소매업용 인력 관리(WFM) 시장 : 시장 점유율 분석, 산업 동향 및 통계 데이터, 성장 예측(2026-2031년)

According to Mordor Intelligence, the workforce management (WFM) in retail market size was valued at USD 1.54 billion in 2025 and is estimated to grow from USD 1.73 billion in 2026 to reach USD 3.09 billion by 2031, at a CAGR of 12.30% during the forecast period (2026-2031).

This report is Segmented by Component (Software, and Services), Deployment Mode (Cloud, On-Premises, and More), Enterprise Size (Large Enterprises, and Small and Medium-Sized Enterprises), Retail Format (Grocery and Supermarkets, Fashion and Apparel, Electronics Retail, Department Stores, Specialty Retail, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Workforce Management (WFM) In Retail Market Trends and Insights

Cloud-Based and AI-Native Scheduling Adoption

Cloud migration remains the strongest near-term force behind the workforce management (WFM) in retail market. AI scheduling tools can process foot traffic, local weather, promotion calendars, and employee availability in 15-minute or 30-minute intervals, giving retailers a planning depth that older systems could not handle well. Adoption friction is also easing on the labor side, with reports showing that 77% of retail associates would trust AI to recommend schedules that match their preferences. Cloud and subscription revenue rose 28% in FY2025 to EUR 92.7 million (USD 100.1 million), equal to 49% of total group revenue, which shows that enterprise buyers are shifting budget toward subscription-led models. As these capabilities become standard expectations, the workforce management in retail market is moving away from basic digitization and toward real-time labor orchestration.

Omnichannel Retail Complexity and Labor Optimization Needs

Omnichannel retail has made labor planning significantly more complex, and that complexity is fueling demand in the WFM in retail market. Store teams now divide their time across in-store service, click-and-collect, curbside handoff, e-commerce picking, and replenishment, meaning a single shift often carries multiple task types. Industry leaders have emphasized that in-store fulfillment works best when retailers create dedicated fulfillment roles or time blocks, which points directly to task-level scheduling rather than static weekly rosters. The challenge is no longer just labor cost. Poor scheduling now undermines order throughput, pickup speed, and customer service simultaneously. Retailers that can align labor deployment with order-wave patterns are better positioned to protect both margin and fulfillment revenue, making advanced workforce management tools central to omnichannel success.

Integration Complexity Across POS, Payroll, HRIS, and E-commerce Systems

Integration burden remains the largest structural restraint on the WFM in retail market. A scheduling engine can optimize labor on paper, but it loses value when it cannot exchange data smoothly with point-of-sale systems, payroll engines, HRIS platforms, and order management tools. Shopify cited EY analysis showing that unified retail infrastructure can reduce implementation costs by 11% and middleware expenses by 27%, which highlights the hidden cost of disconnected technology estates. The problem is sharper where privacy and AI disclosure rules require controlled data movement across systems, including GDPR, CCPA, and Ontario's January 2026 AI transparency requirement for employers with 25 or more staff. That is why vendors are competing harder on certified payroll links, prebuilt connectors, and deployment flexibility, as shown by ATOSS references to DATEV-certified interfaces and SAP-certified modules.

Other drivers and restraints analyzed in the detailed report include:

1. Rising Retail Wage Costs and Margin Pressure
2. Fair Workweek and Labor Compliance Automation Demand
3. Data Privacy and Employee Monitoring Concerns

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Software held 71.24% of the workforce management in retail market share in 2025, and employee scheduling and labor optimization remained the largest software sub-segment at 32.52% of the total market. This position reflects how directly schedule quality affects store coverage, labor cost, and lost sales. Logile reported that 77% of associates believe stores regularly lose sales due to poor scheduling, while 74% are open to AI-driven scheduling based on traffic patterns. Time and attendance, analytics and forecasting, and leave management remain important because they connect scheduling decisions to payroll accuracy and labor visibility. Within the workforce management in retail industry, software has become the control layer that ties labor planning to daily store execution.

