An Output Model for Human Resource Development Analytics

Abstract

Analytics helps organizations excel. Many organizational leaders do not believe their organizations can benefit from analytics, in part because of the perceived complexity of analytics outputs. Analytics outputs are the artifacts produced by analytics systems, including data, information, decisions, and changes in behaviors, to name a few examples. These outputs determine the value and roles analytics play in serving individuals and the organization. This article uses an integrative literature review of the information‐systems literature to develop an analytics system model and hierarchy of outputs. It examines general and human‐resource–development analytics definitions to assess the fit of the analytics outputs identified to the hierarchy of outputs from the analysis of the literature. It provides guidance for human‐resource development and performance improvement practitioners to identify the capabilities of analytics and the fit of these systems to their needs. It identifies research extensions based on the models presented here.

Exploring the phenomenon of HR analytics: a study of challenges, risks and impacts in 40 large companies

“…It involves converting data and information into insights that support HR decision making, leading to smarter action (e.g. Liberatore and Luo, 2010; Lunsford, 2019). If we recognize that a concern with measuring HR variables, such as employee absence and turnover rates, and understanding their drivers, has been a longstanding interest among HR practitioners and their predecessors (e.g.…”

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“…BDA’s primary function of decision-making tools relies on three levels of analytics: descriptive analytics, predictive analytics and prescriptive analytics (Lunsford, 2019). HRM applies descriptive analysis to decide based on past and current performances (Evans, 2015).…”

Інтелектуальний Метод Формування Людських Ресурсів На Короткостроковий Проект

“…У статті [22] досліджено загальні визначення й аналітичні параметри розвитку людських ресурсів, оцінку результатів аналітики, визначених до ієрархічного аналізу літератури. У роботі [23] експериментальні результати показують, що випадкова деревоподібна модель найкраще працює для дослідження в можливості просування персоналу по кар'єрних сходах.…”