市场调查报告书
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劳动力分析市场 - 2018-2028 年全球产业规模、份额、趋势、机会和预测,按组件类型、部署类型、组织规模、最终用途行业、地区和竞争细分Workforce Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Component Type, By Deployment Type, By Organization Size, By End-Use Industry, By Region and Competition |
由于企业越来越多地采用基于云端的劳动力分析解决方案,特别是在发展中国家,劳动力分析市场预计将在预测期内激增,以克服随着更加强的人力资源管理的发展而日益增长的复杂性。劳动力分析可以帮助组织识别员工行为、绩效和敬业度的趋势和模式。透过了解这些模式,组织可以就如何分配资源和提高员工生产力做出更好的决策。它允许企业减少营业额、提高效率并管理分布在多个站点的资料,同时提高效能、可靠性和可扩展性。
此外,人工智慧 (AI) 和机器学习 (ML) 在劳动力分析中的应用不断增加,也增加了对全球劳动力分析市场的需求。为了弥补复杂系统带来的损失,企业越来越多地利用劳动力分析服务来提供有效的人才管理、薪资活动以及提高人员管理的劳动力能力。分析领域进行的众多创新和产品发布预计将增强劳动力分析的功能。反过来,这预计将在预测期内推动市场成长。
利用资料分析来增强劳动力管理和决策的过程称为劳动力分析。此实践衡量员工行为和相关因素对整体业务绩效的影响。为了收集有关劳动力趋势和习惯的见解,它使用各种来源的资料,包括人力资源系统、绩效管理工具和员工调查。为了实现业务目标,人力资源领导者正在整合技术和业务洞察,其中员工分析发挥重要组成部分。随着越来越多的组织认识到劳动力分析市场的价值,劳动力分析市场变得越来越广泛。劳动力分析用于招募和人才管理、员工保留、员工体验、员工绩效以及培训和发展。劳动力分析的主要目的是确定对新部门和职位的需求,并预测单一员工成功的可能性。
市场概况 | |
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预测期 | 2024-2028 |
2022 年市场规模 | 24.3亿美元 |
2028 年市场规模 | 59.9亿美元 |
2023-2028 年复合年增长率 | 15.27% |
成长最快的细分市场 | 卫生保健 |
最大的市场 | 北美洲 |
除了诸如填补时间、每次僱用成本、开始时间、聘用接受率、加入率、保留率、增加率和替换率等传统比率外,它还评估僱用、人员配置、培训和发展、人员、薪酬、和好处。这些劳动力分析通常用于增强劳动力报告、评估 KPI、收集资料、为劳动力提供透明度等。
由于科技的快速发展和对数位技能发展的日益重视,面向未来的组织不断重新定义他们所寻求的人才。如今,有大量关于员工的资料。这些资料包括从绩效评估和人口统计资讯到社交媒体活动和电子邮件通讯的所有内容。为了理解这些资料并找到重要的模式和链接,组织需要人工智慧和机器学习的帮助。人工智慧和机器学习的整合正在帮助企业自动化各种与劳动力分析相关的操作,并减少员工需要完成的手动任务的数量。可以使用支援人工智慧的系统收集有关员工绩效、敬业度、工作幸福感、职业目标、培训要求和其他主题的即时见解。
对即时洞察和预测以优化效能的需求凸显了对资料驱动决策 (DDDM) 的需求。传统上,人力资源在做出决策时依赖直觉和经验,这导致了偏见和次优结果。为了克服偏见并做出与其策略相符的最佳管理决策,数据驱动的决策组织可以使用正确的 KPI 和工具,利用资料做出明智且经过验证的决策。然而,亚马逊、沃尔玛、西南航空和Netflix 等公司正在实施数据驱动的决策演算法,透过识别高绩效员工和潜在的未来领导者来提高保留率,使他们能够更好地管理并发展他们的才能和能力。保持竞争力。
此外,许多企业正在整合基于数据驱动的决策人力资源分析,以获得许多好处,例如改善决策、更好的人才管理、减少人员流动、提高员工敬业度等。因此,组织越来越需要使数据驱动决策(DDDM) 正在推动全球劳动分析市场。
云端服务对于人力资源职能的重要性和可近性日益提高,使企业能够以更少、更快、更经济、更灵活的方式完成更多任务。随着全球向混合未来过渡,企业可以更频繁地使用云端平台,使其 IT 营运具有适应性、可扩展性和敏捷性。由于基于云端的系统不需要硬体基础设施来运行,因此它为企业提供了采用各种标准以无缝且经济高效地在云端上实施、管理和交付新业务模型的优势。云端的整合有助于创造新的人力资源机会,透过吸引新人才、增强现有员工的能力以及使用新流程和技术协调人员,根据业务需求匹配和持续改进人力资源流程。此外,基于云端的劳动力分析解决方案为人力资源/人才职能提供了快速适应不断变化的业务需求的机会。例如,据国际数据公司 (IDC) 称,自 COVID-19 大流行爆发以来,列印基础设施内的技术采用发生了变化。大约 46% 的企业寻求在不久的将来转向基于云端的列印和列印管理。
此外,到 2025 年,云端将取代本地基础设施,成为 65% 的 A2000 组织储存、管理和分析营运资料的主要场所。此外,使用者可以存取一致的员工讯息,从而将人力资源部门从管理任务中解放出来。此外,组织现在可以采用全套人才管理计划,并优化人力资源资料对云端的核心人力资源解决方案和人才管理系统的价值。因此,基于云端的劳动力分析解决方案的日益普及归因于全球市场劳动力分析的成长。
全球劳动力分析市场按组件类型、部署类型、组织规模和最终使用行业进行细分。根据组件类型,市场分为解决方案和服务。解决方案部分进一步分为人才获取和发展优化服务以及薪资和监控。服务部分分为专业服务和託管服务。根据部署类型,市场分为云端和本地。根据组织规模,市场分为中小企业和大型企业。根据最终用途行业,市场分为 BFSI、製造业、IT 和电信、医疗保健、零售等。市场分析也研究区域细分,以设计区域市场细分,分为北美、欧洲、亚太地区、南美以及中东和非洲。
自动资料处理公司、Workday Inc.、IBM Corporation、Cornerstone OnDemand Inc.、埃森哲公司、Kronos Incorporated、Oracle Corporation、SAP SE、Workforce Software, LLC 和 Cisco Systems Inc. 是推动这一成长的主要参与者全球劳动力分析市场。
在本报告中,除了以下详细介绍的产业趋势外,全球劳动力分析市场也分为以下几类:
(註:公司名单可依客户要求客製化。)
