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Key statistics

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

3 of 8

Track

Support

Family rungs priced

—

51-0000

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Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Experienced individual contributor who performs advanced manufacturing operations tasks with minimal supervision. At the Senior Support Specialist (S3) level, the role owns escalated / complex cases, complex or non-standard cases, and drives resolution quality on the team's hardest cases. Guides junior support informally.

What this level does

Independently run the daily operational coordination for a line or cell with little instruction — sequencing jobs, balancing material flow, and adjusting the order of work to keep production targets and delivery commitments on track
Investigate moderately difficult problems such as a recurring downtime pattern or a quality reject trend using production and performance-analysis software, and decide on the routine corrective step within established procedure
Reconcile end-of-shift production, downtime, and yield data, resolve discrepancies between the HMI/MOM records and physical counts, and produce the daily-management metrics summary for the manager
Coordinate handoffs with adjacent functions — staging maintenance requests and confirming material availability with the planner — so the line keeps running across shift changes
Guide newer operators on data-entry, quality-check, and safety sign-off procedures without holding formal supervisory authority

Knowledge applied: Detailed knowledge of line routines and production systems sufficient to run daily coordination and perform non-routine tasks such as reconciling discrepancies and investigating downtime patterns independently.
Complexity & problem solving: Moderately difficult problems requiring judgment; chooses the routine corrective step within established procedure and produces the metrics that expose them.
Collaboration & interaction: Coordinates handoffs with maintenance and planning and guides newer operators; works with little instruction on daily work, no formal leadership.
Typical experience: 2–4 years; skilled in shop-floor operations coordination.

Skills at this level

Manufacturing/process domain knowledge: — Understands how jobs, materials, and setups flow through the lines and cells so day-to-day operations run smoothly, and knows the standard sequences well enough to re-order or re-route work when a changeover or shortage disrupts them.
Manufacturing Operations Management (MOM) software: — Enters and reconciles job completions, material consumption, and downtime codes in the MOM/production-management system, and at senior levels defines the transactions, codes, and dashboards operations coordinators rely on.
Production tracking against targets: — Compares daily production counts and run times against schedule targets, flags shortfalls with their apparent cause (material, changeover, or machine downtime), and produces the daily-management metrics summary.
HMI monitoring: — Reads the Human Machine Interface display to determine run/stop status and machine faults, reports visible stoppages, and correlates HMI records with physical counts when reconciling shift data.
Quality control: — Performs routine quality checks at defined line points, logs the measurements, and sets aside product that fails standard tolerance for review, escalating recurring reject trends for root-cause investigation.
Downtime and yield analysis: — Uses performance-analysis software to spot recurring downtime patterns and yield losses across lines, identifies the root cause, and proposes workflow or process changes that improve labor efficiency and on-time delivery.
Shift and cross-function coordination: — Sequences and balances work across a line or cell, stages maintenance requests, confirms material availability with the planner, and manages handoffs so production continues across shift changes.
Safety and policy compliance: — Follows and, at senior levels, guides others on posted safety regulations and company policies for shop-floor tasks — PPE use, quality holds, and standard sign-off records.
Lean and continuous improvement support: — Supports Lean-culture and continuous-yield-improvement initiatives by supplying hard production data and setting up the tracking that measures process-efficiency and quality gains and confirms whether changes hold.
Data reconciliation: — Resolves discrepancies between HMI/MOM system records and physical counts at end of shift, re-checking figures that look off before they enter the daily production, downtime, and yield reports.

Model-authored from 17 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 S3 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$83k

San Francisco-Oakland-Fremont, CA$74k

Washington-Arlington-Alexandria, DC-VA-MD-WV$69k

Boulder, CO$68k

Seattle-Tacoma-Bellevue, WA$68k

Boston-Cambridge-Newton, MA-NH$65k

Lexington Park, MD$63k

Trenton-Princeton, NJ$63k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $50k; 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 S3 (S3 — Senior Support Specialist) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Escalated / complex cases
Autonomy: Limited supervision
Complexity: Complex or non-standard cases
Impact: Resolution quality on the team's hardest cases
Decision rights: Owns escalation resolution within policy
Leadership: Guides junior support informally

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

Promotion

The next rung from S3 is S4.

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 Accountant	jfo_jfm_accounting-controllership-accounting-management::S3	—	confident0.00
Senior Cost Accountant	jfo_jfm_accounting-cost-accounting::S3	—	confident0.00
Senior General Accountant	jfo_jfm_accounting-general-accounting-management::S3	—	confident0.00
Senior General Accountant	jfo_jfm_accounting-general-accounting::S3	—	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

S3

jfo_jfm_manufacturing-operations-manufacturing-operations-general::S3

Senior Manufacturing Operations Associate

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: S
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").

jfo_jfm_accounting-controllership-accounting-management::S3 · S3confident0.00

jfo_jfm_accounting-cost-accounting::S3 · S3confident0.00

jfo_jfm_accounting-general-accounting-management::S3 · S3confident0.00

jfo_jfm_accounting-general-accounting::S3 · S3confident0.00

jfo_jfm_administrative-corporate-services-administrative-services-ma::S3 · S3confident0.00

jfo_jfm_administrative-corporate-services-service-delivery::S3 · S3confident0.00

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)