Business Intelligence and Human Resource Management: Concept, Cases, and Practical Applications

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Foreword
Preface
Acknowledgements
Editors
Contributors
1 An Introduction to Business Intelligence
1.1 Introduction
1.2 Concept
1.3 Literature Review
1.4 Purpose and Significance of BI
1.4.1 Purpose
1.4.2 Significance
1.5 Features of BI
1.5.1 High-Level Features
1.5.1.1 Management of Metadata
1.5.1.2 Data Visualization
1.5.1.3 Analytics Dashboards
1.5.1.4 Mobile Support
1.5.1.5 Real-Time Data
1.5.2 Safety Features
1.5.2.1 Alternative Authentication Sources
1.5.2.2 Security at the Application Level
1.5.2.3 Row-Level Security
1.5.2.4 Activity Auditing
1.5.3 Essential Features
1.5.3.1 Ad Hoc Reports
1.5.3.2 Ranking Reports
1.5.3.3 Executive Dashboards
1.5.3.4 Pivot Tables
1.6 Importance of BI
1.6.1 Fast and Precise Reporting
1.6.2 Better Data Quality
1.6.3 Ascertain Market Trends
1.6.4 Enhanced Customer Satisfaction
1.6.5 Increased Functional Efficiency
1.6.6 Gain Business Insights
1.6.7 Competitive Analysis
1.6.8 Real-Time Data
1.6.9 Improved Visibility
1.6.10 Data-Driven Business Decision
1.6.11 Enhances Employee Satisfaction
1.7 BI Architecture
1.7.1 Architecture of BI
1.7.1.1 Data Sources
1.7.1.2 Data Warehouse/Data Mart
1.7.1.3 Data Exploration
1.7.1.4 Data Mining
1.7.1.5 Optimization
1.7.1.6 Decisions
1.8 BI Tools
1.8.1 Data Pine
1.8.2 SAP Business Intelligence
1.8.3 Yellowfin BI
1.8.4 Micro Strategy
1.8.5 SAS Business Intelligence
1.8.6 Zoho Analytics
1.8.7 Oracle BI
1.8.8 Looker
1.8.9 Microsoft Power BI
1.8.10 Clear Analytics
1.8.11 Domo
1.8.12 Tableau
1.8.13 IBM Cognoscenti Analytics
1.8.14 Microsoft Power BI
1.8.15 Sisense
1.8.16 Qlik Sense
1.9 Components of BI
1.9.1 Online Analytical Processing
1.9.2 Corporate Performance Management
1.9.3 Real-Time BI
1.9.4 Data Warehousing
1.9.5 Data Sources
1.9.6 Enterprise Resource Planning
1.9.7 Customer Relationship Management
1.9.8 E-Commerce Apps
1.10 BI Limitations and Challenges
1.10.1 Threat of Security Breach
1.10.2 High Prices
1.10.3 Difficulty in Examining Various Data Sources
1.10.4 Unwillingness to Adoption
1.10.5 Blending of Professional and Personal Information
1.10.6 Need for Multiple BI Applications
1.10.7 Complexity
1.11 Limitations with BI Dashboards
1.11.1 Different Conclusion from the Same Data
1.12 Pathway to BI Success
1.12.1 Senior Management Support
1.12.2 Effective Validation Process
1.12.3 Regular Monitoring and Adjustment of BI Use
1.12.4 Skilled or Qualified Staff
1.12.5 Development Environment
1.12.6 Proper Selection of Technology
1.13 Future of BI
1.13.1 Data Storytelling
1.13.2 Data Governance
1.13.3 Self-Service BI
1.13.4 Prescriptive Analysis
1.13.5 Collaborative BI
1.13.6 Natural Language Processing in BI
1.14 Conclusion
References
2 Business Intelligence: A Value-Increasing Strategy for the
Organization
2.1 Introduction
2.2 History of BI
2.3 BI and Its Components
2.3.1 Online Analytical Processing
2.3.2 Executive Information Systems
2.3.3 Data Warehouses
2.3.4 CPM or Advanced Analytics
2.3.5 Real-Time BI
2.3.6 Data Sources
2.4 BI Tools
2.4.1 Streaming Analytics
2.4.2 Prescriptive Analytics
2.4.3 Predictive Analytics
2.4.4 Descriptive Analytics
2.5 Role of BI in Organizational Growth
2.5.1 Improved Speed of Analysis and More
Understandable Dashboards
2.5.2 Reliable and Well-Managed Data
2.5.3 Increases Customers’ Satisfaction
2.5.4 Higher Level of Employee Satisfaction
2.5.5 Enhances Organizational Effectiveness
2.5.6 Decisions Based on Data
2.5.7 Competitive Advantage
2.5.8 Enhance Market Intelligence
2.5.9 A Successful Business Model
2.5.10 Composed and Effective Sales Strategies
2.6 Integration of BI and Business Process Management
2.7 Conclusion
References
3 Transforming HR through BI and Information Technology
3.1 Introduction
3.2 Understanding BI
3.3 Forces Influencing BI
3.4 Implications for Human Resource Architecture
