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New notebooks: Scenario without current spend, VA scenario

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This commit is contained in:
Robert Helewka
2026-07-13 16:32:18 -04:00
parent e88449d15a
commit cbbc9ba839
8 changed files with 19078 additions and 3964 deletions
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studies/202607_CTM_GenesysCX/notebooks/ctm_business_case_corrected.ipynb
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studies/202607_CTM_GenesysCX/notebooks/ctm_business_case_no_current_state.ipynb Normal file
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studies/202607_CTM_GenesysCX/notebooks/ctm_business_case_virtual_agents.ipynb Normal file
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studies/202607_CTM_GenesysCX/notebooks/ctm_migration_wfm.ipynb
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studies/202607_CTM_GenesysCX/notebooks/ctm_token_calculator.ipynb
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studies/202607_CTM_GenesysCX/tests/test_appendix4.py
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@@ -25,11 +25,12 @@ def test_verbatim_crossfoots_to_slide_totals():
a4.crossfoot_tolerance(a4.SLIDE_TOTALS["total_3yr"]) 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) _, _, benefit_rollout = a4.build_rollouts(SITES)
long = a4.benefits_by_year(benefit_rollout) long = a4.benefits_by_year(benefit_rollout)
by_year = long.groupby("year")["benefit"].sum() 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. # Scaling at the finest grain reproduces every verbatim 3-yr value exactly.
for (region, cap), (_, three_yr) in a4.VERBATIM_BENEFITS.items(): for (region, cap), (_, three_yr) in a4.VERBATIM_BENEFITS.items():
got = long.query("region == @region and capability == @cap")["benefit"].sum() 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, long = a4.token_costs_by_year(SITES, meters, DEFAULT_PRICING,
a4.claim_scenario(0.255), core, email, a4.claim_scenario(0.255), core, email,
token_ro, email_ro) 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]'") 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. # Agent Copilot 2028 (ASIA off): 1,490 users × 40 tokens × 12 months.
cp = long.query("cost_line == 'Agent Copilot [named]' and year == 2028") cp = long.query("cost_line == 'Agent Copilot [named]' and year == 2028")
assert cp["annual_cost"].sum() == pytest.approx(1_490 * 40 * 12) assert cp["annual_cost"].sum() == pytest.approx(1_490 * 40 * 12)
# Rule 1: Copilot covers AI Summary at Copilot sites. # Rule 1: Copilot covers AI Summary at Copilot sites.
assert (long.query("cost_line == 'AI Summary & Insights'")["annual_cost"] == 0).all() assert (long.query("cost_line == 'AI Summary & Insights'")["annual_cost"] == 0).all()
# Nothing is live in 2026. # Under the PM timeline NA goes live Oct 2026, so tokens DO accrue in
assert long.query("year == 2026")["annual_cost"].sum() == 0 # 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. # PR NAM steady-month tokens.
assert math.ceil( assert math.ceil(
1_214_358 * DEFAULT_METERS["Predictive Routing"].tokens_per_unit) == 71_433 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 assert ps[2028] == 0.0
# The deck's verbatim year-1 lump stays intact for the as-pitched frame. # 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} 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() 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[2027] == pytest.approx(410_918.40)
assert ms[2028] == pytest.approx(410_918.40) assert ms[2028] == pytest.approx(410_918.40)

11
studies/202607_CTM_GenesysCX/tests/test_migration_wfm.py
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@@ -25,13 +25,14 @@ def test_wfm_scope_and_verbatim_total():
assert ben["benefit"].sum() == pytest.approx(2_314_000) 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()) ben = mw.wfm_benefits_by_year(_default_benefit_rollout())
by_year = ben.groupby("year")["benefit"].sum() by_year = ben.groupby("year")["benefit"].sum()
assert by_year[2026] == 0.0 assert by_year[2026] == 0.0
# ANZ realizes Dec 2027 (1 of 13 live months lands in 2027). # PM timeline: ANZ realizes Sep 2027 → 4 of 16 live months in 2027
assert by_year[2027] == pytest.approx(1_400_000 / 13) # (Sep-Dec); ASIA realizes Jan 2028 → all in 2028.
assert by_year[2028] == pytest.approx(2_314_000 - 1_400_000 / 13) 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(): def test_runrate_saving_annual():
@@ -76,7 +77,7 @@ def test_contracted_frame_with_sow_and_managed_services():
man = a4.managed_services_by_year() man = a4.managed_services_by_year()
total = {y: cur[y] + lic[y] + ps[y] + man[y] for y in a4.YEARS} 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()) 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( runrate = mw.runrate_saving_annual(
a4.tco("ccaas_annual"), managed_annual=a4.MANAGED_SERVICES_ANNUAL) a4.tco("ccaas_annual"), managed_annual=a4.MANAGED_SERVICES_ANNUAL)
label = mw.runrate_breakeven_label(net, runrate) label = mw.runrate_breakeven_label(net, runrate)

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studies/202607_CTM_GenesysCX/tokencalc/appendix4.py
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@@ -113,11 +113,11 @@ TCO_CONTRACTED: dict[str, float] = {
PS_MILESTONES: list[dict] = [ PS_MILESTONES: list[dict] = [
{"name": "SOW Effective Date", "date": dt.date(2026, 3, 15), {"name": "SOW Effective Date", "date": dt.date(2026, 3, 15),
"share": 0.30, "amount": 607_633.94}, "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}, "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}, "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}, "share": 0.20, "amount": 405_089.30},
] ]
PS_CONTRACTED_TOTAL = sum(m["amount"] for m in PS_MILESTONES) 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). #: NTT managed services — commences billing at MCX go-live (🟢 contractual).
#: Not in the deck's TCO at all; an ongoing run-rate cost thereafter. #: Not in the deck's TCO at all; an ongoing run-rate cost thereafter.
MANAGED_SERVICES_ANNUAL = 410_918.40 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: def tco(key: str) -> float:
"""Contracted value where one exists, else the deck's verbatim anchor.""" """Contracted value where one exists, else the deck's verbatim anchor."""
return TCO_CONTRACTED.get(key, TCO_VERBATIM[key]) return TCO_CONTRACTED.get(key, TCO_VERBATIM[key])
#: Genesys/Broadreach deployment schedule (slides 17-21), months from #: Deployment schedule per the current PM delivery timeline (Jul 2026),
#: Jan 2026 inclusive. Benefits realize IMPL + 3 months. #: months from Jan 2026 inclusive. UAT start is the implementation anchor:
IMPL_MONTH = {"NA": 18, "ANZ": 21, "EMEA": 24, "ASIA": 27} #: 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 BENEFIT_LAG_MONTHS = 3
REALIZE_MONTH = {r: m + BENEFIT_LAG_MONTHS for r, m in IMPL_MONTH.items()} 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-early exception retired under the compressed timeline
NA_EMAIL_IMPL_MONTH = 13 #: (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_RAMP_MONTHS = 6 # Genesys ramp programme (🟢 order form)
DEFAULT_TERMINATION = dt.date(2027, 12, 31) # current-platform term contracts 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( def managed_services_by_year(
annual: float = MANAGED_SERVICES_ANNUAL, start: dt.date = MCX_GO_LIVE annual: float = MANAGED_SERVICES_ANNUAL, start: dt.date = MCX_GO_LIVE
) -> dict[int, float]: ) -> 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 then run at the full annual rate — an ongoing cost with no end date
inside the model window.""" inside the model window."""
def _months(y: int) -> int: def _months(y: int) -> int: