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Drawing on human capital theory and the human capital resources framework, this study explores the knowledge, skills, abilities and other characteristics (KSAOs) required by the emerging role of human resource (HR) analysts. This study aims to systematically identify the key KSAOs and develop a competency model for HR Analysts amid the growing digitalization of work.

Adopting best practices for competency modeling set out by Campion et al. (2011), this study first analyzes 110 HR analyst job advertisements collected from five countries: Australia, Canada, Ireland, the United Kingdom and the USA. Second a thematic analysis of 12 in-depth semistructured interviews with HR analytics professionals from Canada and Ireland is then conducted to develop a novel competency model for HR Analysts.

This study adds to the developing and fast-growing field of HR analytics literature by offering evidence supporting a set of six distinct competencies required by HR Analysts including: consulting, technical knowledge, data fluency and data analysis, HR and business acumen, research and discovery and storytelling and communication.

The research findings have several practical implications, specifically in recruitment and selection, HR development and HR system alignment.

This study contributes to the evolving HR analytics literature in two ways. First, the study links the role of HR Analysts to human capital theory and the human capital resource framework. Second, it offers a timely and empirically driven competency model for the emerging role of HR Analysts.

This study aims to explore the emergence of the human resource (HR) analyst role. The job posts on LinkedIn display the industry demand and skills required by the organizations. This study identifies the different knowledge, skills and abilities (KSA) required for an HR analyst role in different stages of professional growth (i.e. entry-level, middle-senior level and top-level) across different industries/sectors as applicable to the crisis.

A total of 80 job posts were extracted from LinkedIn. Details such as industry, job levels, qualifications, job experience, job functions, job descriptions (JDs) and job skills (JS) were collected. Further, 30 videos were extracted from YouTube and converted into text. Text analysis was conducted using NVivo software to analyze JDs, JS and job functions. Using NVivo, word frequency, word cloud, word tree and treemap were created to visualize the data. Finally, ten in-depth interviews were conducted with senior HRA managers based in India to understand the essential competencies required for the HR analyst role and the strategies to develop them.

The findings indicate that not only technical skills are needed, but business and communication skills are particularly important for all job levels during a crisis. The JD word cloud showed words, such as data, business, support and management, and the word tree depicted HR data and change agents as important words with many related sentences as branches. General JS included analytical, communication, problem-solving and management. Technical JS were the most widely used and included structure query language, system applications & products in data processing, human capital management, TABLEAU, management information system and PYTHON. Strategies to develop these competencies included case studies, live projects, internships on HR analytics (HRAs) assignments and mentoring by senior HRA professionals.

The sample used was small, as the study included 80 job posts available on LinkedIn restricted to India. The study was restricted to qualitative approach and text analytics was used. Survey methods and a quantitative approach can be used to collect data from HR recruiters, job holders and senior leaders to understand the role of HRAs in the job market and then these variables can be tested empirically.

Based on the McCartney et al.’s (2020) competency model for the HR Analyst role, this study has explored the KSA framework using data visualization techniques and used text analytics to analyze LinkedIn job posts for different levels, videos from YouTube and in-depth interviews. It also mapped the KSA for the HR analyst role to the various stages of crisis system management given by Mitroff (2005). The use of social media analytics, such as analyzing LinkedIn data and YouTube videos, are highlighted.

To understand human resource (HR) practices outcomes on HR decision making, strategic human resource management (HRM) and organizational performance by exploring the HR data quality along with descriptive and predictive financial and non-financial metrics.

This work utilizes the grounded theory method. After the literature was reviewed, 113 HR managers of multinational and national companies in India were interviewed with a semi-structured questionnaire. The collected interview data was analyzed with NVivo 8.0 software.

It is interesting to uncover the descriptive and predictive non-financial and financial metrics of HR practices and their influence on organizational performance. It was found that HR data quality moderates the relationship between the HR practices outcome and HR metrics. This study found that HR metrics help in HR decision-making for strategic HRM and subsequently affect organizational performance.

This study has uniquely provided the descriptive and predictive non-financial and financial metrics of HR practices and their impact on HR decision making, strategic HRM and organizational performance. This study highlights the importance of data quality. This research offers insights to the HR managers, HR analysts, chief HR officers and HR practitioners to achieve organizational performance considering the various metrics of HRM. It provides key insights to the top management to understand the HR metrics' effect on strategic HRM and organizational performance.

The purpose of this paper is to focus on how the HR function takes advantage of human resource analytics (HRA), including big data (BD), and discuss factors hindering HRA and data utilization. Moreover, the authors discuss the implications of the HRA-induced role transformation of the human resource (HR) function.

This is an explorative case study based on qualitative interviews in nine leading Finnish companies.

