The British Academy for Training and Development offers the IIBA Endorsed Certified HR Analyst Course. The programme aims at equipping HR analysis professionals with the requisite skills and knowledge to succeed in their field. Besides achieving HR analytical and strategic decision-making skills, this course covers a wide range of subjects.

The course begins with an overview of HR analytics, including data-gathering and interpretation techniques. It gradually advances to workforce planning, equipping professionals to understand future HR needs and align them with business goals. It then looks into performance assessment of employees via HR metrics and talent acquisition and engagement strategies, while HR analytics will also assist with decision-making to counter issues of employee retention and development programming.

Attendees will also be taken through organisational behavior, which involves influence and analysis of workplace dynamics. The entire course will cover HR technology and software that allow for smooth and efficient HR procedures. Lastly, this course will embark on the foundations of HR's role in strategic decision-making to ensure that the HR analytical approach drives organizational success in the long run.

As a product of this course, the professional will be able to conduct HR in line with best practices, incorporating data analytics into HR strategy, ensuring improvements in employee management and organisational performance.

Objective:

Primary objectives of this training course are:

Enable attendees to gather, analyze, and interpret human resource data to support decisions.Provide a complete understanding of HR measurements, workforces, and employee engagement tactics.Become adept in using HR technology and data-driven insight to create an improved talent acquisition, employee retention, and performance of the organisation.Enhance strategic thinking and applying HR Analytics to achieve organisational objectives and ensure better business outcomes.Implement data analytics tools and strategies to improve recruitment decisions, and predict employee turnoverAnalyze the impact of learning and development provision on employee motivation using linear regressionPromote a culture of diversity and inclusion within their organization through significance statistical testsPredict employee performance using data from employee engagement surveysApply HR data analysis strategies and tools in their own business environmentWho Should Attend?

This course is ideal for: 

HR professionals wishing to acquire more analytical skills and a better understanding of HR data.HR Managers and HR Analysts who are keen to use advanced analysis techniques in their jobs.Business Analysts and data specialists under HR divisions who desire to incorporate more data-based approaches into their HR strategies.Recruiters, talent acquisition professionals, employee development managers who would like to leverage data in their efforts to increase recruitment, retention, and employee engagement.Organisational leaders and managers interested in using HR analytics toward achieving better strategic decisions and business outcomes.How will attendees benefit?

Attendees of the IIBA Endorsed Certified HR Analyst Course will benefit in several key ways:

Enhanced Analytical Skills: Attendees will learn to use HR data to inform decision-making, thereby improving their ability to analyze metrics around employee performance, engagement, and retention.Increased Efficiency: The course will arm all attendees with the tools of HR technology to streamline HR processes to manage the talent pool in recruiting better and work on workforce planning.Strategic Insight: Attendees will learn how to align HR analytics with business objectives such that insights from data are important for the accomplishment of organizational success and nurture strategic growth.Improved Talent Management: Through the engagement of employees and acquisition of talents, attendees will be enabled in order to better manage and creatively draw in top talents, thus reducing turnover and boosting productivity.Advanced HR Metrics Application: The course will enable attendees by applying advanced HR metrics and workforce planning techniques for the measurement and tracking of HR strategies and programmes' effectiveness.Career Advancement: Certification by IIBA would be a great feather in their cap and enhance their credentials, making the participants more qualified for any further advancement in the HR field.Improved Decision-Making: Guided on data and HR analytics, the attendees will be given the capabilities to ultimately make strategic, data-driven decisions to improve both the employee experience and organisational performance.

At the end attendees will leave the course with the requisite knowledge to direct HR innovation and further develop business outcomes through advanced HR analytics and strategic decision-making.

• Data-driven HR analytics

• Definition of HR analytics

• The analytics process – using data to influence business decisions

• Data

• Metrics

• Analytics

• Action

• Information sources – HR data are not only found in HR departments

• The most commonly used HR information systems and data analysis platforms

• Basic statistics

• Types of variables

• Statistical significance

• Descriptive data vs. data analysis

• Modelling and predictive analysis

• How data are reinventing the HR functions

• HR professionals and data – how to synergize for the best of the business

• Data analysis of recruitment and prediction of employee turnover

• Dependent and independent variables

• Categorical and continuous variables

• Logistic regression analysis methodology - building predictive models

• Removing guesswork from recruitment decisions - data-informed candidate selection decisions

• Testing validity and reliability of candidate selection methods

• Predicting rejection and shortlisting of candidates

• Predicting employee turnover in your organization

• Data-driven learning and development – the impact of training provision on employee motivation

• Transforming answers of questionnaires into continuous data to expand analysis opportunities

• Questionnaire design - testing internal consistency of questionnaires - Cronbach's alpha measure

• Removing irrelevant answers from respondents (outliers) to questionnaires

• Testing if your data is representative using normality test

• Understanding the nature of relationship between business variables using Pearson's correlation  

• Examining the impact of training provision variables on employee motivation using linear regression

• Simulating an alternative model to Kirkpatrick's model for evaluating training impact 

• Deep analysis of diversion and inclusion in the organization

• The importance of diversion and inclusion (ethnic and gender) in organizations

• Wrong ways of using descriptive data to present a case of organization bias

• Significance p value and degrees of freedom

• t-tests and chi square test - a simple mathematical notion

• Analyzing gender bias in workforce and job grades using frequency tables and chi square

• Exploring ethnic diversity across teams using descriptive statistics

• Reporting gender-biased promotions using t-tests 

• Using multiple linear regression to model and predict ethnic diversity variation across teams

• ​Exploring relationships between employee performance, employee engagement, and profitability

• How to measure employee engagement

• Factor analysis to test the reliability of questions in an employee engagement survey

• Analyzing data to explore the relationship between customer loyalty levels and employee engagement levels

• Stepwise multiple regression - an effective tool to explore relationships among business variables

• Using stepwise multiple regression to model employee performance

• Revisiting multiple regression to predict employee sickness

• Modeling change in performance of employees over time using stepwise multiple regression

• Application of HR data analysis in business context - An eight-step methodology

• Step 1: Linking business strategies to people strategies

• Step 2: Identifying business challenges

• Step 3: Forming your business hypothesis

• Step 4: Gathering your data

• Step 5: Choosing analysis tools and strategies

• Step 6: Findings and decisions - turn data to insights

• Step 7: Communicating your conclusion with storytelling and visualization

• Step 8: Evaluating your analytical intervention