What is predictive analytics software?

What is predictive analytics?

Predictive analytics is an application of IoT analytics to create actionable insights from massive volumes of IoT data. By combining available historical data with data mining and statistical modeling techniques, predictive analytics can provide insights into why a certain incident occurred and forecast when that incident may happen again and how to avoid it.

Figure 1: Four steps to predictive analytics.

Predictive analytics use cases

Manufacturers are using IoT to obtain usage and status data from sensors embedded on their equipment at customer sites. By leveraging predictive analytics, manufacturers are enabled to offer predictive capabilities to help customers maximize uptime by predicting maintenance needs. Predictive maintenance IoT data analyzed by predictive analytics enables manufacturers to utilize and offer predictive maintenance services. Predictive maintenance allows you to monitor the condition of a machine, component or product to predict when it is going to break down or fail and to prevent the problem from occurring. By using accurate data to anticipate when maintenance is needed, you’ll reduce downtime and maintenance costs while improving operating efficiency.

Predictive maintenance

IoT data analyzed by predictive analytics enables manufacturers to utilize and offer predictive maintenance services. Predictive maintenance allows you to monitor the condition of a machine, component or product to predict when it is going to break down or fail and to prevent the problem from occurring. By using accurate data to anticipate when maintenance is needed, you’ll reduce downtime and maintenance costs while improving operating efficiency.

Smart field services

Unlike customer support that can be provided remotely, field services require employees of the equipment provider to go to the customer site to perform services such as installation, equipment repairs, part replacement, regular maintenance, and consultative services. As a result, equipment makers must manage teams of technical service providers to diagnose, fix, and improve customer equipment.

Smart field services use predictive analytics to analyze IoT data collected from equipment in the field to better schedule, plan, and execute field services.

This allows the maintenance, field service, customer service, and consultative services teams to provide more accurate, timely maintenance, part replacement, and performance management support.

Inventory management

Predictive analytics makes it easier to manage inventory for spare parts or consumables used as part of equipment operation. A business can better match supply to demand without incurring excess inventory holding costs from warehousing or spoilage. As input costs change, predictive analytics also allow for modeling the impact of price changes on demand to maintain profit margins.

See predictive analytics in action

Learn how SMC uses sophisticated analytics and preventive maintenance to save the company and its end-users costs associated with leakage-caused air loss.

What are predictive analytics tools?

Predictive analytics tools make predictive analytics easier and accessible by empowering people—such as operations managers—to turn IoT data into actionable insights.

A self-service IoT analytics platform for predictive analytics allows you to understand, predict, and act on the powerful insights revealed in your IoT data using integrated real-time streaming and predictive analytics capabilities.

Predictive analytics tools | Key considerations

When choosing an IoT platform for predictive analytics, it’s important to consider:

• Is the platform self-service, or will you need an army of developers to use it?
• Will you be able to connect equipment easily?
• Will you be locked into a particular vendor’s technology stack, including infrastructure, hardware, and proprietary systems?
• Will you be able to integrate IoT data easily with your core systems and processes?
• Will you be able to evolve and expand your solution based on how your needs change over time?
• How easily can you define advanced rules so you can monitor and act on events?
• Will you have access to expertise to help you build a proof of concept and prove its value?

How to implement real-time analytics, predictive analytics

It is critically important for manufacturers to select the best possible platform supported by key enabling technologies like streaming analytics, machine learning, predictive analytics, and a larger ecosystem. Get started today with IoT analytics. Discover what you can do with a holistic view of your IoT data with IoT analytics tools from Cumulocity.