COURSE FORMAT & DELIVERY DETAILS Self-Paced, On-Demand Learning Designed for Maximum Flexibility and Career Impact
This course is built around your schedule, your pace, and your professional goals. From the moment you enroll, you gain full access to a world-class curriculum that evolves with the industry, giving you the tools to master People Analytics in real time and apply them immediately to deliver measurable business outcomes. Immediate Online Access, Zero Deadlines, Total Freedom
The entire course is self-paced and delivered on-demand. There are no fixed start dates, no weekly deadlines, and no time commitments. You decide when and where you learn. Whether you're fitting study into a busy workweek or accelerating your progress over a quiet weekend, the structure supports your lifestyle without compromising depth or quality. Complete in 6–8 Weeks, See Results in Days
Most learners complete the program in 6 to 8 weeks by dedicating 4 to 5 hours per week. However, many report applying core concepts and seeing initial business impact within just a few days. The content is structured to unlock value fast, with early modules focused on immediate-action frameworks you can use in your current role, from talent retention diagnostics to performance measurement design. Lifetime Access + Ongoing Free Updates Forever
You’re not just buying a course-you’re gaining permanent access to a living, evolving resource. Lifetime access means you can revisit material anytime, at any stage of your career. As new analytics models, industry standards, and data regulations emerge, the course is updated at no extra cost, ensuring your skills remain cutting edge and future-proof. Available 24/7 Worldwide, Fully Mobile-Friendly
Access your learning materials anytime, from any device, anywhere on the planet. The platform is fully optimised for smartphones, tablets, and desktops, meaning you can review frameworks during a commute, refine dashboards from a café, or dive into case studies after hours-all without disruption. Global access means no regional restrictions, no downtime, just seamless learning. Direct Instructor Support and Expert Guidance Included
You are not learning in isolation. Throughout the course, you receive structured guidance from seasoned People Analytics practitioners. This includes detailed feedback pathways on applied exercises, curated resource recommendations based on your role, and access to a support system designed to clarify complex topics and accelerate implementation. Whether you're new to data or refining advanced models, expert insight is embedded into your journey. Receive a Globally Recognised Certificate of Completion from The Art of Service
Upon successful completion, you will earn a Certificate of Completion issued by The Art of Service, a globally recognised provider of professional development programs. This credential carries significant weight across industries and geographies. It validates your mastery of People Analytics as a strategic discipline, not just a technical skill, and enhances your credibility with employers, clients, and leadership teams. Transparent, Upfront Pricing – No Hidden Fees
What you see is exactly what you pay. There are no hidden fees, no recurring charges, and no surprise costs. The price includes full curriculum access, lifetime updates, certificate issuance, and all support resources. You invest once, and your access is complete and permanent. Multiple Secure Payment Options Accepted
We accept all major payment methods, including Visa, Mastercard, and PayPal. Transactions are processed through a secure, encrypted gateway to protect your data and ensure a smooth enrollment experience. No additional steps, no complications-just secure, trusted payment processing. 100% Satisfied or Your Money Back – Zero Risk Enrollment
We guarantee your satisfaction. If at any point in the first 30 days you find the course does not meet your expectations, simply request a full refund. No questions, no bureaucracy, no loss. This is our promise to eliminate all risk and ensure you can explore the program with complete confidence. Simple Post-Enrollment Process – Confirmation and Access in Two Steps
After enrolling, you will immediately receive a confirmation email acknowledging your registration. Shortly after, once your course materials are prepared, you will receive a separate email with your secure access details. This two-step process ensures accuracy and smooth delivery, with clear instructions at every stage. “Will This Work for Me?” – A Risk-Reversal Promise
We know you’re evaluating this decision carefully. Perhaps you’re uncertain if your background prepares you for analytics, or if your organisation will value these skills. We’re confident this program works-regardless of your starting point. This works even if you have never written a data query, if your HR team has limited technology access, or if you’re transitioning from a non-technical role. The curriculum is designed for real-world constraints, with step-by-step walkthroughs, role-specific templates, and decision frameworks that scale from entry-level to enterprise. - This works even if you’re not in HR, because People Analytics applies to leadership, operations, talent acquisition, and organisational development.
- This works even if your company hasn’t adopted analytics yet-we show you how to build the case, start small, and demonstrate ROI quickly.
- This works even if you’re not “good at data”-we translate statistics into actionable insights using plain-language explanations and real business scenarios.
