Factors affecting successful big data analytics implementation in public sector of Malaysia

Decision based big data analytics (BDA) has created countless opportunities and challenges for the Malaysian Public Sector. In order to be innovative, the government organizations need to adopt effective ways of decision-making. One such strategy is by understanding and recognizing the enabling factors that contribute to the success of BDA implementation. In this regard, this study explores the effects of organizational, talent and technology resources as the factors affecting successful BDA implementation. This study was developed based on Resource-Based View (RBV) and DeLone & McLean Information Systems Success Model (ISSM) theories. Systematic literature review was conducted to identify the factors affecting successful BDA implementation and to find the research gaps. In this study, a BDA implementation model named BDI model, is proposed. Existing literatures were synthesized and critically analysed which were then became the basis of the model development. A panel of experts was selected to verify the research model and questionnaire design. Data from the expert opinions was analysed by using I-CVI and Kappa analysis. To gain the reliability and validity of items from the revised questionnaires, a pilot study was conducted. Data collected from pilot study was analysed by using Rasch Measurement Model. An empirical study was then performed by administering the instrument to 140 big data practitioners in selected Malaysian Public Sectors through a drop-off survey method. SPSS software was used for descriptive analysis, while PLS-SEM was used for statistical analysis in which eleven hypothesis were tested empirically. The results indicate that resource commitment, analytics skills and managerial skills factors are not significant on BDA implementation, while the rest of the influencing factors such as big data strategy, analytics culture, top management support, data infrastructures, information processing and information quality are statistically significant. In addition, the relationship between analytics culture and BDA implementation is improved by introducing the moderating role of top management support. The revised BDI model was then validated further by the experts using a developed prototype. A usability test with big data users was conducted to assess the feasibility and applicability of the prototype in the field. Based on the expert evaluation and usability testing, the prototype is believed to be able to assist decision-makers understand the key determinants and address the issue on the lack of resources that must be considered during BDA implementation. It is also believed that organizational decision making and future strategic planning can be improved by providing significant information on the strength and shortcomings of the affecting factors on successful BDA implementation