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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 study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.

The aim of this action research was to explore, from a workforce and a patient/carer perspective, the skills and the capacity required to deliver integrated care and to inform future workforce development and planning in a new integrated care system in England.

Semi-structured interviews and focus groups with primary, community, acute care, social care and voluntary care, frontline and managerial staff and with patients and carers receiving these services were undertaken. Data were explored using framework analysis.

Analysis revealed three overarching themes: achieving teamwork and integration, managing demands on capacity and capability and delivering holistic and user-centred care. An organisational development (OD) process was developed as part of the action research process to facilitate the large-scale workforce changes taking place.

This study did not consider workforce development and planning challenges for nursing and care staff in residential, nursing care homes or domiciliary services. This part of the workforce is integral to the care pathways for many patients, and in line with the current emerging national focus on this sector, these groups require further examination. Further, data explore service users' and carers' perspectives on workforce skills. It proved challenging to recruit patient and carer respondents for the research due to the nature of their illnesses.

Many of the required skills already existed within the workforce. The OD process facilitated collaborative learning to enhance skills; however, workforce planning across a whole system has challenges in relation to data gathering and management. Ensuring a focus on workforce development and planning is an important part of integrated care development.

This study has implications for social and voluntary sector organisations in respect of inter-agency working practices, as well as the identification of workforce development needs and potential for informing subsequent cross-sector workforce planning arrangements and communication.

This paper helps to identify the issues and benefits of implementing person-centred, integrated teamworking and the implications for workforce planning and OD approaches.

Despite the growth and adoption of human resource (HR) analytics, it remains unknown whether HR analytics can impact organizational performance. As such, this study aims to address this important issue by understanding why, how and when HR analytics leads to increased organizational performance and uncover the mechanisms through which this increased performance occurs.

Using data collected from 155 Irish organizations, structural equation modeling was performed to test the chain mediation model linking HR technology, HR analytics, evidence-based management (EBM) and organizational performance.

The study's findings support the proposed chain model, suggesting that access to HR technology enables HR analytics which facilitates EBM, which in turn enhances organizational performance.

This research contributes significantly to the HR analytics and EBM literature. First, the study extends our understanding of why and how HR analytics leads to higher organizational performance. Second, the authors identify that access to HR technology enables and is an antecedent of HR analytics. Finally, empirical evidence is offered to support EBM and its impact on organizational performance.

Given that the workforce constitutes a principal resource of primary care, appraisal of models of care requires thorough investigation of the health workforce in all Models of Child Health Appraised (MOCHA) countries. This chapter explores this in terms of workforce composition, remuneration, qualifications and training in relation to the needs of children and young people. We have focused on two principal disciplines of primary care; medicine and nursing, with a specific focus on training and skills to care for children in primary care, particularly those with complex care needs, adolescents and vulnerable groups. We found significant disparities in workforce provision and remuneration, in training curricula and in resultant skills of physicians and nurses in European Union and European Economic Area Countries. A lack of overarching standards and recognition of some of the specific needs of children reflected in training of physicians and nurses may lead to suboptimal care for children. There are, of course, many other professions that also contribute to primary care services for children, some of which are discussed in Chapter 15, but we have not had resources to study these to the same detail.

The purpose of this study was to investigate the provincial-level systems and mechanisms to develop health volunteers to improve the health of the immigrant workforce in Thailand.

This qualitative study obtained data from document research, in-depth interviews with 58 people involved at policy and provincial levels working to develop health volunteers to improve the health of the immigrant workforce. Data were collected from May–October 2017; then the content of the conceptual framework was analyzed, the research objectives were examined and summary and induction analysis interpreted data from documents, observations and interviews.

Thailand has four systems for developing health volunteers to improve the health of the immigrant workforce: recruitment, training and knowledge management, welfare and motivational and financial and other supportive resources. Development is driven through the mechanisms of the Provincial Public Health Office with Non Governmental Organizations (NGOs) and network partners. The health volunteer development exhibits two patterns: developing migrant workers to become migrant health volunteers and developing village health volunteers to perform health care for the immigrant workforce. All development patterns mainly rely upon the regular operating budget, which is often inadequate. Frequently, some provinces make attempts to seek other funding sources. In fact, health volunteer development is subjected to local authorities of the four provinces whose systems and mechanisms of development differ from one another.

The findings from this study could help develop health volunteers to significantly improve the health of the immigrant workforce in the Thai health service system.

Postdocs make up a significant portion of the biomedical workforce. However, data about the postdoctoral position are generally scarce, and no systematic study of the landscape of individual postdoc salaries in the USA has previously been carried out. The purpose of this study was to assess actual salaries for postdocs using data gathered from US public institutions; determine how these salaries may vary with postdoc title, institutional funding and geographic region; and reflect on which institutional and federal policy measures may have the greatest impact on salaries nationally.

