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The main goal of conducting a feasibility study during the business analysis phase for RPA is to evaluate the technical feasibility of the automation solution. This involves assessing whether the processes in question can be automated using RPA technology, and if so, how effectively. It includes examining the nature of each step and activity performed by the operation user, validating whether the process is rule-based or requires additional decisions or analysis, and determining the complexity, volume of transactions, technology landscape, development efforts, data size, and information flow. The feasibility study ensures that the process is suitable for automation and helps in identifying any manual interventions that might be needed during the process1.

A contract typically has consistent components (like parties involved, terms, and signatures) but the actual content varies, making it semi-structured.

UiPath Document Understanding defines semi-structured documents as:

“Documents that contain a mix of structured information (e.g., field labels) and unstructured text (e.g., clauses and paragraphs).”

Contracts fit this description perfectly.

Performer Role: In UiPath’s ReFramework or transactional workflows, the performer process is responsible for consuming transactions from a queue and processing them.

Queue System: It retrieves data from the orchestrator queue and executes the steps defined in the workflow to complete the task.

Complementary to Dispatcher: The dispatcher adds transactions to the queue, while the performer processes them, ensuring a smooth workflow.

Use Cases: Common applications include order processing, invoice handling, and claims management, where a structured input-output sequence is required.

This differentiation is a fundamental concept in UiPath's RPA design principles​​.

The Process Assessment Tool requires input such as the volume of input data to evaluate the potential impact and feasibility of automation. Understanding the volume of data that the process handles is crucial for assessing the workload and designing appropriate automation solutions.

The Traceability Matrix is a project management tool that ensures requirements are linked to deliverables and test cases, confirming that nothing is missed in the project lifecycle.

“The Traceability Matrix is used to track the evolution of requirements, ensuring that all business requirements are accounted for in the test cases and final implementation.”

This promotes accountability and completeness.

End-to-end automation with human in the loop refers to processes automated from start to finish, where human intervention is needed primarily for decision-making points, combining the efficiency of automation with human judgment.

In the Process Overview part of the Process Design Document (PDD), a high-level As-Is Process Map is included. This part typically encompasses the current state of the process, outlining the steps, decisions, and interactions that occur in the process as it currently exists without automation.

The Business Benefit of Flexibility refers to the ability of robots to enable scaling up or down as required when there is an unexpected spike in volume. This flexibility in robotic process automation (RPA) allows businesses to respond dynamically to varying workload demands without the need for proportional increases in human resources or infrastructure.

Prioritization criteria help Business Analysts and stakeholders to decide which processes are most valuable to automate first. It typically considers factors such as:

Business value

Complexity

Frequency of process execution

Risk reduction

As per UiPath’s Business Analyst guidelines:

“Prioritization criteria enable the evaluation and prioritization of automation opportunities based on measurable parameters, ensuring the most beneficial and feasible processes are tackled first.”

Understanding Assisted Task Mining (ATM):

Assisted Task Mining empowers the Business Analyst to collaborate with Subject Matter Experts (SMEs) and capture known tasks for automation. This involves collecting data from real-time actions, analyzing it with AI, visualizing the results, and exporting insights for process optimization​​.

Why Option A is Correct:

Collect Data: This involves capturing real-time actions such as clicks, keystrokes, and screens during task execution.

Analyze with AI: The collected data is processed using AI to identify patterns and variations within the task.

Visualize Results: Results are presented as task maps or workflows to understand processes holistically.

Export Results: The insights can be exported to create a Process Definition Document (PDD) or automation skeleton in UiPath Studio​​.

Why Other Options Are Incorrect:

Option B: Extracting permissions and managing projects are not core stages in ATM.

Option C: Recording all applications and ROI focus are more aligned with Unassisted Task Mining.

Option D: Exporting actions and generating dashboards are not typical ATM stages​​.