Human Resource Analytics Market by Component (Services, Solutions), Deployment Model (Cloud, On Premise), Organization Size, Industry Vertical - Global Forecast 2025-2032
Description
The Human Resource Analytics Market was valued at USD 2.83 billion in 2024 and is projected to grow to USD 3.20 billion in 2025, with a CAGR of 13.45%, reaching USD 7.77 billion by 2032.
An urgent introduction to how human resource analytics is transitioning from administrative reporting to strategic decision intelligence for workforce planning and organizational performance
Human resource analytics is rapidly evolving from a back-office capability into a strategic enabler that informs workforce decisions at every level of the enterprise. Organizations increasingly integrate people data with operational and financial signals to align talent initiatives with business objectives, and this shift drives new requirements for data integration, analytics maturity, and cross-functional governance.
As stakeholders demand deeper, prescriptive insights, technology vendors and service providers are adapting product portfolios and delivery models to bridge analytics, workflow, and user experience. Consequently, HR leaders must balance near-term operational priorities with longer-term investments in skills, data platforms, and change management to ensure analytics initiatives deliver measurable value. Furthermore, as regulatory scrutiny and employee expectations intensify, organizations need robust privacy, ethics, and transparency frameworks to maintain trust while leveraging people analytics.
How converging advances in machine learning, cloud integration, and data governance are reshaping human resource analytics into proactive decision systems for modern enterprises
The landscape of human resource analytics is undergoing transformative shifts driven by converging forces in technology, talent, and governance, and these changes are redefining how organizations capture, interpret, and act on people insights. Advances in machine learning and natural language processing have expanded the scope of analysis from descriptive dashboards to predictive models and automated recommendations, thereby enabling HR teams to anticipate turnover risks, surface skill gaps, and optimize labor allocation with greater precision.
Simultaneously, the proliferation of cloud-native platforms and API-driven integrations has lowered barriers to consolidating disparate data sources, which supports real-time decision-making and tighter alignment with business systems. At the same time, growing expectations around ethical AI and employee privacy have prompted more rigorous data governance practices, affecting the design and deployment of analytics solutions. Together, these shifts pressure organizations to upgrade their technology stack, reskill HR practitioners, and establish cross-functional governance to realize the full potential of analytics while mitigating operational and reputational risks.
Understanding the multifaceted consequences of recent United States tariff changes on procurement strategies, vendor contracts, and deployment choices in human resource analytics
Recent tariff policies in the United States have introduced layered implications for the procurement, deployment, and maintenance of human resource analytics technologies, particularly for organizations that source hardware, specialized analytics appliances, or internationally developed software components. Supply chain adjustments and increased import duties can extend vendor lead times and elevate total cost of acquisition for on-premise infrastructure, prompting many firms to reassess the balance between capital investment and operational agility.
As a result, procurement teams are revisiting vendor contracts, evaluating cloud-first alternatives, and negotiating service-level guarantees that absorb tariff-related risk. In parallel, software publishers and systems integrators are adapting commercial models to protect customers from abrupt cost exposures, offering managed services, regional delivery hubs, and licensing constructs that facilitate smoother transitions. These developments encourage organizations to prioritize deployment elasticity and vendor diversification while reinforcing the need for proactive contract management and scenario planning to maintain continuity of analytics initiatives.
Detailed segmentation insights that clarify how components, deployment models, organization scale, and industry verticals drive differentiated solution priorities and implementation approaches
Segmentation insights reveal how different components, deployment models, organization sizes, and industry verticals shape demand dynamics and solution requirements across the human resource analytics landscape. Based on Component, market offerings bifurcate into Services and Solutions; Services extend across Consulting, Integration & Deployment, and Training & Support while Solutions encompass HR Management, Predictive Analytics, Reporting & Visualization, Talent Management, and Workforce Management, each addressing distinct functional needs and implementation complexities. Consequently, organizations seeking rapid insight prioritise solutions such as Reporting & Visualization and HR Management for operational clarity, whereas those pursuing future-readiness invest in Predictive Analytics and Talent Management to enable proactive workforce strategies.
