With its headquarters in India, Sustainability and continual innovation are the company's motivating factors. Their commitment is visible in the constant improvement of their facilities, procedures, and products, which guarantees a wonderful customer experience and streamlines daily workstreams. AIACME was seeking a means to automate a typical human resources (HR) function processing sick leave certificates in order to advance their internal work processes. In order to comply with rules, the HR team at AIACME processes sick leave documentation on a daily basis.
The primary duty is to read the doctor-signed employee sick leave certificates and enter the pertinent information into the system for sick leave submission. This task can take up to 7 minutes to complete manually for each sick leave request.Reading these materials proved to be the most difficult because the quality was occasionally so bad. In order to improve team performance, we opted to automate this excessively repetitive procedure that did not truly provide much value to the business.
The HR professionals of a manufacturing company are able to concentrate on more important business duties because they are able to save 85% of the time previously spent on manual sick leave submissions.
Machine learning and artificial intelligence can help with cyberattack protection. AIACME employs the robotic process automation (RPA) and artificial intelligence (AI) tools to automate this process.OCR is initially employed to make the text machine-readable because the documents are being received as scanned PDFs or images.The following stage, classification, aids in identifying the type of document—whether a given document is a sick leave certificate or not—and the document's purpose.
A machine learning (ML) model has been developed in the AI centre for data extraction. It has received training to process sick leave certificates. In order to train the model to comprehend fields like person name, address, date of birth, illness start and end dates, recognize some checkmarks, etc., more than 200 papers were employed.
When the extraction (or classification) confidence score is low, the action centre sends the output for human confirmation. If the document is not readable or contains an incorrect file, the HR specialist can assist in validating or correcting the extracted data or send it for rejection.After gathering all the data, the robot logs into the system, locates the employee profile, and completes all the fields required to submit an absence form. The robot then creates and transmits an execution report.
According to the study, the HR team views having more time to devote to important tasks that support an overall improvement in performance as advantageous.
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