Due to the unforeseen circumstances of the COVID-19 pandemic, Enterprise Resource Planning (ERP) has become a saviour for businesses to continue their survival. Once looked at as a strategy that’s falling behind, ERP is now seen as a source of proactive insight that can offer the visibility to plan for tomorrow if unforeseen tragedy strikes. The majority ERP systems require manual work on a daily basis. Manual work used to translate to human workers, but now with the help of Robotic Process Automation (RPA) to complete manual tasks, your organization can leap forward with your ERP system.
ERP and the Decline of Hands-on Human Interaction
Customization is common for ERP systems to carry out specific business needs and ost ERP systems require large amounts of manual work daily. Many companies hear the word manual and automatically assume hands-on human intervention. They believe they can only use humans as bridges between applications or as part of processes.
Companies have found it difficult to install ERP systems and often legacy systems. This is due to their inflexibility as ERP requires custom-coded modifications to address changing business needs. Also, it is important to note that ERP contains large amounts of business-critical data, and this type of data is usually hard to extract. Data entry into ERP systems is a manual process that can use up hours of an employee’s workday. There are times where if not done properly, many errors could occur.
How RPA can help your ERP
One major factor to help fix the inefficiency problems associated with most ERP systems is the use of RPA. The RPA bots can perform the same daily work tasks as human beings, however, RPA does it faster and with almost no errors. Unlike human workers, they can work 24/7 with no breaks or work fatigue. RPA can work across multiple systems, scale up or down, and automatically handle data or system anomalies, and auto-correct. RPA helps to enhance existing systems without impacting them. This becomes especially important when you’re working in a financial context, where complexity and compliance intersect.
From a technical perspective, RPA works best on processes that consist of these characteristics:
- Repetitive
- Constant (meaning little to no changes)
- Rules-based, where human judgment is minimal or very predictable
From a business perspective, RPA works best to help with:
- Efficiency, speed, scaling
- Error rates that are currently too high
- Costly errors
To put it into a real-world use-case scenario, for finance, let’s say, examples of common RPA use for businesses include back and front office tasks such as:
- Sales orders
- Invoice processing
- Employee onboarding
- Intelligent data handling and transfers
- Customer-facing processes
- Managing physical or digital systems
Those are just a handful of the limitless possibilities where RPA can play a critical role for businesses across all industries.
Two basic RPA Implementation Approaches
There are two different approaches to implementing RPA for ERP purposes. The most effective way depends on the company’s culture and its strategic objectives.
The first approach deals with granting employees the ability to automate business processes such as daily repetitive tasks that keep them from working on higher-value tasks. RPA platforms are best used for non-technical people who have little knowledge of software programming. These platforms can help provide a few hours of training so employees can build their own bots to help them complete their daily routine tasks. All the employee has to do is diagram the process they want to automate, then a code is automatically generated to the bot.
Another approach allows the user to record a process instead of diagramming it through automatic code generation to create the software bot. Both of those approaches are considered bottom-up because they do not involve changes to any of the existing ERP or other systems, which are virtually risk-free for RPA.
Artificial Intelligence (AI) capabilities are obtainable for companies that prefer a top-down approach. AI helps to observe human behavior and automatically suggest processes that are good candidates for automation. They can also rank processes by the ROI that any software bot would deliver. What is said to be the greatest advantage of this approach is generating the required code with a single click without the approval of IT.
Four future trends to keep an eye on
According to top industry analysts like Gartner, ERP is supposed to experience a dramatic change in the near future. There will be a whole new mode of opportunities to use RPA, AI, or automation. Below are the top four trends to watch for in the upcoming years.
1. Focus tasked apps
The future expects to support more dynamic and responsive applications. This could eventually lead enterprise software to become more extensive yet invisible. A fully cloud-based, modular ERP platform, involves the truth that lies within the core of the enterprise systems, but the action happens at the edge. Edge applications only need to know what’s relevant to complete the task, hence the name focused task applications.
2. Distributed computing
Distributed computing will help functionality move from the center to the edge. The traditional way this was done was your ERP suite and database were in charge of your environment. Now with modular and intelligent apps, that is no longer the case. Do not be mistaken, continue to house your transactional data in a central location, but use distributed computing for your ERP systems to move functionality to the edge where users are working. This should help to accelerate performance and make the users more effective.
If this process is used correctly, your users will not have to interact on a constant basis with the central transactional database. Alternatively, it will intelligently and automatically give relevant information to users, when they need it and in the environment they prefer. The challenge ensures that each of the individual distributed environments can operate completely on their own.
3. Core automation
Core automation will play an important role in transaction fidelity and data security. The success of your enterprise application environment depends on the data in your core transaction system. It’s helpful to build algorithms to help track these transactions and ensure their completion so they can be utilized across all entities within your computing environment and everything will get recorded in the general ledger (GL).
It’s important to recognize that your architecture has a messaging system that confirms when data is moving into the GL, and you need to ensure that messages come in the proper order. A lot of messaging could add complexity to the process, which means you have to ensure to limit the volume of processing at the edge. This can be done with a central master data system or a centralized machine learning application. This will enable your core to do the learning at the center and when necessary push out requests to the edge more efficiently.
4. RPA will become intrinsic
A modular approach with edge applications operating around core automation will lead to a reduction of complexity and help to drive efficiency. An example of this includes financial systems like order-to-cash and procure-to-pay, where automation can help detect fraud.
This is why integrating RPA into your core ERP system can help protect against future attacks. ERP systems will become more mainstream, so it’s a good idea to start implementing RPA now to be one step ahead.
Find the right RPA system for your planning
When it comes to Enterprise Resource Planning, there’s no need to let it get complicated. Instead, rely on RPA to best manage the resources for the financial needs of your organization. Not only will it improve efficiency and reliability, but it will also help to reduce errors as well as increase the compliance and scalability of your organization.
At K2, we’ve partnered with industry leaders Automation Anywhere to offer RPA training for Finance Professionals. Our Mastering Bots course offers best practices, certificate guidance, web data management, and chat bot development – find out more.
