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Machine Learning and the Business of Tomorrow

Enterra Insights

Louis Columbus ( @LouisColumbus ) explains, “Enterprises are striving to find greater meaning in the massive amounts of data they generate and save every day. Columbus asserts, “Machine learning makes it possible to discover patterns in supply chain data by relying on algorithms that quickly pinpoint the most influential factors to a supply networks’ success, while constantly learning in the process.”[5]

6 Recent Trends in Manufacturing Technology to Increase Agile Responsiveness, Continuous Improvement & Customization

Cerasis

Customization Will Replace Traditional Inventory Management. According to the Global Dispatch, traditional inventory management operations will change in 2017. Inventory management will become more reliant on advanced computer analytics systems to manage inventory in real time.

5 Future Applications of the Industrial Internet of Things in Manufacturing & Logistics

Cerasis

Additionally, overall maintenance costs have dropped by 30 percent, and predictive maintenance has reduced machine-specific failures by 70 percent, reports Louis Columbus of Forbes magazine.

People, Processes, and Technology All Required for Supply Chain Transformation

Enterra Insights

UPS analysts note, “From advances in information availability to cutting-edge manufacturing processes to increased supply chain visibility, there’s no shortage of tools … companies can arm themselves with to stay relevant — and competitive. Cognitive technology can improve decision making, automate and optimize processes, and, democratize access to data (thus, breaking down harmful information silos).