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Key statistics

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

3 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6

41-0000

retail_hospitality

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

An individual contributor who manages day-to-day operational tasks within a single retail store, ensuring smooth functioning of processes such as inventory, scheduling, and compliance. At the Mid-Level Professional (P3) level, the role owns features or a sub-system end-to-end, adapts existing approaches, and drives project / team outcomes. Mentors juniors informally.

What this level does

Manage day-to-day operations of a single store, overseeing staff, managing inventory, and driving sales to plan with day-to-day independence
Budget the store's revenue to ensure a profit, reduce store costs, and take steps to increase profitability by analyzing store performance reports and sales KPIs
Own hiring, scheduling, performance, and development of the store team, resolving diverse operational problems using evaluation of identifiable factors
Plan and execute store-level merchandising, promotions, and service initiatives, escalating only major variances to district leadership

Knowledge applied: Applies full working knowledge of the store operating model — KPIs, budgeting, inventory, and staffing — to run one location independently.
Complexity & problem solving: Evaluates identifiable performance factors to solve diverse store problems and improve profitability, planning own work day-to-day.
Collaboration & interaction: Networks with district leadership and peer store managers; coordinates the store team's activities.
Typical experience: 5+ years retail experience with demonstrated ownership of store operational areas.

Skills at this level

Financial and Business Acumen: — Knows how store numbers work together — reading sales reports and KPIs, budgeting store revenue for profit, and controlling costs to increase profitability across the retail business model.
Store P&L Ownership: — Manages the full store profit-and-loss — hitting the sales plan, running payroll to budget, holding shrink within target, and controlling discretionary operating and occupancy costs.
Retail Staff Scheduling and Delegation: — Arranges associate work schedules to coverage and budget, and delegates floor tasks such as restocking shelves, checking out customers, and reorganizing displays.
Inventory and Shrinkage Control: — Oversees store inventory levels and executes practices that keep shrinkage within target while maintaining stock availability on the floor.
Merchandising Execution: — Maintains and organizes store displays and product presentation to brand standard to support sales generation on the floor.
Store Team Hiring and Development: — Recruits, trains, and develops store associates and managers, building the store leadership pipeline and improving performance through people.
Sales Performance Management: — Drives sales to plan by analyzing store performance, applying techniques to improve KPIs, and taking corrective steps to increase profitability.
Customer Service Leadership: — Sets and holds best-in-class customer service standards on the floor as a core store objective and performance driver.
Multi-Unit Portfolio Leadership: — Oversees a portfolio of 5–20 stores across a territory, ensuring consistent brand execution and aggregated financial and operational goals are met through store managers.
Store Manager Development: — Recruits, trains, coaches, and develops store managers as the critical link between corporate strategy and frontline execution.
District Performance Diagnosis: — Researches root causes of sales and operational performance gaps across multiple locations and creates actionable, prioritized plans for improvement.
New Store Build-Out and Staffing: — Hires managers for new stores in a multi-state territory and travels on-site to support the building and staffing of new retail spaces.
Microsoft Dynamics 365 Finance & Operations / Commerce: — Uses Dynamics 365 Commerce and Finance & Operations to run store sales, inventory, and operational reporting for retail unit management.

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

Store Management — median with , by . Real canon data.

National-base pricing — this family's function differential is pending review, so dollar levels are not function-adjusted (level-over-level % is unaffected).

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 41-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

-5.0%First-Line Supervisors of Retail Sales Workers · United States

1,171,900 → 1,113,160 jobs

125,100 openings / year, split into:

replacement / exits 132,263

Growth — new jobs (-6%)Exits — backfill (100%)

This occupation is projected to contract — every opening is replacing someone leaving, not net new demand.

Projected growth 2024–34 contracting: -5.0%
Growth share of hiring: -6%
Exit / retention pressure high: 100%
Openings / year: 125,100

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 P3 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$134k

San Francisco-Oakland-Fremont, CA$120k

Washington-Arlington-Alexandria, DC-VA-MD-WV$111k

Boulder, CO$110k

Seattle-Tacoma-Bellevue, WA$110k

Boston-Cambridge-Newton, MA-NH$105k

Lexington Park, MD$102k

Trenton-Princeton, NJ$102k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $80k; 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 P3 (P3 — Mid-Level Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Features or a sub-system end-to-end
Autonomy: Works independently on standard work; reviewed on the non-standard
Complexity: Diverse problems; adapts existing approaches
Impact: Project / team outcomes
Decision rights: Owns implementation decisions for own scope
Leadership: Mentors juniors 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 P3 is P4.

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
Chief Stores Officer	jf_store_management::E3	$352,063†	confident0.06
Store Manager	jf_store_management::M3	$120,351†	confident0.06
Senior Sales Associate	jf_store_management::S3	$49,566†	confident0.06
Store Operations Coordinator	jf_store_management::P2	$72,357†	confident0.06

†National-base pricing — this family's function differential is pending review, so the dollar level is not function-adjusted.

Capability cluster

O*NET 41-1011

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

P3

jf_store_management::P3

Store Operations Coordinator

Store Management

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: P
Superfunction: retail_hospitality
Function: store_operations
Family: store_management
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").

Cashier · P3review0.17

Loss Prevention · P3review0.17

Optical · P3review0.17

Pharmacy · P3review0.17

Product Specialty · P3review0.17

General · P3review0.17

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 41-1011	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)