Based on Deployment Model, organizations choose between Cloud and On Premise environments, with Cloud options further differentiated into Hybrid Cloud, Private Cloud, and Public Cloud configurations. This distinction affects scalability, data residency, and integration patterns; public cloud accelerates time-to-value for experimentation, private cloud serves regulated contexts requiring controlled environments, and hybrid cloud offers a compromise that supports phased migrations and sensitive data segmentation. Based on Organization Size, the needs of Large Enterprises diverge from Small & Medium Enterprises in terms of customization, governance maturity, and integration complexity. Large enterprises demand advanced predictive capabilities and enterprise-grade controls, while small and medium organizations prioritize out-of-the-box deployments and embedded best practices that reduce implementation overhead.
Based on Industry Vertical, sector-specific considerations shape analytics adoption and feature prioritization across BFSI, Government & Public Sector, Healthcare & Life Sciences, IT & Telecom, Manufacturing, and Retail & Ecommerce. Financial services and healthcare emphasize compliance, security, and workforce risk modeling; government entities require transparency, interoperability, and public accountability; IT and telecom favour agile, real-time analytics to support project-based resourcing; manufacturing focuses on shift planning and skill-based scheduling; and retail and ecommerce prioritise seasonal workforce optimization and customer-facing competencies. Together, these segmentation dimensions inform product roadmaps, service offerings, and go-to-market strategies as vendors tailor capabilities to distinct enterprise requirements.
How regional market dynamics and regulatory diversity across the Americas, Europe Middle East & Africa, and Asia-Pacific shape solution design, delivery models, and go-to-market strategies
Regional dynamics influence both supply-side innovation and demand-side priorities for human resource analytics, and understanding these variations is central to designing effective market entry strategies and deployment blueprints. In the Americas, organizations emphasize innovation velocity, cloud adoption, and integration with enterprise resource planning and talent platforms, which accelerates demand for modular solutions and consulting services that bridge HR and operations. Meanwhile, in Europe, Middle East & Africa, regulatory nuance and data sovereignty concerns elevate the importance of privacy-first architectures, localized support, and vendor certifications, prompting longer procurement cycles but also deeper strategic partnerships.
Across Asia-Pacific, the market displays heterogeneity with rapid digital adoption in technology-forward economies and pragmatic, cost-sensitive approaches in emerging markets; this creates opportunities for scalable cloud solutions and channel-based delivery models that accommodate diverse maturity levels. Additionally, cross-regional considerations such as global talent mobility, multinational compliance, and distributed work models require vendors and adopters to design interoperable solutions that respect regional constraints while enabling centralized governance. Therefore, leaders must calibrate go-to-market tactics, partnership ecosystems, and deployment templates to reflect these geographic differences while preserving consistent enterprise-level controls and reporting.
Competitive landscape analysis showing how product differentiation, service partnerships, and open architectures determine vendor strength and client adoption in human resource analytics
A review of key companies in the human resource analytics ecosystem highlights a competitive landscape where product differentiation, service excellence, and partnership ecosystems determine market positioning. Leading providers distinguish themselves by integrating robust analytics engines with intuitive user experiences, delivering domain-specific templates and industry accelerators, and offering managed services that reduce time-to-impact for customers. Service specialists complement vendor capabilities by providing consulting, systems integration, and training programs that translate technical outputs into operational decision-making and behavioral change.
Additionally, vendors that prioritize open architectures and API-first design facilitate interoperability with payroll, talent acquisition, learning management, and enterprise planning systems, which enhances adoption in complex IT environments. The competitive environment also rewards companies that invest in trust-building measures such as transparent model explainability, data lineage features, and compliance certifications. Strategic partnerships and channel relationships further amplify reach, enabling providers to combine global product development with localized implementation expertise to meet diverse client needs.
Practical and prioritized recommendations for executives to accelerate analytics value while managing operational risk, governance, and vendor relationships effectively
Actionable recommendations for industry leaders focus on practical steps that accelerate analytics-driven value while mitigating implementation risk and ensuring ethical stewardship of employee data. First, executives should prioritize a modular technology architecture that supports phased rollouts, enabling early wins through reporting and visualization while progressively introducing predictive models and operational integrations. This staged approach reduces risk and builds stakeholder confidence through demonstrable outcomes.
