People Analytics Toolbox

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Key statistics

The identity block — every fact is canon, none is generated.

4 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

—

manufacturing

Coordinates

2 / 4 spaces

pay@2 · 2026-07

What this role is

The most senior executive accountable for enterprise-wide demand forecasting and inventory strategy across all business units and regions. At the Senior Vice President (E4) level, the role owns multiple divisions, enterprise strategy and external stakeholders, and drives cross-division / enterprise. Leads division leaders.

What this level does

Oversee the full demand and forecast planning portfolio across multiple businesses and strategic areas with high autonomy and direct corporate impact
Participate in enterprise strategic development, ensuring the demand signal is a governing input to corporate revenue, capacity, and capital planning
Engage the board, CEO, and industry leaders on demand-planning-driven business risk and opportunity across the corporate portfolio
Set cross-business demand-planning strategy and the operating model that links commercial intelligence, statistical forecasting, and IBP across the enterprise
Own the corporate accountability for forecast integrity as it flows into published guidance and enterprise operating commitments

Knowledge applied: Participates in enterprise strategic development with demand planning as a governing input to corporate revenue, capacity, and capital planning across the portfolio.
Complexity & problem solving: Exercises high autonomy over corporate-impact decisions spanning multiple businesses and strategic areas; forecast integrity flows into published guidance.
Collaboration & interaction: Regular board, CEO, and industry-leader engagement on demand-driven business risk and opportunity.
Typical experience: 20+ years of extensive corporate strategy and executive leadership experience.

Skills at this level

Statistical Demand Forecasting: — Uses historical sales data, statistical models, and predictive analytics to forecast future product demand across multiple aggregation levels and time horizons, producing the baseline that informs production and distribution decisions.
Integrated Business Planning (IBP) Demand Review: — Leads the monthly, assumption-based demand review that reconciles statistical baselines with commercial input into a time-phased consensus demand plan, driving a clear action log and enterprise-level decisions.
Consensus Demand Planning: — Runs the demand dialogue with Sales, Marketing, and Finance to resolve competing views into a single agreed forecast, serving as the integration point between the planning and commercial organizations.
Forecast Accuracy Governance: — Sets and monitors forecast-accuracy and bias targets across products and regions, diagnoses systemic error sources, and drives the process and model improvements that raise signal reliability.
New-Product & Promotional Demand Modeling: — Owns demand assumptions for new item launches from ideation through post-launch stabilization and evaluates promotional plans to establish future lift assumptions in the forecast.
Demand-to-Supply Signal Translation: — Works with Supply, Production, and Deployment planning to convert the consensus/financial forecast into an executable SKU-level operational plan for the network, reconciling demand against capacity and inventory.
Syndicated Consumer Data Integration: — Incorporates market and syndicated consumer data (e.g. Nielsen) and point-of-sale signals into forecast models to sharpen demand estimates and detect market shifts.
Demand Planning Platform Strategy: — Defines the selection, configuration, and investment case for demand planning systems (SAP APO Demand Planning, i2 Rhythm, Forecast Pro, IBM Analytics Planning) to support the enterprise forecasting operating model.
Long-Range Demand Strategy: — Develops multi-year demand outlooks that anchor capacity, sourcing, and network decisions, and links the demand signal to the corporate operating and financial plan.
Executive Stakeholder Negotiation: — Negotiates contested demand assumptions and consensus outcomes with top Sales, Marketing, and Finance leaders where decisions carry working-capital and revenue consequences.

Model-authored from 21 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Demand / Forecast Planning — median with , by . Real canon data.

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

Employment growth 2019–2024, BLS OEWSobserved

+12.7%Purchasing Managers · United States

72,100 → 81,240 jobs

6,400 openings / year, split into:

replacement / exits 6,141

Growth — new jobs (4%)Exits — backfill (96%)

4% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.1%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 6,400

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$669k

San Francisco-Oakland-Fremont, CA$600k

Washington-Arlington-Alexandria, DC-VA-MD-WV$555k

Boulder, CO$548k

Seattle-Tacoma-Bellevue, WA$548k

Boston-Cambridge-Newton, MA-NH$524k

Lexington Park, MD$511k

Trenton-Princeton, NJ$508k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $402k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates E4 (E4 — Senior Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple divisions
Autonomy: Owns cross-division strategy
Complexity: Enterprise strategy and external stakeholders
Impact: Cross-division / enterprise
Decision rights: Owns strategy and investment across divisions
Leadership: Leads division leaders

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from E4 is E5.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
Senior Manager, Demand Planning	jf_demand_forecast_planning::M4	$173,021	confident0.06
Senior Demand Planner	jf_demand_forecast_planning::P4	$112,946	confident0.06
Advanced Demand Planning Analyst	jf_demand_forecast_planning::S4	$58,202	confident0.06
Chief Demand Officer	jf_demand_forecast_planning::E3	$363,257	confident0.06

Capability cluster

O*NET 11-3061

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

E4

jf_demand_forecast_planning::E4

Chief Demand Officer

Demand / Forecast Planning

no content fingerprint

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: E
Superfunction: manufacturing
Function: supply_chain
Family: demand_forecast_planning
Universal level: 4 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

No content fingerprint for this profile.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Distribution Center / Warehouse · E4review0.17

Materials · E4review0.17

Purchasing / Procurement · E4review0.17

Transportation · E4review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 11-3061	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)