New notebooks: Scenario without current spend, VA scenario

studies/202607_CTM_GenesysCX/tests/test_appendix4.py

@@ -25,11 +25,12 @@ def test_verbatim_crossfoots_to_slide_totals():
         a4.crossfoot_tolerance(a4.SLIDE_TOTALS["total_3yr"])
 
 
-def test_benefits_phase_on_the_deck_schedule():
+def test_benefits_phase_on_the_pm_schedule():
     _, _, benefit_rollout = a4.build_rollouts(SITES)
     long = a4.benefits_by_year(benefit_rollout)
     by_year = long.groupby("year")["benefit"].sum()
-    assert by_year[2026] == 0.0, "2026 must be $0 under Genesys's own schedule"
+    # Earliest region (NA) realizes Jan 2027 → 2026 still $0.
+    assert by_year[2026] == 0.0, "2026 must be $0 (NA realizes Jan 2027)"
     # Scaling at the finest grain reproduces every verbatim 3-yr value exactly.
     for (region, cap), (_, three_yr) in a4.VERBATIM_BENEFITS.items():
         got = long.query("region == @region and capability == @cap")["benefit"].sum()
@@ -65,16 +66,18 @@ def test_token_hand_checks():
     long = a4.token_costs_by_year(SITES, meters, DEFAULT_PRICING,
                                   a4.claim_scenario(0.255), core, email,
                                   token_ro, email_ro)
-    # STA 2028: NAM/AUZ/EMEA × 12 months + ASIA × 10 months, by hand.
+    # STA 2028: every site live all 12 months under the compressed PM
+    # timeline (APAC live from Nov 2027) → full-year STA for all sites.
     sta = long.query("cost_line == 'Speech & Text Analytics [named]'")
-    assert sta.query("year == 2028")["annual_cost"].sum() == pytest.approx(715_800)
+    assert sta.query("year == 2028")["annual_cost"].sum() == pytest.approx(751_680)
     # Agent Copilot 2028 (ASIA off): 1,490 users × 40 tokens × 12 months.
     cp = long.query("cost_line == 'Agent Copilot [named]' and year == 2028")
     assert cp["annual_cost"].sum() == pytest.approx(1_490 * 40 * 12)
     # Rule 1: Copilot covers AI Summary at Copilot sites.
     assert (long.query("cost_line == 'AI Summary & Insights'")["annual_cost"] == 0).all()
-    # Nothing is live in 2026.
-    assert long.query("year == 2026")["annual_cost"].sum() == 0
+    # Under the PM timeline NA goes live Oct 2026, so tokens DO accrue in
+    # 2026 (NA only — three live months); no longer a $0 year.
+    assert long.query("year == 2026")["annual_cost"].sum() == pytest.approx(424_350)
     # PR NAM steady-month tokens.
     assert math.ceil(
         1_214_358 * DEFAULT_METERS["Predictive Routing"].tokens_per_unit) == 71_433
@@ -130,8 +133,8 @@ def test_sow_milestones_and_managed_services():
     assert ps[2028] == 0.0
     # The deck's verbatim year-1 lump stays intact for the as-pitched frame.
     assert a4.ps_costs_by_year() == {2026: 2_567_000, 2027: 0.0, 2028: 0.0}
-    # Managed services bill from the month after MCX go-live (Sep 30 → Oct).
+    # Managed services bill from the month after MCX go-live (Oct 16 → Nov).
     ms = a4.managed_services_by_year()
-    assert ms[2026] == pytest.approx(410_918.40 * 3 / 12)
+    assert ms[2026] == pytest.approx(410_918.40 * 2 / 12)
     assert ms[2027] == pytest.approx(410_918.40)
     assert ms[2028] == pytest.approx(410_918.40)

studies/202607_CTM_GenesysCX/tests/test_migration_wfm.py

@@ -25,13 +25,14 @@ def test_wfm_scope_and_verbatim_total():
     assert ben["benefit"].sum() == pytest.approx(2_314_000)
 
 
-def test_wfm_phasing_on_deck_schedule():
+def test_wfm_phasing_on_pm_schedule():
     ben = mw.wfm_benefits_by_year(_default_benefit_rollout())
     by_year = ben.groupby("year")["benefit"].sum()
     assert by_year[2026] == 0.0
-    # ANZ realizes Dec 2027 (1 of 13 live months lands in 2027).
-    assert by_year[2027] == pytest.approx(1_400_000 / 13)
-    assert by_year[2028] == pytest.approx(2_314_000 - 1_400_000 / 13)
+    # PM timeline: ANZ realizes Sep 2027 → 4 of 16 live months in 2027
+    # (Sep-Dec); ASIA realizes Jan 2028 → all in 2028.
+    assert by_year[2027] == pytest.approx(1_400_000 * 4 / 16)
+    assert by_year[2028] == pytest.approx(2_314_000 - 1_400_000 * 4 / 16)
 
