How will AI and Machine Learning Impact ERP Growth?
manufacturingtechnologyinsights

How will AI and Machine Learning Impact ERP Growth?

By Manufacturing Technology Insights | Tuesday, December 18, 2018

ERP systems are essential for enterprise operations, but they are not getting enough attention like other systems as they take a longer time to implement.  This gap can be reduced by integrating cloud ERP systems with AI and machine learning.

Cloud ERP platforms need to create a self-learning information system involving AI and machine learning across all provider networks. Giving a gentle stream of knowledge to AI and machine learning algorithms can accelerate the training of an entire system creating a better business. The voice-based approach can ease several areas’ production operations, from pick-by-voice systems to advanced inspection. Apple’s Siri, Amazon’s Alexa, Google Voice, and Microsoft’s Cortana have the potential to change the operations and process. Assessing supplier quality through machine learning, organizations can keep track of the applications that give them the best business and identify which systems pose risks.

Providing IoT-based data to AI and machine learning facilitates organizations to achieve better data structure efficiently. Based on the machine learning predictive model, businesses can improve accuracy and better collaboration with suppliers by analyzing machine-level data. it is easy to determine when a part needs to be replaced so that the equipment breakdown could be reduced and asset utilization increases. The self-learning algorithm helps to find production problems. Improving product quality through continual learning from supplier inspection, product failure data, and return material authorization will have a positive impact on overall ERP growth. Cloud ERP systems are capable of capturing quality data from supplier to customer across the product lifecycle. Equipment effectiveness can be improved with AI and machine learning. Regression algorithms, which predict valued output data based on past data, help to study the dynamic behavior of an organization. Applying clustering algorithms to find some hidden patterns in a given data set, and with classification algorithms, it is easy to track past order details that help to cancel or modify current orders.

Microsoft Excel may still be one of the most popular data visualization tool in the market, but new tools such as Tableau Desktop or Microsoft’s Power BI are giving users new options for data processing and consumption. ERP is generally focused more on operations than marketing but the module that addresses sales has to become social media savvy.

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