What is predictive analytics software?

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. 

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 on 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.

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?   

Find a powerful platform  

Software AG has been named a Leader in the Gartner Magic Quadrant for Global Industrial Internet of Things Platforms and is positioned furthest for completeness of vision.

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 Software AG.   

Cumulocity IoT 

Empower people—such as operations managers—to turn IoT data into actionable insights using a self-service IoT analytics platform.   

Real-time streaming analytics, historical IoT data analytics and machine learning/predictive analytics come together in one IoT analytics platform—integrated and available on the cloud and/or at the edge. Find out what the Cumulocity IoT platform can do for you today.     

TrendMiner 

Empower process and asset experts with advanced self-service industrial analytics to analyze, monitor and predict the operational performance of manufacturing processes. 

TrendMiner is Software AG’s self-service industrial analytics software for smart factories and Industry 4.0 operations. If you’re on a quest to continuously improve your production processes, take a look at TrendMiner.  

Made by engineers for engineers, TrendMiner is based on a high-performance analytics engine for sensor-generated time-series data. Process engineers and operators can easily search for trends and question process data directly—on their own, without the help of a data scientist.