 
 def test_runrate_saving_annual():
@@ -76,7 +77,7 @@ def test_contracted_frame_with_sow_and_managed_services():
     man = a4.managed_services_by_year()
     total = {y: cur[y] + lic[y] + ps[y] + man[y] for y in a4.YEARS}
     inc, net = a4.case_flows(total, _default_wfm_benefits_by_year())
-    assert sum(net.values()) == pytest.approx(-1_503_013, abs=1_000)
+    assert sum(net.values()) == pytest.approx(-1_468_770, abs=1_000)
     runrate = mw.runrate_saving_annual(
         a4.tco("ccaas_annual"), managed_annual=a4.MANAGED_SERVICES_ANNUAL)
     label = mw.runrate_breakeven_label(net, runrate)

studies/202607_CTM_GenesysCX/tokencalc/appendix4.py

@@ -113,11 +113,11 @@ TCO_CONTRACTED: dict[str, float] = {
 PS_MILESTONES: list[dict] = [
     {"name": "SOW Effective Date",                   "date": dt.date(2026, 3, 15),
      "share": 0.30, "amount": 607_633.94},
-    {"name": "Start of client UAT (first region)",   "date": dt.date(2026, 9, 30),
+    {"name": "Start of client UAT (first region, NA)", "date": dt.date(2026, 10, 16),
      "share": 0.20, "amount": 405_089.30},
-    {"name": "Start of client UAT (last region)",    "date": dt.date(2027, 6, 30),
+    {"name": "Start of client UAT (last region, APAC)", "date": dt.date(2027, 10, 1),
      "share": 0.30, "amount": 607_633.94},
-    {"name": "Completion of last go-live migration", "date": dt.date(2027, 9, 30),
+    {"name": "Completion of last go-live migration",   "date": dt.date(2027, 11, 1),
      "share": 0.20, "amount": 405_089.30},
 ]
 PS_CONTRACTED_TOTAL = sum(m["amount"] for m in PS_MILESTONES)
@@ -125,20 +125,23 @@ PS_CONTRACTED_TOTAL = sum(m["amount"] for m in PS_MILESTONES)
 #: NTT managed services — commences billing at MCX go-live (🟢 contractual).
 #: Not in the deck's TCO at all; an ongoing run-rate cost thereafter.
 MANAGED_SERVICES_ANNUAL = 410_918.40
-MCX_GO_LIVE = dt.date(2026, 9, 30)
+MCX_GO_LIVE = dt.date(2026, 10, 16)
 
 
 def tco(key: str) -> float:
     """Contracted value where one exists, else the deck's verbatim anchor."""
     return TCO_CONTRACTED.get(key, TCO_VERBATIM[key])
 
-#: Genesys/Broadreach deployment schedule (slides 17-21), months from
-#: Jan 2026 inclusive. Benefits realize IMPL + 3 months.
-IMPL_MONTH = {"NA": 18, "ANZ": 21, "EMEA": 24, "ASIA": 27}
+#: Deployment schedule per the current PM delivery timeline (Jul 2026),
+#: months from Jan 2026 inclusive. UAT start is the implementation anchor:
+#: NA Oct 2026 (m10), EMEA Feb 2027 (m14), ANZ Jun 2027 (m18),
+#: APAC Oct 2027 (m22). Benefits realize IMPL + 3 months.
+IMPL_MONTH = {"NA": 10, "EMEA": 14, "ANZ": 18, "ASIA": 22}
 BENEFIT_LAG_MONTHS = 3
 REALIZE_MONTH = {r: m + BENEFIT_LAG_MONTHS for r, m in IMPL_MONTH.items()}
-#: NA Gantt exception: Email implemented Jan 2027, realizes Apr 2027.
-NA_EMAIL_IMPL_MONTH = 13
+#: NA-Email-early exception retired under the compressed timeline
+#: (NA implements Oct 2026; Email cannot realize before NA itself).
+NA_EMAIL_IMPL_MONTH = IMPL_MONTH["NA"]
 
 DEFAULT_RAMP_MONTHS = 6                        # Genesys ramp programme (🟢 order form)
 DEFAULT_TERMINATION = dt.date(2027, 12, 31)    # current-platform term contracts
@@ -321,7 +324,7 @@ def ps_milestones_dataframe() -> pd.DataFrame:
 def managed_services_by_year(
     annual: float = MANAGED_SERVICES_ANNUAL, start: dt.date = MCX_GO_LIVE
 ) -> dict[int, float]:
-    """Managed services bill from the month after go-live (Sep 30 → Oct),
+    """Managed services bill from the month after go-live (Oct 16 → Nov),
     then run at the full annual rate — an ongoing cost with no end date
     inside the model window."""
     def _months(y: int) -> int: