Data Mining for Human Resource Information Systems

Data Mining ◽  
2011 ◽  
pp. 366-381 ◽  
Author(s):  
Lori K. Long ◽  
Mavin D. Troutt
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Systems ◽  
Human Resource ◽  
Data Warehousing ◽  
Organizational Decision Making ◽  
Resource Information ◽  
Potential Applications ◽  
Statistical Studies ◽  
Hr Function

This chapter focuses on the potential contributions that Data Mining (DM) could make within the Human Resource (HR) function in organizations. We first provide a basic introduction to DM techniques and processes and a survey of the literature on the steps involved in successfully mining this information. We also discuss the importance of data warehousing and datamart considerations. An examination of the contrast between DM and more routine statistical studies is given, and the value of HR information to support a firm’s competitive position and organizational decision-making is considered. Examples of potential applications are outlined in terms of data that is ordinarily captured in HR information systems.

Benchmarking Human Resource Information Systems

2009 ◽  
pp. 92-101 ◽  
Author(s):  
Herwig Ostermann ◽  
Bettina Staudinger ◽  
Roland Staudinger
Keyword(s):  
Information Systems ◽  
Human Resource ◽  
Business Performance ◽  
General Term ◽  
Business Information Systems ◽  
Business Context ◽  
Resource Information ◽  
Efficiency And Effectiveness ◽  
Hr Function ◽  
Operations Systems

In its most general term a benchmark represents a point of reference from which measurements can be conducted. Translated into a business context, benchmarks may thus serve as “measurements to gauge the performance of a function, operation, or business relative to others” (Bogan & English, 1994, p. 4). Based on that understanding of performance measurement, the essential business concept of the activity of benchmarking can be defined as the continuous and systematic process of improving strategies, functions, operations, systems, products or services by measuring, comparing and analyzing relevant benchmarks in order to produce superior business performance and outperform competitors (Böhnert, 1999; Ellis & Moore, 2006; Guo, Abir, Thengxiang, & Gelfin, 2007; Haverty & Gorton, 2006; Purdum, 2007; Schmitz, 1998; Spendolini, 1992). As human resource information systems (HRIS) are generally regarded as a key facilitator in promoting and securing the efficiency and effectiveness of the human resource (HR) function and are therefore also thought to represent a performance-critical key element of contemporary human resource management (HRM) (Cummings & Marcus, 1994; Hendrickson, 2003; James, 1997), benchmarking activities show the potential to generate valuable information for the management of HRIS. This information derived from the process of comparison to other business information systems or functions may support the buying decision for a new HRIS and represent an essential stimulus for implementation, design, or maintenance activities in order to ensure superior HR and overall business performance.

scholarly journals Information Communication Technology and Human Resource Management in Modern Organisations: A Concept for 21st Century

2015 ◽  
Vol 2 (2) ◽  
pp. 102-107
Author(s):  
Paul Chepkuto ◽  
Stanley Kipsang ◽  
Mwangi Kungu
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Data Entry ◽  
Resource Planning ◽  
Resource Information ◽  
Hr Managers

Human resource information system is a database system that has been developed to provide the necessary assistance to HR in terms of decision making and reporting of information. It is basically one of the key elements that is critical in the overall management information system (MIS) of an organization. It is an IT-enabled HR service available to the HR managers for data analysis and decision making. HRIS provides the necessary support to the HR managers in making a quality decision by ensuring that there is adequate and timely relevant information that is available. The scope is so wide that it can provide information about every aspect of an employee, starting with his recruitment and ending with his retirement. As such, HRIS facilitates the use of computer technology to streamline HR operations, cut costs and eventually enhance the effectiveness of human resource management. As technology evolves, so does its impact on strategic human resource planning. Human resource information systems are electronic systems that compile information in databases to be easily accessed and analyzed. Some information systems allow automation of processes, such as payroll tax calculations, while others streamline processes by minimizing the need for manual data entry and paper records, thus increasing accuracy and efficiencyDOI: http://dx.doi.org/10.3126/ijssm.v2i2.122898          Int. J. Soc. Sci. Manage. Vol-2, issue-2: 102-107 

The use of human resource information systems in two retail organisations in the Western Cape, South Africa

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Emmanuel Udekwe ◽  
Andre C. De la Harpe
Keyword(s):  
South Africa ◽  
Information Systems ◽  
Human Resources ◽  
Human Resource ◽  
The Body ◽  
Retail Industry ◽  
Successful Implementation ◽  
Western Cape ◽  
Report Generation ◽  
Resource Information

Orientation: The retail industry is the largest contributor to employment and the gross domestic product (GDP) in the Western Cape, South Africa. The management of human resources in this very competitive industry is a high priority for all retailers. The successful implementation, maintenance and use of human resource information systems (HRISs) are an integral part of many retailers.Research purpose: Human resource information systems are difficult to implement and maintain, and as a result, organisations cannot effectively utilise these systems to their benefit. The purpose of this paper is to explore the factors affecting the implementation, maintenance and use of HRISs in two retail organisations in the Western Cape.Motivation of study: Many retailers find it difficult to apply and utilise HRISs to their benefit and to the systems’ full potential. This study explores the challenges retailers are facing when implementing, maintaining and using HRISs.Research design, approach and method: Multiple case studies were used to conduct the research. Data were collected through a semi-structured questionnaire using interviews. Twenty-one interviews were conducted in the two retail companies to gain an understanding of the use of HRISs within these organisations. The data were analysed using a thematic method of analysis. The units of analysis were the Human Resources and the Information Technology departments of both companies. The units of observation were (21) purposively selected employees in the two mentioned departments of both retail organisations.Main findings: This research shows an under-utilisation of the HRIS in both companies as a result of poor data quality, lack of adequate training and the high cost of implementing and maintaining the system. There is a gap in terms of data analytics and report generation. This gap leads to the under-utilisation of the HRISs preventing the retailers to optimise the benefits of the HRIS.Practical and managerial implications: For organisations to reap benefits from HRISs, a change management strategy and a rigorous training programme are needed that will focus on the implemented maintenance and improved usage of these systems.Contribution: The contribution of the study includes proposed guidelines for the effective and efficient use of HRISs. The study further contributes to the body of knowledge in shedding light on the implementation, maintenance and use of HRISs in the retail industry in the Western Cape, South Africa.

Data Science

2018 ◽  
pp. 141-151
Author(s):  
Sabitha Rajagopal
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Research And Development ◽  
Real Time ◽  
Data Science ◽  
Data Warehousing ◽  
Holistic Approach ◽  
Digital Data ◽  
Data Application ◽  
Development Analysis

Data Science employs techniques and theories to create data products. Data product is merely a data application that acquires its value from the data itself, and creates more data as a result; it's not just an application with data. Data science involves the methodical study of digital data employing techniques of observation, development, analysis, testing and validation. It tackles the real time challenges by adopting a holistic approach. It ‘creates' knowledge about large and dynamic bases, ‘develops' methods to manage data and ‘optimizes' processes to improve its performance. The goal includes vital investigation and innovation in conjunction with functional exploration intended to notify decision-making for individuals, businesses, and governments. This paper discusses the emergence of Data Science and its subsequent developments in the fields of Data Mining and Data Warehousing. The research focuses on need, challenges, impact, ethics and progress of Data Science. Finally the insights of the subsequent phases in research and development of Data Science is provided.

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