HRM858 - Human Resources Analytics

Outline info
Last revision date 2018-07-20 13:36:47.84
Last review date 2018-07-20 13:36:53.675

Subject Title
Human Resources Analytics

Subject Description
To be a strategic human resources practitioner, one must be able to provide data driven facts and be able to use them in order to proactively address HR issues and strategically support the business.  Data driven analytics and metrics, provides HR with information to help drive strategic business decisions and build executive partnerships.  To help businesses deliver a competitive advantage over the competition, HR provides analytics on key performance indicators, HR analytics and interpretation of the data for the organization.  This course will provide the theory, concept and best practices in gathering business requirements, planning, research techniques, data analysis, metrics, and reporting. 

Learning Outcomes
Upon successful completion of this subject the student will be able to:

Upon successful completion of this subject the student will be able to:
   •     Recognize how HR analytics supports business decisions, aligns to company goals and builds executive relationships
    •       Prepare and plan your HR analytics project using a systematic approach to collecting, analyzing and interpreting the data
    •       Use requirements gathering tools and techniques:  research and collect the right data for your industry
    •       Identify HR performance frameworks and measurement systems which are aligned with corporate strategy
    •       Build and improve existing measurement systems in order to gain significant business insights
    •       Leverage the power of current information technology to record, retrieve and report on HR information
    •       Analyze data using appropriate metrics, benchmarks and indicators
    •       Convert data into strategic decision-making information
    •       Communicate your findings in a compelling manner to get buy-in and attention from the executive and senior leadership team

Cheating and Plagiarism
Each student should be aware of the College's policy regarding Cheating and Plagiarism. Seneca's Academic Policy will be strictly enforced.

To support academic honesty at Seneca College, all work submitted by students may be reviewed for authenticity and originality, utilizing software tools and third party services. Please visit the Academic Honesty site on for further information regarding cheating and plagiarism policies and procedures.

All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at

Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Disabilities Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.

Topic Outline
The People Analytics Age
    •       How to Migrate from Business Analytics to People Analytics
    •       The Seven Pillars of People Analytics Success
    •       Workforce Planning Analytics
    •       Talent Sourcing Analytics
    •       Talent Acquisition Analytics
    •       Onboarding and Cultural Fit
    •       Talent Engagement Analytics
    •       Analytical Performance Management
    •       Employee Lifetime Value and Cost Modeling
    •       Using Retention Analytics to Protect Your Most Valuable Asset
    •       Employee Wellness, Health, and Safety to Drive Business Performance and Loyalty
    •       Big Data and People Analytics
    •       Future of People Analytics

Mode of Instruction
A combination of teaching methods will be utilized which may include lectures, case studies, discussions, group and individual work.

Prescribed Texts
Title:  People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent
Author(s):  Jean Paul Isson, Jesse S. Harriott, Jac Fitz-enz (Foreword by)
Publisher:  Wiley
ISBN: 978-1-119-05078-0

Reference Material

Required Supplies

Promotion Policy

Grading Policy
A+ 90%  to  100%
A 80%  to  89%
B+ 75%  to  79%
B 70%  to  74%
C+ 65%  to  69%
C 60%  to  64%
D+ 55%  to  59%
D 50%  to  54%
F 0%    to  49% (Not a Pass)
EXC Excellent
SAT Satisfactory
UNSAT Unsatisfactory

For further information, see a copy of the Academic Policy, available online ( or at Seneca's Registrar's Offices.

Modes of Evaluation

Modes of Evaluation

Assignments are due on the dates specified. Should extenuating circumstances arise, please contact your instructor immediately, prior to when your assignment is due, so an appropriate course of action can be established. Late assignments may be subject to a penalty of up to 10% per week and will not generally be accepted beyond two weeks after the assignment due date.

In cases of cheating or plagiarism, the College Academic Policy will prevail.  Please ensure that all assignments and reports are properly documented.

Students are referred to the following web site for the Seneca College Library MLA Style Guides, Academic Honesty Policy and Copyright guidelines:  


Dates for evaluations are specified in the weekly schedule addendum to this outline. The evaluation process may include, but is not limited to, tests, exams, assignments or presentations. Any absences or missed submissions due to medical or other reasons must be supported by medical or other appropriate documentation within one (1) week of the due date. The faculty and program area must be notified immediately in the even of a missed evaluation. Upon acceptance of the documentation, the weighting of the missed deliverable will normally be applied to the final exam.

English Competency:

The ability to communicate effectively is essential for success in business. Therefore, you must demonstrate English competency in this course in both oral and written work. Ensure your written work includes correct sentence structure, spelling and punctuation. Always spell check, edit and proofread your work.

Grading is based on the following marking scheme:

Grading is based on the following marking scheme: 
Term Project                          30%
In Class Case Study           10%
Mid Term Test                       30%
Final Exam                            30%

Please retain this course outline document for future educational and/or employment use.

Approved by: Academic Program Manager Emiliano Introcaso