市場調查報告書
商品編碼
1370769
勞動力分析市場 - 2018-2028 年全球產業規模、佔有率、趨勢、機會和預測,按組件類型、部署類型、組織規模、最終用途行業、地區和競爭細分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 |
由於企業擴大採用基於雲端的勞動力分析解決方案,特別是在發展中國家,勞動力分析市場預計將在預測期內激增,以克服隨著更加強的人力資源管理的發展而日益成長的複雜性。勞動力分析可以幫助組織識別員工行為、績效和敬業度的趨勢和模式。透過了解這些模式,組織可以就如何分配資源和提高員工生產力做出更好的決策。它允許企業減少營業額、提高效率並管理分佈在多個站點的資料,同時提高效能、可靠性和可擴展性。
此外,人工智慧 (AI) 和機器學習 (ML) 在勞動力分析中的應用不斷增加,也增加了對全球勞動力分析市場的需求。為了彌補複雜系統帶來的損失,企業擴大利用勞動力分析服務來提供有效的人才管理、薪資活動以及提高人員管理的勞動力能力。分析領域進行的眾多創新和產品發布預計將增強勞動力分析的功能。反過來,這預計將在預測期內推動市場成長。
利用資料分析來增強勞動力管理和決策的過程稱為勞動力分析。此實踐衡量員工行為和相關因素對整體業務績效的影響。為了收集有關勞動力趨勢和習慣的見解,它使用各種來源的資料,包括人力資源系統、績效管理工具和員工調查。為了實現業務目標,人力資源領導者正在整合技術和業務洞察,其中員工分析發揮重要組成部分。隨著越來越多的組織認知到勞動力分析市場的價值,勞動力分析市場變得越來越廣泛。勞動力分析用於招募和人才管理、員工保留、員工體驗、員工績效以及培訓和發展。勞動力分析的主要目的是確定對新部門和職位的需求,並預測單一員工成功的可能性。
市場概況 | |
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預測期 | 2024-2028 |
2022 年市場規模 | 24.3億美元 |
2028 年市場規模 | 59.9億美元 |
2023-2028 年年複合成長率 | 15.27% |
成長最快的細分市場 | 衛生保健 |
最大的市場 | 北美洲 |
除了諸如填補時間、每次僱用成本、開始時間、聘用接受率、加入率、保留率、增加率和替換率等傳統比率外,它還評估僱用、人員配置、培訓和發展、人員、薪酬、和好處。這些勞動力分析通常用於增強勞動力報告、評估 KPI、收集資料、為勞動力提供透明度等。
由於科技的快速發展和對數位技能發展的日益重視,面向未來的組織不斷重新定義他們所尋求的人才。如今,有大量關於員工的資料。這些資料包括從績效評估和人口統計資訊到社交媒體活動和電子郵件通訊的所有內容。為了理解這些資料並找到重要的模式和鏈接,組織需要人工智慧和機器學習的幫助。人工智慧和機器學習的整合正在幫助企業自動化各種與勞動力分析相關的操作,並減少員工需要完成的手動任務的數量。可以使用支援人工智慧的系統收集有關員工績效、敬業度、工作幸福感、職業目標、培訓要求和其他主題的即時見解。
對即時洞察和預測以最佳化效能的需求凸顯了對資料驅動決策 (DDDM) 的需求。傳統上,人力資源在做出決策時依賴直覺和經驗,這導致了偏見和次優結果。為了克服偏見並做出與其策略相符的最佳管理決策,數據驅動的決策組織可以使用正確的 KPI 和工具,利用資料做出明智且經過驗證的決策。然而,亞馬遜、沃爾瑪、西南航空和Netflix 等公司正在實施數據驅動的決策演算法,透過識別高績效員工和潛在的未來領導者來提高保留率,使他們能夠更好地管理並發展他們的才能和能力。保持競爭力。
此外,許多企業正在整合基於數據驅動的決策人力資源分析,以獲得許多好處,例如改善決策、更好的人才管理、減少人員流動、提高員工敬業度等。因此,組織越來越需要使數據驅動決策(DDDM) 正在推動全球勞動分析市場。
雲端服務對於人力資源職能的重要性和可近性日益提高,使企業能夠以更少、更快、更經濟、更靈活的方式完成更多任務。隨著全球向混合未來過渡,企業可以更頻繁地使用雲端平台,使其 IT 營運具有適應性、可擴展性和敏捷性。由於基於雲端的系統不需要硬體基礎設施來運行,因此它為企業提供了採用各種標準以無縫且經濟高效地在雲端上實施、管理和交付新業務模型的優勢。雲端的整合有助於創造新的人力資源機會,透過吸引新人才、增強現有員工的能力以及使用新流程和技術協調人員,根據業務需求匹配和持續改進人力資源流程。此外,基於雲端的勞動力分析解決方案為人力資源/人才職能提供了快速適應不斷變化的業務需求的機會。例如,據國際數據公司 (IDC) 稱,自 COVID-19 大流行爆發以來,列印基礎設施內的技術採用發生了變化。大約 46% 的企業尋求在不久的將來轉向基於雲端的列印和列印管理。
此外,到 2025 年,雲端將取代本地基礎設施,成為 65% 的 A2000 組織儲存、管理和分析營運資料的主要場所。此外,使用者可以存取一致的員工訊息,從而將人力資源部門從管理任務中解放出來。此外,組織現在可以採用全套人才管理計劃,並最佳化人力資源資料對雲端的核心人力資源解決方案和人才管理系統的價值。因此,基於雲端的勞動力分析解決方案的日益普及歸因於全球市場勞動力分析的成長。
全球勞動力分析市場按組件類型、部署類型、組織規模和最終使用行業進行細分。根據組件類型,市場分為解決方案和服務。解決方案部分進一步分為人才獲取和發展最佳化服務以及薪資和監控。服務部分分為專業服務和託管服務。根據部署類型,市場分為雲端和本地。根據組織規模,市場分為中小企業和大型企業。根據最終用途行業,市場分為 BFSI、製造業、IT 和電信、醫療保健、零售等。市場分析也研究區域細分,以設計區域市場細分,分為北美、歐洲、亞太地區、南美以及中東和非洲。
自動資料處理公司、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. 是推動這一成長的主要參與者全球勞動力分析市場。
在本報告中,除了以下詳細介紹的產業趨勢外,全球勞動力分析市場也分為以下幾類:
(註:公司名單可依客戶要求客製化。)
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.)