Our learners come from diverse backgrounds-HR business partners, talent managers, consultants, team leaders, and even CFOs looking to understand workforce drivers. Testimonials confirm that the program bridges skill gaps, unlocks promotions, and delivers tangible results: - Within three weeks, I redesigned our retention dashboard and identified a 23% flight risk in a critical department. My leadership team now consults me as a strategic partner. – Maria T, HR Director, Germany
- I had no analytics experience. This course gave me the structure and confidence to lead a people data pilot. Six months later, we launched a company-wide analytics initiative. – David L, People Operations, Australia
- he templates and models are so practical. I used the workforce planning module to cut recruitment costs by 18% in my region. – Amina K, Talent Lead, Kenya
This is not theoretical. This is applied, battle-tested knowledge that delivers career ROI from day one. With lifetime access, expert support, global recognition, and a full money-back guarantee, you are protected at every level. The only risk is not taking action-and missing the opportunity to future-proof your career in a data-driven world.
EXTENSIVE & DETAILED COURSE CURRICULUM
Module 1: Foundations of People Analytics – Why It Matters and Where to Start - The business case for People Analytics: linking workforce data to performance outcomes
- Understanding the shift from intuition-based to evidence-based HR decisions
- Defining People Analytics vs HR metrics vs workforce science
- The evolution of data in human capital management
- Common myths that hold professionals back from using data
- How companies across industries are using People Analytics to reduce costs and increase productivity
- Identifying your organisation’s readiness for People Analytics adoption
- The role of ethics, privacy, and employee trust in data usage
- Key legal and compliance considerations in global data handling
- Introduction to data governance and responsible access frameworks
- How to articulate the value of analytics to executives and sceptical stakeholders
- Developing your personal roadmap for mastering People Analytics
- Structuring your learning journey based on experience and organisational context
- Building a mindset of continuous measurement and improvement
- Tools for tracking your progress through the course and applying learnings incrementally
Module 2: Strategic Frameworks for People Analytics Success - The 5-Stage Maturity Model for People Analytics capability
- Balanced Scorecard integration for HR performance tracking
- Using the People Analytics Value Chain to prioritise initiatives
- The HR Strategy Map: aligning workforce metrics with business objectives
- How to apply the Workforce Insight Lifecycle: question, data, analysis, action, feedback
- Designing analytics projects around business problems, not just data availability
- SMART goal setting for People Analytics initiatives
- Aligning analytics efforts with organisational KPIs and OKRs
- The role of stakeholder analysis in shaping project scope
- How to build cross-functional coalitions for data success
- Benchmarking your analytics efforts against industry leaders
- Creating a phased rollout plan for analytics adoption
- Introducing the People Analytics Canvas for end-to-end project design
- Mapping data inputs to business decisions: a systems-thinking approach
- Anticipating and mitigating common implementation risks
Module 3: Data Sources, Collection, and Integration - Identifying the most valuable internal data sources: HRIS, ATS, performance systems, surveys
- Understanding the limitations and biases in workforce data
- How to audit data quality and completeness
- Managing missing, inconsistent, and duplicate data entries
- Linking data across systems: employee ID harmonisation techniques
- Capturing qualitative data and making it analytically usable
- Best practices for survey design to support analytics
- Timing, frequency, and cadence of data collection
- How to create a central data repository without expensive tools
- Using spreadsheets effectively for data consolidation
- Introduction to API concepts and how they enable data flow
- Data refresh schedules and version control protocols
- Understanding structured vs unstructured data in HR
- Extracting insights from email, chat, and collaboration platforms (ethically)
- Integrating external data: market benchmarks, economic indicators, labour trends
- Creating a data dictionary and metadata standards
- Documenting data provenance and transformation steps
- Setting up audit trails for compliance and transparency
- Using timestamps and duration variables for behavioural analysis
- Preparing data for longitudinal and cohort-based studies
Module 4: Core Metrics That Drive Business Impact - The difference between metrics, measures, and indicators
- Leading vs lagging indicators in workforce analytics
- Defining clean, consistent formulas for key HR metrics
- Calculating turnover rate with precision and context
- Voluntary vs involuntary vs regrettable turnover: when to measure which
- Calculating time-to-fill, cost-per-hire, and quality-of-hire
- Retention metrics by tenure, role, level, and manager
- Absenteeism rate calculation and pattern detection
- Presenteeism: how to estimate its impact using proxy data
- Workforce cost per employee and FTE productivity ratios
- Headcount planning accuracy and variance analysis
- Succession pipeline depth and readiness scores
- Learning effectiveness: completion rates, skill gain, transfer to job
- Diversity, equity, and inclusion metrics that matter
- Pay equity analysis: identifying unexplained pay gaps
- Engagement scores and their correlation with performance
