Types of Data Analytics

Four Types of Analysis

Overview

  • In this section, four main types of analysis are discussed:

    • Descriptive Analysis

    • Diagnostic Analysis

    • Predictive Analysis

    • Prescriptive Analysis

  • Importance of understanding these analyses for compensation and benefits analysts, especially as they advance in their careers.

Descriptive Analysis

  • Definition: Descriptive analysis refers to the summarization of raw and historical data into an understandable format.

  • Key Features:

    • Answers the question: "What happened?"

    • Summarizes historical events and processes.

  • Example in Compensation and Benefits:

    • Creating a headcount report of all employees eligible to participate in a compensation and benefits package in preparation for open enrollment time.

Diagnostic Analysis

  • Definition: Diagnostic analysis seeks to understand the cause and effect relationships within the dataset.

  • Key Features:

    • Investigates factors or variables contributing to specific outcomes or behaviors.

    • Answers the question: "Why did it happen?"

  • Scenario Application:

    • In a medical context, when a doctor asks questions to determine what happened, it reflects diagnostic analysis.

Predictive Analysis

  • Definition: Predictive analysis is focused on statistical models and forecasting based on historical data.

  • Key Features:

    • Uses patterns identified from descriptive analysis to anticipate future outcomes.

    • Answers the question: "What is likely to happen in the future?"

  • Application in Benefits:

    • Proactively finding or anticipating the organization and employees' needs regarding future benefits and compensation.

  • Example:

    • A doctor advises on possible future health outcomes if a condition is untreated as part of predictive analysis.

Prescriptive Analysis

  • Definition: Prescriptive analysis combines descriptive and predictive analytics to provide actionable recommendations.

  • Key Features:

    • Answers the question: "How should we act based on the data?"

    • Helps organizations decide on future actions based on current trends and predictions.

  • Analogy in Technology:

    • Platforms like Spotify or Netflix use prescriptive analytics to recommend content based on previous usage patterns.

  • Application in Compensation and Benefits:

    • A compensation and benefits analyst can identify patterns from current offerings and make recommendations for future benefits based on employee usage and requests.

  • Connection Highlight:

    • This analysis helps organizations optimize their compensation and benefits offerings, enhancing employee satisfaction and alignment with actual needs.

Conclusion

  • Understanding and utilizing these four types of analysis is crucial for a successful career as a compensation and benefits analyst, enabling informed decision-making and proactive future planning.