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Legacy State

A ticket for every question of an employee and the resolution time was about 3 days for every ticket

Automated State

Quick turnaround for basic questions

Challenge: Our client, a Fortune 500 fashion retail giant, faced the challenge of managing a significant volume of HR-related queries and questions through incident tickets. With an understaffed HR team, this process resulted in an overwhelming number of tickets, reaching up to 20,000 per year. Additionally, the resolution time for fundamental policy questions took an average of 3 to 5 days. This created a bottleneck in HR support and affected employee satisfaction.

Solution: To address the challenges faced by our client, we implemented a conversational bot using to automate the process of answering HR-related frequently asked questions (FAQs). Our solution aimed to reduce the number of tickets, provide quick turnaround times for basic questions, and enhance overall employee satisfaction.

Process: The RPA bot executed the following steps to automate the handling of HR-related FAQs:

  1. FAQ Document Management: The bot securely saved all the FAQ documents on a cloud platform. This ensured easy access to the knowledge base and facilitated efficient retrieval of relevant information.
  2. Natural Language Processing (NLP): Leveraging the NLP capabilities of the conversational bot, the agent was designed to understand queries and questions from employees in natural language, even accommodating slang or informal language.
  3. Query Analysis: When an employee posed a question, the virtual agent analyzed the query to determine its nature and intent. It compared the query against the stored FAQ documents to identify the most relevant knowledge article.
  4. Knowledge Article Presentation: If the virtual agent found a matching knowledge article, it presented excerpts from the article to the user. The agent also provided a “read more” link for the user to access the complete document and obtain detailed information.
  5. Ticket Creation: If the virtual agent couldn’t find a relevant knowledge article, it created an incident ticket on behalf of the user. The ticket was then assigned to the appropriate HR personnel for further investigation and resolution.
  6. Reporting and Metrics: The bot generated reports and metrics on a weekly basis, providing insights into the number of queries addressed, as well as the tickets created. These reports helped in monitoring the effectiveness of the virtual agent and identifying areas for improvement.
  7. Information Sharing: The bot saved the generated reports and metrics in a shared folder for easy access and reference. It also sent notifications to the relevant stakeholders, including the HR team and business, providing updates on the reports and metrics.
  8. Daily Task Execution: The bot performed these automated tasks on a daily basis, ensuring that employees received prompt responses to their queries and that the incident tickets were efficiently managed.

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