Second, organizations must invest in people and governance by upskilling HR teams in analytics literacy, creating cross-functional councils to oversee data use, and establishing clear policies for privacy, consent, and algorithmic transparency. Third, procurement and vendor management should emphasize contractual flexibility to absorb supply chain and tariff-related disruptions, while negotiating performance-based outcomes that align vendor incentives with business results. Finally, leaders should pursue a productized approach to internal adoption-packaging analytics outputs into repeatable decision workflows for managers and frontline supervisors to ensure that insights translate into consistent actions and measurable improvements in workforce productivity and engagement.
A transparent mixed-methods research methodology combining practitioner interviews, vendor capability mapping, and corroborative secondary analysis to ensure robust insights
This research employs a mixed-methods approach that combines qualitative expert interviews, technology landscape mapping, and secondary analysis of publicly available sources to produce a comprehensive perspective on human resource analytics. Primary inputs include discussions with HR leaders, analytics practitioners, and solution architects to capture real-world use cases, deployment challenges, and success factors. These interviews are complemented by vendor capability assessments that evaluate product functionality, integration options, and service delivery models.
Secondary analysis draws on authoritative public filings, regulatory guidance, and industry reports to contextualize trends and corroborate practitioner insights. Throughout the study, triangulation techniques validate findings across independent sources, and the methodology emphasizes transparency in definitions, inclusion criteria for companies, and categorization rules for components, deployment models, organization sizes, and industry verticals. This layered approach supports credible conclusions and actionable recommendations while acknowledging inherent variability across organizational contexts and regulatory environments.
A strategic conclusion emphasizing the necessity of phased deployment, governance diligence, and alignment of analytics with operational decision workflows for lasting impact
In conclusion, human resource analytics is maturing into a strategic capability that requires aligned investments in technology, talent, and governance to deliver sustained organizational impact. Organizations that adopt a phased, outcome-oriented approach can capture immediate operational benefits through improved reporting and workforce management while progressively building advanced predictive capabilities that support strategic workforce planning and talent optimization. At the same time, evolving regulatory expectations and geopolitical trade considerations require agile procurement practices and privacy-first architectures to preserve continuity and stakeholder trust.
Leaders who integrate analytics into decision workflows, foster cross-functional governance, and prioritize ethical data practices will be best positioned to translate insights into measurable improvements in productivity, retention, and organizational agility. As the landscape evolves, sustained attention to change management, interoperability, and vendor relationships will remain essential to realize the full value of human resource analytics across diverse enterprise contexts.
Please Note: PDF & Excel + Online Access - 1 Year
An urgent introduction to how human resource analytics is transitioning from administrative reporting to strategic decision intelligence for workforce planning and organizational performance
Human resource analytics is rapidly evolving from a back-office capability into a strategic enabler that informs workforce decisions at every level of the enterprise. Organizations increasingly integrate people data with operational and financial signals to align talent initiatives with business objectives, and this shift drives new requirements for data integration, analytics maturity, and cross-functional governance.
As stakeholders demand deeper, prescriptive insights, technology vendors and service providers are adapting product portfolios and delivery models to bridge analytics, workflow, and user experience. Consequently, HR leaders must balance near-term operational priorities with longer-term investments in skills, data platforms, and change management to ensure analytics initiatives deliver measurable value. Furthermore, as regulatory scrutiny and employee expectations intensify, organizations need robust privacy, ethics, and transparency frameworks to maintain trust while leveraging people analytics.
How converging advances in machine learning, cloud integration, and data governance are reshaping human resource analytics into proactive decision systems for modern enterprises
The landscape of human resource analytics is undergoing transformative shifts driven by converging forces in technology, talent, and governance, and these changes are redefining how organizations capture, interpret, and act on people insights. Advances in machine learning and natural language processing have expanded the scope of analysis from descriptive dashboards to predictive models and automated recommendations, thereby enabling HR teams to anticipate turnover risks, surface skill gaps, and optimize labor allocation with greater precision.
