Using AI to develop a framework to prevent employees from missing project deadlines in software projects - case study of a global human capital management (HCM) software company. (August 2022)

• Record Type: Journal Article
• Authors: Sheoraj, Yugeshwaree; Sungkur, Roopesh Kevin
• Is Part Of: Advances in engineering software. Volume 170(2022)
• Publication Date: 2022-08
• Subjects: Project deadlines -- Artificial intelligence (AI) -- AI framework -- Global human capital management (HCM) -- Software industry; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2022.103143
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights : Project deadlines are one of the most critical factors for a project`s success. AI is continuously driving businesses to success and modernizing the world of projects. This research contributes for the company to change the processes and move to an AI workplace to better manage their project deadlines. Abstract: Nowadays Organizations are constantly evolving on the way they manage their projects while innovating and automating certain tasks and processes for a smoother transition of projects. This is being achieved through the integration of Artificial intelligence (AI) and Machine learning. AI is continuously driving businesses to success and modernizing the world of projects. The research is based on a global human capital management company as a case study to investigate on the issues that they face to meet their software project deadlines and then proposing a framework using AI to overcome their challenges. The mixed methods research with both qualitative and quantitative design was opted for this research. A systematic literature review (SLR) was carried out initially to identify the challenges involved in meeting project deadlines as a primary method for data collection. Focus group interviews were then carried out to collect data from team members and project managers working on projects and facing challenges to meet project deadlines. The proposed AI framework was then evaluated and 72.7% participants rated the framework as effective and was keen to integrate AI at their workplace for smooth transition of tasks. A final framework was then proposed after the feedback received from participants.