||||
" )\n",
|
||||
" prop = client.create_proposal(\n",
|
||||
" name=f\"{CLIENT_NAME} — Genesys CX Cloud TEI (sandbox)\",\n",
|
||||
" opportunity_id=opp[\"id\"],\n",
|
||||
" status=\"Draft\",\n",
|
||||
" )\n",
|
||||
" PROPOSAL_ID = prop[\"id\"]\n",
|
||||
" print(f\"Created opportunity {opp['id']} and proposal {PROPOSAL_ID} for {CLIENT_NAME}.\")\n",
|
||||
" else:\n",
|
||||
" raise SystemExit(\"Multiple options — set PROPOSAL_ID or ENGAGEMENT_ID above and re-run.\")\n",
|
||||
"\n",
|
||||
"assert (PROPOSAL_ID is None) != (ENGAGEMENT_ID is None), \\\n",
|
||||
" \"Set exactly one of PROPOSAL_ID / ENGAGEMENT_ID.\"\n",
|
||||
"attach = {\"proposal\": PROPOSAL_ID} if PROPOSAL_ID else {\"engagement\": ENGAGEMENT_ID}\n",
|
||||
"print(f\"Attaching via: {attach}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2b4fcb45",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## 5 · Tool instance & seed the published values"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "0655d1fc",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Created tool 3rzDgVdsjhVv attached to {'proposal': 1}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from core.tei_client import AthenaAPIError\n",
|
||||
"\n",
|
||||
"def _report_id_of(t):\n",
|
||||
" r = t.get(\"report\")\n",
|
||||
" return r.get(\"id\") if isinstance(r, dict) else r\n",
|
||||
"\n",
|
||||
"def _matches_attachment(t):\n",
|
||||
" if PROPOSAL_ID is not None:\n",
|
||||
" opp = t.get(\"opportunity\") or {}\n",
|
||||
" return t.get(\"proposal\") == PROPOSAL_ID or opp.get(\"proposal_id\") == PROPOSAL_ID\n",
|
||||
" eng = t.get(\"engagement\")\n",
|
||||
" eng_id = eng.get(\"id\") if isinstance(eng, dict) else eng\n",
|
||||
" return eng_id == ENGAGEMENT_ID\n",
|
||||
"\n",
|
||||
"candidates = [t for t in client.list_tools() if _report_id_of(t) == REPORT_ID]\n",
|
||||
"tool = next((t for t in candidates if _matches_attachment(t)),\n",
|
||||
" candidates[0] if len(candidates) == 1 else None)\n",
|
||||
"\n",
|
||||
"if tool is None:\n",
|
||||
" try:\n",
|
||||
" tool = client.create_tool(\n",
|
||||
" report_public_id=REPORT_ID,\n",
|
||||
" name=f\"{CLIENT_NAME} — Genesys CX Cloud TEI\",\n",
|
||||
" **attach,\n",
|
||||
" )\n",
|
||||
" print(f\"Created tool {tool['id']} attached to {attach}\")\n",
|
||||
" except AthenaAPIError as e:\n",
|
||||
" if e.status_code == 409: # DUPLICATE_INSTANCE\n",
|
||||
" raise SystemExit(\n",
|
||||
" \"An active tool already exists for this report + attachment. \"\n",
|
||||
" \"Find it with client.list_tools() or pick a different proposal/engagement.\"\n",
|
||||
" ) from e\n",
|
||||
" raise\n",
|
||||
"else:\n",
|
||||
" print(f\"Found existing tool {tool['id']} (status: {tool.get('status')})\")\n",
|
||||
"\n",
|
||||
"TOOL_ID = tool[\"id\"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "86443d76",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Pushed values for 8 fields (genesys_ai_tokens seeded at $0 — published-study baseline).\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"payload = []\n",
|
||||
"for b in seed.BENEFITS: # nominal; Athena risk-adjusts via the field definition\n",
|
||||
" payload.append({\n",
|
||||
" \"field_key\": b[\"field_key\"],\n",
|
||||
" \"year_values\": b[\"year_values\"],\n",
|
||||
" \"notes\": b[\"notes\"],\n",
|
||||
" })\n",
|
||||
"for c in seed.COSTS: # risk-adjusted UP client-side (Forrester methodology)\n",
|
||||
" factor = 1 + c[\"risk_adjustment\"]\n",
