What you need to know about Robotic Process Automation

  • What you need to know about Robotic Process Automation

    What you need to know about Robotic Process Automation

    What is Robotic Process Automation (RPA)?

    Robotic Process Automation (RPA) is the technology that allows a computer software, or a “robot” to mimic a human worker’s interaction with digital systems to execute a business process. RPA robots exploit the user-interface to capture data and manipulate applications just like humans. Robotic Process Automation can handle high-volume, monotonous tasks that previously required human involvement. It can easily expedite back-end tasks for Finance, Supply Chain Management (SCM), Human Resources (HR), etc. and dramatically decrease the cycle time while improving the accuracy. It helps keep your employees off of mundane and repetitive tasks.

     

    What is the difference between Artificial Intelligence (AI) and RPA?

    According to IEEE Standards Association, RPA is the use of a “pre-configured software instance that uses business rules and pre-defined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management.”
    Whereas AI is “the combination of Cognitive Automation, Machine Learning (ML), Reasoning, Hypothesis Generation and Analysis, Natural Language Processing and intentional Algorithm Mutation producing insights and analytics at or above human capability.”
    In a layman’s terms, RPA is basically a software robot mimicking human actions whereas AI uses Machine Learning to simulate human intelligence. Thus RPA is related to “doing” whereas AI is related to “thinking” and “learning”.
    One of the key differences between RPA and AI is that RPA solutions are limited to handling rule-based work and need digitised and structured inputs. Many organisations, however, have to deal with judgement-based processes and unstructured inputs.
    Another key difference between the two is that RPA is process-driven. For RPA you need to have pre-defined processes and steps whereas there is no such need in the case of AI.

     

    How is RPA different from other Enterprise Automation (EA) tools?

    One of the major differences between RPA and other Enterprise Automation tools is that an RPA software can automate an organisation at comparatively lower cost and lesser time. RPA works without compromising your existing IT infrastructure, thus making it highly configurable and cost effective. However, it is not possible or feasible to automate an entire organization with the help of RPA.

     

    What are the benefits of RPA?

    1. Cost Savings – By automating the processes having redundant tasks, you can save a tremendous amount of money. Automating redundant and time-consuming tasks free up your staff to focus on more productive work.
    2. Improved Cycle Time – RPA bots reduce the time taken to complete any task tremendously.
    3. Non-Invasive Nature – One of the biggest advantages of RPA is that it does not replace your existing IT infrastructure. You can leverage the power of RPA without making any disruptions to your existing systems.
    4. High Accuracy – RPA eliminates costly mistakes that can lead to poor decision making.
    5. Increased Output – RPA ensures that the work is being done 24*7*365 without human fatigue, or quality variance. e.g. Customers may want to interact with service providers outside of their business hours. RPA allows you to provide this kind of service.
    6. Scalability – Companies can easily scale up or down their operations and make adjustments based on their needs or seasonality.

     

    Challenges of RPA Implementation

    1. RPA is generally a short-term solution – RPA can provide immediate benefits however they are not long-term or sustainable. You need to make frequent workflow review and optimisation for RPA systems to work.
    2. Current RPA market offers RPA with limited machine learning capability – We still have a long way to go when it comes to truly cognitive learning. The scope for automation will increase tremendously when AI and machine capabilities get integrated with RPA tools; however, we haven’t reached that stage yet.
    3. Unclear expectations – Unreal and uncertain expectations can be one of the biggest challenges when implementing an RPA system. Consequences and outcomes need to be communicated to all the departments and employees to eliminate their apprehensions.

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