- Manager effectiveness metrics derived from team outcomes
- Exit interview thematic analysis for predictive insights
- Calculating the true cost of unfilled roles
- Benchmarking metrics against industry and regional standards
Module 5: Advanced Analytics Techniques and Predictive Modelling - Descriptive, diagnostic, predictive, and prescriptive analytics explained
- Correlation vs causation: avoiding common statistical traps
- Using regression analysis to identify workforce drivers
- Logistic regression for predicting binary outcomes like turnover
- Survival analysis for understanding tenure and exit timing
- Cohort analysis techniques for tracking employee journeys
- Calculating employee lifetime value (ELV) and cost
- Predicting high-potential employees using data signals
- Identifying flight risk using multivariate models
- Building early warning systems for attrition hotspots
- Cluster analysis for segmenting employees into meaningful groups
- Using decision trees for workforce classification and recommendations
- Time series analysis for forecasting hiring needs and attrition
- Monte Carlo simulation for workforce scenario planning
- Natural language processing basics for analysing open-ended feedback
- Sentiment analysis from engagement surveys and exit interviews
- Topic modelling to uncover hidden themes in employee communications
- Machine learning principles for HR professionals (non-technical overview)
- Validating model accuracy and avoiding overfitting
- Communicating uncertainty and confidence intervals in predictions
Module 6: Visualisation, Dashboards, and Storytelling with Data - Principles of effective data visualisation for executives
- Choosing the right chart type for your message
- Dashboard design: layout, colour, fonts, and interactivity
- Creating static and dynamic dashboards in spreadsheets
- Best practices for labelling, legends, and annotations
- Avoiding misleading scales, truncations, and visual distortions
- Using conditional formatting to highlight key insights
- Building scorecards for HR business partners
- Linking dashboard elements to strategic goals
- Data storytelling: structuring narratives around insights
- The three-act framework for presenting analytics findings
- Using contrast, tension, and resolution in data presentations
- Turning technical findings into compelling executive summaries
- Anticipating and answering stakeholder questions in advance
- Creating data packs for board-level reporting
- Using before-and-after comparisons to show impact
- Visualising trends, comparisons, distributions, and relationships
- Designing accessible dashboards for diverse audiences
- Incorporating data into change management campaigns
- Measuring the influence of your data story with follow-up metrics
Module 7: Talent Acquisition and Workforce Planning Analytics - Analysing the end-to-end hiring funnel for bottlenecks
- Time-to-hire by role, source, and recruiter
- Cost-per-hire breakdown: advertising, agency, internal costs
- Evaluating sourcing channel effectiveness using ROIs
- Quality-of-hire measurement frameworks
- Time-to-productivity for new hires by role and cohort
- Retention of hires by recruiter, source, and interview panel
- Predictive modelling for candidate success
- Using structured interviews and assessment scores in analytics
- Analysing offer acceptance and decline reasons
- Forecasting hiring needs using business growth models
- Demand-driven workforce planning techniques
- Scenario planning for headcount under different business conditions
- Modelling the impact of automation and restructuring
- Skills gap analysis using internal and external benchmarks
- Creating a talent supply map for critical roles
- Succession analytics: readiness, bench strength, diversity
- Analysing internal mobility and promotion patterns
- Identifying career path bottlenecks and equity issues
- Building heatmaps for talent concentration and flight risk
Module 8: Performance, Engagement, and Retention Analytics - Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
Module 1: Foundations of People Analytics – Why It Matters and Where to Start - The business case for People Analytics: linking workforce data to performance outcomes
- Understanding the shift from intuition-based to evidence-based HR decisions
- Defining People Analytics vs HR metrics vs workforce science
- The evolution of data in human capital management
- Common myths that hold professionals back from using data
- How companies across industries are using People Analytics to reduce costs and increase productivity
- Identifying your organisation’s readiness for People Analytics adoption
- The role of ethics, privacy, and employee trust in data usage
- Key legal and compliance considerations in global data handling
- Introduction to data governance and responsible access frameworks
- How to articulate the value of analytics to executives and sceptical stakeholders
- Developing your personal roadmap for mastering People Analytics
- Structuring your learning journey based on experience and organisational context
- Building a mindset of continuous measurement and improvement
- Tools for tracking your progress through the course and applying learnings incrementally
Module 2: Strategic Frameworks for People Analytics Success - The 5-Stage Maturity Model for People Analytics capability
- Balanced Scorecard integration for HR performance tracking
- Using the People Analytics Value Chain to prioritise initiatives
- The HR Strategy Map: aligning workforce metrics with business objectives
- How to apply the Workforce Insight Lifecycle: question, data, analysis, action, feedback
- Designing analytics projects around business problems, not just data availability
- SMART goal setting for People Analytics initiatives
