When you think of automation, robotic process automation (RPA) software may be the first thing that comes to mind. It’s one of the wider-known forms of automation. You may have come across RPA tools at your own business, but if you haven’t, or if you want to understand more about the full range of RPA benefits, these real-world examples will help you visualize what RPA can do.
These examples are based on ways real companies are using RPA to improve a variety of business processes—everything from HR and finance to legal and operations. You’ll also spot some companies using bots as part of a larger automation strategy (which is an automation best practice). We’ll touch on that later, but one of the guidelines to keep in mind around RPA usage is that it’s great for specific tasks—but not for everything.
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RPA can be used across industries and departments to speed up processes, improve productivity, increase accuracy, boost customer satisfaction, give new life to old tech, and stay compliant. Here are a few examples:
Consider a company that runs parking services. They manage a high volume of payments for parking services daily, and each payment generates an individual sales transaction associated with data collected by control equipment and parking meters. When there is a discrepancy, employees have to reconcile these two data points manually so that the company can link its revenue collection to its revenue streams. This repetitive task requires a lot of staff time. They decide to use RPA to automate this task. Here’s how:
A bot consults a master file with information on accounts, then downloads the bank movements of each account.
The bot applies a pre-established set of business rules, generates an Excel spreadsheet with a reconciliation proposal when there’s a discrepancy, and sends it to the finance team.
The finance team reviews the proposal, resolves any discrepancies, then approves the proposal.
A second bot enters each reconciled item into the ERP system.
This improved process allows employees to shift their focus to higher value cognitive work, like analyzing the root causes of discrepancies and creating new business reconciliation rules.
[ See this real-world example in action: Lean how Telpark used RPA to automate its payment reconciliations. ]
Employee onboarding goes on at every company. And without automation, it’s typically a manual and time-consuming process. But with RPA and other automation tools, it can be much faster and easier: When an employee accepts an offer and sets a start date, a digital workflow with RPA can trigger the necessary steps to get them started. Rather than handling every onboarding task manually, recruiters and HR workers only have to address problems or exceptions if and when they arise.
Here’s what it could look like:
The recruiter enters the start date in the onboarding workflow. The workflow uses automation to create a new hire portal and notifies the new employee via email. The new hire enters their information and uploads the necessary forms.
Business rules (another form of automation) based on the employee’s role and department inform how IT sets up their computer and permissions. IT uses this to get everything ready for the employee’s first day.
An RPA bot connects to the payroll software, a legacy system that does not offer an application programming interface (API), to set up direct deposit with the employee’s banking information.
Another automation capability added to the workflow using low-code triggers an email to the facilities manager to assign a workspace and security credentials.
Voila! The employee is all set up and ready with minimal work from the HR team. Notice that only one of these steps involved RPA. That’s because RPA is great for some tasks, but for more complex processes, it works best in partnership with other automation capabilities.
You could also use RPA to streamline these HR use cases:
Compliance and privacy
Employee lifecycle management
Employee compliance management
RPA can also streamline the billing process. For example, take a global customer with a high volume of invoices across countries. They have to validate the currencies, amounts, and tax rates for each geography—while increasing pressures like shorter payment terms motivate them to make the process faster and more accurate.
This company could build an RPA bot to process the invoices. Here’s how how it works:
Finance sends customer invoices to the billing team.
A bot downloads them, scans them and captures the data, validates the information, and submits the invoice to the right customer.
Once the bot is done, it generates a final report for the billing team’s control and audit.
This speeds up the team’s invoice processing time and average payment collection time and improves invoice accuracy for each collection cycle.
[ See this RPA example in action: Learn how Entelgy automates their billing processes. ]
You can also use RPA for other finance processes:
Know Your Customer (KYC)
Same-day fund transfers
Customer lifecycle management
Building profit and loss reports
Building cash flow statements
Creating account statements
Distributing account statements
Many enterprise organizations have multiple legacy databases storing customer information. Without RPA, an employee might have to repeatedly search for customer information in one database, then manually add it to another. This type of work is monotonous and doesn’t require analytical thinking—but it’s crucial to the company’s operations. Here’s how RPA could improve the process:
The bot logs into the legacy system. (Because this legacy database doesn’t have an available API, an RPA bot is a great solution.)