3.4.1 Implications for Human Resource Practices
3.4.2 Implications for HR Professionals
3.4.2.1 Strategic Skills
3.4.2.2 Business Skills
3.4.2.3 Problem-Solving Skills
3.4.2.4 Research Skills
3.4.2.5 Statistical Skills
3.4.2.6 HR Functionaries’ Transformational Change
3.4.2.7 Organization of HR
3.4.2.8 Integration of Plans
3.4.2.9 HR and Line Partnership
3.4.2.10 Benchmarking
3.5 HR and IT
3.5.1 Factors Affecting HR and IT Fit
3.6 Conclusion
References
4 The Role of Business Intelligence in Organizational Sustainability in the Era of IR 4.0
4.1 Introduction
4.2 Overview of BI: Evolution and Growth
4.2.1 BI, Business Analytics and Artificial Intelligence: All
About Data and Beyond
4.2.2 Application of BI: The Paradigm Shift and Process Flow
4.2.3 Common Myths Relevant to BI
4.3 Role and Significance of BI in IR 4.0 Era
4.3.1 Industrial Revolution 4.0
4.3.2 Benefits of BI in IR 4.0
4.4 Scope and Application of BI in HR Environments
4.4.1 Application of BI into HR Environments: The BI Infrastructure
4.4.2 Operational Set of BI in Organizations for Strategic Decision-Making
4.5 Challenges and Constraints in BI Application into Rigid Work Culture
4.6 Model to Apply BI in Organizations to Create Sustainable Organizations with the Proposed Methodology and Process Flow
4.7 Discovering New Informational Flow and the Way Forward
4.8 Future Scope of BI
4.9 Conclusion
References
5 Business Intelligence and Branding
5.1 Introduction
5.1.1 Definitions of AI
5.2 AI Objectives
5.2.1 Engineering Aims
5.2.2 Psychological Aims
5.2.3 General Philosophical Aims
5.3 Subsets of AI
5.4 Machine Learning
5.4.1 Categories of ML Algorithms
5.4.2 Supervised Learning
5.4.3 Unsupervised Learning
5.4.4 Reinforcement Learning
5.4.5 Deep Learning
5.5 Natural Language Processing
5.6 Concept of BI
5.7 BI Applications and Tools
5.7.1 Decision Support System
5.8 Users of BI: Following Are the Users of BI
5.9 How BI Systems Are Implemented
5.10 Benefits of BI
5.11 Role of BI in Marketing
5.12 New Marketing Strategies and Digital Marketing
5.12.1 Content Marketing
5.12.2 Mobile Marketing
5.12.3 Integrated Digital Marketing
5.12.4 Continuous Marketing
5.12.5 Personalized Marketing
5.12.6 Visual Marketing
5.12.7 Search Engine Optimization
5.13 BI and Consumer Analytics
5.14 Advantages in Adapting AI-Enabled BI Systems
5.15 AI, Technology Mapping and Branding
5.16 AI, BI and Brand Strategy
5.16.1 AI-Generated Content
5.16.2 Smart Content Cure
5.16.3 Voice Search
5.16.4 Programmatic Media Buying
5.16.5 Propensity Modelling
5.16.6 Predictive Analytics
5.16.7 Lead Scoring
5.16.8 Ad Targeting
5.16.9 Dynamic Pricing
5.16.10 Web and App Personalization
5.16.11 Chatbots
5.16.12 Re-targeting
5.16.13 Predictive Customer Service
5.16.14 Marketing Automation
5.16.15 Dynamic Emails
5.17 BI and Branding Short Case Studies
5.18 Risks and Limitations in AI-Enabled BI in Marketing and Branding
5.19 BI System Disadvantages
5.20 Conclusion
References
6 Role of Business Intelligence and HR Planning in Modern Industrialization
6.1 Business Intelligence
6.2 Significance of BI
6.2.1 Business Expansion
6.2.2 Process Improvements
6.2.3 Predictive Actions
6.2.4 Productivity Improvements
6.2.5 Customer Retention
6.2.6 Real-Time Data
6.2.7 Competitive Advantage
6.2.8 Quality
6.3 Purpose and Benefits of BI
6.4 Importance of HR Planning in Modern Industries
6.5 BI for HR Planning
6.5.1 Analyze Workforce Gaps (Steps 1–4)
6.5.2 Action Plan (Step-5)
6.5.3 Monitoring and Control (Step-6)
6.5.4 Review and Feedback (Step-7)
6.6 BI Architecture and Components
6.6.1 Data Management
6.6.2 Advanced Analytics
6.6.3 Business Performance
6.6.4 Information Delivery
6.6.5 Business Architecture of BI Application
6.7 BI and Analytical Tools and Applications
6.8 BI Adoption Strategy
6.8.1 Vendor Approach
6.8.2 Government Approach
6.8.3 MSME Approach
6.9 Conclusion
References
7 The Current State of Business Intelligence Research:
