Artificial intelligence refers to computers and machines or robot-based machines performing various tasks using human-like intelligence. ERP (Enterprise resource planning) is software that helps integrate different departments and collect data in one place. It reduces the use of multiple software and assists in data analysis and reporting. Artificial Intelligence and its impact on Cloud ERP are revolutionizing the way businesses operate, streamline processes, and gain insights from data. Cloud ERP allows access to organizations over the internet and runs on a vendor’s cloud platform as opposed to an on-premises network.
Business organizations are now adopting the latest technologies to grow and sustain their business in this highly competitive market. Artificial intelligence, Machine learning, and ERP solutions have been game-changers for enterprises. But with the technological advancements in digital business models day by day, companies are re-evaluating the role of ERP.
Cloud ERP has replaced ERP and is becoming necessary for companies; to quickly respond to their needs and make future decisions. By integrating Artificial intelligence and machine learning, Cloud ERP can provide additional advantages. And it also fills the gap that legacy ERP systems can’t.
Companies are now required to respond faster to unexpected problems they are likely to face and make smart and quicker decisions in the new business model. Legacy ERP systems are not designed to provide the data when needed. Moreover, it gives other vital integration options to customize applications and usability. The integration of AI in medical imaging with AI and machine learning in cloud ERP can enable seamless data sharing and analysis, leading to more efficient and accurate diagnoses. Cloud ERP solutions provide flexibility to organizations to prioritize their growth. It can also provide artificial intelligence and machine learning insights that can regenerate the contribution of business growth and ERP systems.
The constant changes and learnings of an ERP make business models thrive. Here are some ways in which AI and machine learning can play a crucial role and improve Cloud ERP:
Self-learning System
Cloud ERP needs to strengthen and produce a self-learning system that arranges artificial intelligence and machine learning across supplier networks. IoT in eCommerce can be integrated with AI and machine learning in cloud ERP to provide real-time insights into inventory levels, customer behavior, and supply chain performance. This cloud-based system integrates various ERP services, apps, and quick access monitors and delivers data to AI and machine learning. This process helps the system to learn faster. There is also a requirement for better web services in the cloud ERP integration roadmap to connect with various suppliers and buyers systems. This system will ensure the growth of the business.
Improvement with Virtual Agents
A virtual agent refers to software that functions on specific rules and artificial intelligence applications to provide automated services. It could also be described as a computer-generated, animated, artificial intelligence-based virtual character that helps in customer services by being an online customer service representative. Virtual agents are generally used by companies in the customer service department. They help to answer daily customer questions and perform simple tasks.
For example, Virtual agents are used in various organizations for customer interactions in starting the call with their call centers. They are also used in click-to-chat features present on companies’ websites. The Chatbot is also such a tool used for dealing with customer services like interacting with them, tracking their orders, and solving their problems. These agents are also being used in companies for handling employee needs or issues.
For instance, these agents are connected with various IT functions for providing help desk services and to guide employees in different tasks and processes. These virtual agents also have the potential to; improvise in the area of manufacturing by using pick-up-voice systems. Apple’s Siri, Amazon’s Alexa, Google Assistant, and Microsoft Cortana can be helpful to streamline various operations, provide guidance, and give directions in complex tasks. For example, Machinery manufacturers are also using voice agents to provide detailed work-related instructions.
IoT (Internet of things) with ERP
Internet of things refers to the network of physical devices around the world that are embedded with sensors, softwares, and other modes of technology. They are connected with the internet and help in sharing or exchanging data with other devices.
Cloud ERP platforms can take advantage of the massive data stream generated through IoT devices by; designing the support at the data structure level first. Cloud ERP systems can provide the backbone for businesses to seamlessly integrate their metaverse experiences with their existing operations. This IoT-based data with AI and machine learning can help companies; fill up the intelligence gap they face while applying new business models. Cloud ERP can accelerate production asset maintenance and asset tracking by designing in IoT support.
Insight into OEE
OEE (Overall equipment effectiveness) refers to measuring manufacturing operations and comparing whether they are being utilized to their full potential. In simple terms, it checks manufacturing productivity. Artificial intelligence and machine learning can provide information regarding how an OEE can be improved. This platform serves as a self-learning knowledge platform and enables monitoring data from machines and production assets.