- Aligning analytics efforts with organisational KPIs and OKRs
- The role of stakeholder analysis in shaping project scope
- How to build cross-functional coalitions for data success
- Benchmarking your analytics efforts against industry leaders
- Creating a phased rollout plan for analytics adoption
- Introducing the People Analytics Canvas for end-to-end project design
- Mapping data inputs to business decisions: a systems-thinking approach
- Anticipating and mitigating common implementation risks
Module 3: Data Sources, Collection, and Integration - Identifying the most valuable internal data sources: HRIS, ATS, performance systems, surveys
- Understanding the limitations and biases in workforce data
- How to audit data quality and completeness
- Managing missing, inconsistent, and duplicate data entries
- Linking data across systems: employee ID harmonisation techniques
- Capturing qualitative data and making it analytically usable
- Best practices for survey design to support analytics
- Timing, frequency, and cadence of data collection
- How to create a central data repository without expensive tools
- Using spreadsheets effectively for data consolidation
- Introduction to API concepts and how they enable data flow
- Data refresh schedules and version control protocols
- Understanding structured vs unstructured data in HR
- Extracting insights from email, chat, and collaboration platforms (ethically)
- Integrating external data: market benchmarks, economic indicators, labour trends
- Creating a data dictionary and metadata standards
- Documenting data provenance and transformation steps
- Setting up audit trails for compliance and transparency
- Using timestamps and duration variables for behavioural analysis
- Preparing data for longitudinal and cohort-based studies
Module 4: Core Metrics That Drive Business Impact - The difference between metrics, measures, and indicators
- Leading vs lagging indicators in workforce analytics
- Defining clean, consistent formulas for key HR metrics
- Calculating turnover rate with precision and context
- Voluntary vs involuntary vs regrettable turnover: when to measure which
- Calculating time-to-fill, cost-per-hire, and quality-of-hire
- Retention metrics by tenure, role, level, and manager
- Absenteeism rate calculation and pattern detection
- Presenteeism: how to estimate its impact using proxy data
- Workforce cost per employee and FTE productivity ratios
- Headcount planning accuracy and variance analysis
- Succession pipeline depth and readiness scores
- Learning effectiveness: completion rates, skill gain, transfer to job
- Diversity, equity, and inclusion metrics that matter
- Pay equity analysis: identifying unexplained pay gaps
- Engagement scores and their correlation with performance
- Manager effectiveness metrics derived from team outcomes
- Exit interview thematic analysis for predictive insights
- Calculating the true cost of unfilled roles
- Benchmarking metrics against industry and regional standards
Module 5: Advanced Analytics Techniques and Predictive Modelling - Descriptive, diagnostic, predictive, and prescriptive analytics explained
- Correlation vs causation: avoiding common statistical traps
- Using regression analysis to identify workforce drivers
- Logistic regression for predicting binary outcomes like turnover
- Survival analysis for understanding tenure and exit timing
- Cohort analysis techniques for tracking employee journeys
- Calculating employee lifetime value (ELV) and cost
- Predicting high-potential employees using data signals
- Identifying flight risk using multivariate models
- Building early warning systems for attrition hotspots
- Cluster analysis for segmenting employees into meaningful groups
- Using decision trees for workforce classification and recommendations
- Time series analysis for forecasting hiring needs and attrition
- Monte Carlo simulation for workforce scenario planning
- Natural language processing basics for analysing open-ended feedback
- Sentiment analysis from engagement surveys and exit interviews
- Topic modelling to uncover hidden themes in employee communications
- Machine learning principles for HR professionals (non-technical overview)
- Validating model accuracy and avoiding overfitting
- Communicating uncertainty and confidence intervals in predictions
Module 6: Visualisation, Dashboards, and Storytelling with Data - Principles of effective data visualisation for executives
- Choosing the right chart type for your message
- Dashboard design: layout, colour, fonts, and interactivity
- Creating static and dynamic dashboards in spreadsheets
- Best practices for labelling, legends, and annotations
- Avoiding misleading scales, truncations, and visual distortions
- Using conditional formatting to highlight key insights
- Building scorecards for HR business partners
- Linking dashboard elements to strategic goals
- Data storytelling: structuring narratives around insights
- The three-act framework for presenting analytics findings
- Using contrast, tension, and resolution in data presentations
- Turning technical findings into compelling executive summaries
- Anticipating and answering stakeholder questions in advance
- Creating data packs for board-level reporting
- Using before-and-after comparisons to show impact
- Visualising trends, comparisons, distributions, and relationships
- Designing accessible dashboards for diverse audiences
- Incorporating data into change management campaigns
- Measuring the influence of your data story with follow-up metrics
Module 7: Talent Acquisition and Workforce Planning Analytics - Analysing the end-to-end hiring funnel for bottlenecks
- Time-to-hire by role, source, and recruiter
- Cost-per-hire breakdown: advertising, agency, internal costs
