What Are Prescriptive Analytics?

Businesses typically use statistical methods to analyze past performance, predict outcomes, and figure out the best strategies for growth….
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Businesses typically use statistical methods to analyze past performance, predict outcomes, and figure out the best strategies for growth. Statistics are used to improve efficiency and understand how specific decisions affect performance. In a retail setting, for example, sales projections involve analytics. And businesses use statistical methods to figure out what’s working and what isn’t. These numbers serve as evidence and reaffirm decision-making processes.

Statistical methods are used in every aspect of life and can be applied to any industry regardless of how small or large it may be. So, can statistics be used to generate recommendations? And how well does it aid in making intelligent decisions? On this page, you’ll learn about prescriptive analytics and how this statistical method can benefit businesses.

The Method of Prescriptive Analytics


If you’ve landed on this page, you’re likely wondering, “What are prescriptive analytics, and how can it help my business?” For starters, it’s a statistical method that can help an organization find the best way forward based on historic data. The idea is to focus on actionable insights rather than monitor data. Businesses can predict future outcomes and leverage those predictions to ensure the best course of action. It’s a great way to guide business decisions based on the effects of algorithms. These algorithms help optimize the results of future events and evaluate the risks involved simply by using mathematics and computer science.

Prescriptive Analytics in a Real-World Example

To generate specific recommendations, an algorithm-based model needs to be utilized. For example, let’s say that a human resources manager has to help elevate their team and is looking to recommend an upgrade course for employees to improve their skill set. But some team members may lack a particular skill set, and they would be unable to take the recommended upgrade course. With prescriptive analytics, the human resources manager can use an algorithmic model to identify the team members who need other recommendations. Then, the model can send an automated proposal based on their current skill set, leading them to the initial upgrade course. Of course, the information provided for this statistical method must be accurate. That way, the model can develop the correct answers. You can customize all algorithms to specific situations depending on your needs.

Benefits of Prescriptive Analytics

Using a prescriptive model has several benefits. This includes revenue generation, gross margin management, and expense reduction. When a business has the data to understand customer behavior, it can accelerate sales cycles and open up new avenues for up-selling. Algorithmic models can even help with inventory management, which reduces the costs of manual processes and long-term stock storage. Prescriptive analytics can also provide insight into the products and services that businesses should prioritize based on current market conditions. Analytics models can anticipate purchase patterns and outcomes based on past data. Overall, this results in more profitability, better productivity, and more transparency.

Disadvantages of Prescriptive Analytics


Although prescriptive analytics is helpful, there are some caveats to utilizing huge amounts of data. For example, it can be challenging to define a fitness function. A fitness function typically helps obtain the best solution, but it requires an in-depth understanding of a business. Another issue one might encounter with prescriptive analytics tools is human bias. Since humans write most models, these algorithms will have preferences. However, there are some techniques to combat this, one of them being machine learning (ML). Enterprises can use ML to generate algorithmic models based on collected data to avoid biases.

Finding a range of solutions involves statistical models based on well-thought-out algorithms. Prescriptive analytics is a method that can aid in decision-making, and there are plenty of use cases of prescriptive analytics that have resulted in better efficiency and more revenue.