They can provide crucial insights into areas of improvement. Manufacturers in the future are likely to accept this opportunity to get a detailed view of how they can normalize the OEE platform in their company.
Algorithms to Track Data
Data is a valuable asset for a company. It reflects on the performance of an organization and helps them to make future decisions. ERP solutions help with data collection, analysis, and reporting. But there are certain limits to it, which can be fulfilled by Cloud ERP; with the help of artificial intelligence and machine learning. Algorithms based on them can find various patterns in different data sets.
They can also predict which lots from which suppliers are likely to be of higher or lower quality. Different suppliers provide various quality and delivery schedules. Machine learning helps to figure out which supplier provides better quality.
Close the Gap between Various Business Software
Companies use various software such as PLM, CAD, ERP, and CRM in their daily business activities. They all perform different functions for businesses. CAD and PLM help with product designing, CRM for sales and marketing, and manufacturing with ERP. Cloud ERP providers should look into how AI and machine learning can help to close the configuration gap that is present between these softwares.
A single lifecycle-based view of product configuration is the most successful product configuration strategy. Artificial intelligence and machine learning can help configuration lifecycle management and avoid losing time and sales.
Demand Forecasting
Demand forecasting refers to a process of predicting future consumer demand over a particular amount of time by using data available to a company. Demand forecasting is a necessary process because; it gives businesses information about market requirements. Based on which companies can make better future decisions. Without this, companies face the risk of their decisions not being effective, which leads them to waste their time and resources. ERP solution integrates data from every business department and enables a central base for data which is beneficial for companies to avoid using multiple data resources and softwares.
Furthermore, it also helps with data analysis and data reporting. With the help of a self-learning knowledge system, Cloud ERP can improvise on data delaying that provides much higher accuracy of the forecast. High-quality data can improve demand forecasting and provide better collaboration with suppliers based on insights available from machine learning-based predictive models. Demand forecasting with a cloud ERP helps in sales, marketing, etc.
Improvising Machine Health
Companies are promoting the use of machines and robots in various repetitive manual tasks. It helps them to; increase productivity and use human potential for other essential activities. But while utilizing them, it is also necessary to make sure of their condition. Cloud ERP lets you collect the data of every machine’s health level. It is done by using sensors equipped with a specific IP address. Cloud ERP offers a great opportunity to get machine-level data and to find patterns in production performance by using machine learning techniques.
This method is very beneficial in industries where machinery breakdowns are likely to occur often, which can lead to lost sales for the company. For instance, Oil refineries use machine learning models that comprise of 1000 or more variables related to material input, output, and perimeters of processes like weather conditions to predict machine health.
Predicting Production Problems
Cloud ERP platforms must have self-learning algorithms that use production reports to predict future production problems. Maintaining smoothness in business processes is essential to growing your business. And for that business organizations have to check up on every area of the production line, which includes inventory, manufacturing, quality of product, packaging, etc. Halt in any stage of production can cause company harm. And to survive in the market, businesses should maintain the smooth flow of their processes.
This could only be done by keeping track of problems faced in the past and improving in the future with the data available. Legacy ERP systems would not have detected these problems, which could lead to a slowdown or stopped the process entirely. But with AI and machine learning, Cloud ERP can predict these issues and let the company know beforehand to avoid them.
Improve Product Quality
Delivering and meeting customer needs is crucial for companies to sustain and expand the customer base. It also helps in building the reputation of an organization. And it is possible by maintaining the quality of the product. Any fault in products can lead to losing customers and puts a bad impression of a company in between their competitors and in the market. Cloud ERP platforms can measure the entire lifecycle of a product.
Machine learning algorithms can help in improving product quality by collecting, analyzing, and learning from supplier inspection, quality control, and product failure data. Legacy ERP systems can not generate such accurate data. Therefore, machine learning could be a convenient asset to know why the product fails.
It is evident from the above-mentioned points that AI and Machine learning plays a vital role in Cloud ERP. And in the future also they will be impacting Cloud ERP platforms to add more new features beneficial for the businesses.
Author’s Bio:
Deepali Daiya likes to read and write on technologies that form the bedrock of the modern-day and age like ERP, CRM, Web Apps, machine learning, data science, AI, and robotics. Deepali works for Sage Software Solutions Pvt. Ltd., a leading provider of ERP and CRM solutions to small and mid-sized businesses in India.
