USING MICROLEARNING MODULES IN AN INTEGRATED TALENT ACQUISITION FRAMEWORK TO ENHANCE CORPORATE TALENT MANAGEMENT PROCESS

摘要

During the writing on this paper, one of Context's clients, a Nordic provider of energy services and solutions, is piloting a talent acquisition program which based on the framework described earlier. The first observations made based on the pilot, raise the issues of improved efficiency of scanning, identifying and selecting of potential new employees for the company. The initial process from raising attention among potential candidates until the "GO" decision is semi-automated - meaning that full manual review of applications and applicant information is not needed. While both manual and automated methods are combined to make the matching process (employee candidate vs. open position) as smooth and efficient as possible, we should expect more precise outcomes and more committed employees who prefer to remain in the position for longer. The old model of recruitment did not give applicants sufficient understanding about the work tasks they were to apply, so many decisions were made based on inadequate information.