Services are forecast to grow at a 14.12% CAGR through 2031, making them the fastest-growing component of the workforce management (WFM) in retail market. This reflects the fact that platform value depends on rollout quality, local rule configuration, and change management across large store networks. UKG stated that 57% of frontline workers prefer employer communication only through mobile, and 70% said their employer does not offer on-demand pay, which shows how implementation scope is widening beyond core scheduling into engagement and pay-adjacent functions. As the workforce management in retail industry becomes more platform-led, services are gaining weight because retailers need sustained support to make advanced features work across hundreds of locations.

Cloud accounted for 66.38% of the workforce management (WFM) in retail market size in 2025, which reflects the continued shift away from heavy on-premises infrastructure. Retailers favor cloud because it lowers upfront technology burden and speeds access to new AI and compliance features. Quinyx stated that more than 65% of WFM deployments are now cloud-based and pointed to returns above 10 times the original investment over 3 years through better scheduling, lower overtime, and reduced administration. Cloud also fits the regulatory reality of retail labor management, because rule updates can be pushed centrally instead of patched location by location. On-premises systems still retain some relevance where data sovereignty, internal control, or union requirements keep sensitive data closer to local infrastructure.

Hybrid deployment is projected to grow at a 13.23% CAGR through 2031, making it the fastest-growing deployment mode in the workforce management in retail market. This pattern reflects a practical compromise for large retailers that want cloud agility but still need tighter control over payroll or HR data. ATOSS Software SE's FY2025 results showed a two-track approach that supports enterprise clients with governance constraints while still encouraging fuller cloud adoption through AI-led capabilities. Hybrid growth also makes sense because many retailers still run core payroll or HRIS functions on older systems, and a mixed architecture reduces the risk of latency, data duplication, and integration friction.

Geography Analysis

North America held 38.92% of workforce management in retail market share in 2025, which kept it as the largest regional contributor. The region benefits from higher enterprise software spending, earlier adoption of AI-led labor tools, and the widest spread of predictive scheduling rules. UKG stated that it serves 69 of the NRF Top 100 retailers, which shows how deeply enterprise workforce platforms are already embedded in the North American retail base. Legion's rollout with Dollar Tree across more than 9,000 stores and 18 distribution centers shows the scale at which large North American deployments now operate. The regulatory environment continues to support demand, because cities such as Seattle, New York, Chicago, San Francisco, Portland, and Los Angeles County have turned compliance automation into a practical requirement rather than an optional add-on.

Europe remains a structurally important region for the workforce management (WFM) in retail market because labor regulation, time recording, and data governance requirements are forcing upgrade cycles. ATOSS Software SE highlighted retail customers such as OBI, C&A, Decathlon, and Primark, which shows that the region combines deep enterprise demand with long implementation cycles. The June 7, 2026 deadline for national transposition of the EU Pay Transparency Directive is adding another layer of reporting and audit pressure to workforce analytics. South America, the Middle East, and Africa are still earlier in adoption, but organized retail expansion and tighter labor oversight are creating greenfield openings for cloud-native vendors with multilingual and multi-country support.

Asia-Pacific is forecast to grow at a 13.02% CAGR, making it the fastest-growing geography in the WFM in retail market size through 2031. GaiaWorks stated that it serves more than 1,800 enterprises across 34 countries, and one 3C retail case delivered a 10.8% improvement in sales conversion and a 28% reduction in wasted labor hours through traffic-based scheduling. A separate GaiaWorks case study on a Chinese convenience chain reported a 20% reduction in labor costs after deployment of AI smart scheduling tied to store-level demand models. The region's growth is also supported by labor-rule updates such as Hong Kong's 468 transition and by the wider spread of AI-led retail execution in markets such as India, where organized retail is scaling fast.

