What Is Prescriptive Analytics?

What Is Prescriptive Analytics?

Many business leaders, marketers, and other professionals who work with data still haven't heard of prescriptive analytics. But it's time to familiarize yourself with this important step in the business analytics process. In fact, not only does prescriptive analytics constitute a powerful weapon for businesses that deploy it, it may soon become a necessity for remaining competitive.


Business analytics is, of course, the process of taking in data, analyzing it, and using the results of that analysis to guide the direction of an organization. It can do this by providing descriptions of where the business has come from; serving up predictions about where it is headed if it stays on the same course; and delivering powerful insights for strategic changes to achieve desired outcomes.


Prescriptive analytics can help define your businesses direction for improving customer satisfaction, increasing revenue, improving products, and more. For example, retailers can use prescriptive analytics to adjust prices in response to competitor behavior and revenue targets. Acute care facilities can use prescriptive analytics to schedule staffing in anticipation of patient needs. Manufacturers can use predictive analytics to prioritize particular orders over others to meet future demand. And the list goes on.


In fact, both prescriptive and predictive analytics provide the means to harness the power of the data already flowing through your business systems to not only help you see where you are heading, but to help you make the best decisions possible for getting where you want to go.


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Analytics for Better Outcomes

Predictive analytics is part of a larger toolset for data analysis that can help you identify ongoing and changing trends and predict future trends from them. From there, it can also can reveal the need for course changes in order to meet revenue, employee or customer retention, and other goals. Making sense of all your data is the job of three primary types of analytics.


  • Descriptive analytics shows decision-makers where the business stands now. It can be used to gauge whether your organization is meeting current revenue and other targets. Inputs for descriptive analytics include customer surveys, transaction histories and web traffic. The larger the data set, the more accurate your insights will be.


  • Predictive analytics goes a step farther. It takes information about trends and uses it to make predictions about where the business is going if nothing else changes. For example, given past and current patterns, analytics might help decision-makers look ahead to project future sales and opportunities. Machine learning artificial intelligence (AI) can help this process by automating the data-crunching workload.


  • Prescriptive analytics is the final puzzle piece, representing the pinnacle of analytics. Using information gathered through descriptive and predictive analytics, prescriptive analytics recommends specific actions that business leaders can take to achieve desired outcomes. Fed with enough relevant data, prescriptive analytics systems can do the most to help you move the needle when it comes to strategic insights.

The Power of Automation

Your best friend when it comes to using prescriptive analytics is AI. You can use AI systems to process and analyze massive amounts of data for real-time business insights. Off-the-shelf AI solutions provide the ability for the average business user to understand and act on a company's data — without the need for data scientists and programmers.


Prescriptive analytics solutions can help business leaders make better decisions across a wide range of activities in real-time, including:


  • Reorganizing resources to compensate for the loss of a vital employee.


  • Taking action to avoid losing that employee in the first place.


  • Lowering energy costs without negatively impacting productivity.


  • Optimizing supply chains.


  • Adjusting prices to find the right balance between protecting margins and providing value to customers.


  • Cutting maintenance costs while proactively replacing equipment before it fails.


  • Negotiating more favorable contracts.


Automated analytics solutions are based on sophisticated advanced data science technologies, including machine learning, heuristics, and natural language processing. New tools, such as Ki, can put the power of AI-driven analysis into the hands of everyone in your company, from C-suite executives to marketing specialists. Using AI-powered software will give you and your team the power to use prescriptive analytics to assess and improve every major function across your business.


To learn more about specific use cases for prescriptive analytics to minimize customer churn, download our white paper, How to Target Your Best Customers and Keep Them.



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