People Analytics Toolbox

Ask about this role

grounded in this role's JobFrame record + structure

Download this job's description (markdown) → derived live from this record.

Key statistics

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

1 of 8

Track

Executive

Family rungs priced

—

51-0000

—

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Executive leader accountable for all upstream processing manufacturing operations across the organization's production network. At the Director (Executive) (E1) level, the role owns a significant function with strategic authority, strategic and cross-functional, and drives function-wide enterprise impact. Executive leadership of a function.

What this level does

Leads the complete upstream processing production function through Production Managers and Supervisors, owning GMP-compliant execution of cell-culture/fermentation operations, output targets, and equipment readiness — where the supervision chain plans daily tasks, assigns production goals from schedules, trains operators on equipment and safety, and monitors output against quality standards
Sets upstream production strategy and annual operating goals aligned to organizational objectives, translating demand into shift structures, staffing, and processing-variable/control-point standards that reporting managers establish and enforce
Directs continuous-improvement and lean/Six Sigma programs for upstream lines through the MOM and production-management platforms (e.g., Siemens Opcenter Execution, SYSPRO MOM with Advanced Planning and Scheduling), holding managers accountable for eliminating waste and root-causing complex, recurring process failures while sustaining yield
Owns serious functional consequences — process deviations, batch losses, and GMP compliance findings surfaced through Enterprise Quality Management Software (EQMS) and quality/compliance software — interfacing with quality, supply chain, and site leadership on escalations a single supervision chain cannot absorb
Establishes and enforces the upstream equipment lifecycle standard (assembly, cleaning, sterilization, processing-variable set-up, control-point monitoring via HMI/process-control software), maintaining production standards across the function

Knowledge applied: Applies detailed knowledge of upstream GMP manufacturing — raw-material weighing/checking, equipment assembly/cleaning/sterilization, processing-variable set-up, and control-point monitoring — to run a complete function through Manager/Supervisor reports rather than performing these tasks directly, using MOM and quality/compliance platforms as the control surface.
Complexity & problem solving: Sets functional strategy and directs root-cause resolution of complex, recurring process failures across the upstream area; balances output, yield, quality, and GMP compliance within one function.
Collaboration & interaction: Interfaces with other executives and major customers on upstream commitments; leads a sub-function or small business unit through its supervision chain, which assigns daily production goals and trains operators.
Typical experience: Executives at this rung typically bring 12–15+ years of manufacturing and management experience; the retrieved evidence documents supervisor/associate roles and does not itself carry executive-band seniority signals, so this figure extrapolates the upstream-production accountability up a leadership chain.

Skills at this level

Upstream Bioprocess Operations: — Directs GMP-compliant cell-culture/fermentation production — raw-material weighing and checking, process-equipment assembly, cleaning and sterilization, processing-variable set-up, and control-point monitoring — to grow and harvest product prior to downstream purification.
Lean Manufacturing and Continuous Improvement: — Uses lean manufacturing tools to eliminate waste, identify and implement cost-reduction measures, and drive operational efficiency across upstream production lines.
Six Sigma: — Applies Six Sigma methodology to reduce process variation, stabilize yield, and root-cause recurring upstream process failures at scale.
Digital Transformation and Automation of Production: — Deploys advanced automation, AI integration, and MOM digital-transformation capability to instrument and optimize upstream manufacturing execution and process control.
Manufacturing Operations Management Platforms: — Operationalizes production through MOM execution, intelligence, and quality software (e.g., Siemens Opcenter, SYSPRO MOM with Advanced Planning and Scheduling) to schedule work, monitor output, and analyze performance.
Enterprise Quality and GMP Compliance Systems: — Standardizes and governs quality-and-compliance and Enterprise Quality Management Software (EQMS) to enforce production standards, manage deviations, and secure GMP inspection outcomes across sites.
Process Control and HMI Monitoring: — Sets processing variables and monitors control points and equipment through Human-Machine Interface (HMI) / process-control software, facilitating corrections to malfunctions within process control points.
Manufacturing ERP and MRP Planning: — Uses cloud manufacturing ERP and MRP systems (e.g., NetSuite, MRPeasy) to plan production, manage inventory and BOMs, and align upstream throughput with demand across units.
Production Workforce Leadership: — Leads production teams and supervision chains through allocation of tasks, resources, and schedules, training, and results-driven direction to meet output and safety targets.
Enterprise Manufacturing Strategy and Capital Allocation: — Sets production strategy, network capacity, make-vs-buy, site specialization, and capital investment to secure yield, cost, and quality at enterprise scale.
Enterprise Risk and Business Continuity Governance: — Governs enterprise-level compliance, batch-integrity, and supply-resilience risk where manufacturing failures carry material financial and reputational consequence.
Executive and External Stakeholder Engagement: — Negotiates critical production and tech-transfer commitments with top leaders and major customers, and represents production operations to regulators, boards, and industry forums.

Model-authored from 20 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

No priced rungs for this family's ladder yet.

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 51-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+8.6%First-Line Supervisors of Production and Operating Workers · United States

631,100 → 685,140 jobs

67,700 openings / year, split into:

replacement / exits 66,862

Growth — new jobs (1%)Exits — backfill (99%)

1% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +1.2%
Growth share of hiring: 1%
Exit / retention pressure high: 99%
Openings / year: 67,700

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 E1 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$282k

San Francisco-Oakland-Fremont, CA$253k

Washington-Arlington-Alexandria, DC-VA-MD-WV$234k

Boulder, CO$231k

Seattle-Tacoma-Bellevue, WA$231k

Boston-Cambridge-Newton, MA-NH$221k

Lexington Park, MD$216k

Trenton-Princeton, NJ$214k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $169k; 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 E1 (E1 — Director (Executive)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A significant function with strategic authority
Autonomy: Sets functional strategy
Complexity: Strategic and cross-functional
Impact: Function-wide enterprise impact
Decision rights: Owns strategy and investment for the function
Leadership: Executive leadership of a function

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

Promotion

The next rung from E1 is E2.

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
VP, Controllership / Accounting Management	jfo_jfm_accounting-controllership-accounting-management::E1	—	confident0.00
Vice President, Cost Accounting	jfo_jfm_accounting-cost-accounting::E1	—	confident0.00
VP, General Accounting	jfo_jfm_accounting-general-accounting-management::E1	—	confident0.00
VP, General Accounting	jfo_jfm_accounting-general-accounting::E1	—	confident0.00

Capability cluster

O*NET 51-1011

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

E1

jfo_jfm_manufacturing-operations-production-supervision-upstream-processing::E1

VP, Manufacturing Operations (Upstream Processing)

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
Universal level: 1 / 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").

jfo_jfm_accounting-controllership-accounting-management::E1 · E1confident0.00

jfo_jfm_accounting-cost-accounting::E1 · E1confident0.00

jfo_jfm_accounting-general-accounting-management::E1 · E1confident0.00

jfo_jfm_accounting-general-accounting::E1 · E1confident0.00

jfo_jfm_administrative-corporate-services-administrative-services-ma::E1 · E1confident0.00

jfo_jfm_administrative-corporate-services-administrative-support::E1 · E1confident0.00

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 51-1011	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)