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Key statistics

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

2 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

11-0000

retail_hospitality

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Senior executive overseeing all store operations across the entire company. At the Senior Director (Executive) (E2) level, the role owns multiple functions or a major area, multi-function strategy and risk, and drives major-area outcomes. Leads function leaders.

What this level does

Lead multiple operational functions or divisions (e.g., store operations plus loss prevention, workforce planning and store systems) through VPs, aligning them to one estate-execution strategy
Set cross-functional operating standards where trade-offs between shrink control, labor cost and customer experience carry high consequence for the division's viability
Sponsor the rollout of new systems and technology platforms across all store locations, arbitrating between store operations, IT and merchandising priorities
Negotiate critical operating matters — banner-wide staffing models, safety liability, third-party service contracts — with top leadership and major partners
Own the divisional operations budget and performance, where decisions on store formats, closures or standardization can materially affect company results

Knowledge applied: Applies cross-functional judgment across store operations, loss prevention, workforce and store systems; resolves abstract, high-consequence operating trade-offs.
Complexity & problem solving: Tackles division-level problems — labor models, technology rollouts, format standardization — where decisions may impact the division's or company's viability.
Collaboration & interaction: Negotiates critical operating matters with top leaders and major partners; leads VPs across multiple functions.
Typical experience: 15+ yrs with strategic leadership of operations functions or significant business units.

Skills at this level

Visual merchandising: — Implements planograms and store-layout principles across the estate, checking adjacencies and signage so that floor execution drives sales and maintains safety.
Loss prevention: — Sets and governs structured shrink-control programs — store audits, staff training and investigation protocols — to hold the estate to a defined shrink target.
Data analysis: — Analyzes operational data such as shrink trends, process-compliance rates, payroll efficiency and store sales to identify where store operations must improve.
Store SOP development: — Develops and maintains standard operating procedures for store operations, receiving, cash handling and safety, and rolls them out consistently across locations.
Store compliance auditing: — Audits store adherence to operating standards through field visits, checklists and performance-data review, and drives corrective action where stores fall short.
Multi-store systems rollout: — Leads the deployment of new systems and technology platforms across multiple store locations, sequencing rollout to minimize disruption to daily trading.
Operations P&L and budget ownership: — Owns operational budgets and cost lines (payroll efficiency, shrink, operating cost) and aligns operational spending with company growth and profitability objectives.
Operational risk management: — Manages estate-wide operational risk — in-store safety liability, shrink exposure and continuity of store operations — and aligns operational strategy to enterprise objectives.
Store operations strategy: — Sets the multi-year operating model for the store estate — format strategy, labor model and store-execution standards — translating enterprise goals into how stores run.

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

General — 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 11-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+49.3%General and Operations Managers · United States

2,400,280 → 3,584,420 jobs

308,700 openings / year, split into:

replacement / exits 292,364

Growth — new jobs (5%)Exits — backfill (95%)

5% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +4.4%
Growth share of hiring: 5%
Exit / retention pressure high: 95%
Openings / year: 308,700

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 E2 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$524k

San Francisco-Oakland-Fremont, CA$470k

Washington-Arlington-Alexandria, DC-VA-MD-WV$435k

Boulder, CO$429k

Seattle-Tacoma-Bellevue, WA$429k

Boston-Cambridge-Newton, MA-NH$411k

Lexington Park, MD$400k

Trenton-Princeton, NJ$398k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $315k; 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 E2 (E2 — Senior Director (Executive)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple functions or a major area
Autonomy: Owns area-level strategy
Complexity: Multi-function strategy and risk
Impact: Major-area outcomes
Decision rights: Owns strategy and resourcing across functions
Leadership: Leads function leaders

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

Promotion

The next rung from E2 is E3.

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 Store Operations Supervisor	jf_store_operations_general::M2	$110,455†	confident0.06
Store Operations Analyst	jf_store_operations_general::P2	$72,357†	confident0.06
Store Operations Coordinator	jf_store_operations_general::S2	$42,923†	confident0.06
Vice President of Store Operations	jf_store_operations_general::E1	$169,459†	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 11-1021

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

E2

jf_store_operations_general::E2

SVP of Store Operations

General

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: retail_hospitality
Function: store_operations
Family: store_operations_general
Universal level: 2 / 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 · E2review0.17

Loss Prevention · E2review0.17

Optical · E2review0.17

Pharmacy · E2review0.17

Product Specialty · E2review0.17

Store Management · E2review0.17

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 11-1021	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)