All That You Need To Know About Prescriptive Analytics

By Author: Jency Durairaj
Total Articles: 5
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Analytics is the core driving factor of any business. The analytics tree consists of three branches, descriptive, predictive, and prescriptive analytics.  
In this piece let’s discuss the most crucial analytics – prescriptive analytics and how it influences business decisions. 
What is Prescriptive Analytics and how it works? 
Prescriptive analytics is a type of data analytics that employs both descriptive analytics and predictive analytics to forecast and advise robust solutions for any situation. 
To give you a clear context: 
Descriptive Analytics – tells you what happened 
Predictive Analytics – tells you what might happen 
Prescriptive Analytics - Descriptive Analytics + Predictive Analytics – tells you what the best solution or next right step among various possibilities is.  
For instance, consider an interview being ...
... conducted for a specific type of job. Every company searches for the best talent available in the market for the same. In such a circumstance, it has been commonly observed that employing human resources to choose the right candidate for the job without any bias or nepotism is unlikely. Leveraging a prescriptive algorithm in such a situation can help detect the right candidate with the precise skillsets as well as give an automatic and unbiased recommendation, making the job simple, objective and free from human biases. 
Benefits of prescriptive analytics 

Smart and Fast Decisions 

Prescriptive analytics enables you to make fact-based decisions and pay heed to non-obvious choices that may pose potential risks. Besides, you can stretch your limits - go to great lengths to figure out robust solutions for various plausible scenarios.  

Transform information into actionable insights 

Prescriptive analytics reduces confusion in decision making and prescribes actions by providing the big picture of dynamic outcomes on the choice of different actions for decision-makers, thus transforming information into action.  
How to prepare yourself for prescriptive analytics 

Gather appropriate data 

The quality of any type of analytics depends on the quality of the data. In today’s big data era, large amounts of data are pulled across various sources. Hence, it is advisable to make sure to resample one's data to reduce redundancy and ambiguity.  

Expand Horizons in data classification 

Exploring different metrics and expanding horizons in data classification helps identify and map potential attributes for decision-making.  
Consider the case of customer segmentation - the traditional pointer for data classification to determine product quality is customer product expectation versus product reality. Applying other perspectives like ‘customer churn factor’, ‘customer engagement’ or ‘customer sentiment’ helps glean 360-degree contextual understanding about the product’s quality with prescriptive analytics. 

Employ Data as a Service 

Data collection is easier said than done. As surplus data is produced every second of the day across digital devices and networks, it is worthwhile to leverage third-party data services that already possess diverse metrics and tested scenarios. Reducing time in data collection will get one more time to experiment with different prescriptive algorithms to obtain a valuable output. 
Summing Up 
The bottom line for progress in any area of a business relies on the speed and quality of decisions made. As companies are exploring various technological advancements to reduce errors in decision making, prescriptive analytics may be the best shot to make optimal decisions in less time to drive business value.