|
||||
" payload.append({\n",
|
||||
" \"field_key\": c[\"field_key\"],\n",
|
||||
" \"year_values\": {y: round(v * factor, 2) for y, v in c[\"year_values\"].items()},\n",
|
||||
" \"initial\": round(c[\"initial\"] * factor, 2),\n",
|
||||
" \"notes\": c[\"notes\"],\n",
|
||||
" })\n",
|
||||
"\n",
|
||||
"client.update_values(TOOL_ID, payload)\n",
|
||||
"print(f\"Pushed values for {len(payload)} fields \"\n",
|
||||
" f\"(genesys_ai_tokens seeded at $0 — published-study baseline).\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "509b52be",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## 6 · Calculate & verify\n",
|
||||
"\n",
|
||||
"**Tier 1 — pipeline correctness:** Athena must match `seed.ATHENA_EXPECTED`\n",
|
||||
"(the published model re-discounted under Athena's Year-0-as-Year-1 rule)\n",
|
||||
"within 0.5%.\n",
|
||||
"\n",
|
||||
"**Tier 2 — reconciliation:** show Athena vs the published totals. The\n",
|
||||
"implementation initial (\\$1.309M, ~32% of cost PV) is discounted by Athena\n",
|
||||
"but not by Forrester, so costs PV reads ~\\$119k lower and ROI ~11pp higher\n",
|
||||
"than published. That delta is methodology, not data error."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "0728b42e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"════════════════════════════════════════════════════════\n",
|
||||
" TEI Financial Summary\n",
|
||||
"════════════════════════════════════════════════════════\n",
|
||||
" Total Benefits (PV): $ 14,840,637\n",
|
||||
" Total Costs (PV): $ 3,938,170\n",
|
||||
"────────────────────────────────────────────────────────\n",
|
||||
" Net Present Value: $ 10,902,466\n",
|
||||
" ROI: 277%\n",
|
||||
" Payback: 4.0 months\n",
|
||||
"════════════════════════════════════════════════════════\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"summary = client.calculate(TOOL_ID)\n",
|
||||
"client.print_summary(TOOL_ID)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "aba8fc21",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>metric</th>\n",
|
||||
" <th>published (Forrester)</th>\n",
|
||||
" <th>expected (Athena methodology)</th>\n",
|
||||
" <th>athena actual</th>\n",
|
||||
" <th>vs expected</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>total_benefits_pv</td>\n",
|
||||
" <td>14,840,638</td>\n",
|
||||
" <td>14,840,640</td>\n",
|
||||
" <td>14,840,637</td>\n",
|
||||
" <td>-0.00%</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>total_costs_pv</td>\n",
|
||||
" <td>4,057,170</td>\n",
|
||||
" <td>3,938,170</td>\n",
|
||||
" <td>3,938,170</td>\n",
|
||||
" <td>+0.00%</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>net_present_value</td>\n",
|
||||
" <td>10,783,468</td>\n",
|
||||
" <td>10,902,470</td>\n",
|
||||
" <td>10,902,466</td>\n",
|
||||
" <td>-0.00%</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>roi_percentage</td>\n",
|
||||
" <td>266</td>\n",
|
||||
" <td>277</td>\n",
|
||||
" <td>277</td>\n",
|
||||
" <td>+0.01%</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" metric published (Forrester) expected (Athena methodology) \\\n",
|
||||
"0 total_benefits_pv 14,840,638 14,840,640 \n",
|
||||
"1 total_costs_pv 4,057,170 3,938,170 \n",
|
||||
"2 net_present_value 10,783,468 10,902,470 \n",
|
||||
"3 roi_percentage 266 277 \n",
|
||||
"\n",
|
||||
" athena actual vs expected \n",
|
||||
"0 14,840,637 -0.00% \n",
|
||||
"1 3,938,170 +0.00% \n",
|
||||
"2 10,902,466 -0.00% \n",