Workforce analytics market is predicted to proliferate during the forecast period due to the increasing adoption of cloud-based workforce analytics solutions, especially in developing countries by enterprises to overcome the growing complexity along with the development of more enhanced human resource management. Workforce analytics can help organizations identify trends and patterns in employee behaviour, performance, and engagement. By understanding these patterns, organizations can make better decisions about how to allocate resources and improve employee productivity. It allows businesses to reduce turnover, increase efficiency and manage data spread across several sites while enhancing performance, dependability, and scalability.
Additionally, the increasing uptake of Artificial Intelligence (AI) and Machine Learning (ML) in workforce analytics is increasing the demand for the global workforce analytics market. In an effort to compensate for the losses in complexity systems, businesses are increasingly utilizing workforce analytics services to provide effective talent management, payroll activities, and increasing workforce capability in people management. Numerous innovations and product launches carried out in analytics are expected to enhance the features of workforce analytics. This, in turn, is expected to drive market growth during the forecast period.
The process of employing data analysis to enhance workforce management and decision-making is known as workforce analytics. The practice measures the impact of workforce behavior and related factors on overall business performance. In order to gather insights on workforce trends and habits, it uses data from a variety of sources, including HR systems, performance management tools, and employee surveys. To achieve business goals, HR leaders are integrating technology and business insights in which staff analytics plays an essential component. The workforce analytics market is becoming more widespread as more organizations recognize its value. Workforce analytics is utilized for recruitment and talent management, employee retention, employee experience, employee performance, and training and development. The main purposes of workforce analytics are to identify the need for new departments and positions and predict the probability of an individual employee's success.
Market Overview | |
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Forecast Period | 2024-2028 |
Market Size 2022 | USD 2.43 Billion |
Market Size 2028 | USD 5.99 Billion |
CAGR 2023-2028 | 15.27% |
Fastest Growing Segment | Healthcare |
Largest Market | North America |
In addition to conventional ratios such as time to fill, cost per hire, time to start, offer acceptance rate, accession rate, retention rate, add rate, and replacement rate, it evaluates hiring, staffing, training and development, personnel, compensation, and benefits. These workforce analytics are generally used in enhancing workforce reporting, evaluating KPIs, collecting data, providing transparency to the workforce, etc.
