Predictive Analytics

Predictive analytics is a branch of advanced analytics that makes predictions about future outcomes using historical data combined with statistical modeling, data mining techniques and machine learning.

Today, companies today are inundated with data from log files to images and video, and all of this data resides in disparate data repositories across an organization. To gain insights from this data, data scientists use deep learning and machine learning algorithms to find patterns and make predictions about future events. Predictive analytics can be deployed in across various industries for different business problems. Below are a few industry use cases to illustrate how predictive analytics can inform decision-making within real-world situations.

Industries of Predictive Analytics​:

    – Banking
    – Healthcare
    – Human resources (HR)
    – Marketing and sales
    – Supply chain analytics

Service's Of Predictive Modeling

Security

Every modern organization must be concerned with keeping data secure. A combination of automation and predictive analytics improves security. Specific patterns associated with suspicious and unusual end user behavior can trigger specific security procedures.

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Risk reduction

In addition to keeping data secure, most businesses are working to reduce their risk profiles. For example, a company that extends credit can use data analytics to better understand if a customer poses a higher-than-average risk of defaulting. Other companies may use predictive analytics to better understand whether their insurance coverage is adequate.

Operational efficiency

More efficient workflows translate to improved profit margins. For example, understanding when a vehicle in a fleet used for delivery is going to need maintenance before it’s broken down on the side of the road means deliveries are made on time, without the additional costs of having the vehicle towed and bringing in another employee to complete the delivery.
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Improved decision making

Running any business involves making calculated decisions. Any expansion or addition to a product line or other form of growth requires balancing the inherent risk with the potential outcome. Predictive analytics can provide insight to inform the decision-making process and offer a competitive advantage.
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