Simultaneously, the proliferation of cloud-native platforms and API-driven integrations has lowered barriers to consolidating disparate data sources, which supports real-time decision-making and tighter alignment with business systems. At the same time, growing expectations around ethical AI and employee privacy have prompted more rigorous data governance practices, affecting the design and deployment of analytics solutions. Together, these shifts pressure organizations to upgrade their technology stack, reskill HR practitioners, and establish cross-functional governance to realize the full potential of analytics while mitigating operational and reputational risks.
Understanding the multifaceted consequences of recent United States tariff changes on procurement strategies, vendor contracts, and deployment choices in human resource analytics
Recent tariff policies in the United States have introduced layered implications for the procurement, deployment, and maintenance of human resource analytics technologies, particularly for organizations that source hardware, specialized analytics appliances, or internationally developed software components. Supply chain adjustments and increased import duties can extend vendor lead times and elevate total cost of acquisition for on-premise infrastructure, prompting many firms to reassess the balance between capital investment and operational agility.
As a result, procurement teams are revisiting vendor contracts, evaluating cloud-first alternatives, and negotiating service-level guarantees that absorb tariff-related risk. In parallel, software publishers and systems integrators are adapting commercial models to protect customers from abrupt cost exposures, offering managed services, regional delivery hubs, and licensing constructs that facilitate smoother transitions. These developments encourage organizations to prioritize deployment elasticity and vendor diversification while reinforcing the need for proactive contract management and scenario planning to maintain continuity of analytics initiatives.
Detailed segmentation insights that clarify how components, deployment models, organization scale, and industry verticals drive differentiated solution priorities and implementation approaches
Segmentation insights reveal how different components, deployment models, organization sizes, and industry verticals shape demand dynamics and solution requirements across the human resource analytics landscape. Based on Component, market offerings bifurcate into Services and Solutions; Services extend across Consulting, Integration & Deployment, and Training & Support while Solutions encompass HR Management, Predictive Analytics, Reporting & Visualization, Talent Management, and Workforce Management, each addressing distinct functional needs and implementation complexities. Consequently, organizations seeking rapid insight prioritise solutions such as Reporting & Visualization and HR Management for operational clarity, whereas those pursuing future-readiness invest in Predictive Analytics and Talent Management to enable proactive workforce strategies.
Based on Deployment Model, organizations choose between Cloud and On Premise environments, with Cloud options further differentiated into Hybrid Cloud, Private Cloud, and Public Cloud configurations. This distinction affects scalability, data residency, and integration patterns; public cloud accelerates time-to-value for experimentation, private cloud serves regulated contexts requiring controlled environments, and hybrid cloud offers a compromise that supports phased migrations and sensitive data segmentation. Based on Organization Size, the needs of Large Enterprises diverge from Small & Medium Enterprises in terms of customization, governance maturity, and integration complexity. Large enterprises demand advanced predictive capabilities and enterprise-grade controls, while small and medium organizations prioritize out-of-the-box deployments and embedded best practices that reduce implementation overhead.
Based on Industry Vertical, sector-specific considerations shape analytics adoption and feature prioritization across BFSI, Government & Public Sector, Healthcare & Life Sciences, IT & Telecom, Manufacturing, and Retail & Ecommerce. Financial services and healthcare emphasize compliance, security, and workforce risk modeling; government entities require transparency, interoperability, and public accountability; IT and telecom favour agile, real-time analytics to support project-based resourcing; manufacturing focuses on shift planning and skill-based scheduling; and retail and ecommerce prioritise seasonal workforce optimization and customer-facing competencies. Together, these segmentation dimensions inform product roadmaps, service offerings, and go-to-market strategies as vendors tailor capabilities to distinct enterprise requirements.
