How to Improve Supply Chains with Machine Learning

It is seen that enterprises seem to be attaining double-digit improvements in forecasting error rates, demanding planning productivity, reduction in costs and on-time shipments. There are many supply chain challenges that are time, cost and resource constraint-based which makes machine learning the ideal technology to solve them.

It is estimated that AI techniques will be an embedded and augmented component across 25% of all supply chain technology solutions by 2023 intelligent algorithms. The following are ten ways that machine learning can be seen to be revolutionizing supply management:

  1. 01. Machine learning-based algorithms are said to be the foundation of the next generation logistics technologies. It can be seen that machine learning can contribute to solve complex constraint, cost and delivery problems that companies face today.

  2. 02. It is seen that the wide variation in data sets which are generated form the Internet of Things sensors, telematics, intelligent transport systems and traffic data can deliver the most value in improving the supply chains with the use of machine learning.

  3. 03. Machine learning has the ability to reduce logistics costs by finding patterns in track-and-trace data that is captured using IoT enabled sensors, which can contribute to $6M in annual savings.

  4. 04. Machine learning-based techniques can help to reduce errors by upto 50%.

  5. 05. Machine learning has the capacity to enable logistics and supply chain operations in order to optimize capacity utilization, improve customer experience, reduce risk and create new business models.

  6. 06. It is seen that manufacturers are investing in machine learning-based applications which is able to detect and act on inconsistent supplier quality levels and deliveries.

  7. 07. Insights gained from machine learning is seemed to be reducing the risk and the potential for fraud and at the same time also improving the product and process quality.

  8. 08. Machine learning seems to be provide predictive and perspective insights by making rapid gains in end-to-end supply chain visibility. This in turn is helping companies react faster than before.

  9. 09. Machine learning also seems to be providing the foundation for thwarting privileged credential abuse.

  10. 10. There is improvement in asset utilization and reduction in operating costs through the capitalization on machine learning for predicting preventative maintenance for freight and logistics machinery.
Read more at forbes.com
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