What is Prescriptive Analytics?

The human resource department can now collect more data than ever before and use that data to make a variety of judgments and observations. In recent years, HR teams have been more familiar with various types of analytics and attempted to figure out how they may be used by their teams and organizations, but one sort of analytics remains elusive for many organizations: prescriptive analytics.

Prescriptive analytics is a sort of data intelligence that enables firms to combine descriptive analytics (what most organizations are doing presently) with a forward-looking perspective. Prescriptive analytics gives users insight into what will happen next, but it also gives the organization information about what it should do next.

Benefits :

1. Prescriptive analytics, which includes descriptive and predictive analysis, is one of the steps in HR analytics. It gives decision-making choices based on descriptive and predictive analytics data.

2. Prescriptive analytics frequently prioritizes precision over interpretation. If you give an algorithm all the factors you can think of, it can predict what will happen with a high degree of accuracy.

3. It can be used to identify a solution among a variety of options, utilizing various simulation and optimization approaches to determine the best course of action.

4. Companies can use Prescriptive Analytics to acquire informed recommendations on how to improve the next steps in their HR policies and strategies.

5. Along with predictive analytics, prescriptive analytics help to create a more effective data-based strategy.

6. Both predictive and prescriptive analytics is critical to making business decisions based on data.

7. Prescriptive analytics offers specific recommendations for changing the future.


There's no better opportunity to examine how prescriptive analytics affects your decision-making processes if your company is new to it. Start with a single query or a single process that you'd like to improve. Gather information on the subject or process in question, then go through each sort of analytics to get a complete view.

1. Descriptive: What trends does the data show?

2. Diagnostic: What factors contribute to those trends? Why are those trends occurring?

3. Predictive: If applicable, determine whether a trend is one you can expect to continue or recur.

4. Prescriptive: Finally, dive into prescriptive analytics. If you have a proprietary algorithm or third-party analytics tool, run it using your company’s data. Alternatively, conduct a manual analysis of possible next steps based on what you’ve discovered about your question or process. How will each option impact the situation’s outcome and, thus, your goal?

Prescriptive analytics doesn’t need to be daunting; with the right foundation, it can be a powerful tool to help optimize processes, formulate strategies, and reach organizational goals.

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