Design, planning, and governance – the three pillars of RPA success

Contributed by Cigniti Technologies.

A robot, by definition, is a machine that mimics and replicates human actions to automate certain activities. Robotic process automation or RPA is a robotic software that employs machine learning to study the exact steps taken by a manual resource to fulfill a task and then perform the same task at much faster pace and much better efficiency.

The manual steps act as the data on which the RPA software feeds and executes the desired action with precision. Its automation capabilities make it capable of performing about 50-60 tasks every day, equivalent to the work of up to five full-time employees. The speed and power of RPA help enterprises achieve scalability and flexibility in production, enabling them to deliver value to their customers at an accelerated pace. The eradication of need for human intervention eliminates the possibility of human errors, thus, offering high level of accuracy in process completion. By reducing the required manual labor and manhours, RPA yields a cost-effective, resource-efficient solution for tedious processes.

RPA is vital for repetitive business processes that are essential but eat valuable time of employees, leaving them exhausted and burnt out to focus on higher priority tasks. Ideal for standard, rule-based steps, RPA is primarily used by the modern enterprises to automate mundane processes such as data entry and validation, record maintenance, calculations and transactions, and more. While RPA brings about 25-50% reduction in overall costs, enterprises should formulate a fitting strategy to guarantee a successful deployment. This demands consideration of three key areas that define the viability of an RPA strategy.


It is not feasible to automate everything. Human cognition is irreplaceable, and since RPA is only suitable for standard, iterative processes, it is critical to first lay out a detailed plan of why to automate, what to automate, how to automate, and when to automate.

It is required that all the processes are segregated on the basis of how much time does each of them consume. Doing so provides complete visibility of the existing processes as well as time spent per process. Such end-to-end visibility comes handy in prioritizing all the processes as per the value add to the overall business goals. Once the tedious processes are identified and prioritized, they should be standardized in order to ensure proper automation using RPA, as it cannot work optimally on those processes that have additional variables beyond the pre-defined “if, then, else” rules.


With a thorough plan and process visibility, it becomes easy to analyze and determine which set of RPA tools, platform, framework, and infrastructure best fit the identified processes. The RPA architecture should be designed while considering both the process goals and the organizational goals, such that they are in tandem with each other and help organization progress on the optimization scale.

Designing an RPA architecture needs a meticulous strategy that encompasses multiple components such as robotic components library, execution data, logs, and infrastructure, software bots, configuration settings, analytic data, tools and applications, configuration management, and compliance guidelines.


To make sure that the execution path stays on track of the determined plan and design, governance is crucial. Establishing a Robotic Process Automation Center of Excellence (RPA CoE) enables enterprises to integrate the RPA strategy with the defined processes in such a way that it not only helps achieve accuracy and efficiency, but also allows organizations to scale and succeed in their goals.

Test Automation with RPA

With the advancements in the field of AI, machine learning, and natural language processing (NLP), RPA looks even more promising in software testing scenario as it dons the hat of “Cognitive”.

The current IT landscape is mandating adoption of Agile & DevOps methodologies. For enterprises striving to excel in terms of speed, efficiency, and quality, test automation is imperative. As a majority of testing processes are iterative, RPA fits the picture perfectly when formulating a test automation strategy.

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