How regional market dynamics and regulatory diversity across the Americas, Europe Middle East & Africa, and Asia-Pacific shape solution design, delivery models, and go-to-market strategies
Regional dynamics influence both supply-side innovation and demand-side priorities for human resource analytics, and understanding these variations is central to designing effective market entry strategies and deployment blueprints. In the Americas, organizations emphasize innovation velocity, cloud adoption, and integration with enterprise resource planning and talent platforms, which accelerates demand for modular solutions and consulting services that bridge HR and operations. Meanwhile, in Europe, Middle East & Africa, regulatory nuance and data sovereignty concerns elevate the importance of privacy-first architectures, localized support, and vendor certifications, prompting longer procurement cycles but also deeper strategic partnerships.
Across Asia-Pacific, the market displays heterogeneity with rapid digital adoption in technology-forward economies and pragmatic, cost-sensitive approaches in emerging markets; this creates opportunities for scalable cloud solutions and channel-based delivery models that accommodate diverse maturity levels. Additionally, cross-regional considerations such as global talent mobility, multinational compliance, and distributed work models require vendors and adopters to design interoperable solutions that respect regional constraints while enabling centralized governance. Therefore, leaders must calibrate go-to-market tactics, partnership ecosystems, and deployment templates to reflect these geographic differences while preserving consistent enterprise-level controls and reporting.
Competitive landscape analysis showing how product differentiation, service partnerships, and open architectures determine vendor strength and client adoption in human resource analytics
A review of key companies in the human resource analytics ecosystem highlights a competitive landscape where product differentiation, service excellence, and partnership ecosystems determine market positioning. Leading providers distinguish themselves by integrating robust analytics engines with intuitive user experiences, delivering domain-specific templates and industry accelerators, and offering managed services that reduce time-to-impact for customers. Service specialists complement vendor capabilities by providing consulting, systems integration, and training programs that translate technical outputs into operational decision-making and behavioral change.
Additionally, vendors that prioritize open architectures and API-first design facilitate interoperability with payroll, talent acquisition, learning management, and enterprise planning systems, which enhances adoption in complex IT environments. The competitive environment also rewards companies that invest in trust-building measures such as transparent model explainability, data lineage features, and compliance certifications. Strategic partnerships and channel relationships further amplify reach, enabling providers to combine global product development with localized implementation expertise to meet diverse client needs.
Practical and prioritized recommendations for executives to accelerate analytics value while managing operational risk, governance, and vendor relationships effectively
Actionable recommendations for industry leaders focus on practical steps that accelerate analytics-driven value while mitigating implementation risk and ensuring ethical stewardship of employee data. First, executives should prioritize a modular technology architecture that supports phased rollouts, enabling early wins through reporting and visualization while progressively introducing predictive models and operational integrations. This staged approach reduces risk and builds stakeholder confidence through demonstrable outcomes.
Second, organizations must invest in people and governance by upskilling HR teams in analytics literacy, creating cross-functional councils to oversee data use, and establishing clear policies for privacy, consent, and algorithmic transparency. Third, procurement and vendor management should emphasize contractual flexibility to absorb supply chain and tariff-related disruptions, while negotiating performance-based outcomes that align vendor incentives with business results. Finally, leaders should pursue a productized approach to internal adoption-packaging analytics outputs into repeatable decision workflows for managers and frontline supervisors to ensure that insights translate into consistent actions and measurable improvements in workforce productivity and engagement.
A transparent mixed-methods research methodology combining practitioner interviews, vendor capability mapping, and corroborative secondary analysis to ensure robust insights
This research employs a mixed-methods approach that combines qualitative expert interviews, technology landscape mapping, and secondary analysis of publicly available sources to produce a comprehensive perspective on human resource analytics. Primary inputs include discussions with HR leaders, analytics practitioners, and solution architects to capture real-world use cases, deployment challenges, and success factors. These interviews are complemented by vendor capability assessments that evaluate product functionality, integration options, and service delivery models.
Secondary analysis draws on authoritative public filings, regulatory guidance, and industry reports to contextualize trends and corroborate practitioner insights. Throughout the study, triangulation techniques validate findings across independent sources, and the methodology emphasizes transparency in definitions, inclusion criteria for companies, and categorization rules for components, deployment models, organization sizes, and industry verticals. This layered approach supports credible conclusions and actionable recommendations while acknowledging inherent variability across organizational contexts and regulatory environments.
