Abstract

The objective of this study is to examine the challenges affecting Information Technology Projects in Public Sector, with Kenya Revenue Authority as a Case Study. A lot of changes have occurred in organisational and functional processes calling for these changes to be managed. These changes have led to organisations adopting Information and Communications Technology (ICT) and implementation of systems such as Integrated Tax Management System (ITMS) which seeks to enhance service delivery. Traditionally, Public Service organisations had little need to worry about market share and increasing competition since they operate in a monopolistic environment. But in recent time and with a view to achieving the Vision 2030 goals through performance contracting, emphasis on Public Sector Management approaches has forced public organizations to pay closer attention to their service delivery as consumers have begun to expect and demand more for their tax cents. Kenya Revenue Authority has undergone a lot of transformation in order to cope with the changes that have arisen with time and this has even forced the organization to re-structure. These changes include business re-engineering, automation of business and functional processes some of which is implementation of ITMS, and Enterprise Resource Planning (ERP). Factors such as stakeholder involvement/support, resource allocation, training/skills level, change management and top management could affect implementation of these systems. In respect of the above objectives of the study, data will be collected using self administered questionnaires from a sample of one hundred and fifty (150) Kenya Revenue Authority employees who will randomly selected from the eight departments in which automation has been implemented. These departments are Customs Services, Domestic Taxes, Road Transport, Human Resources, Finance and Procurement, ICT, Administration and PMBO. Data collected will be analysed using Statistical Packages for Social Sciences (SPSS) which will descriptive statistics inform of frequencies, percentages and mean scores. The data will then be summarised and presented using tables, pie charts, and bar graphs. Based on the findings the researcher will then make a conclusion and give recommendations.