Volume, mix, and case-handling inputs that feed the ARIMA forecast and OLS capacity model.

ARIMAOLS

Volume scenario

Scales case volume mart and ARIMA training target vs AOP baseline.

Base — AOP plan (139K cases/mo Jan ’26)

ARIMAOLSSupply

Region scope

Narrows panel extract and regional capacity filters.

All regions · 7,032 FTE CO&S total

OLSOpEx

Product mix

Reweights $900M activity pools and case complexity profile.

Current mix — institutional 42%, wealth 31%

OLS

Average handle time shift — primary OLS regressor with case volume.

Base AHT from ops.aht_telemetry rolling 90-day

OLS

Complexity index

Case complexity multiplier in capacity feature mart.

Base index = 1.0 · aligned to Q4 case mix

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Capacity & Workforce

Do we have the people? OLS FTE regression · regional gaps · supply ARIMA · what-if predictions

Do we have the people to handle it?

OLS regression predicts required FTE from case volume, AHT, and complexity. Use the what-if lab to stress-test assumptions and quantify staffing gap movement.

Staffing gap: -120 FTE net (7,032 available vs 7,325 required) at 91% utilization.
Regression fit: Adj. R² 0.95 across CO&S functions — trained on combined_monthly + fte_regression datasets.
Supply outlook: 137 open reqs · 8.2% rolling attrition · Dec ’26 HC forecast 7,381.

Existing Workforce — Current FTE Inventory

7,032 FTE on hand — gap vs model requirement drives hiring decisions

91% util

Current FTE

7,032

Nov 2025 actual · Workday HC mart

Utilization

91%

Target band 85–93%

Americas

3,842

55% of CO&S

EMEA

2,156

31% of CO&S

APAC

1,034

15% of CO&S

Regional FTE — predicted vs actual

Function mix — OLS regression

Regional Composition

Current headcount by geography · Workday HC mart

Region	Headcount	Share	Status
Americas	3,842	55%	On target
EMEA	2,156	31%	Gap
APAC	1,034	15%	On target

Americas & APAC on target · EMEA −130 FTE vs model · KYC / AML −230 FTE function gap

Function Mix

Current FTE by CO&S workstream

Function	Current FTE	Share	Goal
Onboarding	2,510	36%	Watch
KYC / AML	1,910	27%	Gap
Acct Opening	1,420	20%	On target
Client Service	1,192	17%	Gap

Acct Opening at plan · Onboarding within tolerance · KYC / AML & Client Service below model

Workforce Supply — ARIMA + OLS

Forward headcount path — attrition and hiring funnel drive Dec ’26 outlook

MAPE 1.6%

Rolling Attrition

8.2%

+0.4pp vs LY

Open Reqs

137

Scaled to region scope

Time-to-Fill

42 days

Illustrative assumption · target 35 days

HC Forecast (Dec 26)

7,381

95% CI band

Headcount — forecast vs realized actual

Forecast issued Dec 25 · compare as months elapse · 4 of 6 realized months included

Rolling MAPE0.1%

MAE5

Bias-5 FTE

CI hit rate100%

Months elapsed since forecast4 mo · through Apr 26

Regional Staffing Goals

Model vs current HC · Americas & APAC on target · EMEA −130 FTE vs model · KYC / AML −230 FTE function gap

Region	vs Model	Goal
Americas	+136	On target
EMEA	−130	Gap
APAC	+61	On target

Americas & APAC on target · EMEA −130 FTE vs model · KYC / AML −230 FTE function gap

Supply Levers

Hiring funnel — 137 open reqs; 78% offer accept; 6.2 wk time-to-productivity.
Attrition regression — Cox hazard by tenure; EMEA 1.14× multiplier on base hazard.

Regression What-If Lab

Current assumptions match baseline — adjust levers in the sidebar or try a preset to see OLS FTE shift.

required_FTE = β₀ + β₁·cases + β₂·AHT + β₃·complexity + region_FE + εTraining: combined_monthly · fte_regression · regional_capacity · scenarios

OLS FTE model

Quick what-if

Baseline required FTE7,325Default assumptions

Scenario required FTE7,325+0 vs baseline

Utilization91% → 91%Modeled band 85–93%

Staffing gap-120 → -120After causal + planning relief

Driver decomposition

Multiplicative OLS attribution — each row shows isolated FTE impact from assumption changes.

Driver	Dataset	Mult Δ	FTE impact
Case volume (scenario + outlook)	combined_monthly	×0.961 → ×0.961	+0
AHT assumption	combined_monthly	×1.000 → ×1.000	+0
Complexity index	combined_monthly	×1.000 → ×1.000	+0
Workforce & supply levers	fte_regression	×1.000 → ×1.000	+0
External environment	external_factor_overlay	×1.000 → ×1.000	+0
Region scope	regional_capacity	×1.000 → ×1.000	+0

Function-level predictions

Function	Baseline	Scenario	Δ	Actual
Onboarding	2,576	2,576	+0	2,510
KYC / AML	2,057	2,057	+0	1,910
Acct Opening	1,365	1,365	+0	1,420
Client Service	1,327	1,327	+0	1,192

Source: fte_regression · refreshed on each model run

Scenario path comparison

What-If Lab

Compare two model runs side-by-side to quantify how assumption changes move demand, staffing gap, and program impact. Baseline is pinned automatically — run a preset or adjust the sidebar, then compare against baseline.

Try a preset

Before (baseline)After (compare)

Select two different runs above, or click a preset to run a scenario and compare against baseline.

Run history

Baseline
AOP baseline · default assumptions04:30 PM · In-line with plan · Steady state
139K demand-120 gapATT +4.33