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Workload Automation vs RPA in 2024: Top 5 Differences & Synergies

Workload automation (WLA) and robotic process automation (RPA) are valuable tools for businesses’ automation infrastructure. Both tools reduce the number of manual tasks in an organization by automating repetitive processes. Both have benefits such as decreasing human error and cost, increasing efficiency, and creating transparency. 

Companies can be undecided between WLA and RPA for their automation needs. However, the tools have different functionalities and use cases that cannot substitute for each other. This article will define the differences between WLA and RPA and explain how they can work together as complementary technologies.

What is workload automation?

Workload automation is the process of using software to centralize and automate scheduling, initiating, and monitoring business workflows and transactions across physical, virtual, and cloud systems. Workload automation provides centralized control over the workflows across the enterprise. 

Through central access to workflows, IT professionals can schedule and monitor various processes and streamline the business service delivery. The tool enables businesses to optimize information exchange between departments, facilitates data access and transfer, and eliminates manual-work-induced errors. 

As workload automation works both on-premise and on cloud systems, it is easy to integrate it into complex enterprise environment. Moreover, compliance and transparency through audit trail, optimized data storage and incident management are among the benefits of integrating workload automation in workflow management. 

It is important to note that workload automation interacts with back-end code. Hence, it requires a certain level of technical expertise to use. However, in recent years many vendors have produced tools that are low-code/no-code, making it possible for professionals without a technical background to utilize the benefits of automation on workflows. There are also more specialized versions of workload automation tools, such as enterprise job scheduling and Windows job scheduling software.

What is RPA? 

Robotic process automation (RPA) is a productivity tool for creating customized bots that can observe and recreate user’s interactions with GUI components to execute rule-based tasks. Unlike workload automation, RPA bots interact with the user interface. For example, IT professionals can build RPA bots for data extraction and processing.

However, the capabilities of RPA are not limited to screen-scraping. Next-generation RPA bots, also known as cognitive RPA, can utilize AI to execute more complicated tasks by analyzing data. For instance, by reviewing previous reporting scenarios, RPA tools can implement repetitive tasks for financial reporting

Top 5 Differences between Workload Automation and RPA

  1. Scope of work:
    • RPA is focused on tasks involving the frontend used by humans. It is designed to automate repetitive, rule-based tasks traditionally performed by humans using GUI. It can handle data entry, form filling, and generating reports. If the process is complicated or requires human judgment, RPA may not be suitable for that specific process. Explore RPA use cases.
    • WLA is focused on automated software process in the backend. It focuses on scheduling, initiating, and managing system tasks within complex business or IT processes. It is used for running batches of jobs in a coordinated sequence across multiple, complex, interdependent systems and applications in a fault-tolerant manner. Explore WLA use cases. RPA bots can also be used to coordinate backend processes however, WLA solutions are more specialized for this purpose and may have more advanced features.
  2. Users: RPA is typically used by a business user while WLA tends to be used by a technical user due to its more technical scope of work.
  3. Integration:
    • RPA is good at integrating with systems that lack APIs or are difficult to integrate through traditional methods. It is non-invasive and doesn’t require deep system integration.
    • WLA requires more sophisticated integration and interaction with the underlying systems. It is better suited for scenarios where a deep level of integration is required and is often used in environments with a mature IT infrastructure.
  4. Complexity of Processes:
    • RPA is often used for simple, rule-based processes. Handling many different types of exceptions or complex decision making can increase the complexity of RPA bots and can present challenges in maintenance.
    • WLA is used for complex business processes involving various dependencies and conditions. It has robust capabilities for handling exceptions, conditional workflows, and dependencies between tasks.
  5. Operational Efficiency:
    • RPA can help to improve operational efficiency of business units by automating repetitive tasks, freeing up human resources for more complex, higher-value work.
    • WLA optimizes IT operations by streamlining and automating the management of business processes across multiple systems and platforms.

Leveraging WLA and RPA together

Workload automation enables enterprises to automate their business service process across different platforms. Businesses can integrate RPA bots into the workflow to optimize repetitive tasks and reduce the necessity for human labor. There are two primary use cases of RPA integration into Workload Automation:

  • Workload automation tools feed data into RPA bots from different business departments and can replace the role of a human trigger to initiate an RPA bot. 
  • Workload automation tools can be used in RPA exception handling and orchestration. WLA tools can monitor the RPA operations and request human intervention if necessary. 

An example of RPA integration in workload automation can be seen in profit & loss analysis of equity trading firms. Firstly, workload automation software transfers data from the clearing house to the firm with ETL (extract, transform, load). WLA software can then trigger RPA bots to read the data and take various actions based on the data. For example, journal entries can be generated and reports can be prepared. This allows the business team to modify their own automation solutions based on business or market changes.

Do WLA and RPA solutions have overlapping functionalities?

RPA solutions have been investing in backend automation capabilities. 1. Therefore, RPA orchestrators provided by RPA vendors can also orchestrate RPA bots and most RPA bots have API connection capabilities.

For more on Workload Automation and RPA:

If you are looking for workload automation or RPA  solutions, check out our data-driven lists of workload automation and RPA tools. 

To explore tools and vendors for RPA integration in your business processes, check out our previous article on the comparison of the top RPA solutions: 55 RPA Tools & Vendors.

If you still have any questions about RPA, feel free to read our in-depth whitepaper on the topic:

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And we can help you find the right solution for your business:

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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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