What is Prescriptive Analytics?

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What is Prescriptive Analytics?

Businesses looking to go modern and optimize their processes may be asking, “what is prescriptive analytics?” Thankfully, data science software topics like machine learning, business intelligence, and data analytics have been made much more accessible in the last few years. Industry leaders in the data science software field like TIBCO provide valuable information and resources on their websites for business owners and computer science students to utilize.

The increasing need for quality data governance and utilization has given way to unprecedented innovation in the business intelligence field. The best way to retain a competitive edge is to stay informed about the critical role data science software plays in business processes.


Prescriptive analytics is closely tied to predictive and descriptive analytics. The primary difference between each of these types of analytics is that prescriptive analytics focuses on actionable insight. Descriptive and prescriptive analytics collect and monitor data to provide insight. Then, prescriptive analytics steps in to consider the possible outcomes predictive analytics provided and utilize that data to create an actionable business strategy.

These algorithms are then determined through the use of mathematical and computer science statistical methods. The main goal of this type of analytics is to provide your company with the most efficient solution-turned-action possible. Prescriptive analytics is the result of the successful use of the predictive model. In other words, each form of analytics completes one another.


Prescriptive analytics can be applied to nearly every industry. However, there is a particular need for the prescriptive approach in businesses that experience constant fluctuations. For example, the prescriptive analytical method is an exceptionally profitable practice within the real estate market. The housing market is affected by a number of worldly events. For instance, the economy, the stock market, environmental conditions, and the typical supply and demand fluctuations that all organizations must consider.

Prescriptive analytics benefits these businesses by driving down human resource expenses and increasing productivity by handling data monitoring. Every business generates large amounts of data. Using an analytical model to track and organize external factors and internal operations data is a tall order in itself. Putting together that collective data and turning it into practical solutions and action plans is an even more intricate process. Automating this workflow can help business owners turn their efforts towards achieving more direct company goals, like customer satisfaction and retention.

What constitutes actionable insight?

Analytical insights are incredibly beneficial to organizations because they provide an outside perspective regarding operational models, customer demographics, influential external factors, and more. However, it can be tough to know the best way to use this information in the course of action. Actionable insights do more than provide you with decision options.

They cause you to view the situation from a data-centric perspective and provide possible plans. By providing your organization with specific actions, you can reduce pressure on those in leadership positions by eliminating possibly biased decision-making. All human beings learn from experience, and these collective experiences shape the way we view data, make assessments, and come to conclusions. It is essential to keep in mind that our collective experiences are not universal.

Our perspective shifts depending on the knowledge we have retained from our personal actions. Prescriptive analytics can help your organization see the bigger picture and each of the miniature moving parts that make up the bigger picture. Prescriptive analytics can also be used for risk assessment models, research trials, and pricing models. The primary usage of this type of analytics is for anticipation of implications and mitigation of possible risk factors. Although, analytics can be implemented in several different ways depending on your business model and its current needs.

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