- Evaluating sourcing channel effectiveness using ROIs
- Quality-of-hire measurement frameworks
- Time-to-productivity for new hires by role and cohort
- Retention of hires by recruiter, source, and interview panel
- Predictive modelling for candidate success
- Using structured interviews and assessment scores in analytics
- Analysing offer acceptance and decline reasons
- Forecasting hiring needs using business growth models
- Demand-driven workforce planning techniques
- Scenario planning for headcount under different business conditions
- Modelling the impact of automation and restructuring
- Skills gap analysis using internal and external benchmarks
- Creating a talent supply map for critical roles
- Succession analytics: readiness, bench strength, diversity
- Analysing internal mobility and promotion patterns
- Identifying career path bottlenecks and equity issues
- Building heatmaps for talent concentration and flight risk
Module 8: Performance, Engagement, and Retention Analytics - Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- The 5-Stage Maturity Model for People Analytics capability
- Balanced Scorecard integration for HR performance tracking
- Using the People Analytics Value Chain to prioritise initiatives
- The HR Strategy Map: aligning workforce metrics with business objectives
- How to apply the Workforce Insight Lifecycle: question, data, analysis, action, feedback
- Designing analytics projects around business problems, not just data availability
- SMART goal setting for People Analytics initiatives
- Aligning analytics efforts with organisational KPIs and OKRs
- The role of stakeholder analysis in shaping project scope
- How to build cross-functional coalitions for data success
- Benchmarking your analytics efforts against industry leaders
- Creating a phased rollout plan for analytics adoption
- Introducing the People Analytics Canvas for end-to-end project design
- Mapping data inputs to business decisions: a systems-thinking approach
- Anticipating and mitigating common implementation risks
Module 3: Data Sources, Collection, and Integration - Identifying the most valuable internal data sources: HRIS, ATS, performance systems, surveys
- Understanding the limitations and biases in workforce data
- How to audit data quality and completeness
- Managing missing, inconsistent, and duplicate data entries
- Linking data across systems: employee ID harmonisation techniques
- Capturing qualitative data and making it analytically usable
- Best practices for survey design to support analytics
- Timing, frequency, and cadence of data collection
- How to create a central data repository without expensive tools
- Using spreadsheets effectively for data consolidation
- Introduction to API concepts and how they enable data flow
- Data refresh schedules and version control protocols
- Understanding structured vs unstructured data in HR
- Extracting insights from email, chat, and collaboration platforms (ethically)
- Integrating external data: market benchmarks, economic indicators, labour trends
- Creating a data dictionary and metadata standards
- Documenting data provenance and transformation steps
- Setting up audit trails for compliance and transparency
- Using timestamps and duration variables for behavioural analysis
- Preparing data for longitudinal and cohort-based studies
Module 4: Core Metrics That Drive Business Impact - The difference between metrics, measures, and indicators
- Leading vs lagging indicators in workforce analytics
- Defining clean, consistent formulas for key HR metrics
- Calculating turnover rate with precision and context
- Voluntary vs involuntary vs regrettable turnover: when to measure which
- Calculating time-to-fill, cost-per-hire, and quality-of-hire
- Retention metrics by tenure, role, level, and manager
- Absenteeism rate calculation and pattern detection
- Presenteeism: how to estimate its impact using proxy data
- Workforce cost per employee and FTE productivity ratios
- Headcount planning accuracy and variance analysis
- Succession pipeline depth and readiness scores
- Learning effectiveness: completion rates, skill gain, transfer to job
- Diversity, equity, and inclusion metrics that matter
- Pay equity analysis: identifying unexplained pay gaps
- Engagement scores and their correlation with performance
- Manager effectiveness metrics derived from team outcomes
- Exit interview thematic analysis for predictive insights
- Calculating the true cost of unfilled roles
- Benchmarking metrics against industry and regional standards
Module 5: Advanced Analytics Techniques and Predictive Modelling - Descriptive, diagnostic, predictive, and prescriptive analytics explained
- Correlation vs causation: avoiding common statistical traps
- Using regression analysis to identify workforce drivers
- Logistic regression for predicting binary outcomes like turnover
- Survival analysis for understanding tenure and exit timing
- Cohort analysis techniques for tracking employee journeys
- Calculating employee lifetime value (ELV) and cost
- Predicting high-potential employees using data signals
- Identifying flight risk using multivariate models
- Building early warning systems for attrition hotspots
- Cluster analysis for segmenting employees into meaningful groups
- Using decision trees for workforce classification and recommendations
- Time series analysis for forecasting hiring needs and attrition
- Monte Carlo simulation for workforce scenario planning
- Natural language processing basics for analysing open-ended feedback
- Sentiment analysis from engagement surveys and exit interviews
- Topic modelling to uncover hidden themes in employee communications
- Machine learning principles for HR professionals (non-technical overview)