|
||||
"3 277 +0.01% "
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Payback: 4 months (expected ≈ 4)\n",
|
||||
"✅ Tier 1 passed — pipeline reproduces the study under Athena's discounting.\n",
|
||||
"ℹ️ Tier 2: published ROI 266% vs Athena ~277% — explained Year-0 delta (see above).\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"rows, ok = [], True\n",
|
||||
"for key in (\"total_benefits_pv\", \"total_costs_pv\", \"net_present_value\", \"roi_percentage\"):\n",
|
||||
" actual = float(summary.get(key) or 0)\n",
|
||||
" expected = seed.ATHENA_EXPECTED[key]\n",
|
||||
" published = seed.PUBLISHED[key]\n",
|
||||
" diff = (actual - expected) / expected\n",
|
||||
" rows.append({\n",
|
||||
" \"metric\": key,\n",
|
||||
" \"published (Forrester)\": f\"{published:,.0f}\",\n",
|
||||
" \"expected (Athena methodology)\": f\"{expected:,.0f}\",\n",
|
||||
" \"athena actual\": f\"{actual:,.0f}\",\n",
|
||||
" \"vs expected\": f\"{diff:+.2%}\",\n",
|
||||
" })\n",
|
||||
" ok &= abs(diff) <= 0.005\n",
|
||||
"\n",
|
||||
"display(pd.DataFrame(rows))\n",
|
||||
"print(f\"Payback: {summary.get('payback_period_months')} months (expected ≈ 4)\")\n",
|
||||
"assert ok, \"Athena diverged >0.5% from its own expected methodology — investigate.\"\n",
|
||||
"print(\"✅ Tier 1 passed — pipeline reproduces the study under Athena's discounting.\")\n",
|
||||
"print(\"ℹ️ Tier 2: published ROI 266% vs Athena ~277% — explained Year-0 delta (see above).\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "181c7b55",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## 7 · Save a baseline version & persist IDs"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "d8102590",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Saved version 1 (baseline).\n",
|
||||
"Saved to /Users/robert/git/palladium/.env:\n",
|
||||
" PALLADIUM_GENESYSCX_REPORT_PUBLIC_ID=UCb2hSJprSBx\n",
|
||||
" PALLADIUM_GENESYSCX_TOOL_PUBLIC_ID=3rzDgVdsjhVv\n",
|
||||
" PALLADIUM_GENESYSCX_PROPOSAL_ID=1\n",
|
||||
"\n",
|
||||
"Next → 01_business_case.ipynb (AI token cost entry + sensitivity).\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"if not client.list_versions(TOOL_ID):\n",
|
||||
" client.save_version(TOOL_ID, note=(\n",
|
||||
" \"Baseline — published Forrester CX Cloud TEI figures (Dec 2025). \"\n",
|
||||
" \"genesys_ai_tokens at $0 per the published study; set the annual \"\n",
|
||||
" \"cost from the Genesys quote in 01_business_case before client use.\"\n",
|
||||
" ))\n",
|
||||
" print(\"Saved version 1 (baseline).\")\n",
|
||||
"\n",
|
||||
"ids = {\n",
|
||||
" \"PALLADIUM_GENESYSCX_REPORT_PUBLIC_ID\": REPORT_ID,\n",
|
||||
" \"PALLADIUM_GENESYSCX_TOOL_PUBLIC_ID\": TOOL_ID,\n",
|
||||
"}\n",
|
||||
"if PROPOSAL_ID is not None:\n",
|
||||
" ids[\"PALLADIUM_GENESYSCX_PROPOSAL_ID\"] = str(PROPOSAL_ID)\n",
|
||||
"if ENGAGEMENT_ID is not None:\n",
|
||||
" ids[\"PALLADIUM_GENESYSCX_ENGAGEMENT_ID\"] = str(ENGAGEMENT_ID)\n",
|
||||
"\n",
|
||||
"env_path = update_env(**ids)\n",
|
||||
"print(f\"Saved to {env_path}:\")\n",
|
||||
"for k, v in ids.items():\n",
|
||||
" print(f\" {k}={v}\")\n",
|
||||
"print(\"\\nNext → 01_business_case.ipynb (AI token cost entry + sensitivity).\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4fc81c99-f073-486a-9f65-f207e96e59cd",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.12.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Reference in New Issue
Block a user