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Introduction: The rapid growth of high technology has urged many organisations to dynamically look for innovative ways, ideas, testing, and ingenious solution in improving their current product, process, system, and technology. For contemporary business, artificial intelligence (AI)-based people analytics is an instrument currently employed to develop a better prosperous future.

Purpose: The study aims to investigate the usage of AI in human resource management (HRM) practices. It also examines the benefits and challenges of using AI in implementing people analytics in organisations.

Methodology: This chapter contains a systemic review of articles and papers on analytics. The presented qualitative study did a literature review based on the articles published in the last five years and extracted from the Scopus database.

Findings: This chapter indicated that AI-based people analytics is on the verge of changing various aspects of HRM practices better to furnish it for a vibrant, ever-changing workplace. It concludes different usage of AI in people analytics for better managing human resources (HR) at the workplace. Also explored the benefits and challenges of implementing AI in the people analytics domain.

Implications: This chapter will help understand ongoing practices of AI-enabled process benefits and challenges. This insight will help develop a better AI-enabled function for a better decision-making system. The future scope of the study is how to overcome the challenges.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

The purpose of this paper is to explore the key ingredients that people analytics teams require to contribute to organizational performance. As the information that is currently available is fragmented, it is difficult for organizations to understand what it takes to execute people analytics successfully.

To identify the key ingredients, a narrative literature review was conducted using both traditional people analytics and broader business intelligence literature. The findings were summarized in the People Analytics Effectiveness Wheel.

The People Analytics Effectiveness Wheel identifies four categories of ingredients that a people analytics team requires to be effective. These are enabling resources, products, stakeholder management and governance structure. Under each category, multiple sub-themes are discussed, such as data and infrastructure; senior management support; and knowledge, skills, abilities and other characteristics (KSAOs) (enablers).

Many organizations are still trying to set up their people analytics teams, and many others are struggling to improve decision-making by using people analytics. For these companies, this paper provides a comprehensive overview of the current literature and describes what it takes to contribute to organizational performance using people analytics.

This paper is designed to provide organizations and researchers with a comprehensive understanding of what it takes to execute people analytics successfully. By using the People Analytics Effectiveness Wheel as a guideline, scholars are now better equipped to research the processes that are required for the ingredients to be truly effective.

Given its relative novelty, the field of people analytics remains rather obscure in terms of its success criteria. The purpose of this paper is to unveil some of the hidden secrets of people analytics.

The paper reviews the common characteristics of those companies who have already been successful with it in their operations to date.

These 16 best practices cover the role of the CHRO and the employees as well as HR’s general position within a company.

While not all of the 16 best practices need to be in place, incorporating a few of them will provide significant benefit to businesses and employees.

While several of the best practices laid out in this paper directly impact personnel policies, they also all empower HR managers to be a force for good through optimised people analytics.

The paper presents a hitherto scattered set of best practices as forerunners in the novel field of people analytics.

This paper aims to contribute to the literature on human resources (HR) digitalization, specifically on HR analytics, disentangling the concept of analytics applied to HR and explaining the factors that hinder companies from moving to analytics. Therefore, the central research questions addressed in this study are: what does HR analytics encompass? What impedes the adoption of analytics in HR within organizations?

The authors performed a comprehensive literature review on analytics as applied in HR. The authors relied on two of the major multidisciplinary publication databases (i.e. Scopus and WoS). A total of 64 manuscripts from 2010 to 2019 were content analyzed.

The results reveal that there is an ongoing confusion on HR analytics conceptualization. Yet, it seems that there is an emerging consensus on what HR analytics encompasses. The authors have identified 14 different barriers for HR analytics adoption grouped into four categories, namely, data and models, software and technology, people and management. Grounding on them the authors propose a set of 14 key factors to help to successfully adopt HR Analytics in companies.

This paper brings clarity over the conceptualization of HR analytics by offering a comprehensive definition. Additionally, it facilitates business and HR leaders in making informed decisions on adopting and implementing HR analytics. Moreover, it assists HR researchers in positioning their paper more explicitly in current debates and encouraging them to develop some future avenues of research departing from some questions posed.

This paper aims to highlight the importance of analytics and its advantages in the human resource domain using the example of Google, which has extensively used analytics to improve various aspects of people management.

The paper discusses human resource analytics and illustrates how it has been successfully implemented by Google to enable better decision-making.

Implementation of analytics in the area of human resources can make people-related decision-making objective, transparent and data-driven and, thus, make the function “quantitative” in nature.