- Validating model accuracy and avoiding overfitting
- Communicating uncertainty and confidence intervals in predictions
Module 6: Visualisation, Dashboards, and Storytelling with Data - Principles of effective data visualisation for executives
- Choosing the right chart type for your message
- Dashboard design: layout, colour, fonts, and interactivity
- Creating static and dynamic dashboards in spreadsheets
- Best practices for labelling, legends, and annotations
- Avoiding misleading scales, truncations, and visual distortions
- Using conditional formatting to highlight key insights
- Building scorecards for HR business partners
- Linking dashboard elements to strategic goals
- Data storytelling: structuring narratives around insights
- The three-act framework for presenting analytics findings
- Using contrast, tension, and resolution in data presentations
- Turning technical findings into compelling executive summaries
- Anticipating and answering stakeholder questions in advance
- Creating data packs for board-level reporting
- Using before-and-after comparisons to show impact
- Visualising trends, comparisons, distributions, and relationships
- Designing accessible dashboards for diverse audiences
- Incorporating data into change management campaigns
- Measuring the influence of your data story with follow-up metrics
Module 7: Talent Acquisition and Workforce Planning Analytics - Analysing the end-to-end hiring funnel for bottlenecks
- Time-to-hire by role, source, and recruiter
- Cost-per-hire breakdown: advertising, agency, internal costs
- Evaluating sourcing channel effectiveness using ROIs
- Quality-of-hire measurement frameworks
- Time-to-productivity for new hires by role and cohort
- Retention of hires by recruiter, source, and interview panel
- Predictive modelling for candidate success
- Using structured interviews and assessment scores in analytics
- Analysing offer acceptance and decline reasons
- Forecasting hiring needs using business growth models
- Demand-driven workforce planning techniques
- Scenario planning for headcount under different business conditions
- Modelling the impact of automation and restructuring
- Skills gap analysis using internal and external benchmarks
- Creating a talent supply map for critical roles
- Succession analytics: readiness, bench strength, diversity
- Analysing internal mobility and promotion patterns
- Identifying career path bottlenecks and equity issues
- Building heatmaps for talent concentration and flight risk
Module 8: Performance, Engagement, and Retention Analytics - Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- The difference between metrics, measures, and indicators
- Leading vs lagging indicators in workforce analytics
- Defining clean, consistent formulas for key HR metrics
- Calculating turnover rate with precision and context
- Voluntary vs involuntary vs regrettable turnover: when to measure which
- Calculating time-to-fill, cost-per-hire, and quality-of-hire
- Retention metrics by tenure, role, level, and manager
- Absenteeism rate calculation and pattern detection
- Presenteeism: how to estimate its impact using proxy data
- Workforce cost per employee and FTE productivity ratios
- Headcount planning accuracy and variance analysis
- Succession pipeline depth and readiness scores
- Learning effectiveness: completion rates, skill gain, transfer to job
- Diversity, equity, and inclusion metrics that matter
- Pay equity analysis: identifying unexplained pay gaps
- Engagement scores and their correlation with performance
- Manager effectiveness metrics derived from team outcomes
- Exit interview thematic analysis for predictive insights
- Calculating the true cost of unfilled roles
- Benchmarking metrics against industry and regional standards
Module 5: Advanced Analytics Techniques and Predictive Modelling - Descriptive, diagnostic, predictive, and prescriptive analytics explained
- Correlation vs causation: avoiding common statistical traps
- Using regression analysis to identify workforce drivers
- Logistic regression for predicting binary outcomes like turnover
- Survival analysis for understanding tenure and exit timing
- Cohort analysis techniques for tracking employee journeys
- Calculating employee lifetime value (ELV) and cost
- Predicting high-potential employees using data signals
- Identifying flight risk using multivariate models
- Building early warning systems for attrition hotspots
- Cluster analysis for segmenting employees into meaningful groups
- Using decision trees for workforce classification and recommendations
- Time series analysis for forecasting hiring needs and attrition
- Monte Carlo simulation for workforce scenario planning
- Natural language processing basics for analysing open-ended feedback
- Sentiment analysis from engagement surveys and exit interviews
- Topic modelling to uncover hidden themes in employee communications
- Machine learning principles for HR professionals (non-technical overview)
- Validating model accuracy and avoiding overfitting
- Communicating uncertainty and confidence intervals in predictions
Module 6: Visualisation, Dashboards, and Storytelling with Data - Principles of effective data visualisation for executives
- Choosing the right chart type for your message
- Dashboard design: layout, colour, fonts, and interactivity
- Creating static and dynamic dashboards in spreadsheets
- Best practices for labelling, legends, and annotations
- Avoiding misleading scales, truncations, and visual distortions
- Using conditional formatting to highlight key insights
- Building scorecards for HR business partners
- Linking dashboard elements to strategic goals
- Data storytelling: structuring narratives around insights
- The three-act framework for presenting analytics findings
