The term Predictive Analytics utilizes a variety of data analysis techniques, such as automated machine learning (ML), data mining, and artificial intelligence (AI), to create predictive models, which extracts information from datasets to identify patterns of previous behavior and to predict future outcomes. In the past two decades, changes in technology have made computing power and data storage much more accessible for organizations and other business entities. As a result, businesses are producing massive volumes of data that can be leveraged to achieve a competitive advantage. Organizations that can effectively capture data from their business operations have the opportunity to generate insights that can reveal hidden risks and opportunities. In the business world, predictive analytics is rapidly gaining momentum. That’s because when businesses execute predictive analytics effectively, they become more agile, more efficient, and most importantly, more profitable. 

• In manufacturing sectors, predictive analytics models can increase efficiency and revenues. By forecasting the location and frequency of machine failures, predictive analytics can anticipate production delays. By projecting future demands, manufacturers can accurately order supplies, thereby reducing raw material waste.
  
• In software companies, predictive analytics can determine which customers are at the highest risk of canceling their products or services or switching to a competitor. This gives sales executives the opportunity to engage with customers to try to change their minds. Customer service teams can use predictive analytics to determine the category and severity of a case as it is logged, so it can be routed appropriately.
  
• In the healthcare sector, predictive analytics can help improve business performance. They could make huge advances in efficiency, patient care, and health outcomes by broadening their use of predictive analytics.
  

Nobody knows what the future holds. But with predictive analytics, we can make a good guess at what tomorrow might look like.