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Role of HR Analytics in Decision Making

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

Role of HR Analytics in Decision Making

Objective: Demonstrate how HR analytics can inform and improve organizational decision making.

Context: With the rise of data-driven management in India, HR analytics offers powerful tools for optimizing workforce strategies and outcomes, but many firms underutilize these insights.

What you'll build: You will identify relevant HR data sources, analyze key HR metrics using Excel, Power BI, Tableau, or statistical software like SPSS, R, and Python, and develop predictive models to uncover actionable insights. The project emphasizes interpreting HR data to support strategic decisions and improve business performance.

Deliverables: Deliver a working analytics dashboard, predictive model outputs, and a summary report with recommendations.

Milestones

1. Identify HR data sources

10 marks 7d

List at least three distinct HR data sources relevant to workforce analytics, such as employee surveys, payroll records, or performance evaluations. For each source, briefly describe the type of data collected and its potential value in HR decision-making. Submit your findings in a clearly organized table or bullet-pointed list.

2. Analyze key metrics

10 marks 7d

Select two critical HR metrics (e.g., turnover rate, time-to-hire) from your identified data sources. Calculate these metrics using sample or real data, and present your analysis with supporting charts or tables. Ensure your submission clearly explains the calculation method and interprets what the results indicate for HR strategy.

3. Showcase predictive models

15 marks 7d

Develop and present at least one predictive model (e.g., logistic regression for attrition risk) using HR data. Include a summary of the modeling process, key variables used, and the model's predictive performance (such as accuracy or ROC curve). Submit your code, outputs, and a brief explanation of how the model supports HR decision-making.

4. Recommend actionable insights

15 marks 9d

Based on your metric analysis and predictive modeling, propose two specific, data-driven recommendations for HR policy or process improvement. Clearly justify each recommendation with evidence from your findings, and describe the expected impact on organizational outcomes. Submit your recommendations in a concise, actionable format.

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Upcoming sessions

Session	Window	Enrolled
Role of HR Analytics in Decision Making	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

data-start="630" data-end="646"> HR Analyticsdata-start="647" data-end="683"> Data Analysis and Interpretationdata-start="684" data-end="707"> HR Metrics and KPIsdata-start="708" data-end="730"> Data Visualizationdata-start="731" data-end="761"> Decision-Making Frameworksdata-start="762" data-end="807"> Report Writing and Business Communication

Tools used

Analytics Tools: Microsoft ExcelPower BITableau Statistical Software: SPSSRPython (PandasMatplotlibSeaborn) HR Software: SAP SuccessFactorsBambooHRWorkday (for real-world examples) Survey Tools: Google FormsSurveyMonkey (for primary data) Documentation: MS WordPowerPoint

Prerequisites

Basic knowledge of HR functions (recruitmentretentionperformanceetc.) Familiarity with statistics and data interpretation Understanding of decision-making processes in HR Introduction to data analytics tools

Available mentors

Priyang Kumar

Free

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