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Let's start with descriptive analytics. This type of analytics helps us understand past events, like employee turnover. It tells us what has happened over a specified period.
Can you give us an example of how descriptive analytics is used in HR?
Certainly! For example, by analyzing last year's turnover rates, HR can pinpoint trends and determine why employees left.
So descriptive analytics is really about looking back?
Exactly! Remember, we can think of it as the ‘what’ of analytics. It lays the foundation for further insights.
To recap, descriptive analytics answers the question: 'What has happened?'
Now, let's move on to predictive analytics. This involves forecasting what may happen in the future.
So, does that mean it can tell us who is likely to leave the company?
Yes, that's right! For instance, by analyzing patterns in employee data, we can predict which employees are at risk of leaving.
What kind of data would be used for that?
Good question! We would look at factors like performance ratings, satisfaction surveys, and even attendance records.
To summarize, predictive analytics answers the question: 'What might happen in the future?'
Finally, we have prescriptive analytics. This form not only predicts but also suggests actions to achieve specific outcomes.
How does that work exactly?
Great question! For instance, if predictive analytics indicates a risk of high turnover, prescriptive analytics may recommend specific retention strategies, like enhanced training programs.
So it’s like a road map for HR decisions?
Exactly! Remember: prescriptive analytics answers the question: 'What should we do?'
In conclusion, HR analytics is vital in moving from intuition-based to evidence-based decision-making.
Descriptive tells the tale, of events gone by; Predictive looks ahead, to what may lie nigh. Prescriptive shows the path, to take and not to shy.
Once a wise HR manager used past data (descriptive) to see trends, predicted future turnover (predictive), and prescribed training programs (prescriptive) to improve employee retention.
Don't forget: 'D, P, and P' for Descriptive, Predictive, and Prescriptive - the three pillars of HR analytics.
Remember D = Past, P = Future, and P = Actions (DPP) for understanding analytics types.
Term
Descriptive Analytics
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Term
Predictive Analytics
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Prescriptive Analytics
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The application of data analysis in HR to improve decision-making and outcomes.
Analyzing past data to understand trends and events.
Forecasting future trends based on historical data.
Offering recommendations on actions to improve outcomes.
HR analytics utilizes data to enhance decision-making in human resources.
This section explains the importance of HR analytics, describing its three main types: descriptive, predictive, and prescriptive analytics. It emphasizes how HR analytics transitions organizations from intuition-based to evidence-based decision-making.
HR analytics is a key driver in modern human resource management, facilitating data-driven decision-making. This section elaborates on three key forms of analytics: Descriptive Analytics helps HR professionals understand past performance, Predictive Analytics forecasts future HR trends, and Prescriptive Analytics offers actionable advice for improving HR outcomes. By moving from intuition-based decisions to a focus on data, organizations can enhance hiring, retention, performance, and overall effectiveness.