- Using contrast, tension, and resolution in data presentations
- Turning technical findings into compelling executive summaries
- Anticipating and answering stakeholder questions in advance
- Creating data packs for board-level reporting
- Using before-and-after comparisons to show impact
- Visualising trends, comparisons, distributions, and relationships
- Designing accessible dashboards for diverse audiences
- Incorporating data into change management campaigns
- Measuring the influence of your data story with follow-up metrics
Module 7: Talent Acquisition and Workforce Planning Analytics - Analysing the end-to-end hiring funnel for bottlenecks
- Time-to-hire by role, source, and recruiter
- Cost-per-hire breakdown: advertising, agency, internal costs
- Evaluating sourcing channel effectiveness using ROIs
- Quality-of-hire measurement frameworks
- Time-to-productivity for new hires by role and cohort
- Retention of hires by recruiter, source, and interview panel
- Predictive modelling for candidate success
- Using structured interviews and assessment scores in analytics
- Analysing offer acceptance and decline reasons
- Forecasting hiring needs using business growth models
- Demand-driven workforce planning techniques
- Scenario planning for headcount under different business conditions
- Modelling the impact of automation and restructuring
- Skills gap analysis using internal and external benchmarks
- Creating a talent supply map for critical roles
- Succession analytics: readiness, bench strength, diversity
- Analysing internal mobility and promotion patterns
- Identifying career path bottlenecks and equity issues
- Building heatmaps for talent concentration and flight risk
Module 8: Performance, Engagement, and Retention Analytics - Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- Principles of effective data visualisation for executives
- Choosing the right chart type for your message
- Dashboard design: layout, colour, fonts, and interactivity
- Creating static and dynamic dashboards in spreadsheets
- Best practices for labelling, legends, and annotations
- Avoiding misleading scales, truncations, and visual distortions
- Using conditional formatting to highlight key insights
- Building scorecards for HR business partners
- Linking dashboard elements to strategic goals
- Data storytelling: structuring narratives around insights
- The three-act framework for presenting analytics findings
- Using contrast, tension, and resolution in data presentations
- Turning technical findings into compelling executive summaries
- Anticipating and answering stakeholder questions in advance
- Creating data packs for board-level reporting
- Using before-and-after comparisons to show impact
- Visualising trends, comparisons, distributions, and relationships
- Designing accessible dashboards for diverse audiences
- Incorporating data into change management campaigns
- Measuring the influence of your data story with follow-up metrics
Module 7: Talent Acquisition and Workforce Planning Analytics - Analysing the end-to-end hiring funnel for bottlenecks
- Time-to-hire by role, source, and recruiter
- Cost-per-hire breakdown: advertising, agency, internal costs
- Evaluating sourcing channel effectiveness using ROIs
- Quality-of-hire measurement frameworks
- Time-to-productivity for new hires by role and cohort
- Retention of hires by recruiter, source, and interview panel
- Predictive modelling for candidate success
- Using structured interviews and assessment scores in analytics
- Analysing offer acceptance and decline reasons
- Forecasting hiring needs using business growth models
- Demand-driven workforce planning techniques
- Scenario planning for headcount under different business conditions
- Modelling the impact of automation and restructuring
- Skills gap analysis using internal and external benchmarks
- Creating a talent supply map for critical roles
- Succession analytics: readiness, bench strength, diversity
- Analysing internal mobility and promotion patterns
- Identifying career path bottlenecks and equity issues
- Building heatmaps for talent concentration and flight risk
Module 8: Performance, Engagement, and Retention Analytics - Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- Linking engagement survey data to operational outcomes
- Analysing eNPS trends by team, location, and tenure
- Identifying engagement drivers through statistical analysis
- Measuring the ROI of engagement initiatives
- Turnover cost modelling: separation, replacement, lost productivity
- Calculating regrettable vs non-regrettable attrition
- Analysing exit interview themes quantitatively and qualitatively
- Building predictive models for flight risk at individual and team levels
- Linking manager behaviours to team retention and performance
- Analysing performance distribution across the organisation
- Calibration analytics: identifying rater leniency and bias
- Performance potential matrices using data, not just perception
- Linking learning participation to performance improvement
- Measuring the impact of recognition programmes on motivation
- Analysing burnout signals through absence and system usage patterns
- Using well-being survey data to inform support initiatives
- Remote work analytics: productivity, connectivity, isolation risks
- Hybrid work model effectiveness by team and function
- Analysing digital footprint data ethically to understand collaboration
- Creating early intervention systems for at-risk employees
Module 9: Learning, Development, and Skills Analytics - Measuring training completion, satisfaction, and application
- Kirkpatrick model integration with data collection
- Linking learning hours to performance and promotion
