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

studies/202512_GenesysCX/ctm-token-calculator/tests/test_business_case.py

@@ -0,0 +1,117 @@
+"""Business case maths + exports."""
+
+from __future__ import annotations
+
+import pytest
+
+from tokencalc.business_case import build_business_case, npv, payback_years
+from tokencalc.defaults import (
+    CTM_DEFAULT_FEATURE_SCOPES,
+    CTM_DEFAULT_SITES,
+    CTM_DEFAULT_TAKEOUTS,
+    DEFAULT_METERS,
+    DEFAULT_PRICING,
+)
+from tokencalc.exports import (
+    export_excel,
+    scenario_state_from_json,
+    scenario_state_to_json,
+)
+
+
+def test_npv_hand_check():
+    """100/yr for 3 years @ 8%: 92.593 + 85.734 + 79.383 = 257.710."""
+    assert npv([100, 100, 100], 0.08) == pytest.approx(257.710, abs=0.001)
+
+
+def test_payback_interpolation():
+    # -100 in Y1, +200 in Y2 → breakeven halfway through Y2 = 1.5 years
+    assert payback_years([-100, 200, 0]) == pytest.approx(1.5)
+    assert payback_years([-100, -100, -100]) is None
+    assert payback_years([50, 50, 50]) == pytest.approx(0.0)
+
+
+def _case(scenario="realistic", **kw):
+    return build_business_case(
+        CTM_DEFAULT_SITES, CTM_DEFAULT_FEATURE_SCOPES, DEFAULT_METERS,
+        DEFAULT_PRICING, CTM_DEFAULT_TAKEOUTS, scenario, **kw,
+    )
+
+
+def test_business_case_shape():
+    case = _case()
+    assert set(case) == {
+        "cost_by_year", "benefit_by_year", "takeouts_by_year",
+        "net_by_year", "cumulative_net", "npv",
+        "payback_period_years", "roi_3yr",
+    }
+    for key in ("cost_by_year", "benefit_by_year", "net_by_year"):
+        assert {"Y1", "Y2", "Y3"} <= set(case[key].columns)
+
+
+def test_net_consistency():
+    """NET row must equal benefits + takeouts − costs, per year."""
+    case = _case()
+    nb = case["net_by_year"].set_index("line")
+    for y in ("Y1", "Y2", "Y3"):
+        assert nb.loc["NET", y] == pytest.approx(
+            nb.loc["TOTAL BENEFITS", y]
+            + nb.loc["TOTAL TAKEOUTS", y]
+            - nb.loc["TOTAL COSTS", y]
+        )
+    # cumulative is a running sum of NET
+    assert nb.loc["Cumulative net", "Y3"] == pytest.approx(
+        sum(nb.loc["NET", y] for y in ("Y1", "Y2", "Y3"))
+    )
+
+
+def test_npv_matches_net_rows():
+    case = _case()
+    nb = case["net_by_year"].set_index("line")
+    net = [nb.loc["NET", y] for y in ("Y1", "Y2", "Y3")]
+    assert case["npv"] == pytest.approx(npv(net, 0.08))
+
+
+def test_three_scenarios_distinct():
+    npvs = {s: _case(s)["npv"] for s in ("floor", "realistic", "stretch")}
+    assert len({round(v) for v in npvs.values()}) == 3
+    assert npvs["floor"] < npvs["realistic"] < npvs["stretch"]
+
+
+def test_implementation_amortization():
+    base = _case()
+    with_impl = _case(implementation_cost=900_000)
+    nb, nb2 = (
+        c["net_by_year"].set_index("line") for c in (base, with_impl)
+    )
+    for y in ("Y1", "Y2", "Y3"):
+        assert nb2.loc["TOTAL COSTS", y] == pytest.approx(
+            nb.loc["TOTAL COSTS", y] + 300_000
+        )
+
+
+def test_excel_export_readable(tmp_path):
+    case = _case()
+    path = export_excel(
+        {
+            "Business Case": case["net_by_year"],
+            "Costs": case["cost_by_year"],
+            "Benefits": case["benefit_by_year"],
+        },
+        tmp_path / "ctm.xlsx",
+    )
+    import openpyxl
+
+    wb = openpyxl.load_workbook(path)
+    assert set(wb.sheetnames) == {"Business Case", "Costs", "Benefits"}
+
+
+def test_scenario_json_roundtrip(tmp_path):
+    p = tmp_path / "state.json"
+    scenario_state_to_json(
+        CTM_DEFAULT_SITES, CTM_DEFAULT_TAKEOUTS, CTM_DEFAULT_FEATURE_SCOPES, p
+    )
+    sites, takeouts, scopes = scenario_state_from_json(p)
+    assert [s.site_name for s in sites] == [s.site_name for s in CTM_DEFAULT_SITES]
+    assert takeouts[0].annual_cost == CTM_DEFAULT_TAKEOUTS[0].annual_cost
+    assert scopes[0].adoption_curve == CTM_DEFAULT_FEATURE_SCOPES[0].adoption_curve