RPA Challenges and Solutions for Beginners
Robotic Process Automation (RPA) is a robust technology that automates repetitive, rule-based activities, enhancing efficiency and accuracy. But its implementation isn’t free of challenges. Some of the most frequent RPA Challenges are choosing the right processes, change resistance by employees, and scalability.
These are overcome by a clear strategy, communication, and strong governance. Ready to become a master of RPA and overcome these challenges? Download our exclusive RPA course syllabus today!
RPA Challenges and Solutions
Following are 10 typical RPA issues, their resolution, and real-time examples.
Selecting the Incorrect Process
Challenge: It is a failed project if an automatable process is not rule-based, is too variable, or has low volume of transactions. RPA works best with repetitive tasks that have a well-defined and predictable path.
Solution:
- Perform a deep process analysis.
- Use process mining software to determine high-volume, highly repetitive, and rule-based tasks.
- Engage stakeholders and process owners early on to map the process complexity and pain points.
Real-Time Example: A bank automates its credit card application process. The process is a good candidate because it involves a high volume of applications, each requiring the same steps: data entry, credit checks, and status updates. Automating a creative design task, however, would be a poor use case.
Resistance to Change
Challenge: Employees may fear job displacement or worry about their new roles once tasks are automated. This can lead to a lack of support and, ultimately, project failure.
Solution:
- Roll out a robust change management plan.
- Educate employees on the value of RPA in terms of how it liberates them from repetitive tasks to concentrate on higher-value, strategic work.
- Provide training in how to engage with the new automated systems and establish new, more compelling roles.
Real-Time Example: A finance department streamlines its month-end report creation. Rather than merely making the announcement, the firm gives workshops to employees to demonstrate how the robots will process data gathering and report formatting. They then emphasize how it will enable the human team to work on a more in-depth analysis of the reports to spot new business opportunities.
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Scalability Issues
Challenge: A pilot RPA project may work as a starting point, but expanding it to enterprise-scale may not be easy. With more processes and more bots, management and maintenance get complicated.
Solution:
- Create a Center of Excellence (CoE).
- A CoE offers a centralized model of governance, simplifies development practices, and guarantees a pipeline of processes that are suitable for automation.
- This is a structured approach where solutions are developed for future growth and are easily maintainable.
Real-Time Example: A big insurance firm automates one line of policy claims processing successfully. To grow, they establish an RPA CoE to oversee all automation initiatives within the firm to ensure consistency and avoid a disorganized, uncontrolled “bot army.”
Legacy System Integration
Challenge: Most organizations possess older legacy systems that don’t have contemporary APIs, so it proves challenging for RPA bots to communicate with them.
Solution:
- RPA software is actually tailored to manage this using UI automation and screen scraping.
- This way, the bot can simulate human-like behavior such as clicking, typing, and navigating through a user interface, essentially skirting the requirements of an API.
Real-Time Example: An employee data legacy system is used by an HR department. An RPA bot can be coded to log in, go to an employee’s profile, and scrape his/her data to create a new hire report without an API. The code would be something like this (in a pseudo-code format):
Sample Code: Python
# Pseudo-code for a Python-based RPA tool (e.g., Robot Framework)
# This isn’t a runnable script but shows the logic
Open Application “Legacy HR System”
Enter Username “bot_user”
Enter Password “bot_password”
Click Button “Login”
Wait Until Page Contains “Dashboard”
Go To Page “Employee Search”
Type Text “John Doe” into “Search Field”
Click Button “Search”
Wait Until Element “Employee Profile” is Visible
Get Text from “Name Field” and Save as ${name}
Get Text from “ID Field” and Save as ${employee_id}
…
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Security and Compliance
Challenge: RPA bots typically process sensitive information and must have access to a number of systems, creating substantial security threats if not properly managed.
Solution:
- Enforce robust access control and credential management.
- Store credentials in secure, encrypted vaults and provide bots with only the necessary access to accomplish their functions.
- Continuously audit bot activity logs to maintain compliance and identify any unusual activity.
Real-Time Example: A medical professional applies RPA to automate the processing of patient files. The bots have access to only the relevant patient data and their passwords are located in a safe, encrypted vault. All bot interactions are logged and audited to meet data privacy rules such as HIPAA.
