Human Resource Management (HRM) 101: HR Analytics and Technology People Analytics Descriptive Predictive Prescriptive

What This Is

People Analytics is the application of data analysis and statistical techniques to understand and improve HR-related processes and outcomes. This involves using descriptive, predictive, and prescriptive analytics to inform HR decisions. For example, Google uses People Analytics to optimize its hiring process, reducing time-to-hire by 25% and increasing diversity by 30%. By leveraging data, Google can make more informed decisions about talent acquisition, development, and retention.

Key Models & Frameworks

• Descriptive Analytics: The process of analyzing historical data to understand what has happened. This involves summarizing and visualizing data to identify trends and patterns.
• Predictive Analytics: The use of statistical models and machine learning algorithms to forecast future outcomes based on historical data. This involves identifying correlations and causal relationships between variables.
• Prescriptive Analytics: The application of analytics to recommend specific actions or decisions based on predictive models. This involves using data to inform strategic decisions and optimize business outcomes.
• Kirkpatrick's Four Levels: A model for evaluating training effectiveness, which includes Reaction, Learning, Behavior, and Results.
• Hofstede's Cultural Dimensions: A framework for understanding cultural differences between countries, which includes Power Distance, Individualism, Masculinity, Uncertainty Avoidance, Long-Term Orientation, and Indulgence.
• The Balanced Scorecard: A framework for measuring organizational performance, which includes Financial, Customer, Internal Processes, and Learning and Growth perspectives.
• The McKinsey 7S Framework: A model for understanding organizational design and effectiveness, which includes Strategy, Structure, Systems, Skills, Style, Staff, and Shared Values.
• The HR Business Partner (HRBP) Model: A framework for HR professionals to partner with business leaders, which includes HRBP roles, responsibilities, and competencies.
• The HR Analytics Maturity Model: A framework for assessing HR analytics capabilities, which includes levels of maturity, such as Descriptive, Predictive, and Prescriptive.

Legal & Compliance Notes

• Title VII of the Civil Rights Act: Prohibits employment discrimination based on race, color, national origin, sex, or religion.
• FLSA (Fair Labor Standards Act): Regulates minimum wage, overtime pay, and child labor laws.
• OSHA (Occupational Safety and Health Act): Regulates workplace safety and health standards.
• NLRA (National Labor Relations Act): Protects employees' right to organize and engage in collective bargaining.

Step-by-Step Process

1. Define the problem or opportunity: Identify the HR-related issue or opportunity that requires analytics.
2. Gather and clean data: Collect relevant data from various sources, such as HR systems, surveys, and external databases.
3. Analyze and interpret data: Use statistical techniques and machine learning algorithms to analyze and interpret the data.
4. Develop predictive models: Create predictive models to forecast future outcomes based on historical data.
5. Prescribe actions or decisions: Use predictive models to recommend specific actions or decisions to address the problem or opportunity.
6. Monitor and evaluate results: Track the effectiveness of the recommended actions or decisions and adjust the analytics process as needed.

Common Mistakes

• Mistake: Assuming that HR analytics is only about data analysis and not about business acumen.
• Correction: HR analytics requires a deep understanding of business operations and strategy to inform data-driven decisions.
• Mistake: Failing to communicate analytics insights effectively to stakeholders.
• Correction: HR analytics professionals must be able to communicate complex data insights in a clear and concise manner to influence business decisions.
• Mistake: Ignoring the importance of data quality and accuracy.
• Correction: HR analytics relies on high-quality and accurate data to produce reliable insights.

Exam / Certification Tips

• Tricky distinction: Exempt vs non-exempt employees under the FLSA.
• Common question pattern: Case studies that require HR analytics professionals to apply data-driven insights to real-world business problems.
• Important concept: The difference between descriptive, predictive, and prescriptive analytics.

Quick Practice Scenario

Scenario: A company experiences a high turnover rate among its customer-facing employees. What is the first step in using HR analytics to address this issue?

Answer: Define the problem or opportunity, including the specific metrics and data required to understand the issue.

Explanation: The first step in using HR analytics is to clearly define the problem or opportunity, including the specific metrics and data required to understand the issue. This involves gathering relevant data, such as turnover rates, employee satisfaction surveys, and performance metrics.

Last-Minute Cram Sheet

• Descriptive analytics: Analyzes historical data to understand what has happened.
• Predictive analytics: Forecasts future outcomes based on historical data.
• Prescriptive analytics: Recommends specific actions or decisions based on predictive models.
• Kirkpatrick's Four Levels: Reaction, Learning, Behavior, and Results.
• Hofstede's Cultural Dimensions: Power Distance, Individualism, Masculinity, Uncertainty Avoidance, Long-Term Orientation, and Indulgence.
• The Balanced Scorecard: Financial, Customer, Internal Processes, and Learning and Growth perspectives.
• The McKinsey 7S Framework: Strategy, Structure, Systems, Skills, Style, Staff, and Shared Values.
• The HR Business Partner (HRBP) Model: HRBP roles, responsibilities, and competencies.
• The HR Analytics Maturity Model: Descriptive, Predictive, and Prescriptive levels of maturity.
• Title VII of the Civil Rights Act: Prohibits employment discrimination based on race, color, national origin, sex, or religion.
• FLSA (Fair Labor Standards Act): Regulates minimum wage, overtime pay, and child labor laws.
• OSHA (Occupational Safety and Health Act): Regulates workplace safety and health standards.
• NLRA (National Labor Relations Act): Protects employees' right to organize and engage in collective bargaining.
• ⚠️ Exempt means no overtime pay – not 'exempt from all labor laws'.