- Skills inventory creation and maintenance
- Mapping current vs required skills by role and future state
- Using data to personalise learning pathways
- Calculating return on learning investment (ROLI)
- Analysing cost-per-learner and cost-per-skill-gained
- Identifying high-impact training programmes through A/B testing
- Peer learning network analysis and facilitation
- Measuring knowledge retention over time
- Analysing internal certification uptake and impact
- Using pre- and post-assessment scores for skill gain measurement
- Tracking informal learning through collaboration data
- Skills adjacency analysis for career mobility
- Forecasting future skill needs based on strategy
- Identifying learning deserts and equity gaps
- Analysing mentorship programme outcomes
- Measuring coachability and growth mindset indicators
- Building a learning culture index
Module 10: Leadership, Diversity, and Inclusion Analytics - Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- Leadership pipeline analytics by gender, ethnicity, age
- Promotion rate disparities and equity benchmarks
- Representation metrics across levels, functions, and regions
- Pay equity analysis: controlling for role, experience, performance
- Conducting intersectional analysis (e.g., gender x ethnicity)
- Measuring the impact of D&I initiatives on business outcomes
- Analysing sponsorship and mentorship access by group
- Turnover and engagement gaps among underrepresented groups
- Inclusive meeting participation metrics (from calendar data)
- Language analysis in performance reviews for bias detection
- Building a D&I maturity dashboard
- Setting science-based targets for representation improvement
- Tracking supplier diversity and external impact
- Measuring psychological safety through survey composites
- Leadership effectiveness by team diversity characteristics
- Succession planning inclusiveness metrics
- Equity in access to high-visibility projects
- Analyzing retention of diverse talent by manager
- Measuring the business case for inclusion using performance data
- Creating a Chief Diversity Officer dashboard
Module 11: Hands-On Projects and Applied Case Studies - Project 1: Build a turnover prediction model using real-world sample data
- Project 2: Design and implement a recruitment funnel analysis
- Project 3: Create an engagement driver report for senior leaders
- Project 4: Develop a skills gap analysis for a critical function
- Project 5: Construct a compensation equity audit framework
- Project 6: Build a performance calibration dashboard
- Project 7: Design a leadership pipeline health report
- Project 8: Develop a workforce planning scenario model
- Project 9: Conduct a cost-of-vacancy analysis for key roles
- Project 10: Create a learning impact evaluation report
- Analysing real anonymised datasets from global organisations
- Applying statistical techniques to solve actual business problems
- Using templates to structure project deliverables
- Peer review guidance for improving analytical rigour
- Receiving feedback on your methodology and presentation
- Iterating on projects to refine insights and recommendations
- Documenting your analytical process for audit and replication
- Presenting findings as if to a C-suite audience
- Linking recommendations to actionable next steps
- Building a portfolio of analytics work for career advancement
Module 12: Integration, Change Management, and Organisational Adoption - Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability
Module 13: Certification, Career Advancement, and Next Steps - Overview of the certification process and requirements
- Completing the final assessment: applied case submission
- Peer review and expert evaluation of your work
- Receiving your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn, CV, and professional profiles
- Leveraging certification in job applications and promotion discussions
- Networking with alumni and industry practitioners
- Joining the Practitioner Community for ongoing support
- Accessing monthly content updates and industry insights
- Staying current with emerging trends in People Analytics
- Pursuing advanced specialisations and follow-on programs
- Transitioning into roles such as HR Analyst, People Scientist, OD Consultant
- Negotiating higher compensation using demonstrated analytics capability
- Becoming an internal champion for data-driven HR
- Building a personal brand as a trusted analytics advisor
- Using gamified progress tracking to stay motivated
- Setting long-term career goals with analytics at the core
- Mentorship pathways for post-certification growth
- Accessing exclusive job boards and opportunities
- Continuously applying and evolving your skills with lifetime access
- Developing a People Analytics implementation roadmap
- Creating a business case for analytics investment
- Securing buy-in from HR and business leaders
- Running pilot projects to demonstrate early wins
- Scaling analytics from one team to enterprise level
- Building a centre of excellence for People Analytics
- Defining roles: People Analyst, HRBP, Data Steward
- Establishing data sharing agreements across departments
- Running effective data review meetings with leadership
- Embedding analytics into regular HR processes
- Training non-analysts to interpret data correctly
- Creating self-serve dashboards for managers
- Developing a data literacy curriculum for HR teams
- Managing resistance to data-driven decision making
- Communicating insights without triggering defensiveness
- Linking analytics to performance management systems
- Integrating insights into talent review cycles
- Using data to support organisational redesign
- Measuring the adoption and impact of analytics initiatives
- Continuous improvement of analytics capability