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6/21/2024 | 3 Minute Read

Hyperautomation vs RPA: A guide for MSPs

Contents

    The Ultimate Guide to Hyperautomation

    Discover everything MSPs need to know about hyperautomation and use cases.

    In the realm of digital transformation, advanced automation is a game-changer for MSP businesses. As you work to deliver efficient and streamlined solutions to your clients, there are two terms at the center of the conversation: hyperautomation and robotic process automation (RPA).

    Understanding these terms will help you make informed decisions to improve your processes in ways that make sense for your specific MSP business. Let’s dig into the definitions and use cases for each.

    What is hyperautomation?

    Hyperautomation is an advanced end-to-end approach that integrates several automation technologies to automate complex business processes and deliver digital transformation at speed and scale. These technologies include robotic process automation (RPA), workflow orchestration, artificial intelligence (AI), machine learning (ML), process mining, and advanced analytics.

    Hyperautomation creates an operational harmony using the people, process, and technology (PPT) framework, which can benefit all stakeholders.

    What is RPA?

    Robotic process automation (RPA) is the basic building block of hyperautomation. RPA applications require little more than basic training or programming to excel at simple repetitive tasks such as data entry or document scanning. Think of RPA as simple scripts written to perform very narrowly defined and specific tasks by freeing up valuable time and resources. RPA eliminates human error, accelerates processes, and ensures consistent execution.

    Hyperautomation vs RPA: What's the difference?

    RPA is task-based automation that can be used outside of a more complete hyperautomation process. Its greatest value is in automating repetitive, rule-based tasks that have traditionally needed to be completed by a human in a user interface. It’s limited to these types of tasks, but it improves efficiency and reduces manual effort and human errors. Essentially, it eliminates some of the tasks that your teams would love to take off their plate so they can focus on more value-add tasks.

    RPA is one piece of the hyperautomation pie. When it’s combined with other technologies— including generative AI, machine learning, process mining, machine learning, and more—the output is hyperautomation.

    Hyperautomation goes beyond individual tasks and focuses on optimizing entire processes. It relies on centralized data to emphasize integration and orchestration across multiple systems and applications to create a seamless flow of information, actions, and decision-making functions. Essentially hyperautomation has use cases across your entire organization, which is a game-changer for MSPs.

    When to use hyperautomation vs RPA

    When to use RPA

    RPA is ideal for automating manual, time-consuming, and error-prone tasks that do not require complex decision-making. RPA is suitable as standalone automation when:

    • The primary goal is to improve efficiency and reduce human error in performing routine tasks
    • The process involves repetitive tasks that follow a predefined set of rules
    • The tasks are performed on user interfaces, such as data entry, form filling, or screen scraping
    • The process does not require significant integration with other systems or complex data manipulation

    When to use hyperautomation

    Hyperautomation combines RPA with other technologies, such as artificial intelligence and machine learning, and focuses on end-to-end automation. It aims to automate complex business processes that involve multiple systems, data sources, and decision-making. Hyperautomation is suitable when:

    • The goal is to achieve end-to-end automation and optimize the entire process, rather than just automating individual tasks
    • The process involves multiple steps and requires integration across different systems or applications
    • There is a need for intelligent decision-making based on data analysis or machine learning algorithms
    • The process requires a high level of flexibility and adaptability to handle changing conditions or exceptions

    To move forward with RPA or hyperautomation, first assess your specific automation needs and consider the complexity and scope of the processes you want to automate.

    Whichever path is best for your current business, you can start saving time and resources and start considering new revenue streams or otherwise transform the way you do business. Check out our blog to understand more hyperautomation benefits and use cases specific to MSPs. Or dig even deeper with “The Ultimate Guide to Hyperautomation” eBook.

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