Descriptive analytics

Definition

Descriptive analytics refers to the process of analyzing historical data to understand trends, patterns, and insights that can inform decision-making. It provides a summary of past events, helping organizations identify what has happened in their operations, such as employee performance and turnover rates. This analysis is crucial in human resources as it lays the foundation for more advanced analytics, guiding strategies and improving workforce management.

5 Must Know Facts For Your Next Test

1. Descriptive analytics often employs various statistical methods to summarize large datasets, providing a clear view of historical performance.
2. In HR, descriptive analytics can help organizations assess employee satisfaction levels by analyzing past survey results.
3. It enables companies to track key performance indicators (KPIs) over time, aiding in workforce planning and management decisions.
4. Dashboards and reports generated from descriptive analytics can facilitate real-time monitoring of HR metrics.
5. By understanding historical data through descriptive analytics, organizations can identify areas for improvement before implementing predictive or prescriptive analytics.

Review Questions

• How does descriptive analytics support decision-making in human resources?
  • Descriptive analytics supports decision-making in human resources by providing a comprehensive overview of historical data, which helps HR professionals identify trends and patterns related to employee performance, turnover rates, and engagement levels. By analyzing past events, HR can make informed decisions about recruitment strategies, training programs, and employee retention initiatives. This foundational understanding allows organizations to tailor their approaches effectively based on historical insights.
• Discuss the relationship between descriptive analytics and predictive analytics in HR practices.
  • Descriptive analytics serves as a building block for predictive analytics in HR practices. While descriptive analytics focuses on summarizing historical data to understand what has happened, predictive analytics takes this a step further by using that historical data to forecast future outcomes. For example, HR departments can analyze past employee turnover rates with descriptive analytics and then apply predictive models to anticipate future turnover trends, enabling proactive strategies to retain talent.
• Evaluate the implications of using descriptive analytics for workforce management in an organization.
  • Using descriptive analytics for workforce management has significant implications for an organization’s effectiveness. By leveraging insights from historical data, HR teams can identify strengths and weaknesses within their workforce. This evaluation helps create targeted training programs, enhance employee engagement strategies, and improve overall organizational performance. Furthermore, understanding past trends allows companies to allocate resources more efficiently and develop strategic plans that align with their workforce dynamics.

Related terms

Predictive Analytics: A form of analytics that uses historical data and statistical algorithms to forecast future outcomes and trends.

Business Intelligence: Technologies and strategies used by organizations for data analysis of business information to support better business decision-making.

Data Visualization: The representation of data through visual elements like charts and graphs, making complex data more accessible and understandable.