People Analytics (PA) has been growing in popularity in the circles of Human Resource (HR) innovators and scholars (Isson and Harriott, 2016; Angrave et al., 2016) in the last 15 years (Tursunbayeva et al., 2018). PA includes the set of skills, technologies, and information sources that make it possible to capitalize, manage and analyze related data, with the aim of providing greater decision-making and strategic support in terms of acquisition, management, development, and retention of people (Madini and Flecchia, 2020). Organizational strategists (Van den Heuvel and Bondarouk, 2017), HR innovators, and PA vendors (Tursunbayeva et al., 2018) envision a bright future for PA. However, organizations are still struggling with introducing it (Peeters et al., 2020). Most of them seem to still lack a clear vision on what PA is and the value of PA for their organizations. This is particularly true for some specific contexts. For example, PA in the United States or the Netherlands is already tested and studied results-oriented and objectively “data-driven” approach (Tursunbayeva et al., 2018), while in others it still represents only a promising and cutting-edge innovation (Pejić Bach et al., 2020). This seems to be exactly what is happening in Italy. Recent research observed that there is a growing attention to big data and HRM in Italy while context-specific empirical relevant research is virtually non-existent (Tursunbayeva et al., 2018; Zhang et al., 2021). Though these are imperative to furthering an understanding of the impacts of PA in diverse specific settings (Ridge-Newman, 2015). Thus, in our research we aim to conduct a context specific study to explore PA in Italy. Specifically, we set to explore relevant potential PA application scenarios to HRM, its values, and structures for approaching PA developments. Considering such multifaceted aim of our research, we draw on a multi-dimensional framework developed by the Center for Advanced HR Studies at Cornel University (CAHRS, 2010), the applicability of which was recently verified by Van Den Heuvel and Bondarouk (2017) in the Netherlands. This framework consists of four central topics: 1. Application of PA (e.g., organizational goals or themes); 2. Value of PA; 3. Structure of PA (e.g., positioning within organizations and relevant actors); and 4. System support (support from relevant technology). To achieve our aim, we also draw on a unique data source: Google Alerts (GA) that was collected for over four years.
People Analytics applications, value, structure, and system support: An explorative study from Italy”
Di Lauro
;Antonelli Gilda;
2022-01-01
Abstract
People Analytics (PA) has been growing in popularity in the circles of Human Resource (HR) innovators and scholars (Isson and Harriott, 2016; Angrave et al., 2016) in the last 15 years (Tursunbayeva et al., 2018). PA includes the set of skills, technologies, and information sources that make it possible to capitalize, manage and analyze related data, with the aim of providing greater decision-making and strategic support in terms of acquisition, management, development, and retention of people (Madini and Flecchia, 2020). Organizational strategists (Van den Heuvel and Bondarouk, 2017), HR innovators, and PA vendors (Tursunbayeva et al., 2018) envision a bright future for PA. However, organizations are still struggling with introducing it (Peeters et al., 2020). Most of them seem to still lack a clear vision on what PA is and the value of PA for their organizations. This is particularly true for some specific contexts. For example, PA in the United States or the Netherlands is already tested and studied results-oriented and objectively “data-driven” approach (Tursunbayeva et al., 2018), while in others it still represents only a promising and cutting-edge innovation (Pejić Bach et al., 2020). This seems to be exactly what is happening in Italy. Recent research observed that there is a growing attention to big data and HRM in Italy while context-specific empirical relevant research is virtually non-existent (Tursunbayeva et al., 2018; Zhang et al., 2021). Though these are imperative to furthering an understanding of the impacts of PA in diverse specific settings (Ridge-Newman, 2015). Thus, in our research we aim to conduct a context specific study to explore PA in Italy. Specifically, we set to explore relevant potential PA application scenarios to HRM, its values, and structures for approaching PA developments. Considering such multifaceted aim of our research, we draw on a multi-dimensional framework developed by the Center for Advanced HR Studies at Cornel University (CAHRS, 2010), the applicability of which was recently verified by Van Den Heuvel and Bondarouk (2017) in the Netherlands. This framework consists of four central topics: 1. Application of PA (e.g., organizational goals or themes); 2. Value of PA; 3. Structure of PA (e.g., positioning within organizations and relevant actors); and 4. System support (support from relevant technology). To achieve our aim, we also draw on a unique data source: Google Alerts (GA) that was collected for over four years.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
