5 ways Machine Learning can give you better insights from your ERP software

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Machine-learning

Machine Learning is gaining wide acceptance across the corporate sector due to its vast applications. Some of the most typical machine learning applications are product recommendations on Netflix and Uber, spam filters on Gmail, search results on Google, and verification of payment transactions by banks. The most significant advantage of machine learning is that you don’t need to reprogram it for different situations. Instead, it allows the ERP software to learn by gathering data and repeatedly performing the same tasks. 

It’s necessary to understand that you require sufficient high-quality data to get the best insights from machine learning algorithms. As a general principle, if your model has 10 independent variables, you need about 100 examples for gaining accurate insights. 

According to Gartner, about 70% of companies will be using AI by 2021. Fortune Business Insights projects that the global industry 4.0 market will reach USD 260.71 billion by 2026. So if you are planning to invest in ERP software, keep these points in mind as AI and ML technologies will work as a differentiator between various ERP systems.  

This article will provide 5 ways machine learning can give you better insights from your ERP software and make concrete decisions based on data.

  1. Machine learning automates finance

Financial processes sometimes require ‘exception handling’. Suppose you receive payment without an order number. You will need to check which order the payment corresponds to, and if there is a shortfall or excess, you also require a mechanism to deal with it. Machine learning algorithms allow ERP software to identify varying situations and check existing processes to increase the number of invoices that can be matched automatically. Thus, you will drastically reduce the work you outsource, and your finance team will get more time to focus on problems that require brainstorming and collective team effort.

  1. Machine learning detects frauds.

Online frauds are rising. According to the Association of Certified Fraud Examiners, companies lose about 5% of revenues each year due to frauds. Machine learning provides an efficient solution to this problem. It spots exceptions and anomalies by building rigorous models based on the following factors:

  1. Internal and external sources of data
  2. Past company transactions
  3. Social media posts

By considering such data points, machine learning algorithms allow ERP software to stop fraudulent transactions in real-time. 

The best use case scenario comes from the banking industry. Banks can use historical customer data to identify unusual transactions and payment patterns. Machine learning algorithms also efficiently handle other areas such as tax evasion and cybersecurity.

  1. Machine learning performs predictive maintenance.

Let’s understand it with the help of an example. Suppose you sell electronic products and one of your customers purchases a refrigerator from you. After a few days, the compressor blows off, and you get a lot of flak from the customer. Later, the customer spreads bad word-of-mouth about your company that impacts your client base. 

Now let’s see the other side of the story. If your ERP software uses machine learning algorithms, they will detect irregularities in the compressor before it gets dysfunctional. The ERP software will alert the technical team, who can then help the customer. 

  1. Machine learning makes supply chains smooth.

Machine learning algorithms monitor and analyze logistics data to determine and eliminate supply chain risks. They can check millions of news feeds and public social data in numerous languages to recognize accidents or natural calamities. During the coronavirus pandemic’s peak, the healthcare industry was reeling under extreme pressure because of insufficient supplies of life-saving instruments. Machine learning algorithms helped ERP systems identify the hospitals that required emergency supplies, which helped save numerous lives. 

  1. Machine learning performs drone-based inventory management.

Machine learning algorithms can control drones that can perform external inspections of warehouses and inventories. The drones can be fitted with cameras that send high-resolution pictures to the ERP system, where machine learning algorithms will detect any cracks or surface changes in the infrastructure. 

Conclusion

Industrial revolution 4.0 technologies like Artificial Intelligence, Machine Learning, and the Internet of Things are gaining significant importance in the corporate world. Today, the question is no longer whether you should invest in ERP systems powered by machine learning algorithms or not. Instead, you must compare the benefits and drawbacks inherent in the technology and apply ERP systems that solve your specific challenges. 

Author Bio: 

Nishant likes to read and write on technologies that form the bedrock of modern-day and age like web apps, machine learning, data science, AI, and robotics. His expertise in content marketing has helped grow countless business opportunities. Nishant works for Sage Software Solutions Pvt. Ltd., a leading provider of CRM and ERP systems to small and mid-sized businesses in India.

 

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