5 Benefits of Predictive Analytics

Predictive analytics has become an essential tool across several industries. Before predictive data became commonplace, analysts looked at past trends and made estimations about the future. Today, with the right artificial intelligence and machine learning, data scientists can better predict the future and make plans for various outcomes. This tool has become so valuable that predictive analytics is used across dozens of industries and thousands of companies. Here are five key benefits of this tool and how it can benefit you.

1. Companies can budget better.

One of the key benefits of predictive analytics is the ability to allocate budgets to account for preferences and changes in the business. For example, a marketing algorithm might notice that website traffic is higher on weekends and spend less during the week to prepare for that increased demand. A retail enterprise might use predictive analytics to forecast future trends and busy shopping days so they can schedule more employees to work. In both cases, the company budgets are spent strategically, maximizing potential customer interactions and profits while reading waste. This allows for smarter statistical modeling and financial risk management in near real-time.

2. Companies can catch problems early on.

With previous analytics models, companies were left figuring out what went wrong using historical data in the past in hopes of fixing it in the future. However, with the current predictive models, brands are more sensitive to problems and can adjust their behavior before problems get out of hand.

Through predictive analysis, an algorithm might gather useful information and fire an alert when there are changes to a website’s traffic, either warning the IT department of a potential attack or letting the sales and fulfillment teams know to expect a rush of orders. Some AI tools are even authorized to take action when they detect these predictions. They can shut down a website or mark popular items as sold out. These actions protect companies and prevent serious issues.

3. Predictive analytics can identify problems with employees.

If there is one way most companies can use predictive analytics, it is to improve the information that human resources has in order to prevent employee turnover. HR teams can look at insights and anomalies like performance reviews, absenteeism, commuting distance, and time spent at work to identify “high risk” employees who are likely to quit. They can then take steps to address the situation to keep that employee on. Lower turnover can help companies save money and create healthier work cultures.

4. Teams can set reasonable goals with predictive models.

Most companies rely on goals to keep moving forward and motivate employees. These goals need to be challenging so teams work hard, but not impossible which could negatively impact morale. This is where the use of predictive analytics can give you a competitive advantage. Predictive analytics helps companies set reasonable goals. They can ask employees to hit certain numbers one week and then stretch during another. This makes predictive analytics essential for seasonal projects, like retailers that have big holiday rushes.

5. Predictive analysis organizes data.

While the focus of many predictive tools is to help take action, the core purposes of these predictive analytics systems are to aggregate big data and present it in a manner that is clear and useful.

By 2025, the International Data Corporation estimates that the total amount of digital data inputs and outputs created will be 163 zettabytes. Every minute of every day, people create data. For example, Netflix users watch 694,444 hours of video daily. Web-users also send 4,800,000 gifs per minute. Both people and companies create data, which needs to be sorted and organized.

As long as people create datasets, there will be a need for data analytics. Predictive analytics and predictive search are just the next reasonable steps.

As you can see, there are several uses for predictive analytics across all industries. Once you see the value of this predictive analytics solutions, you can look for other ways to apply it in your business.