The results indicate that both technical and human obstacles, operating with very basic HR processes and traditional information systems and poor data quality, hinder adoption of advanced HRA. This, combined with lacking skills in analytics and business understanding, inability to go beyond reporting, misconceptions related to BD and traditional compliance-oriented HR culture pose further challenges for the data analytics capacity and business partner role of the HR function. Senior executives expect no significant advancements of HRA, while HR professionals saw potential value in BD, although skepticism was not uncommon. The results point toward a need for increased cooperation with data analysts and HR professionals in provision and understanding the HR-related data for business-related decision making. Furthermore, cultural change and organizational redesign may be called for, in addition to overcoming technological obstacles related to BD, for it to have an impact on HR practices. HRA utilization and role transition of the HR function seem closely related and this transformation can be mutually reinforcing.

This study provides and theorizes explorative data on HRA within a group of some of the largest Finnish companies, pointing toward an immature state of the art in BD and HRA utilization and there being a relationship between HRA and the role transition of the HR function in organizations.

Discusses the limitations of labour market analysis (LMA), which is widely advocated as a successor to conventional manpower planning. Argues the need for a more systematic approach within the framework of policy formulation and implementation. The proposed “policy‐focused” approach would overcome some of the problems associated with LMA, in particular its lack of a disciplinary framework and operational process.

Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist perspective, which limits understanding of actual HRA activities in the complex organisational environment. This paper therefore draws on the practice-based approach, using a novel framework to conceptualise HRA-as-practice.

The authors conducted a systematic literature review of 100 academic and practitioner-oriented publications to analyse existing HRA literature in relation to practice theory, using the “HRA-as-practice” frame.

The authors identify the main practices involved in HRA, by whom and how these practices are enacted, and reveal three topics in nomological network of HRA-as-practice: HRA technology, HRA outcomes and HRA hindrances and facilitators, which the authors suggest might actualize enactment of HRA practices.

The authors offer HR function and HR professionals a basic ground to evaluate HRA as a highly contextual activity that can potentially generate business value and increase HR impact when seen as a complex interaction between HRA practices, HRA practitioners and HRA praxis. The findings also help HR practitioners understand multiple factors that influence the practice of HRA.

This systematic review differs from the previous reviews in two ways. First, it analyses both academic and practitioner-oriented publications. Second, it provides a novel theoretical contribution by conceptualising HRA-as-practice and comprehensively compiling scattered topics and themes related to HRA.

Analytics enable HR to make strategic contributions, but not all analytics offer equal insights. Alec Levenson compares the usefulness of ROI, cost‐benefit, and impact analysis. He also explains why the time is right for HR to build an HR analytics centre of expertise and create a foundation of analytic skills across the function.

Data visualizations in some form or another have served as decision-support tools for many centuries. In conjunction with advancements in information technology, data visualizations have become more accessible and more efficient to generate. In fact, virtually all enterprise resource planning and human resource (HR) information system vendors offer off-the-shelf data visualizations as part of decision-support dashboards as well as stand-alone images and displays for reporting. Plus, advances in programing languages and software such as Tableau, Microsoft Power BI, R, and Python have expanded the possibilities of fully customized graphics. Despite the proliferation of data visualization, relatively little is known about how to design data visualizations for displaying different types of HR data to different user groups, for different purposes, and with the overarching goal of improving the ways in which users comprehend and interpret data visualizations for decision-making purposes. To understand the state of science and practice as they relate to HR data visualizations and data visualizations in general, we review the literature on data visualizations across disciplines and offer an organizing framework that emphasizes the roles data visualization characteristics (e.g., display type, features), user characteristics (e.g., experience, individual differences), tasks, and objectives (e.g., compare values) play in user comprehension, interpretation, and decision-making. Finally, we close by proposing future directions for science and practice.

Driven by the rapidly accelerating pace of technology-enabled developments within human resource management (HRM), human resource (HR) analytics is infiltrating the research and business agenda. As one of the first in its field, the purpose of this paper is to explore what the future of HR analytics might look like.

Using a sample of 20 practitioners of HR analytics, based in 11 large Dutch organizations, the authors investigated what the application, value, structure, and system support of HR analytics might look like in 2025.

The findings suggest that, by 2025, HR analytics will have become an established discipline, will have a proven impact on business outcomes, and will have a strong influence in operational and strategic decision making. Furthermore, the development of HR analytics will be characterized by integration, with data and IT infrastructure integrated across disciplines and even across organizational boundaries. Moreover, the HR analytics function may very well be subsumed in a central analytics function – transcending individual disciplines such as marketing, finance, and HRM.

The results of the research imply that HR analytics, as a separate function, department, or team, may very well cease to exist, even before it reaches maturity.

Empirical research on HR analytics is scarce, and studies on scenarios, values, and structures of expected developments in HR analytics are non-existent. This research intends to contribute to a better understanding of the development of HR analytics, to facilitate business and HR leaders in taking informed decisions on investing in the further development of the HR analytics discipline. Such investments may lead to an enhanced HR analytics capability within organizations, and cultivate the fact-based and data-driven culture that many organizations and leaders try to pursue.