Freedom of Information Act Requests were submitted to US public universities or university systems containing campuses with at least 300 science, engineering and health postdocs, according to the 2015 National Science Foundation’s Survey of Graduate Students and Postdoctorates in Science and Engineering. Salaries and job titles of postdocs as of December 1, 2016, were requested.

Salaries and job titles for nearly 14,000 postdocs at 52 US institutions around December 1, 2016, were received. Individual postdoc names were also received for approximately 7,000 postdocs, and departmental affiliations were received for 4,000 postdocs. This exploratory study shows evidence of a postdoc gender pay gap, a significant influence of job title on postdoc salary and a complex relationship between salaries and the level of institutional National Institutes of Health/NSF funding.

These results provide insights into the ability of institutions to collate and report out annualized salary data on their postdocs, highlighting difficulties faced in tracking and reporting data on this population by institutional administration. Ultimately, these types of efforts, aimed at increasing transparency regarding the postdoctoral position, may lead to improved support for postdocs at all US institutions and allow greater agency for postdocs making decisions based on financial concerns.

The 30 MOCHA (Models of Child Health Appraised) countries are diverse socially, culturally and economically, and differences exist in their healthcare systems and in the scope and role of primary care. An economic analysis was undertaken that sought to explain differences in child health outcomes between countries. The conceptual framework was that of a production function for health, whereby health outputs (or outcomes) are assumed affected by several ‘inputs’. In the case of health, inputs include personal (genes, health behaviours) and socio-economic (income, living standards) factors and the structure, organisation and workforce of the healthcare system. Random effects regression modelling was used, based on countries as the unit of analysis, with data from 2004 to 2016 from international sources and published categorisations of healthcare system. The chapter describes the data deficiencies and measurement conundrums faced, and how these were addressed. In the absence of consistent indicators of child health outcomes across countries, five mortality measures were used: neonatal, infant, under five years, diabetes (0–19 years) and epilepsy (0–19 years). Factors found associated with reductions in mortality were as follows: gross domestic product per capita growth (neonatal, infant, under five years), higher density of paediatricians (neonatal, infant, under five years), less out-of-pocket expenditure (neonatal, diabetes 0–19), state-based service provision (epilepsy 0–19) and lower proportions of children in the population, a proxy for family size (all outcomes). Findings should be interpreted with caution due to the ecological nature of the analysis and the limitations presented by the data and measures employed.

The purpose of the paper is to explore the meaning of Human Resources (HR) analytics and introduce the HR analytics cycle as a proactive and systematic process for ethically gathering, analyzing, communicating and using evidence-based HR research and analytical insights to help organizations achieve their strategic objectives.

Conceptual review of the current state and meaning of HR analytics. Using the HR analytics cycle as a framework, the authors describe a seven-step process for building evidence-based and ethical HR analytics capabilities.

HR analytics is a nascent discipline and there are a multitude of monikers and competing definitions. With few exceptions, these definitions lack emphasis on evidence-based practice (i.e. the use of scientific research findings in adopting HR practices), ethical practice (i.e. ethically gathering and using HR data and insights) and the role of broader HR research and experimentation. More importantly, there are no practical models or frameworks available to help guide HR leaders and practitioners in doing HR analytics work.

The HR analytics cycle encompasses a broader range of HR analytics practices and data sources including HR research and experimentation in the context of social, behavioral and organizational science.

This paper introduces the HR analytics cycle as a practical seven-step approach for making HR analytics work in organizations.

This research analyzed the existing academic and grey literature concerning the technologies and practices of people analytics (PA), to understand how ethical considerations are being discussed by researchers, industry experts and practitioners, and to identify gaps, priorities and recommendations for ethical practice.

An iterative “scoping review” method was used to capture and synthesize relevant academic and grey literature. This is suited to emerging areas of innovation where formal research lags behind evidence from professional or technical sources.

Although the grey literature contains a growing stream of publications aimed at helping PA practitioners to “be ethical,” overall, research on ethical issues in PA is still at an early stage. Optimistic and technocentric perspectives dominate the PA discourse, although key themes seen in the wider literature on digital/data ethics are also evident. Risks and recommendations for PA projects concerned transparency and diverse stakeholder inclusion, respecting privacy rights, fair and proportionate use of data, fostering a systemic culture of ethical practice, delivering benefits for employees, including ethical outcomes in business models, ensuring legal compliance and using ethical charters.

This research adds to current debates over the future of work and employment in a digitized, algorithm-driven society.

The research provides an accessible summary of the risks, opportunities, trade-offs and regulatory issues for PA, as well as a framework for integrating ethical strategies and practices.

By using a scoping methodology to surface and analyze diverse literatures, this study fills a gap in existing knowledge on ethical aspects of PA. The findings can inform future academic research, organizations using or considering PA products, professional associations developing relevant guidelines and policymakers adapting regulations. It is also timely, given the increase in digital monitoring of employees working from home during the Covid-19 pandemic.