Improving software project management quality through the use of analytics on project management data

Abstract

Software project management has been less effective as a result of being focused on resource management and the completion of projects within allocated resources and other confines. There has not been much focus on improving software project management quality through improved decision-making, software project management standards and methodologies, hence the focus of this study to explore the possibility of using data analytics with project management standards and methodologies to improve software project management quality. The main question to be addressed in this study is: Can data analytics use in software project management improve decision-making and project management quality? This study, therefore, explores and provides insight on data analytics use, by means of a survey that was completed by software project managers. A questionnaire was used to collect data from software project managers. The gathered data was captured and analysed using the Statistical Package for the Social Sciences (SPSS), and the analysed data was used for validity testing, while the reliability of the measurement items was tested using Cronbach’s Alpha. A hypothesis was used to evaluate the effect of data analytics use on software project management quality. The research made use of the positivist research method. The study established that data analytics has not yet been widely adopted by software project managers and organisations alike, as both the project managers and organisations have not done enough to promote the training in, and the adoption of data analytics. The research also established that data analytics can improve software project management quality through improved decision-making and in complementing software project management standards. The study findings will be beneficial to software project managers, researchers and organisations as it reveals the factors that are necessary to effectively use data analytics in software project management, as well as highlighting how data analytics improves software project management quality