Unclear ROI
Challenge: Projects will fail if the up-front investment and sustaining cost of RPA (licenses, infrastructure, maintenance) does not yield an obvious, measurable return on investment.
Solution:
- Do a detailed cost-benefit analysis prior to starting.
- Put monetary measures on the benefits of time saved, reduced errors, and improved throughput.
- Begin with a pilot project that has high chances of yielding a rapid ROI to prove value.
Real-Time Example: An accounts payable team does some math and determines that processing 10,000 invoices by hand every month takes 200 hours. Automating it, they estimate a monthly saving of 150 hours. This tangible saving compensates for the expense of the RPA software and build-out.
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Inadequate Process Documentation
Challenge: Unless the process is well established and documented, the behavior of the bot will be unpredictable, resulting in mistakes and exceptions.
Solution:
- Build a Process Definition Structure (PDD).
- This document carefully describes each step of the process, and all exceptions that may arise and how to manage them. The PDD is the guide for developing the bot.
Real-Time Example: For the automated payroll process, the PDD would define the action to take if an employee’s timesheet is empty, if there is a missing tax document, or if a bonus needs to be applied so the bot knows how to do these exceptions.
Lack of Technical Skills
Challenge: There is a lack of trained RPA developers and analysts. Dependent on an internal resource without training may result in poorly constructed and unmaintainable bots.
Solution:
- Spend money on upskilling and training current workers.
- Some RPA platforms provide certifications and training courses.
- Alternatively, collaborate with an RPA implementation consulting firm and benefit from their expertise.
Real-Time Example: An IT department of a company is assigned an RPA project but does not have experience. They take a few people for certification in a tool like UiPath or Automation Anywhere, allowing them to establish a skilled in-house team.
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Handling Unexpected Exceptions
Challenge: Despite a proper document process, there can be unexpected deviations or system updates that a bot cannot deal with and will fail.
Solution:
- Build the automation with strong error handling and exception management.
- The bot should be set up to gracefully deal with standard errors (such as a webpage failing to load) and, in the case of unexpected exceptions, to alert a human for intervention instead of crashing.
Real-Time Example: A bot is executing customer orders on a website. If the layout of the website is modified, the bot may not be able to locate the “Checkout” button. The automation should be set up to capture a screenshot of the failure, record the details, and mail a message to a human operator so that he/she can correct the process. A basic email alert code may appear as follows (using Python with smtplib):
Sample Code: Python
# Pseudo-code for sending an error email
import smtplib
def send_error_notification(error_message):
sender_email = “bot@company.com”
receiver_email = “rpa_team@company.com”
password = “your_secure_password” # Stored in a secure vault
message = f”Subject: RPA Bot Error!\n\nBot encountered an error: {error_message}”
with smtplib.SMTP_SSL(“smtp.gmail.com”, 465) as server:
server.login(sender_email, password)
server.sendmail(sender_email, receiver_email, message)
# In the main bot script
try:
# Attempt to run the automated task
pass
except Exception as e:
send_error_notification(str(e))
Over-automation of a Flawed Process
Challenge: Automating a broken or inefficient process will not correct it; it will only execute a broken process more quickly, maybe making its adverse impacts greater.
Solution:
- Optimize the process first.
- Prior to any automation, the process needs to be streamlined and optimized.
- This can mean cutting out unnecessary steps, standardizing data, and reducing the complexity of the workflow.
- RPA would then be applied to the newly optimized process.
Real-Time Example: An HR department has a complicated process for gathering employee input, with various spreadsheets and manual data transfers. Automating the mess would be a bad idea. It should first make the process simple by moving to a single, centralized survey platform. Then, an RPA bot can then be employed to extract data from that platform and automatically create a summary report.
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Conclusion
Navigating RPA challenges requires a strategic approach. By addressing challenges like process selection, change management, and security head-on, organizations can unlock significant value. The key is a clear roadmap and the right expertise to ensure successful, scalable automation. Ready to become an RPA expert and solve these challenges? Enroll in our specialized RPA course in Chennai and start your journey today!