The document provides an overview of Human Resource Information Systems (HRIS) and HRIS analytics, detailing their components, types, and importance in HR management. It explains how HRIS centralizes employee data and automates processes, while HRIS analytics helps organizations analyze HR data for improved decision-making and optimized strategies. The document also discusses future trends such as AI integration and predictive analytics, emphasizing the need for leveraging technology in HR.

1. UNDERSTANDING
HRIS AND HRIS
ANALYTICS

2. LEVERAGING
TECHNOLOGY FOR
EFFICIENT HR
MANAGEMENT
Introduction
Components of HRIS
Introduction to HRIS Analytics
Types of HRIS Analytics
HR Metrics and KPIs
Case Study: Implementing HRIS
Analytics
Future Trends in HRIS and HRIS
Analytics
Relationship of HRIS with HRIS
analytic
Conclusion
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3. INTRODUCTION

4. DEFINE HRIS
HRIS (Human Resource Information System)
is a software solution that helps organizations
manage their HR operations and processes
electronically. It centralizes employee data,
automates routine tasks, and supports
strategic HR decision-making.
Importance of HR technology: Explain how HR
technology has revolutionized HR
management, making processes more
efficient, accurate, and strategic.
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5. COMPONENTS
OF HRIS

6. HRIS COMPONENTS
HRIS Modules:
Employee Information Management: Store and manage employee
data such as personal information, employment history, and
performance evaluations.
Payroll: Automate payroll processes, including salary calculations,
tax deductions, and direct deposits.
Time and Attendance: Track employee work hours, manage leave
requests, and generate attendance reports.
Benefits Administration: Administer employee benefits such as
health insurance, retirement plans, and paid time off.
Recruiting: Manage the recruitment lifecycle, from job posting and
applicant tracking to candidate evaluation and onboarding.
Training and Development: Plan, deliver, and track employee training
programs and professional development activities.
Integration and Customization: Discuss the importance of
integrating HRIS with other systems (e.g., accounting software,
CRM) and customizing it to meet the organization's specific needs. 6

7. INTRODUCTION
TO HRIS
ANALYTICS

8. DEFINE HRIS
ANALYTICS
Define HRIS Analytics: HRIS analytics involves
analyzing HR data to gain insights into
workforce trends, identify areas for
improvement, and support data-driven
decision-making.
Importance of Data Analytics in HR
Management: Explain how HR analytics helps
HR professionals understand employee
behavior, predict future trends, and optimize
HR processes.
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9. TYPES OF HRIS
ANALYTICS

10. TYPE OF HRIS ANALYTICS
Descriptive Analytics: Descriptive analytics involves
analyzing historical HR data to understand past trends and
patterns (e.g., employee turnover rates, demographic
distributions).
Predictive Analytics: Predictive analytics uses statistical
algorithms and machine learning techniques to forecast
future HR trends and outcomes (e.g., predicting employee
turnover, identifying high-performing candidates).
Prescriptive Analytics: Prescriptive analytics provides
recommendations and actionable insights based on HR data
analysis, helping organizations make informed decisions and
optimize HR strategies.
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11. HR METRICS AND KPIS
Examples of HR Metrics
Employee Turnover Rate: The
percentage of employees who leave
the organization within a certain
period.
Time to Fill: The average number of
days it takes to fill a vacant position.
Cost per Hire: The total cost
incurred to fill a vacant position,
including recruitment advertising,
agency fees, and employee training.
Training ROI: The return on
investment from employee training
and development programs.
Key Performance Indicators
(KPIs)
KPIs are specific metrics used to
measure the performance of HR
processes and initiatives (e.g.,
employee engagement, talent
acquisition effectiveness, HR
service delivery).
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12. HRIS ANALYTICS TOOLS
Overview of popular HR analytics software/tools
1. ADP Workforce Now
2. BambooHR
3. SAP SuccessFactors
4. Workday
5. PeopleSoft
12

13. CASE STUDY: IMPLEMENTING HRIS
ANALYTICS
Provide a real-life example of a company that implemented HRIS
analytics to improve HR performance and achieve strategic
objectives.
Discuss the challenges faced during the implementation process
and the solutions implemented to overcome them.
Highlight the benefits realized from implementing HRIS analytics,
such as improved decision-making, increased employee
productivity, and reduced turnover.
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14. FUTURE TRENDS IN HRIS AND HRIS ANALYTICS
1. AI and Machine Learning Integration: Discuss how AI and machine
learning technologies are being integrated into HRIS to automate
repetitive tasks, personalize employee experiences, and enhance
decision-making.
2. Predictive Workforce Analytics: Predictive workforce analytics will
enable organizations to anticipate future HR trends and outcomes,
allowing them to proactively address workforce challenges and
opportunities.
3. Blockchain for HR Data Security: Explore the potential of blockchain
technology to enhance HR data security, privacy, and transparency by
creating tamper-proof, decentralized HR databases.
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15. HRIS ITS RELATED TO HRIS
ANALYTIC
HRIS stands for Human Resource Information System. It's essentially a
software solution that facilitates the management of HR processes and
data. HRIS encompasses a wide range of functionalities, including
employee data management, payroll processing, recruitment,
performance management, and more.
HRIS analytics, on the other hand, refers to the analytical capabilities
embedded within HRIS software or performed using data collected by
HRIS. These analytics involve the analysis of HR-related data to gain
insights into various aspects of human resources management, such as
workforce productivity, employee engagement, turnover rates, recruitment
effectiveness, and training impact.
In essence, while HRIS focuses on the system itself and its functionalities
for managing HR processes, HRIS analytics leverage the data within the
system to provide actionable insights for strategic decision-making and
optimizing HR practices. They are closely related as the analytics
component adds value to the HRIS by enabling data-driven decision-
making and performance evaluation.
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16. CONCLUSION
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Recap the key points discussed in the presentation,
emphasizing the importance of HRIS and HRIS
analytics in modern HR management.
Encourage the audience to leverage technology to
optimize HR processes, improve decision-making,
and drive business success.

17. THANK YOU
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