CTM Calculators: Add PS billing milestones, Adjust Genesys RAMP

studies/202512_GenesysCX/ctm-token-calculator/tokencalc/appendix4.py

@@ -107,6 +107,26 @@ TCO_CONTRACTED: dict[str, float] = {
     "ccaas_annual": 3_200_000,     # signed licence run-rate (deck pitched $4.3M/yr)
 }
 
+#: NTT professional services — SOW billing milestones (🟢 contractual).
+#: The deck's verbatim anchor books $2.4M PS in year 1; the signed SOW
+#: bills $2,025,446.48 in four milestones split 50/50 across 2026-27.
+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),
+     "share": 0.20, "amount": 405_089.30},
+    {"name": "Start of client UAT (last region)",    "date": dt.date(2027, 6, 30),
+     "share": 0.30, "amount": 607_633.94},
+    {"name": "Completion of last go-live migration", "date": dt.date(2027, 9, 30),
+     "share": 0.20, "amount": 405_089.30},
+]
+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)
+
 
 def tco(key: str) -> float:
     """Contracted value where one exists, else the deck's verbatim anchor."""
@@ -120,7 +140,7 @@ 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
 
-DEFAULT_RAMP_MONTHS = 12                       # Genesys ramp programme
+DEFAULT_RAMP_MONTHS = 6                        # Genesys ramp programme (🟢 order form)
 DEFAULT_TERMINATION = dt.date(2027, 12, 31)    # current-platform term contracts
 
 # ── Region ⇄ site mapping ────────────────────────────────────────────
@@ -275,12 +295,42 @@ def licence_costs_by_year(
             for y in YEARS}
 
 
-def ps_costs_by_year() -> dict[int, float]:
-    """Base professional services + training — verbatim, year 1 only."""
-    return {2026: TCO_VERBATIM["prof_services_y1"] + TCO_VERBATIM["training_y1"],
+def ps_costs_by_year(contracted: bool = False) -> dict[int, float]:
+    """Base professional services + training.
+
+    Verbatim: the deck's $2.4M PS lump plus training, all in year 1.
+    Contracted: PS phased on the SOW billing milestones (50/50 across
+    2026-27, $2.03M total); training stays the verbatim year-1 line —
+    the SOW milestones don't itemize it separately.
+    """
+    training = TCO_VERBATIM["training_y1"]
+    if contracted:
+        ps = {y: 0.0 for y in YEARS}
+        for m in PS_MILESTONES:
+            ps[m["date"].year] += m["amount"]
+        return {y: ps[y] + (training if y == 2026 else 0.0) for y in YEARS}
+    return {2026: TCO_VERBATIM["prof_services_y1"] + training,
             2027: 0.0, 2028: 0.0}
 
 
+def ps_milestones_dataframe() -> pd.DataFrame:
+    """The SOW billing milestones as a display table."""
+    return pd.DataFrame(PS_MILESTONES)
+
+
+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),
+    then run at the full annual rate — an ongoing cost with no end date
+    inside the model window."""
+    def _months(y: int) -> int:
+        if y < start.year:
+            return 0
+        return 12 if y > start.year else 12 - start.month
+    return {y: annual * _months(y) / 12 for y in YEARS}
+
+
 # ── Token consumption (missing cost #1) ──────────────────────────────
 
 
@@ -293,7 +343,6 @@ def claim_scenario(email_auto_respond_rate: float = 0.255) -> Scenario:
         voice_summarization_eligibility=0.0,
         voice_knowledge_eligibility=0.0,       # unused by the Appendix-4 scope set
         email_auto_respond_rate=email_auto_respond_rate,
-        email_auto_suggest_acceptance=0.0,     # Auto-Suggest is inside Copilot (V2 #1)
         consumption_cost_realization={1: 1.0, 2: 1.0, 3: 1.0},
     )