43 Back Office Automation Examples in 2024: RPA, WLA, AI/ML

Although back-office employees do not directly face the customer, 60% of customer dissatisfaction originates from the back-office. Many tasks in IT, HR, and finance are repetitive, data-based, and labor intensive, which makes the back-office a great candidate for automation using AI and RPA, and workload automation. According to research, RPA in the back office can reduce 70% of the cost of a full time employee, providing a quick and tangible ROI to organizations.

Applying AI and automation tools to back-office processes

AI, RPA, WLA, and analytics contribute to optimizing task automation in the back office tasks by handling repetitive tasks while leveraging cognitive abilities:

• Robotic process automation: RPA is one of the fastest to implement yet customizable technology solution. Bots can be programmed to completely handle repetitive, time-consuming tasks, reducing manual error and providing faster results.
• Workload automation: Workload automation (WLA) tools schedule, trigger, execute, and monitor workflows across different business platforms from a centralized point. Monitoring back-office workflows improves the overall data management and compliance.
• Analytics: Applying analytics to back-office data identifies ways to improve the company’s performance
• Process mining / task mining: Specific analytics approaches such as these technologies help understand their processes better and identify ways to improve them
• Image recognition and computer vision enabled document automation: These enable the processing of unstructured back-office data, such as financial and procurement invoices, reports, and employees handwriting.
• Natural language processing: NLP enables the use of chatbots as digital assistants facilitating back office tasks like booking vacation requests or other HR queries.
• Machine learning: ML algorithms can learn from both structured or unstructured back office data:
  • Supervised ML algorithms can use this data to train predictive models of processes such as digital twin of an organization.
  • Unsupervised ML algorithms can find patterns in data, enabling anomaly detection of system and operational errors, as well as best and worst practices in different processes.

Back-office automation examples

Tasks such as data entry and update are common among all back-office departments. However, department-wise automatable tasks are:

Finance department

RPA bots can automate ±42% of finance operations in accounting such as:

1. Account payable
2. Account receivable
3. Client reporting
4. Controlling
5. Financial reporting
6. Record keeping
7. Payroll automation

Other AI solutions in financial back offices include applying:

8. Analytics for:
   • internal, external, and compliance auditing
   • identification of material misstatements in the general ledger
9. Language understanding algorithms for contract reviews to identify non-compliant terms
10. Image recognition for double checking invoices and financial statements, and eliminating duplicates

IT department

IT tasks automation, also called ITPA, can benefit from RPA in these areas:

11) Installing software

Bots can be trained to:

• Automate software requests and approvals
• Download licensed software
• Install and update available software on pre-assigned servers and user machines

12) Monitoring servers and applications

• Monitor and save server performance data
• Prepare reports

13) Alerting

Bots can automate notifications of server issues and downtime. In addition, analytics’ reports can identify recurring errors and downtimes, making it easier for the IT department to spot future bugs.

WLA tools on the other hand, can monitor the workflow execution, detect failures in execution and trigger alarms to notify users of errors.

14) Data migration

Bots can recognize required files and formats which need to be migrated from one system to another, and input them into pre-defined folders in the designated system. Bots can also retain migration data in a log to allow system user to check the process, and input and output system data.

15) Data backup

Bots can automate data backup, recovery, and restoration. On the other hand, leveraging image recognition and computer vision can limit backing up duplicate data which might be named differently.

16) Batch processing

Batch processing means processing of multiple transactions, simultaneously, and in a sequential order. Bots can handle batch processing such as:

• Synchronizing, deleting, and emptying folders
• Creating and sending notifications to users

Workload automation tools can also be used to perform batch processes (e.g. ETL, FTP) as they can schedule, initiate, and execute processes at certain time schedules or triggering events.

17) Creating and updating user emails

Bots can create user emails, update user information from HR lists, and add specific employees to position-relevant mailing lists.

18) Creating and resetting user passwords

Bots can create, passwords for new user emails, devices, and software accounts, as well as reset and verify passwords of existing users.

19) Reduce cybersecurity threats

Bots can eliminate unauthorized logins, automate detection of viruses and hacks, as well as limit human involvement in managing sensitive or privileged data.

Others

RPA bot can:

20. Manage service requests automatically
21. Automate asset management
22. Automate job scheduling
23. Optimize storage capacity
24. Automate onboarding process
25. Automate offboarding process

HR department

RPA bots can improve task efficiency and reduce HR operation time, as well as enhance employee satisfaction. RPA use cases in HR include:

26. Candidate sourcing
27. Employment history verification
28. Arranging interviews
29. Administer Offer Letters
30. Onboarding automation
31. Travel & Expense Management
32. Attendance Management
33. Payroll Management
34. Managing employees’ data
35. Aggregating data for performance reviews
36. Managing employee offboarding

On the other hand, analytics in HR can:

37. Improve hiring
38. Improve retention
39. Use aggregated employee performance data for objective auditing and scoring
40. Provide insight about employee’s motivation and productivity, as well as company culture

To learn more about RPA and analytics in HR, feel free to read our detailed articles What is RPA for HR? – Top 9 RPA use cases in HR [2021] and Setting up analytics in HR

Supply chain

Supply chain processes produce numerous documents in different formats, such as delivery orders, dock receipts, bill of lading (B/L), etc. Processing and storing these documents is necessary to maintain efficiency and compliance in supply chain back offices. Automation solutions include:

41. Leveraging AI/ML, image recognition, and OCR in document automation for data capturing, clustering information on the document, and sending the document to relevant employees.
42. Applying analytics to supply chain data for planning staff and inventory programs.
43. Using augmented reality applications for warehouse planning and operations, transportation optimizations, and inventory management.

To learn more about implemented technologies in the supply chain department, feel free to read our in-depth article Supply Chain Automation in 2021

Benefits of back-office automation

Implementing automation solutions in the back-office enables:

• Reduction of administrative errors
• Enhanced communication among business departments
• High ROI:
  • Bot licensing costs between €3,000-€8,000 annually, on the other hand, hiring a full-time employee (FTE) will cost the company €30,000+ but this depends highly on the country
  • According to research, one bot can replace 3 FTEs and work on weekends and holidays. However, we see that this depends on the bot and the use case. There are numerous cases where a bot automates only part of the work of an employee.
• Analytics benefits
  • Back office employees process large volumes of data resulting in a rich, multi-format database about the business, enabling statistical and predictive analysis of organization’s processes. This can be beneficial for implementation of process mining and modeling a digital twin of an organization.

For more on automation

To learn more about automation, read:

• Guide to Hyperautomation: Technologies, Pros & Cons
• Top 12 Hyperautomation Use Cases & Examples
• Front Office Automation: 5 Ways To Boost Customer Satisfaction

To learn more about RPA use cases in different business departments, download our in-depth whitepaper on RPA:

If you are looking to buy off-the-shelf RPA solutions for your business, benefit from our data-driven list of RPA vendors, and contact us to help you