Prescriptive Analytics is one of the steps of Business analytics, including descriptive and predictive analysis. It suggests decision options to take advantage of the results of descriptive and predictive analytics.
It can be utilized to find a solution among various variants, using different simulation and optimization techniques to indicate the path that should be taken.
With Prescriptive Analytics, companies can get smart recommendations to optimize the next steps in their strategy.
Along with predictive analytics, prescriptive analytics help to create a more effective data-based strategy.
Both predictive and prescriptive analytics is critical to making business decisions based on data.
However, the most significant difference between predictive and prescriptive analytics is that predictive analytics predicts what will happen in the Future. In contrast, prescriptive analytics offers specific recommendations for changing the future.
With Prescriptive analytics, we can find a solution among various variants to optimize resources and increase operational efficiency. This tool uses different simulation and optimization techniques to indicate the path that should be taken.
A prescriptive analysis is based on:
- Operations investigation
- Predictive Analysis
- Mathematical techniques and statistics
Its application seeks to determine each assumption’s limitations based on the study of data and applying mathematical algorithms and probabilistic techniques.
It can be said that it is a learning process that adapts to obtain the best possible result in all real situations that must be faced.

Why prescriptive analysis matters to your business?
Thanks to information obtained through prescriptive analysis, it is possible for companies to make future decisions, such as:
- Calculate past sales of a product to determine the number of replacements.
- Know the tendency of customers in certain products to launch marketing campaigns, according to users’ needs.
- Predict equipment failures, which provides for maintenance at the right time.
- Know customers’ purchasing habits and punctuality of payment to determine whether it is appropriate to grant credit.
It is possible that some of these decisions can be made manually and correctly. However, the information is bigger and more complicated, and the processes, although more complex, need to be resolved urgently.
Prescriptive analysis has benefits such as:
- Optimization of processes, campaigns, and strategies.
- Minimizes maintenance needs and interconnects them for better conditions.
- Reduce costs without affecting performance.
- It increases the likelihood that companies will approach and plan for internal growth properly.
- Qualitative research method – know the characteristics that distinguish it.
- Production optimization.
- Efficient supply chain management.
- Improved customer service and experience.
Due to its complexity, there are still few companies that use prescriptive analysis.
However, prescriptive analysis benefits have already become evident in many fields, including, but not limited to, healthcare, insurance, financial risk management, and sales and marketing operations.
Among its most significant advantages, it stands out that it allows decision making based on data, Allowing an end-to-end view of costs, processes, and performance.
It is possible to quantify risks and have access to actions considered ideal in different circumstances. Algorithms have the ability, through current data, to predict consequences arising from each decision made.
Therefore, it allows you to follow the path that offers more satisfactory results.
The prescriptive analysis allows more effective planning to be carried out in Marketing and Sales actions, bringing information that significantly impacts business intelligence.
Therefore, decisions are made according to facts, knowing the consequences that will arise from them.
Despite the prescriptive analysis potential, it will only affect a joint work between machine and human being.
That’s because technology doesn’t make decisions alone. She organizes the information, analyzes the scenario, and indicates the best thing to do, leaving the professional to proceed with the suggestions.

Conclusion
As we saw, Prescriptive Analytics has great potential to support businesses, optimizing resources, and increasing operational efficiency.
They no longer need to use their efforts to analyze data, make projections and research needs, and think of solutions that suggest options that can be used to make future decisions and reduce risk.
This powerful AI tool allows you to process data continuously and improve forecasts to offer new alternatives when making your business decisions.
Other articles you may want to read
If you want to learn more about AI, Machine Learning, and Data Science, I suggest you have a look at these other articles:
23 Amazing Youtube Channels for you to Learn AI, Machine Learning, and Data Science for Free…