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Why is ML important in ERP?

Abzooba Admin

– Abzooba Solution Team

Enterprise resource planning system integrated with machine learning is the new talk of the town. With the current surging rates of data utilization in the current market, traditional ERP systems would find it hard to cope up. This ERP and ML combo can efficiently and accurately keep a tab on sales data, manage supply lines, and customize the system according to various needs.

“Machine learning as a service” market has already crossed US$1 billion in 2019. At the current rate, it is expected to grow up to US$8 billion by 2025. It’s high time that organizations start integrating ML services into ERP. In this article, we would be talking about how ML can help in ERP.

ML can help categorize the target audience:

Target audience categorization is essential. Products and services can be strategically diverted towards a particular category, which may require it while keeping it away from those who don’t. If done manually, categorizing the audience in specific parameters can be extremely time taking. But with the help of ML, you can do it quickly and automatically. It saves company resources and revenues as well as the workforce.

Predicting customer attrition:

Using pre-existing data, ML can predict which users have a high rate of attrition. Once recognized and confirmed, this resource can help companies prepare in advance for the user base changes.In their reports, McKinsey mentioned that by using machine learning, customer attrition rates could be reduced by as much as 15%. This data was only for organizations in the telecom sector, but we can see the bigger picture.

Automation of customer care services:

With ML, providing personalized customer care becomes more effortless. Chatbots using NLP are already in the market, which can completely replace maintaining a consumer care team 24*7. The chatbots can automatically make recommendations based on user data like order history, basic info, etc.

Predicting future requirements and improve interdepartmental communication:

The enterprise resource planning report would compile data from all the branches of the organization. Artificial Intelligence and machine learning can easily create a database to connect all branches efficiently. It can manage the demand and supply chain and automatically predict requirements and orders based on current stocks.Analyzing the previous records, ML can help predict when the orders would surge or drop. It enables the company to pre-plan for the changes.

Machine Learning can help Find out the root cause of maintenance problems:

Image Source: Google

An ERP System integrated with ML can help engineers predict potential failures in the system and take counteractions. It helps in improving MRO performance and helps in easy generation of revenue streams.

Production Quality and Capacity:

Machine learning can help control the product quality and production rate at the basic level. The infrastructure of the organization can be smartly handled to churn out maximum production at an efficient rate. Pieces of equipment can be continuously monitored with ML to save revenue (as mentioned in the previous point). ML helps recognize the internal processes or components, negatively affecting the production rate and modifying it. Above were the ways ML helps in ERP. It helps make quick and calculated business decisions, but it also helps an organization’s computer systems self-learn using mathematical analysis from already present statistical data. It improves the overall productivity of the organization.


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