Data driven decision making in public administration: An assessment based on business intelligence maturity model

The governance practices that have emerged over the last 30 years and the decision-making processes in the governmental mechanisms have been changing. Emerging information technologies are more questionable and have brought up governance, which is a management approach according to effective resource distribution. Many developed countries benefit from a more rational and fair use of public resources and analytical management to provide a sustainable ergonomic life for their citizens. For the many opportunities that the state offers its citizens, such as health, safety and education, Information Technologies (IT) is at the service of citizens. From e-government applications to industry 4.0, IT is an indispensable position. In this context, the decision-making patterns in public administration also change. Managers make more use of information technologies when they decide. Within the framework of this new management approach, the use of information technologies will inevitably grow and develop in public administration in the long term. This will increase the importance of data-based and model-based decision support systems and make them more popular. The public will also know the level of decision makers in the context of Data Driven Decision Making (DDDM), in other words, the knowledge of their maturity levels will reveal what they should do to improve these systems. Institutions that are not at a certain maturity level cannot use business intelligence Business Intelligence (BI) applications in their decisions. Determination of maturity levels in the BI context will be an important step for drawing their own roadmap for their DDDM. It will also arise from the suitability of BI practices for decision-making mechanisms of public institutions. Within the scope of this thesis, first of all, decision making theories in public administration will be examined and new management concept and developing information technologies will be discussed. Then, a general definition of DDDM, which is one of the Decision Support Systems, will be made and the DDDM applications for the public sector will be discussed. The maturity of BI for DDDM will be discussed and the maturity models for the public will be investigated. It will also be questioned whether the use of business intelligence practices for public administration is appropriate. Finally, in-depth semi-structured interviews with 3 public institution managers will be analyzed and the BI maturity levels will be put in place in the context of DDDM for Public Institutions. The maturity level of the institutions concerned will be determined by the maturity level.