HR metrics and workforce analytics: it is a journey, not a destination

Abstract

Purpose The main objective in adopting the use of metrics and analytics is to use the expertise of HR professionals in human resource management regarding their understanding of the best way to recruit, select, train, design, motivate, develop, evaluate, and retain employees at an organization to help achieve its goals more effectively. Design/methodology/approach The first and foremost step to generate metrics and analytics strategies in an organization is identification of existing problems faced by them. Owing to the changing environment and global requirement, the labor measurement also changes. The main focus is on the problems faced by the organization and human resources in the working environment. Findings Through the use of human resources measures and workforce analytics, decision-makers will gain the ability to more effectively manage and improve human resources programs and processes. This in turn improves the effectiveness of the workforce and organizational performance. Practical implications Metrics and analytics is a better problem-solving measure in organizations, because in any situations, decisions are made after analyzing the tactical choices. Social implications The development of effective human resource metrics and workforce analytics is likely to be seen in the future as a very important source of competitive advantage. Originality/value The use of human resource metrics and workforce analytics improves organizational effectiveness and strategic decision-making of managers that positively impact the organization’s performance as a whole.

Measure what matters: descriptive and predictive metrics of HRM-pathway toward organizational performance

“…The HR metrics provide – (1) Efficiency measurements – quantification of waste in investments, (2) Effectiveness – delivery of program outcomes as per plan, (3) Impact – Strategic effect of the outcomes at firm level. HR metrics are important to measure HR outcomes and also to comprehend the success of the HR department (Durai et al , 2019; Fink and Sturman, 2017; Marler and Boudreau, 2017; Sivathanu and Pillai, 2019a, b) The usage of the present data of descriptive metrics emerging from HR practices can help in developing predictive analytical models (Fitz-enz, 2010; Edwards and Edwards, 2019).…”

21st century HR: a competency model for the emerging role of HR Analysts

“…In a similar vein, van der Togt and Rasmussen (2017) have argued that HR Analysts need to have a strong business focus, a deep understanding of behavioral science, excellent data and statistical skills and the ability to tell a data story. Additional skills highlighted in the extant HR analytics literature as essential for HR Analysts include problem-solving capabilities (Durai et al , 2019), analytical and IT skills (Mishra et al , 2016), building and testing conceptual and predictive models (Mishra et al , 2016; Minbaeva, 2018), data mining (Liu et al , 2020) and a familiarity with software packages from broader data science, including R and Python (McIver et al , 2018; Tonidandel et al , 2018; Falletta and Combs, 2020; Pessach et al , 2020).…”

Examining the dark side of human resource analytics: an empirical investigation using the privacy calculus approach

“…HR analytics contains six steps. These are identifying the most effective outcomes, creating a cross-functional plan for data, implementing adequate measures for assessing critical outcomes, executing the plan, modifying the plan in the postimplementation period and making other necessary rectifications (Mondore et al , 2011; Durai et al , 2019). HR analytics helps improve organizations’ decision-making in HR-related issues (Levenson, 2011; López-Arceiz et al , 2019).…”

“…HR analytics helps managers analyze data that is essential for decision-making. HR analytics is perceived to be an integral part of decision-making (Durai et al, 2019). An organization may…”