| Lecture 1 |
-- |
Topics: (no slides)
- Formal introduction
- Course details
- Syllabus
|
|
|
| Lecture 2 |
-- |
Topics: (slides)
- HR analytics intro why analytics in HR; evidence-based HR; maturity model
|
|
|
| Lecture 3 |
-- |
Topics: (slides)
- HR data landscape HRIS/ATS/LMS/payroll; data privacy; definitions and standards
|
|
|
| Lecture 4 |
-- |
Topics: (slides)
- Metrics that matter headcount/FTE, turnover, time-to-fill, cost-per-hire; dashboards
|
|
|
| Lecture 5 |
-- |
Topics: (slides)
- Metrics that matter headcount/FTE, turnover, time-to-fill, cost-per-hire; dashboards
|
|
|
| Lecture 6 |
-- |
Topics: (slides)
- Metrics that matter headcount/FTE, turnover, time-to-fill, cost-per-hire; dashboards
|
|
|
| Lecture 7 |
-- |
Topics: (slides)
- Metrics that matter headcount/FTE, turnover, time-to-fill, cost-per-hire; dashboards
|
|
|
| Lecture 8 |
-- |
Topics: (slides)
- Data cleaning & quality missing values, coding, bias in measurement; HR data dictionary
|
|
|
| Lecture 9 |
-- |
Topics: (slides)
- Data cleaning & quality missing values, coding, bias in measurement; HR data dictionary
|
|
|
| Lecture 10 |
-- |
Topics: (slides)
- Data cleaning & quality missing values, coding, bias in measurement; HR data dictionary
|
|
|
| Lecture 11 |
-- |
Topics: (slides)
- Descriptive analytics slices by BU/location/grade; segmentation; visualization basics
|
|
|
| Lecture 12 |
-- |
Topics: (slides)
- Descriptive analytics slices by BU/location/grade; segmentation; visualization basics
|
|
|
| Lecture 13 |
-- |
Topics: (slides)
- Descriptive analytics slices by BU/location/grade; segmentation; visualization basics
|
|
|
| Lecture 14 |
-- |
Topics: (slides)
- Attrition analytics I voluntary vs involuntary; cohorts; survival/tenure curves intuition
|
|
|
| Lecture 15 |
-- |
Topics: (slides)
- Attrition analytics I voluntary vs involuntary; cohorts; survival/tenure curves intuition
|
|
|
| Lecture 16 |
-- |
Topics: (slides)
- Attrition analytics II drivers; interviews vs data; building an attrition risk model (concept).
|
|
|
| Lecture 17 |
-- |
Topics: (slides)
- Attrition analytics II drivers; interviews vs data; building an attrition risk model (concept).
|
|
|
| Lecture 18 |
-- |
Topics: (slides)
- Recruitment analytics funnel, source effectiveness, quality-of-hire; adverse impact basics.
|
|
|
| Lecture 19 |
-- |
Topics: (slides)
- Recruitment analytics funnel, source effectiveness, quality-of-hire; adverse impact basics.
|
|
|
| Lecture 20 |
-- |
Topics: (slides)
- Performance analytics ratings bias, calibration, OKRs/KPIs; linking performance to outcomes.
|
|
|
|
-- |
-- |
(Feb 25) Last Date for Proposal Submission. |
|
|
-- |
-- |
Mid Semester Exam Week |
Best of Luck.
|
| Lecture 21 |
-- |
Topics: (slides)
- Performance analytics ratings bias, calibration, OKRs/KPIs; linking performance to outcomes.
|
|
|
| Lecture 22 |
-- |
Topics: (slides)
- Compensation analytics pay equity, compa-ratio, banding; total rewards effectiveness.
|
|
|
| Lecture 23 |
-- |
Topics: (slides)
- Compensation analytics pay equity, compa-ratio, banding; total rewards effectiveness.
|
|
|
| Lecture 24 |
-- |
Topics: (slides)
- Learning & development training effectiveness, Kirkpatrick levels, skills analytics.
|
|
|
| Lecture 25 |
-- |
Topics: (slides)
- Learning & development training effectiveness, Kirkpatrick levels, skills analytics.
|
|
|
| Lecture 26 |
-- |
Topics: (slides)
- Engagement analytics surveys, eNPS, sentiment; action planning and causality caveats
|
|
|
| Lecture 27 |
-- |
Topics: (slides)
- Engagement analytics surveys, eNPS, sentiment; action planning and causality caveats
|
|
|
| Lecture 28 |
-- |
Topics: (slides)
- Workforce planning demand/supply forecasting; skills gap; scenario planning
|
|
|
| Lecture 29 |
-- |
Topics: (slides)
- Workforce planning demand/supply forecasting; skills gap; scenario planning
|
|
|
| Lecture 30 |
-- |
Topics: (slides)
- Diversity, equity, inclusion analytics representation, mobility, pay equity; fairness metrics.
|
|
|
| Lecture 31 |
-- |
Topics: (slides)
- Diversity, equity, inclusion analytics representation, mobility, pay equity; fairness metrics.
|
|
|
| Lecture 32 |
-- |
Topics: (slides)
- Causal thinking in HR correlation vs causation; experiments and quasi-experiments
|
|
|
|
-- |
-- |
(Mar 30) - Last Date of Mid Presentation. |
|
| Lecture 33 |
-- |
Topics: (slides)
- Predictive modeling basics classification/regression; overfitting; validation; interpretability.
|
|
|
| Lecture 34 |
-- |
Topics: (slides)
- Predictive modeling basics classification/regression; overfitting; validation; interpretability.
|
|
|
| Lecture 35 |
-- |
Topics: (slides)
- Predictive modeling basics classification/regression; overfitting; validation; interpretability.
|
|
|
| Lecture 36 |
-- |
Topics: (slides)
- People risk & compliance privacy, governance, audit trails; ethical constraints
|
|
|
| Lecture 37 |
-- |
Topics: (slides)
- Storytelling with HR data executive narratives, visuals, recommendations and tradeoffs
|
|
|
| Lecture 38 |
-- |
Topics: (slides)
- Storytelling with HR data executive narratives, visuals, recommendations and tradeoffs
|
|
|
| Lecture 39 |
-- |
Topics: (slides)
- Storytelling with HR data executive narratives, visuals, recommendations and tradeoffs
|
|
|
| Lecture 40 |
-- |
Topics: (slides)
- Building an HR analytics function operating model, tools, stakeholder management
|
|
|
| Lecture 41 |
-- |
Topics: (slides)
- Capstone & Presentations an HR business problem solved end-to-end
|
|
|
| Lecture 42 |
-- |
Topics: (slides)
|
|
|
|
-- |
-- |
(Apl 30) Last Date of Codes Submission. |
|
|
-- |
-- |
(Apl 30) Dead Line for Final Presentation Video Submission. |
|
|
-- |
-- |
(Apl 30) Dead Line for Report Submission. |
|
|
-- |
-- |
End Semester Exam Week |
Best of Luck.
|
|
Link Added on Last Date for Submission :
|
BM622H
