Automating Employee Document Extraction from HR & Payroll Management Portals: A Case Study

Client Overview

Industry: Technology & Compliance Solutions
Business Scope:
The company utilizes VeraSuite, a compliance management platform, to maintain and manage large volumes of employee records, certifications, and training documents.
Due to the large number of employees and growing compliance demands, company required a solution to automate the extraction of employee-related documents from various portals (examples include VeraSuite, Netchex, ADP, and PayComm) based on specific instructions shared by client stakeholders.

Problem Statement

The client faced several pain points in their manual document extraction process:

High Manual Overhead: Extracting employee documents required logging into the VeraSuite portal and manually downloading the needed files, which was time-intensive and laborious.
Data Volume Challenge: With hundreds of employees and frequent updates to required documentation, the workload increased significantly over time.
Human Errors: Manually filtering employee data and downloading the correct documents often led to missed files or incorrect extractions.
Lack of Process Scalability: The process could not be easily scaled due to its reliance on human effort, especially during compliance audits or document update cycles. - Delayed Compliance Delivery: Manual effort led to delays, risking non-compliance and impacting operational efficiency.

Solution: Automating Document Extraction from Portals

To address these challenges, a two-bot RPA architecture was implemented using UiPath – Dispatcher and Performer – to automate the complete document extraction pipeline from the VeraSuite portal.

Technology Stack

Process Overview

Dispatcher Bot – Employee Detail Extraction

Automated Workflow:

Logged into the different portals using secure credentials.

Navigated to the employee directory.

Extracted the list of all current employees and exported essential metadata such as employee ID, name, and department

Populated a structured Excel that served as the input for the Performer bot. - Uploaded the data to Google Sheets for downstream processing.

Performer Bot – Document Extraction and Download

Fetched employee records from the Google Sheets.

For each employee:

Logged into the portals and searched based on employee ID. - Followed client-specific instructions to identify required documents (e.g., training certificates, onboarding forms, safety compliance files).

Downloaded all relevant documents into a structured folder hierarchy categorized by employee name and document type.

Validated downloaded files for completeness.

Implementation Approach

Step 1: Requirement Gathering & Planning

Understood document extraction rules and mapping from client stakeholders. - Created a list of document categories and employee-related metadata. - Estimated bot runtime based on the average number of employees and portal response time.

Step 2: Development & Testing

Developed the Dispatcher to extract employee details and build queue items.

Developed the Performer to process each employee queue and handle portal navigation and download tasks.

Built Excel-based rules for mapping document names to extraction types.

Step 3: Deployment & Monitoring

Implemented error logging and retry mechanisms.

Scheduled runs based on the frequency of document updates from the client.

Step 4: Optimization

Optimized bot speed by caching employee session data and reducing redundant portal interactions.

Results & Impact

Quantitative Outcomes

75% Reduction in manual effort for document extraction.

50% Faster turnaround in compliance document readiness.

Zero Errors in document categorization and downloading phase.

Qualitative Benefits

Improved Compliance Readiness: Automated document gathering ensures that no files are missing during audits.

Scalability: The Dispatcher-Performer model can handle thousands of employees without performance degradation.

Standardized Folder Structures: Ensured organized storage of documents aligned with naming conventions.

Reduced Human Dependency: Freed staff from repetitive tasks, allowing them to focus on more critical compliance tasks.

Key Takeaways

RPA Enables Precision
Automating document extraction reduces human error in processes where accuracy is critical.

The dispatcher-performer Model is Scalable
Breaking the process into logical units allows seamless scaling.

Proactive Error Handling is Essential
Automated exception handling and alerts helped maintain quality and compliance.

Standardization Improves Usability
Structured downloads and naming conventions made documents easier to access and audit

Looking to automate your data reporting and improve operational efficiency? Contact us today to explore a tailored RPA solution for your business!

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High-Level Process Flow After Automation