Future-ready organizations are continuously redefining the talent they seek as a result of quickly evolving technology and an increased emphasis on developing digital skills. Nowadays, there are enormous amounts of data available on employees. This data includes everything from performance reviews and demographic information to social media activity and email communications. To understand this data and find significant patterns and links, organizations require the aid of AI and machine learning. The integration of AI and machine learning are aiding enterprises to automate a variety of workforce analytics-related operations and reducing the number of manual tasks that employees need to complete. Real-time insights regarding employee performance, engagement levels, work happiness, career goals, training requirements, and other topics may be gathered using systems that are AI-enabled.
Moreover, AI algorithms are even capable of forecasting results for hiring, learning and development, and staff retention. For instance, a recent study by the World Economic Forum projects that by 2025, 75 million jobs worldwide will be automated by AI. Moreover, according to IBM Global AI Adoption Index 2022, in 35% of cases, enterprises reported employing AI in their operations, while 42% said they are investigating it in other cases. The advancement in technologies is aiding in replacing and upgrading workforce analytics enabling the enhancement of manual systems, and constantly balancing the overall management between employees and employers to maintain workforce stability. Therefore, the increasing adoption of AI and machine learning in workforce analytics is propelling the growth of the global workforce analytics market in the forecast period.
The need for real-time insights and predictions to optimize performance has highlighted the requirement for Data-driven Decision Making (DDDM). Traditionally human resources have relied on intuition and experience while making decisions, which has led to biases and suboptimal outcomes. To overcome the biases and make the best managerial rulings that are aligned with their strategies, data-driven decision-making organizations can use data to make informed and verified decisions by using the right KPIs and tools. However, companies, such as Amazon, Walmart, Southwest Airlines, and Netflix, are implementing data-driven decision-making algorithms to increase retention rates by identifying high-performing employees and potential future leaders, enabling them to manage better and develop their talent and stay competitive.
Moreover, many enterprises are integrating data-driven based decision-making HR analytics for numerous benefits such as improved decision-making, better talent management, reduced turnover, enhanced employee engagement, etc. Thus, the growing need for organizations to make Data-driven Decision Making (DDDM) is driving the global workforce analytics market.
Cloud services growing importance and accessibility for the HR function gives businesses the possibility to accomplish more with less, faster, more affordably, and with more flexibility. Businesses can use cloud platforms more frequently to make their IT operations adaptable, scalable, and agile as the globe transitions to a hybrid future. As cloud-based systems do not require hardware infrastructure to operate, it provides an edge to enterprises to adopt a wide range of standards for seamlessly and cost-effectively implementing, managing, and delivering new business models on the cloud. The integration of the cloud is assisting in the creation of new HR opportunities for matching and continually improving HR processes in accordance with business demands by luring in new talent, enhancing the abilities of present employees, and coordinating personnel with new procedures and technology. In addition, cloud-based workforce analytics solutions provide the opportunity for HR/Talent functions to adapt to changing business needs dramatically and quickly. For instance, according to International Data Corporation (IDC), technology adoption within the print infrastructure has changed since the onset of the COVID-19 pandemic. Around 46% of businesses are seeking to move to cloud-based printing and print management in the near future.
Additionally, by 2025, the cloud will replace on-premises infrastructure as the principal place where operational data is stored, managed, and analyzed for 65% of A2000 organizations. Furthermore, the users can access consistent employee information that are freeing HR from administrative tasks. Moreover, organizations can now embrace the complete range of talent management programs and optimize the value of HR data to cloud-based core HR solutions and talent management systems. Therefore, the increasing uptake of cloud-based workforce analytics solutions is attributed to the growth of workforce analytics in the global market.
The global workforce analytics market is segmented by component type, deployment type, organization size, and end-use industry. Based on component type, the market is segmented into Solutions and Services. The solution segment is further bifurcated into talent acquisition and development optimization services and payroll and monitoring. The service segment is divided into professional services and managed services. Based on deployment type, the market is bifurcated into Cloud and On-premises. Based on organization size, the market is segmented into small- and medium-sized enterprises and large enterprises. Based on the end-use industry, the market is segmented into BFSI, manufacturing, IT & Telecom, healthcare, retail, and others. The market analysis also studies the regional segmentation to devise regional market segmentation, divided among North America, Europe, Asia-Pacific, South America, and the Middle East & Africa.
Automatic Data Processing Inc., Workday Inc., IBM Corporation, Cornerstone OnDemand Inc., Accenture Plc, Kronos Incorporated, Oracle Corporation, SAP SE, Workforce Software, LLC, and Cisco Systems Inc. are among the major players that are driving the growth of the global workforce analytics market.
In this report, the global workforce analytics market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
(Note: The companies list can be customized based on the client requirements.)