A Review of Digital Technologies in HRM

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Richa Priya, et. al.


Advancement in technology has led to the present age being described as the “digital age”. Human Resource (HR) is a department which is typically managed in person rather than an automated process. Digital HR can be deified as the administrative support of the HR functions in an organization by using internet technology (Voermans & M.van, 2007). Broderick & Boudreau,(1992) defined Human resource information system as the amalgamation data-centric computer software and hardware that compile, document, store, manage and deliver the data that can be used for the betterment of human resources.

The domain of analytics uses various quantitative methods  in-order to organize, examine and abridge  a huge amount of data (Mortensonet al., 2015). Understanding a huge amount of data owned by organizations is of deep interest as it empower the organization for informed decision making (George & Kamalanabhan, 2016). The various technologies currently being used in HR domain focuses to identify data, capture data, modelling and predicting of data, in order to upsurge productivity of the organization.

The present review intends to study the recent trends in technologies used by organizations in the area HRM. The review is based on peer-reviewed articles from databases including EBSCO, Emerald and Sage publications. References from organizational reports have also been included, since academic articles are sparse in the topic of study which includes technologies in HRM and cloud in HRM. 

Using digital technologies in HR will lead to improvement in organizational performance through talent-related decisions, forecast workforce requirement, optimizing talent through development and planning. It will also enable HR to help an organization to achieve corporate goals through informed decision making. Additionally, it enables managing employees through recruitment, training, employee satisfaction, productivity, assigning of tasks as per the qualification. It also helps in identifying the reason for attrition and identifying high-value employees for leaving.

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