Foundational Competencies
The Human Resource (HR) Foundational Competencies underpin and span across the HR Functional Competencies. They serve as core enablers supporting HR functional activities.
Data Analytics and Insights
Data Analytics and Insights
Deploy a range of data analysis tools and techniques to derive actionable insights and communicate business implications.
Hover on the blue underlined text to discover which HR Mindset and Behaviour is embedded in the Performance Statement.
IHRP Certified Associate
- Collect data from a variety of sources in adherence with the organisation’s data governance and privacy policies and relevant legislation.
- Prepare and clean data to ensure quality of data and its usability for further analysis.
- Conduct checks to assess the credibility and validity of data and data sources.
- Organise data and analysis outcomes to be stored and retrieved in line with organisational requirements.
- Deploy data models, statistical software and tools to process data sets.
- Implement data visualisation techniques and tools to present information and insights.
IHRP Certified Professional
- Review and refine data collection, preparation and cleansing processes, in adherence to data governance and privacy concepts and principles and relevant legislation.
- Collate and integrate financial, HR and other data sources to design HR metrics, identify causal relationships, analyse trends, develop forecasts and projections, and draw insights and foresights for decision making.
- Analyse data by employing data mining, modelling, predictive analytics, and benchmarking tools and techniques to create insights and foresights to guide decision-making.
- Derive relevant insights from analysis and recommend enhancements to the organisation’s HR practices and initiatives in alignment with business strategy.
- Develop evidence-based, insightful presentations and persuasive communications, using data visualisation and storytelling tools and techniques.
- Identify and assess the need for new processes, systems and tools to conduct data processing, analysis and visualisation and deliver insights.
- Review HR-related activities and processes to identify any areas where data collection systems could be implemented or improved.
- Keep abreast of local and global HR trends and developments to provide further benchmarking insights on data analysis outcomes.
- Assess the design and use of Artificial Intelligence (AI) and technology tools for fairness and equity in analysing talent data.
IHRP Senior Professional
- Define and prioritise business issues to be investigated using people-related data analytics in consultation with business leaders and relevant wider stakeholders.
- Evaluate ways for data to be captured and analysed, such as dashboards, to demonstrate the value and impact of HR-related activities across the organisation.
- Define a code of ethics for people-related data analytics to ensure data security and uphold fairness and equity in using the data to make talent decisions.
- Evaluate employee data handling practices and processes to ensure compliance with employee data protection policy, ethical guidelines and relevant legislation to ensure privacy and security of confidential employee data.
- Evaluate a variety of data sets to anticipate implications of business activity on HR practices.
- Develop evidence-based, forward-looking talent strategies based on actionable workforce and talent insights.
- Evaluate and communicate business implications and actionable insights to business leaders using appropriate data visualisation and storytelling strategies to drive action.
- Perform trend analysis by understanding the competitive environment in which the business interacts.
- Assess the extent of in-house people analytics capability and engage with external providers of benchmarking or analytics services to supplement identified gaps.
- Evaluate data collection, storage and organisation processes to recommend any areas where standardised and systematic data cleaning could be implemented.
- Drive the optimisation of data analytics processes by deploying Artificial Intelligence (AI) and automation tools.