People Analytics Toolbox

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grounded in this role's JobFrame record + structure

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Key statistics

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

3 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

11-0000

manufacturing

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Top executive accountable for the organization's end-to-end demand forecasting strategy and its alignment with supply and inventory decisions. At the Vice President (E3) level, the role owns a division, market and competitive strategy, and drives division-wide. Leads a division's leadership team.

What this level does

Lead demand planning for a large division or region through senior executives, shaping the corporate demand-planning strategy at enterprise scale
Own enterprise-level forecast risk — the exposure of inventory, obsolescence, and missed revenue that a systemic demand-signal failure would create — and the governance that contains it
Set the strategic direction for how IBP demand review integrates with the enterprise financial and operating plan across all business units in scope
Represent demand-planning capability externally to major customers and in industry forums, translating market and syndicated consumer signals into enterprise demand strategy
Sponsor large-scale transformation of forecasting methods, data (syndicated/consumer/point-of-sale), and platforms as a major strategic initiative

Knowledge applied: Shapes corporate demand-planning strategy for a large division or region, integrating enterprise financial and operating plans with the demand signal.
Complexity & problem solving: Owns enterprise-level forecast risk and critical strategic impact; contains systemic demand-signal failure exposure across business units.
Collaboration & interaction: Represents demand-planning capability externally to major customers and industry forums; participates in corporate strategy setting.
Typical experience: 15–20+ years with demonstrated enterprise-impact leadership.

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?

SOC 11-0000 · national

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 this role sits — growth vs. pay

level E3 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$605k

San Francisco-Oakland-Fremont, CA$543k

Washington-Arlington-Alexandria, DC-VA-MD-WV$502k

Boulder, CO$495k

Seattle-Tacoma-Bellevue, WA$495k

Boston-Cambridge-Newton, MA-NH$474k

Lexington Park, MD$462k

Trenton-Princeton, NJ$459k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $363k; 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 E3 (E3 — Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A division
Autonomy: Accountable for division strategy and P&L
Complexity: Market and competitive strategy
Impact: Division-wide
Decision rights: Owns division strategy, budget, and org
Leadership: Leads a division's leadership team

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

Promotion

The next rung from E3 is E4.

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
Demand Planning Manager	jf_demand_forecast_planning::M3	$124,177	confident0.06
Demand Planner	jf_demand_forecast_planning::P3	$85,090	confident0.06
Senior Demand Planner	jf_demand_forecast_planning::S3	$51,142	confident0.06
SVP of Demand Planning & Forecasting	jf_demand_forecast_planning::E2	$332,990	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

E3

jf_demand_forecast_planning::E3

Chief Demand Officer

Demand / Forecast Planning

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: 3 / 8

Content

content@2

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

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 · E3review0.17

Materials · E3review0.17

Purchasing / Procurement · E3review0.17

Transportation · E3review0.17

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)