The bot scans existing data, extracts the data, and saves it in a file.
The bot then logs in and uploads the file to the second database, generating a report for employee review.
Automating this task with RPA saves employees hours on manual work and gives them time to focus on other projects. The bot brings them in as needed to review.
For any organizations with hourly or non-exempt employees, auditing digital time cards can be an overwhelming task. If employees generally clock in at the start and end of a shift, as well as during a shift for morning and afternoon breaks, a total of eight punches would appear on a card for every shift worked. A human would have to spend hours on the repetitive task of auditing each time card to make sure employees are being paid properly. Fortunately, RPA can help here, too:
The bot reviews each time card and identifies entries that don’t have the right number punches.
The bot applies pre-defined business rules that dictate what to do with entries that are missing punches.
If the bot finds any time cards that can’t be corrected by existing business rules and flags these cards for an employee to validate.
Using a bot to streamline the audit process helps the business pay employees faster, reduces the chances of mistakes, and gives payroll employees time back to focus on higher value work.
A large, publicly traded company wants to reduce the risk of insider trading, but there are so many trades in the trade window that it takes the legal team hours to review. They decide to use automation to help reduce cycle time:
Employees answer a series of questions that determine whether they have insider knowledge. This self-service form eliminates ad hoc email requests.
Business rules identify and approve all requests that can move forward without manual review.
The investment website has no API, so once the trade is approved, an RPA bot logs in with a browser to approve trading.
The workflow disables trading after the scheduled delay so no team member has to remember to do it manually.
If there are any exceptions, smart services redirect the task to the legal team for review.
This automated process saves the legal team time, reduces opportunities for human error, and ensures a greater level of protection for the company.
As you’ve seen in these RPA examples, companies can use bots to improve processes across their organization. But you’ve also seen that RPA is just one piece of a bigger web of automation.
RPA is most effective when handling tasks that meet these criteria:
Tasks with few variations or exceptions. If a task is always performed in the same way every time, RPA works well. It’s not a fit for situations that have many variations, like if invoices all need to go to different locations versus to just one database. Otherwise, you’d have to build a new bot to address each new situation.
High-volume tasks. RPA creates the most value when it takes over on a task that happens a lot, like sending order confirmations by email or processing thousands of stock trade requests. The exception is for low-volume tasks where you’re trying to reduce errors or become compliant. In these cases, RPA can also work well.
Rules-based tasks. Business rules guide RPA bots to know what to do in certain situations. Bots work best when there are a set of consistent rules to follow.
Tasks existing in well-defined processes, systems, and workflows. If the environment around the bot is mature and consistent, RPA will work well. When systems and processes are changing, the bot owner will have to make frequent changes to the RPA workflow, which defeats the purpose of letting it run on its own.
Tasks with structured data and readable inputs. RPA needs the data and inputs to be clearly defined so the bot can easily search for information. If the data is unstructured or unreadable, you can still use RPA, but you’ll want to bring in other automation tools to make sure it works smoothly.
Additionally, RPA is a great solution for when you need to connect systems with no API in place. When your company implements a new technology but it can’t connect to your existing systems, RPA can unify these systems quickly without the need to develop new APIs. And eventually, if an API becomes available, you could upgrade that part of your workflow to an integration.
A word of caution about RPA: although its benefits are immense, RPA is not meant to be a one-size-fits-all solution for your automation needs. When you face a more complex issue or need a more stable solution long-term, consider pulling in these other automation tools, in addition to RPA:
Business rules. Business rules instruct other elements, such as RPA, how to carry out tasks or deliver information. These rules follow an “if X, then Y” format.
Intelligent document processing (IDP). Extract data from structured documents and turn it into digital text. The best IDP software can pre-process scanned documents, classify them into different categories, extract relevant data with natural language processing and machine learning, validate and enrich data, and automatically bring in humans to handle exceptions or proof work.
Smart services. Create integrations, actions, steps, and dependencies with smart services. These services can send a push notification or an email, export data, or schedule an activity. Additionally, in a low-code process automation platform, you can easily add them to a workflow.
In tandem with RPA, these automation tools expand your capacity to improve all sorts of processes across an organization, as opposed to just using RPA in isolated silos.
[ Which emerging automation trends deserve your attention now? Get the Gartner Hyperautomation 2022 Trends Report. ]