HR Metrics and Data Analytics Certification Training Course

Why Select this Training Course? 

Some challenges plaguing HR professionals include predicting employee turnover and making the right recruitment call. These challenges can best be determined using key human resource metrics and data analysis to make informed decisions. HR analytics and metrics methodologies help to enhance organisational and individual workplace performances.

The Rcademy HR Metrics and Data Analytics Certification Training Course will expose participants to vital HR metrics and a step-by-step guide on analysing workplace data to help predict future organisational human resource needs. The course will introduce attendees to how to use Excel functions to predict and investigate HR data. They will also learn human relations tools and methodologies and how to overcome the challenges of HR analytics.

What are the Essential HR Metrics for Organisations?

HR metrics are data points that enable personnel to track human resource and recruitment activities, such as employee retention, compensation, engagement, time-to-hire, performance, and cost-per-hire. This allows organisations to maintain a close eye on the functionality of their programs while helping them make adjustments where necessary. HR metrics are, therefore, methods of evaluating a specific area within an organisation and how they can manage unforeseen events.

Some of the top HR metrics for companies and organisations include:

• Turnover
• Diversity
• Learning
• Headcount
• Talent acquisition
• Compensation
• Spans and layers
• Total cost of the workforce

What are the Types of HR Analytics?

When running a diverse and multi-faceted human resource department, depending on guesswork and instinct in decision-making is not viable. Suppose you want to take your HR department to the next level while making data-based decisions. In that case, it is crucial to understand the basics of HR analytics and how it can offer you valuable insights. HR analytics is essential for evaluating and interpreting data connected to an organisation’s workforce to obtain useful insights and make data-driven decisions. This includes assessing data connected to vital aspects of the organisation, such as employee performance, recruitment, retention engagement, and other HR functions.

Human resource analytics is a fast-growing field that has become increasingly vital for the growth of organisations of all sizes. The following are types of HR analytics organisations can employ to optimise their performances:

• Descriptive analytics
• Predictive analytics
• Diagnostic analytics
• Prescriptive analytics

Who Should Attend?

The following personnel should attend the Rcademy HR Metrics and Data Analytics Certification Training Course:

• Data analysts tasked with collecting, evaluating, and storing data from market research, logistics, sales numbers, and linguistics in ways that enable companies and businesses to make better decisions.
• Data scientists responsible for identifying issues present in businesses and using data to design solutions for effective decision-making.
• Finance analysts charged with monitoring a firm’s financial operations and evaluating business performances and market situations to generate forecasts.
• Business analysts
• Financial auditors responsible for evaluating the accounting statements, data, and financial statements of an organisation.
• Managers and supervisors tasked with overseeing the smooth running of an organisation.
• HR officers tasked with monitoring and managing every aspect of the recruitment process, education and development of new employees.

What are the Course Objectives?

The Rcademy HR Metrics and Data Analytics Certification Training Course develops participants’ knowledge and understanding of human relation metrics and data analytics. The objectives of this training exercise include the following:

• Understand the fundamentals of data analytics and its relationship with the human resource department
• Appreciate the role of data analytics in understanding performance and behaviour
• Define the general principles of organisational change
• Learn how to utilise a range of assessment metrics to boost organisational input
• Understand how to run detailed analysis assessments
• Recognise how to generate decisions using empirical evidence rather than opinion
• Learn how to use data to analyse trends in the HR industry
• Understand how to set a benchmark and attract competent talent from the market

How will this Course be Presented?

This training course is participant-based and specially curated to meet their expectations while growing their skills and knowledge. Different techniques and approaches that ensure active learning by participants will be employed to deliver the training. The course will be delivered by experts in the field with years of practice and experience. The modules are designed from extensive and in-depth research on the subject.

The Rcademy HR Metrics and Data Analytics Certification Training Course provides theoretical and practical learning by providing lecture notes, slides on the subject, real-life scenarios, and lecture notes. Participants will partake in presentations, quizzes, seminar workshops, and constant feedback on the lessons taught to gauge their satisfaction.

What are the Topics Covered in this Course?

Module 1: HR Metrics, Data Analytics, Strategy and the HR Department

• The rationale for an evidence-based approach
• Defining data analytics and predictive analytics
• Key HR metrics
• Data, insights and information
• The human capital approach
• HR’s contribution to strategy design
• Personnel management versus strategic HRM

Module 2: Data Utilised by HR Analytics Tools

• Employee tenure
• External data
• Internal data
• Performance appraisal
• Employee background check
• Employee compensation and benefits
• Competent and high-performing employees
• Revenue per employee
• Training requirement

Module 3: Putting HR Metrics and Analytics into Action

• Human resource planning
• Talent management and succession planning
• Training needs analysis and skills analysis
• Absence management
• Recruitment analytics
• The balanced scorecard

Module 4: Driving Organisational Change

• Theories of organisational change and how to employ them
• Resistance to change
• Impediments and enablers of change
• Understanding the cultural context
• The dynamic nature of business and technology driving change
• Executing strategic change

Module 5: The HR Data Analysis Process

• Understanding organisational objectives
• Collating and analysing HR data
• Recognising the metrics and aligning with organisational objectives
• Chunking data to evaluate impacts on the organisation
• Reviewing policies and procedures to make amends
• Excel data analysis ToolPak

Module 6: HR Metrics and Analytics in Action

• Recruitment and selection
• Workforce planning
• Learning and development
• HR effectiveness and efficiency
• Attendance, absence and well-being
• Talent management and succession planning

Module 7: Metrics for Employee Productivity and Performance I

• Employee motivation
• The psychological contract
• Employee engagement
• Performance management
• Empowerment and accountability
• Training, webinars and seminar
• Conclusion and action planning

Module 8: Metrics for Employee Productivity and Performance II

• Employee utilisation
• Total workforce cost
• Self-rated productivity
• Tasked-to-executed ratio
• Focus hours/day
• Sales growth percentage
• Revenue-to-sales representative

Module 9: HR Analytics Cycle

• Building and sensitising the HR teams
• Working with the legal team
• Finalising HR analytics solutions
• Executing HR analytics on small projects
• Designing an analytics culture by coaching and monitoring the progress

Module 10: Data Collection and Analysis

• Methods of data collection
• Employee self-report and self-assessment measures
• Dealing with data security
• Running data diagnostics
• Electronic workforce surveillance and analytics
• Determining information to be analysed

Module 11: Inferential Statistics

• Defining and describing hypothesis testing
• Making hiring decisions using Z-test
• Checking the effectiveness of training programs using paired T-tests
• Evaluating productivity decisions using ANOVA
• Solving salary-related challenges using correlation and covariance
• Designing business models for predicting HR results using linear regression
• Investigation promotion bias using ANOVA single-factor

Module 12: Customer Service Metrics

• Feedback mechanism: positive, unresolved, unhelpful, negative
• First-call complain resolution
• Ticket creation per resolution
• Response time/ticket creation