Certified HR Analytical Professional

To fully leverage on the power of analytics for HR decision making, HR practitioners need to be equipped with the competency in order to undertake the work. Competency levels may be classified as foundation level, which allows the practitioner to undertake most descriptive data analyses, and advanced level, which allows for analyses that yield predictive and prescriptive insights.  Insights of the latter forms are the most useful and can translate into the greatest competitive advantage for companies.

Programme Objectives

Objective 1:

To raise the competency level of HR practitioners to an advanced level so that they can leverage on an array of analytical tools suitable for decision making in the HR context.  More specifically, the application of advanced analytical tools taught in this programme will allow insights to be obtained that will benefit companies in the following ways:

• To assess the ROI of HR initiatives.  Additionally, knowing the ROI of initiatives enable the practitioner to focus only on initiatives that yield the best outcomes for the organisation. 
   
• To identify the key factors (traits) that discriminate between high performers and weak performers in every function e.g. sales function. This raises recruitment effectiveness and also allows resources to be channelled to those with the highest potential.
   
• To identify key organisational influences that impact employees’ satisfaction and engagement.  Such insights allow for the development of positive work climates which will lead to higher individual performance and, consequently, organisation success.  Additionally, this will also lead to lower employment turnover and, consequently, reduce insurance premiums.  
   
• To develop behavioural key performance indicators for employees in various functions by linking customer satisfaction to employee behaviour. 
   
• To raise customer satisfaction by applying insights to improve employee-customer interaction quality.  For instance, better matching of relationship managers in a bank with clients of different profiles, and better matching of customer-facing retail staff with a company’s various customer groups in different retail departments.

Objective 2:
The highly competitive business climate today demands that the best employees are recruited.  To this end, companies often rely on psychometric profiling of employees to identify traits suitable for certain job functions.  On its own, the use of psychometric profiles may be inadequate for such purposes.  The use of data modelling methods addressed in this programme aims to develop better employee performance models by using psychometric profile data as one of the many input sources, in addition to demographic characteristics, employment history, preferences etc. to develop good predictive models to aid recruitment, and job matching functions.

Objective 3:
To provide participants with the knowledge and skillsets in helping them conceptualise analytics application for HR confidently. Participants will develop their thoughts in this area through an exposure to HR analytics practices of companies and the discussion of HR cases used in the programme.

This is a highly interactive programme where class sharing, discussion and exercises will be employed alongside with analytical softwares (SPSS and WrapPLS) hands-on practices to help participants gain a good grasp of HR analytics.

Programme Outline

• The application of advanced level analytics in the HR contexts

    – Catergorisation of HR analytics
    – HR questions addressed with higher level analytics
    – Linking HR practices and business outcomes

• Development of advanced level analytical competencies (hands-on with SPSS, WarpPLS and PERMAP).  Gaining competences in these areas will allow the benefits mentioned in the programme objectives to be achieved.  The coverage of the scope of analyses includes but are not limited to the following:

    – Factor Analysis
    – Multiple Regression Models (with and without latent constructs)
    – Conjoint Analysis and Best-Worst Scaling Models
    – Logistic Regression Analysis
    – Perceptual Mapping
    – Structural Equation Modelling

• Translation of HR issues into analytical issues (development of analytical thinking).  This development will be in the form of presentations by the instructor, case studies discussed by participants and the reflection of how analytical methods can be used in their companies.

Participants have to meet a minimum attendance rate of 75% and have to complete all assessment(s) required by the course. Only upon meeting the minimum attendance and passing the assessment will participants be issued a Certificate of Completion.

Participants who fail the assessment will be given a chance for re-assessment at a fee of SGD100.00 (excluding prevailing GST). Each participant is allowed 1 re-assessment. The re-assessment has to be taken within 7 calendar days from the end of the course date.  It will be held on a weekday specified by SMU Academy and conducted during office hours. Please note that re-assessment fees are not supported by SSG Funding.

Participants who meet the minimum attendance rate but do not achieve a pass for the assessment will be issued a Certificate of Participation.

SMU will provide laptops pre-loaded with analytics software to all course participants.