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Key statistics

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

4 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 experienced individual contributor who analyzes and improves store operational performance without direct management authority. At the Senior Professional (P4) level, the role owns a system or set of related features, devises new approaches, and drives multi-team / function outcomes. Technical lead for focused efforts; mentors several.

What this level does

Carry full accountability for a single store location including hiring, firing, budgets, and overall performance, selecting the operating methods that drive results
Manage the complete store P&L — meeting the sales plan, managing payroll to budget, keeping shrink within target, and controlling discretionary operating expenses
Run the store as a general manager of a standalone business unit with in-depth accountability for revenue, costs, personnel, and customer experience
Analyze complex store performance variables and implement corrective plans across staffing, inventory, and customer experience to protect margin
Develop assistant managers and high-potential associates into the store leadership pipeline

Knowledge applied: Applies in-depth command of the retail business model to run a store as a standalone unit, selecting operating methods and owning full P&L.
Complexity & problem solving: Performs in-depth analysis of complex, interacting variables — sales, payroll, shrink, expense, occupancy — to protect and grow margin.
Collaboration & interaction: Coordinates across corporate functions and influences decisions affecting the store; leads and develops the store team.
Typical experience: 8+ years retail experience, typically as a full-accountability store manager.

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 P4 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$178k

San Francisco-Oakland-Fremont, CA$160k

Washington-Arlington-Alexandria, DC-VA-MD-WV$148k

Boulder, CO$146k

Seattle-Tacoma-Bellevue, WA$146k

Boston-Cambridge-Newton, MA-NH$139k

Lexington Park, MD$136k

Trenton-Princeton, NJ$135k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $107k; 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 P4 (P4 — Senior Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A system or set of related features
Autonomy: Self-directed; reviewed at critical decision points
Complexity: Complex, ambiguous problems; devises new approaches
Impact: Multi-team / function outcomes
Decision rights: Owns technical decisions for a system; influences adjacent design
Leadership: Technical lead for focused efforts; mentors several

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

Promotion

The next rung from P4 is P5.

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 Retail Officer	jf_store_management::E4	$389,207†	confident0.06
Senior Store Manager	jf_store_management::M4	$167,689†	confident0.06
Advanced Store Operations Coordinator	jf_store_management::S4	$56,408†	confident0.06
Store Operations Coordinator	jf_store_management::P3	$82,468†	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

P4

jf_store_management::P4

Senior Store Operations Analyst

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: 4 / 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 · P4review0.17

Loss Prevention · P4review0.17

Optical · P4review0.17

Pharmacy · P4review0.17

Product Specialty · P4review0.17

General · P4review0.17

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)