No modern enterprise can hope to get by, let alone succeed, without smart data analytics solutions. The rise of big data means that businesses are dealing with higher volumes of data than ever, and the volume is expected to double every few years. There’s no way to gather effective insights from such volumes using legacy systems or traditional means.
There’s also no denying that data is one of the most important resources available for any organization, but it can only be used effectively with the right tools designed by data scientists. One of the most important technologies that modern business users should utilize to drive decision-making is a prescriptive analytics tool.
Put simply, prescriptive analytics is a way to use data to find the best action to take to move forward with a specific scenario. IN order to understand how this is possible, it’s important to review two other types of analytics.
Descriptive Analytics: This is the use of business intelligence (BI) tools to examine data sets. The goal is to gain better insights into what happened in the past or what’s happening currently. This is often done through data visualizations, such as pie charts, graphs, and tables.
Predictive Analytics: This is the use of statistics and data modeling to make predictions about future business performance and outcomes. Predictions are often based on a combination of historical data and current data gathered from descriptive analytics.
Prescriptive analytics uses concepts from both of these approaches, but it takes things to the next level. With prescriptive analysis, you aren’t just using algorithms to determine what will happen—you’re also finding out what you should do about it.
How does it work?
Prescriptive analytics uses computer algorithms that gather both structured data and unstructured data to find statistical patterns in your organization’s data in order to guide future decisions. The goal is to find what will happen based on the available data and also determine the consequences of future possibilities to recommend the best course of action.
This is made possible thanks to advancements in machine learning that allow artificial intelligence to use statistical classification to create decision tools that analyze potential outcomes. It considered both the existing conditions involved in a problem and the results of each possible decision to solve it. This level of decision support makes a prescriptive analytics solution the final step of smart business analytics.
How do you use prescriptive analytics effectively?
The most important thing to remember when using prescriptive analytics software is that it can only be as accurate as the data it’s given. In other words, you need to really break down the problem you’re trying to solve if you hope to generate an effective solution. For example, consider that one of your objectives for this quarter is to increase sales by five percent.
You’ll need to use descriptive analytics to gain actionable insights into last quarter’s sales and determine where and how they fell short. Once you have this information, you can load it into your prescriptive analytics, so it can start creating statistical models to help you solve these shortcomings. It will then present your decision options and guide you through the likely results of each one, so you can pick the best course of action based on the available information.
What are the challenges involved?
One challenge that comes up for many use cases is the fact that it’s difficult for an algorithm to determine which available option is the most appropriate action for a business to take. This is why it’s important for data scientists to train algorithms based on company goals. Most statistical models are also created with inherent human biases. One of the most popular solutions for this is to use machine learning capabilities to generate models based on new data that are always coming in.
Advanced analytics can sometimes be challenging to use, but creating statistical models that generate valuable insights is crucial for any modern enterprise that wants to gain a competitive edge.