(How) do advanced data and analyses enable HR analytics success? A neo-configurational analysis

Abstract

PurposeEnabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality.Design/methodology/approachTheoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success.FindingsThe authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success.Research limitations/implicationsMajor limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task.Originality/valueThe authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.

Integrative Literature Review on People Analytics and Implications From the Perspective of Human Resource Development

“…Many researchers argue that analytic competence is the core condition for successful analytics and that advanced analyses lead to better decision-making quality in the HR field (Kryscynski et al, 2018; McIver et al, 2018; Minbaeva, 2018; Strohmeier et al, 2022). However, this is also the most frequently mentioned reason the practice of people analytics has not been widely adopted.…”

“…As the saying “garbage in, garbage out” illustrates, low-quality data such as inconsequential log data or disjointed and fragmented data offer limited value in generating insights, regardless of the size of the data. Strohmeier et al (2022) found that data veracity is necessary for advanced decision-making support in the HR field, whereas data volume, velocity, and variety are unnecessary. Data accessibility is also important because gaining access to data from other functions is not easy due to the tendency to form silos within organizations (Angrave et al, 2016; Giermindl et al, 2022; Marler & Boudreau, 2017).…”

“…Although many studies have emphasized the use of big data, people analytics within the HRD field tends to use small data rather than big data. Big data are characterized by substantial volume, rapid velocity, and wide variety; however, few organizations possess data of such magnitude and diversity (Andersen, 2017; Strohmeier et al, 2022). The application of big data in people analytics may eventually become widespread.…”

“…However, given the currently limited adoption of people analytics, prioritizing the acquisition of high-quality data is crucial. This is because sophisticated analytics are derived from superior data, which in turn enhances the quality of decision-making processes (Garcia-Arroyo & Osca, 2021; McIver et al, 2018; Strohmeier et al, 2022).…”

Intelligent scheduling of enterprise human resource group based on big data

“…Employees will be able to play independent roles in the work, but when they change to another work, they will have problems in team integration, incompetence problems. The effectiveness of human resources in many business project management is not low, which is important in the inability to complete the time and work of the staff appointment time [2]. Therefore, it is the most important problem faced by the human resource scheduling in the business multi-tasking management to send the right person to the specific job in time and successfully good work.…”