Leveraging AI and ML Techniques for an Efficient Cloud ERP System
The inception of new technologies and fierce competition in the market is providing impetus to the organizations to re-evaluate their ERP model. Traditional ERP systems do not provide the required flexibility and scalability for efficient business growth. On the other hand, modern ERP systems allow businesses to adopt a growth-centric approach by leveraging many recent technologies like artificial intelligence (AI), machine learning (ML), cloud services, and many others.
Modern ERP systems enable enterprises to execute their strategies effectively and provide flexibility to prioritize their growth plan over IT constraints. Cloud-based ERP systems offer excellent integration options and more flexibility to customize applications and improve usability. Here is a detailed analysis of the ways in which modern cloud-based ERP systems can be improved to bridge the gap with legacy ERP systems:
Self Learning Knowledge System: Enterprises grow when their ERP system is continually learning. Cloud-based ERP systems can quickly learn if it integrates ERP web services, apps, and real-time monitoring data to the AI and ML platforms. AI and ML platforms can provide meaningful insights with the analysis of this data. APIs also needs to be included to connect with the data of supplier and buyer systems.
Virtual Agents: Virtual agents like Siri, Alexa, and Cortana have the potential to redefine many business processes. These agents can be modified to streamline operations by offering contextual guidance and direction to complex tasks.
IoT data: IoT devices generate massive pipelines of structured and unstructured data. Modern ERP systems can capitalize this data stream by designing support at the data structure level. AI and ML tools can leverage IoT data to provide critical business information.
Overall Equipment Effectiveness (OEE): AI and ML techniques can utilize the IoT data from equipment for predictive analysis. This will provide meaningful insights into the performance of equipment. Real-time monitoring will allow the evolving ERP systems to provide much-needed information about the area for improvement.
Machine Learning Algorithms: ML tools use constraint-based algorithms to find patterns in diverse data sets. An analysis of these patterns will allow companies to understand the quality and delivery schedule performance levels of the suppliers.
Cloud ERP Vs On-premise ERP
Deacom Delivers New Ecommerce System for Process Manufacturers
Transform the Marketing and Sales Capabilities
By Deborah Gash, VP & CIO, Saint Luke’s Health System
By Setrag Khoshafian, Chief Evangelist & VP of BPM...
By Sam Talbot, Director, Worldwide Service, Otis Elevator
By Darrin Whitney, CIO, GENBAND
By Chris Mandel, SVP-Strategic Solutions, Sedgwick
By Rick Schooler, VP & CIO, Orlando Health
By Wes Wright, CTO, Sutter Health
By Jenny Watson, VP-Digital Marketing & Direct, AutoNation
By Arnold Leap, CIO, 1-800-Flowers.com
By Rob Klopp, CIO & Deputy Commissioner-Systems, Social...
By Bill Schimikowski, VP, Customer Experience, Fidelity...
By Tim Porzio, VP-Operations & Infrastructure, IS&T, Sodexo...
By Robert Roser, CIO, Fermilab
By Kevin Kometer, CIO, CME Group
By Joseph Eng, CIO, TravelClick
By Merijn te Booij, CMO, Genesys
By Matt Schlabig, CIO, Worthington Industries
By John Boden, Vice President of Information and Member...
By Christy Hartner, SVP, Commerce Bank
By Greg Toornman, VP, Global Materials, Logistics, and...