In recent years, there has been an explosion in the development of natural language processing (NLP) and robotic process automation (RPA) technologies. These tools have been developed to make enterprise resource planning (ERP systems) more efficient and effective in handling business processes.
At its core, NLP involves the use of machine learning algorithms to analyze and interpret human language. With the help of NLP, ERP systems can extract valuable insights from text data, including contracts, invoices, and other documents. This can enable organizations to gain a better understanding of their business processes, identify inefficiencies, and make data-driven decisions.
On the other hand, RPA involves the use of software robots to automate repetitive, manual tasks. By automating these tasks, organizations can free up their employees’ time to focus on higher-level tasks that require human intervention.
But what is the end game of combining NLP and RPA with ERP systems? The answer is simple: better efficiency, greater accuracy, and increased profitability.
With the help of NLP, ERP systems can generate better signals for AI, which can then understand, predict, and prescribe actions. For example, AI can identify opportunities for discounts from vendors on multiple purchases from different departments, enabling organizations to save money. AI can also optimize accounts payable schedules to ensure maximum discounts are achieved in all deals, leading to increased revenue.
However, the real magic happens when RPA is integrated into the mix. RPA can take many of these prescriptive AI programs, powered by NLP, and automate or replace processes. For instance, it can automate document processing, enabling organizations to reduce the time and effort required to handle invoices, contracts, and other documents. This can lead to increased efficiency, reduced errors, and cost savings.
Ultimately, NLP and RPA can make ERP systems more intelligent, efficient, and effective. These technologies can help organizations gain a competitive advantage in today’s fast-paced business environment. However, it is essential to remember that while trusting AI is crucial, organizations should dip their feet in the water before jumping right in. Running AI like an owner-operator, testing it, and making sure it delivers the right outcomes is crucial to its success.
In conclusion, NLP and RPA are crucial technologies that can help organizations achieve their business goals. By integrating them into ERP systems, organizations can gain valuable insights, identify inefficiencies, and make data-driven decisions. Moreover, by automating repetitive tasks, they can free up employees’ time to focus on more important tasks, leading to increased productivity and profitability. As these technologies continue to evolve, we can expect to see more innovative applications that help organizations achieve their full potential.