A strategic conclusion emphasizing the necessity of phased deployment, governance diligence, and alignment of analytics with operational decision workflows for lasting impact
In conclusion, human resource analytics is maturing into a strategic capability that requires aligned investments in technology, talent, and governance to deliver sustained organizational impact. Organizations that adopt a phased, outcome-oriented approach can capture immediate operational benefits through improved reporting and workforce management while progressively building advanced predictive capabilities that support strategic workforce planning and talent optimization. At the same time, evolving regulatory expectations and geopolitical trade considerations require agile procurement practices and privacy-first architectures to preserve continuity and stakeholder trust.
Leaders who integrate analytics into decision workflows, foster cross-functional governance, and prioritize ethical data practices will be best positioned to translate insights into measurable improvements in productivity, retention, and organizational agility. As the landscape evolves, sustained attention to change management, interoperability, and vendor relationships will remain essential to realize the full value of human resource analytics across diverse enterprise contexts.
Please Note: PDF & Excel + Online Access - 1 Year
Table of Contents
181 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Implementing AI-driven predictive analytics to proactively identify high turnover risk and reduce attrition rates
- 5.2. Integrating real-time workforce analytics dashboards to enable data-driven leadership decisions across global teams
- 5.3. Utilizing sentiment analysis of employee feedback to measure organizational culture and boost engagement initiatives
- 5.4. Deploying personalized learning and development analytics to optimize skill gap identification and training effectiveness
- 5.5. Applying advanced people analytics to forecast talent needs and align workforce planning with strategic objectives
- 5.6. Combining HR analytics with diversity, equity and inclusion metrics to foster equitable hiring and retention practices
- 5.7. Leveraging natural language processing on performance reviews to identify hidden insights and improve appraisal fairness
- 5.8. Automating compliance reporting through HR analytics to ensure adherence to evolving labor laws and regulations
- 5.9. Harnessing employee experience data through end-to-end analytics to enhance retention and productivity strategies
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Human Resource Analytics Market, by Component
- 8.1. Services
- 8.1.1. Consulting
- 8.1.2. Integration & Deployment
- 8.1.3. Training & Support
- 8.2. Solutions
- 8.2.1. Hr Management
- 8.2.2. Predictive Analytics
- 8.2.3. Reporting & Visualization
- 8.2.4. Talent Management
- 8.2.5. Workforce Management
- 9. Human Resource Analytics Market, by Deployment Model
- 9.1. Cloud
- 9.1.1. Hybrid Cloud
- 9.1.2. Private Cloud
- 9.1.3. Public Cloud
- 9.2. On Premise
- 10. Human Resource Analytics Market, by Organization Size
- 10.1. Large Enterprises
- 10.2. Small & Medium Enterprises
- 11. Human Resource Analytics Market, by Industry Vertical
- 11.1. BFSI
- 11.2. Government & Public Sector
- 11.3. Healthcare & Life Sciences
- 11.4. It & Telecom
- 11.5. Manufacturing
- 11.6. Retail & Ecommerce
- 12. Human Resource Analytics Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Human Resource Analytics Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Human Resource Analytics Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. SAP SE
- 15.3.2. Oracle Corporation
- 15.3.3. Workday Inc.
- 15.3.4. IBM Corporation
- 15.3.5. ADP LLC
- 15.3.6. UKG Inc.
- 15.3.7. Tableau Software LLC
- 15.3.8. Visier Inc.
- 15.3.9. Crunchr BV
- 15.3.10. Culture Amp Pty Ltd
- 15.3.11. Lattice HQ Inc.
- 15.3.12. Gloat Ltd.
- 15.3.13. Eightfold AI Inc.
- 15.3.14. Glint Inc.
- 15.3.15. HiBob Ltd.
- 15.3.16. Nakisa Inc.
- 15.3.17. Zoho Corporation Pvt Ltd
- 15.3.18. Ceridian HCM Holding Inc.
- 15.3.19. BambooHR LLC
- 15.3.20. Keka Technologies Pvt Ltd
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