Although analytics has been widely implemented in functions such as finance and marketing, it is yet to gain a strong foothold in the domain of human resources. This paper discusses how Google, a leading organization in the field of technology, has been able to take impactful people-related decisions with the help of analytics.

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.

Human capital analytics (HCA) is integral to all other human capital processes. With a mature analytics practice, leaders can make better decisions more quickly and with greater confidences. This paper aims to describe results of research that shows how organizations in Middle East countries are investing in HCA. Specifically, it describes as follows: the extent to which they are investing; types of projects in which they are investing; and factors critical to making analytics work.

While research may include respondents from organizations in developing countries, only recently have efforts been made to monitor progress specifically in these countries. This paper attempts to describe the most recent findings of such research, paying specific attention to the use of HCA in the Middle East.

Organizations in the Middle East embrace HCA. While still in its infancy, analytics is poised to be a strategic driver that will lead to improved organizational performance.

Whether investing in leadership development, talent acquisition, employee engagement or talent development, analytics plays a central role in informing decisions about people investments. To make HCA work, Middle East organizations plan to continue building capability through training; embracing technology and striving to link data across programs and platforms; and integrating systems, processes and people with other functions, particularly finance. In the end, organizations will seamlessly integrate HCA into all processes to drive organization performance.

Human resource analytics (HRA) has developed as a new business trend and challenge, stressing the strategic relevance of human resource management (HRM) to senior management executives. HRA is a process that uses statistical techniques, to link HR practices to organizational performance. The purpose of this study is to carry out recent development in HRA, bibliometric analysis and content analysis to present a comprehensive account of HRA to fill the gap in the evolution and status of its research.

The study is based on the recent advances in HRA in terms of it evolution and advancement by analyzing and drawing conclusions 480 articles retrieved from the Web of Science (WoS) database from 2003 to March 2022. The methodology is divided into four steps: data collection, analysis, visualization and interpretation. The study performed a rigorous bibliometric assessment of HRA using the bibliometric R-package and VOS viewer.

The findings based on the literature survey, and bibliometric analysis, reveal the path-breaking articles, the prominent authors, most contributing institutions and countries that have contributed to the HRA scholarship. The results show that the number of publications has significantly increased from 2015 onwards, reaching a maximum of 101 journals in 2021. The USA, China, India, Canada and the United Kingdom were the most productive countries in terms of the total number of publications. Human Resource Management Journal, Human Resource Management, International Journal of Manpower, and Journal of Organizational Effectiveness-People and Performance are the top four academic outlets in the field of HRA. Additionally, the study identifies four clusters of HRA research and the knowledge gaps in HRA scholarship.

The present study is based on the articles retrieved from the WoS. The study underpins HRA research to understand the trends and presents a structured account. However, the study is not free from limitations. It is recommended that future research could be undertaken by combining WoS and Scopus databases to have a more detailed and comprehensive view. This study indicates that the field is still in its infancy stage. Hence, there is a need for more arduous research on the topic to help develop a better understanding of this field.

The findings of knowledge clusters will drive future researchers to augment the field. The evolution of the four clusters and their subsequent development will fill the gaps in the literature. This study enriches the HRA literature and the findings of this study may assist academicians, researchers and managers in furthering their research in the identified research clusters

The purpose of this paper is to examine the evolution of the concept of human resource analytics (HRA) and propose an operational framework demonstrating the sources generating data for HRA, as well as the impact of HRA on multiple levels in the organization.

A review of literature was conducted to present the existing body of knowledge and build upon for the development of an operational framework for successful implementation of HRA as a human resources (HR) process.

Building upon the existing literature, this paper presents an operational HRA framework, positioning HRA as an analytical process through integrating advanced statistical methodology. HRA presents a tool to obtain evidence-based analytical results for improving people-related performance, operational effectiveness, and ultimately the impact of the business strategy. By using HR big data, HRA impacts multiple organizational levels, from individual employees to HR functions and the organizational strategy.

While research on data analytics has recently flourished across various management fields, this has not been the case for the broader field of HR. This is especially a growing concern as the lack of understanding of the basics and fundamentals of people analytics in the field of HR may delay the effective implementation and operationalization of HRA and present additional barriers impacting on-going HR activities, as well as HR’s role as a strategic business partner. HR practice may greatly benefit from gaining an understanding of HRA and the multi-levels of impact it may have on the organization.

This paper explores various concepts related to HRA by examining terms such as “HR metrics” vs “HR” and “HR big data” vs “big data.” Furthermore, the comprehensive HRA operational framework presented in this paper provides HR professionals and researchers with a better understanding of HRA in the age of data analytics and artificial intelligence.