Predictive analytics can help your organization forecast future outcomes based on historical data and analytical techniques such as machine training.

Predictive Analytics is a data analysis category that aims to predict future outcomes based on historical data and analytical techniques such as statistical modeling and machine training. The science of predictive analytics can generate future insights with a significant degree of precision. With the help of sophisticated tools and models for predictive analytics, each organization can now use previous and current data to reliably forecast trends and behaviors in future milliseconds, days or years.

Predictive analytics is accepted in a wide range of organizations, with a global market that is projected to reach approximately $ 10.95 billion by 2022, growing at a compound annual growth rate of (CAGR) of around 21 percent between 2016 and 2022, according to a report by Zion Market Research from 2017.

How does predictive analytic work?

The power of predictive analytics comes from a wide range of methods and technologies, including Big Data, data mining, statistical modeling, machine training, and mathematical processes. Organizations use predictive analysis to track current and historical data in order to determine, based on the obtained parameters, the trends, and forecasts of events and circumstances that should occur at a given time.

With predictive analytics, organizations can find and use templates that are in the data to assess the risks and opportunities. For example, models can be designed to detect the links between different behavior factors. Such models allow the assessment of any promise of any risk that would constitute a set of conditions, directing informed decision-making in various categories of supply chain and procurement events.

What are the benefits of predictive analytics?

Over the centuries, looking to the future has always had three basic goals: money, fame, and power. The predictive analytics does not really change the reasons why people want to know what will happen next week, next month or next year, but only looking into the future more precisely and reliably than the previous tools.

Money:

Predictive analytics can help those who adopt it to find ways to save and earn money. Retailers often use forecasting programs to anticipate inventory needs, manage delivery schedules, and configure store scheduling to maximize sales. Airlines often use predictive analytics to determine ticket prices according to last year's travel trends. Hotels, restaurants and other participants in the hospitality industry can use this technology to forecast the number of guests in any night activity in order to maximize occupancy and revenue.

Glory:

No job has achieved success if it dies in the toss. By optimizing marketing campaigns with predictive analytics, organizations can reach new customer reactions or purchases, as well as promote opportunities for selling new products. Predictive models can help companies attract, retain and nurture their most important customers.

Power:

Predictive analysis can be used to detect and prevent various types of criminal behavior before any serious damage occurs. By using predictive analytics to study user behavior and actions, the organization can detect unusual activities, from credit card fraud to corporate spying and cyber attacks.

What makes predictive analytics different from traditional analytics?

The difference between conventional analytics and predictive analytics is simple and clear. While traditional analytics generally focus on insights relating to the current state, the predictive analytics aims to provide users with an insight into the near and long-term future to determine the likely trends and upcoming behavior.