A Bibliographic Analysis
7.1 Introduction
7.2 Methodology
7.3 Analysis
7.3.1 Descriptive Analysis
7.3.2 Network Analysis of Publications
7.4 Collaboration Network of Authors, Institutes, and Countries
7.4.1 Collaboration Network of Authors
7.4.2 Collaboration Network of Institutes
7.4.3 Collaboration Network of Countries
7.5 Conclusion
7.6 Future Direction and Limitation
References
8 Empirical Assessment of Artificial Intelligence Enablers
Strengthening Business Intelligence in the Indian Banking
Industry: ISM and MICMAC Modelling Approach
8.1 Introduction
8.2 Literature Review
8.3 Identification of the Enablers for ISM Modelling
8.4 Methodology
8.5 Results and Discussion
8.6 MICMAC Analysis
8.7 Conclusion
8.8 Implications
8.9 Limitations
References
9 Measuring the Organizational Performance of Various Retail Formats in the Adoption of Business Intelligence
9.1 Introduction
9.2 Literature Review
9.2.1 Overview of BI
9.2.2 Discussion of TOE Framework and Development of Research Hypotheses
9.2.2.1 Technological Factors
9.2.2.2 Organizational Factors
9.2.2.3 Environmental Factors
9.2.2.4 BI Adoption
9.3 Research Methodology
9.3.1 Sampling
9.3.2 Demographics of the Respondents
9.4 Data Analysis
9.4.1 Reliability and Validity
9.4.1.1 Cronbach’s Alpha
9.4.2 Exploratory Factor Analysis
9.4.3 Construct Validity
9.4.4 Structural Equation Modeling
9.5 Discussion
9.6 Conclusion
References
10 Implementation and Scope of Business Intelligence and Oracle Transportation Management System in Tata Steel Supply Chain
10.1 Introduction
10.2 Literature Review
10.3 Methodology and Analysis
10.4 Scope of the Study
10.5 Analysis
10.5.1 Set Up and Configurations
10.5.2 Centralized Data Handling
10.5.3 Multi-Tasking Functions
10.5.4 Financial Aid
10.5.5 Transportation Intelligence
10.5.6 Warehousing Guide
10.6 Shipment Management
10.7 Logistics Modeling
10.8 Interface
10.9 Conclusion
References
11 New Marketing Perspective in Post-Covid Era with the Application of Business Intelligence
11.1 Introduction
11.2 Research Strategy
11.2.1 Methodology
11.2.2 Scope of This Research
11.2.3 Research Framework
11.2.4 Discussion
11.3 Change in Market Structure
11.4 Change in Business Operations
11.5 Technological Advances: Business Intelligence
11.5.1 Analysis and Interpretation
11.6 Research Implications: Changes in Marketing Operations
11.6.1 Product Decisions
11.6.1.1 Strategic Move
11.6.2 Price Decisions
11.6.2.1 Strategic Move
11.6.3 Promotion Decision
11.6.3.1 Strategic Move
11.6.4 Placement/Distribution Decision
11.6.4.1 Strategic Move
11.7 Conclusion
11.8 Limitations
References
12 The Application of Text Mining in Detecting
Financial Fraud: A Literature Review
12.1 Introduction
12.2 Data and Methodology
12.3 Text Mining
12.4 Conclusion
References
13 Effectiveness of Robotics Process Automation in Increasing the Productivity of Employees and Organizations with Reference to Business Analytics
13.1 Background and Introduction
13.2 Problem Context
13.3 Objectives
13.4 Literature Review
13.5 Methodology
13.6 Hypothesis
13.7 Data Analysis
13.7.1 Respondents Based on Age Working on RPA
13.7.2 Respondents Based on Gender Working on RPA
13.7.3 KMO and Bartlett’s Test
13.7.4 Chi Square Analysis
13.7.5 Relationship between the Understanding of the Real Meaning of RPA and RPA Can Save Time on Repetitive Tasks
13.7.6 Relationship between the Understanding of the Real
Meaning of Robotic Process Automation and RPA Can
Significantly Reduce Costs
13.7.7 Relation between the Understanding of the Real Meaning of RPA and RPA Implementation Costs Too High Compared to ROI
13.7.8 ANOVA
13.8 Findings and Discussion
13.9 Recommendations
13.10 Conclusion
References
14 Business Intelligence Application through Customer Relationship Management in LIC of India: A Case Study
14.1 Introduction
14.2 Literature Review
14.3 Methodology
14.4 Analysis and Findings
14.5 Concluding Remarks
References
Index