1. UKG Inc.
2. Dayforce
3. WorkForce Software, LLC
4. Quinyx AB
5. Legion Technologies, Inc.
6. Deputechnologies Pty Ltd.
7. ATOSS Software SE
8. TimeClock Plus, LLC
9. Planday A/S
10. Rota Geek Limited
11. SISQUAL Workforce Management, Lda.
12. Swt Software Limited
13. Logile, Inc.
14. Orquest S.L.
15. Icron Technologies
16. Agendrix Inc.
17. Tommy Associates Pty Ltd.
18. TimeForge Labor Management
19. StoreForce Solutions Inc.
20. Evolia

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Cloud-Based and AI-Native Scheduling Adoption
  • 4.2.2 Omnichannel Retail Complexity and Labor Optimization Needs
  • 4.2.3 Rising Retail Wage Costs and Margin Pressure
  • 4.2.4 Fair Workweek and Labor Compliance Automation Demand
  • 4.2.5 Task-Level Labor Planning for Click-and-Collect and Micro-Fulfillment
  • 4.2.6 Cross-Store Labor Pooling and Gig-Like Shift Flexibility
• 4.3 Market Restraints
  • 4.3.1 Integration Complexity Across POS, Payroll, HRIS, and E-commerce Systems
  • 4.3.2 Data Privacy and Employee Monitoring Concerns
  • 4.3.3 Forecast Drift from Promotion-Led Demand Spikes and Returns Surges
  • 4.3.4 Frontline Manager Override Bias and Low Trust in AI Schedules
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Threat of New Entrants
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Bargaining Power of Suppliers
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Software
    • 5.1.1.1 Employee Scheduling and Labor Optimization
    • 5.1.1.2 Time and Attendance Management
    • 5.1.1.3 Workforce Analytics and Forecasting
    • 5.1.1.4 Leave and Absence Management
    • 5.1.1.5 Task and Execution Management
    • 5.1.1.6 Employee Self-service and Communication
  • 5.1.2 Services
• 5.2 By Deployment Mode
  • 5.2.1 Cloud
  • 5.2.2 On-premises
  • 5.2.3 Hybrid
• 5.3 By Enterprises Size
  • 5.3.1 Large Enterprises
  • 5.3.2 Small and Medium-sized Enterprises
• 5.4 By Retail Format
  • 5.4.1 Grocery & Supermarkets
  • 5.4.2 Fashion & Apparel
  • 5.4.3 Electronics Retail
  • 5.4.4 Department Stores
  • 5.4.5 Specialty Retail
  • 5.4.6 Convenience Stores
  • 5.4.7 E-commerce Retailers
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Chile
    • 5.5.2.4 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 Germany
    • 5.5.3.2 United Kingdom
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Rest of Europe
  • 5.5.4 Asia-Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 India
    • 5.5.4.4 Australia
    • 5.5.4.5 South Korea
    • 5.5.4.6 Southeast Asia
    • 5.5.4.7 Rest of Asia-Pacific
  • 5.5.5 Middle East
    • 5.5.5.1 Saudi Arabia
    • 5.5.5.2 United Arab Emirates
    • 5.5.5.3 Turkey
    • 5.5.5.4 Rest of Middle East
  • 5.5.6 Africa
    • 5.5.6.1 South Africa
    • 5.5.6.2 Egypt
    • 5.5.6.3 Nigeria
    • 5.5.6.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments).
  • 6.4.1 UKG Inc.
  • 6.4.2 Dayforce
  • 6.4.3 WorkForce Software, LLC
  • 6.4.4 Quinyx AB
  • 6.4.5 Legion Technologies, Inc.
  • 6.4.6 Deputechnologies Pty Ltd.
  • 6.4.7 ATOSS Software SE
  • 6.4.8 TimeClock Plus, LLC
  • 6.4.9 Planday A/S
  • 6.4.10 Rota Geek Limited
  • 6.4.11 SISQUAL Workforce Management, Lda.
  • 6.4.12 Swt Software Limited
  • 6.4.13 Logile, Inc.
  • 6.4.14 Orquest S.L.
  • 6.4.15 Icron Technologies
  • 6.4.16 Agendrix Inc.
  • 6.4.17 Tommy Associates Pty Ltd.
  • 6.4.18 TimeForge Labor Management
  • 6.4.19 StoreForce Solutions Inc.
  • 6.4.20 Evolia

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-Need Assessment