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Top 7 Business Use Cases of RPA in ERP Applications in 2024

ERP started as a singular database for large manufacturers to track their inventory and production levels. Today, it has evolved into a web of interconnected applications for automating the front and back ends of a business. 

Though ERP players like SAP had their start in the 70s, the ERP market is still growing thanks to both new companies growing large enough to require ERP systems as well as existing users upgrading their ERP installations. ERP market grew of 4% p.a. in 2020, reaching $40B in revenues.

New adopters and upgraders need to be aware of the latest trends in ERP including automating ERP systems with RPA which we explain below

What is an ERP application?

An ERP (enterprise resource planning) application is an evolution of MRP (material resource planning). 

In the ‘60s, via a collaboration between the business JI Case and IBM, the first MRP was created to keep track of: 

  • The level of inventory at hand 
  • The number of orders placed 
  • The timing of the manufacturing process 

MRP gave rise to ERP mainly by expanding its sphere of influence. Today, the modern ERP application keeps not only track of inventory-production levels but also human resources, finances, supply chain, project planning, and more. 

What is cloud ERP?

Contrary to the traditional MRP and ERP solutions that needed IT infrastructure and were deployed on-premise, modern ERP solutions can be cloud-based. This has benefits such as:

  • Ease of maintenance
  • Ease of remote access: Especially during the pandemic, this feature lowered operational discontinuities because the staff and the management could access the data of different operations from their homes.
  • Pre-configured security features: Given the wider attack surface of cloud ERPs, they are expected to be hardened against cyber breaches

What role does RPA play in ERP applications?  

RPA can be implemented to reduce the time-consuming and manual effort that is needed to exchange data between different ERP applications. 

For instance, during the onboarding process, a company should include the new employee’s information on the payroll. The payroll, which contains all employees’ salary data, is usually stored in accounting software (ERP number 1). And the HR software (ERP number 2) includes the employee’s contracts and personal information. 

Every time a new employee is hired, their financial data from the HR software (bank information, salary, tax number, etc.) must be copied and pasted onto the payroll as soon as they begin working.

Companies can use RPA bots to continuously monitor the employee portal every time a new employee is hired. This way, they can automatically read the person’s contract, find the financial information, extract it, and put it on the payroll with little to no human involvement. Learn more about payroll automation.

This example was an introduction to how RPA-ERP integration would play out. In the next section, we will discuss other use cases. 

What are the use cases of RPA in ERP?

1. Customer service

Chatbots have been implemented in customer service to take up the task of answering customers’ FAQ questions and allow customer representatives to tend to more value-driven tasks. 

For instance, if a customer asks the chatbot why they are experiencing a shipping delay, it can look up the customer’s order number and find out its whereabouts via the company’s logistics application. 

RPA that is embedded into the chatbot’s capabilities is responsible for automatically taking this information back and forth between the ERP applications and relaying the answer to the customer. 

2. Invoice capturing

Invoice capturing is using NLP and OCR to extract useful information from an invoice. RPA can be leveraged to bridge the gap between when the data is captured and where it ends up. 

For instance, after a sale has been made, the amount, date, the counterparty’s name, and the description of the transaction should be extracted from the sales invoice and be turned into an entry into the sales books.

RPA can be the agent that undertakes this exchange of information between the two ERP systems. 

3. Contract automation

Contract automation is useful in the onboarding process because the software can automatically copy-paste the new hire’s information from the HR database onto a pre-approved contract template and email it to him/her to sign. 

It’s RPA technology that takes employee data from one application and copies it onto another. Automating this process is helpful to HR teams because first, it means they do not have to spend their time doing it, and second, it ensures the accurate transfer of information because the robots will be exchanging the information that actually appears on the database. 

4. Financial closing 

Financial close is a lengthy process that contains multiple sub-categories, such as making entries on the general ledger, reconciling balances, closing the books, generating reports, etc. 

But if you have not consolidated your close process by using a financial close automation tool, then you likely are using separate legacy systems each dancing to its own rhythm. A person should be there to move the data around. 

RPA can be leveraged to take up this task instead of an accountant. They will automatically:

  • Make entries as a sale or a purchase is made (see bullet point 1), 
  • Verify it against the invoice and reconcile the balance, 
  • Include it in the reporting document, 
  • And write the transaction off. 

Each step is done on a separate ERP software. But RPA will move the information around until the workflow reaches a conclusion. 

5. Personalized marketing campaigns 

Marketing campaigns can be personalized to the user’s tastes and interests to achieve a higher degree of lead capturing. 

For instance, an e-commerce personalization application collects user data for making tailor-made suggestions. These suggestions, along with the users’ data, thanks to RPA, can be turned into mass emails to be sent at periodic intervals.  

6. Order to cash (O2C) 

Order to cash (O2C) is the end-to-end process of receiving an order, verifying inventory, shipping the goods, receiving the payment, and settling the transaction. 

The sequential series of steps are each done on a different ERP system. For instance, orders that are received go to the order management system, while verifying inventory happens on inventory management software. So where is the invisible hand that checks the inventory of the specific good that the order has been received for? 

Through API, these various applications are linked to one another and allow for the exchange of information (this is true for all aforementioned scenarios as well). However, RPA is what, for example, copies the serial number from the invoice for the ordered commodity and pastes it on the “look up inventory” tab of the order management system to see if it is in stock or if it needs to be ordered from outside.  

So in the same way, the RPA verifies the good to be in stock, automatically schedules a shipment delivery, and will write off the transaction once the payment has been made. 

7. Patient scheduling 

In healthcare, scheduling patient visits efficiently to avoid timing conflicts and to ensure that each patient meets with the specialized physician can be arduous. 
The patients’ data is stored on the patient management ERP solution, while the doctors’ and staff’s scheduling data is stored in the medical staff scheduling software. RPA bots can use OCR and NLP to read a patient’s file and understand the reason for their proposed visit through sentiment analysis. It then automatically matches that patient with the next available specialized doctor, schedules a visit in between the physician’s free time, and sends an automatic email or push notification to the patient notifying them of the date of the appointment. 

For more, feel free to read how one of the most popular ERP systems, SAP, implements RPA solutions.

Or you can see how other RPA solutions can be used to bring automation to RPA

For more on RPA & ERP

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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