PERCEPTION OF BARRIERS TO DATA DRIVEN DECISION MAKING PRACTICES IN PUBLIC SECTOR UNIVERSITIES OF SOUTHERN KHYBER PAKHTUNKHWA PAKISTAN

Abstract

Data driven decision making (DDDM) has become an important approach for improving evidence based planning, resource allocation and institutional decision making process in higher education. Public sector universities are increasingly generating and using academic, administrative, financial, planning and development and research related data to support effective institutional decision making. The aim of the study is to investigate the data driven decision making practice and barriers to implement it. All the heads of department, deans of faculty and administrative officers of the public sectors universities of southern Khyber Pakhtunkhwa are constituted the population of the study. The self developed valid and reliable questionnaire was distributed among all the participants for the collection of data. Data was collected from 71% population. For statistical analysis, descriptive statistics (Mean and Standard Deviation) and inferential statistics (one way ANOVA) are used. The findings reveals that data is used in academic and administrative affairs, strategic planning and resource allocation, teaching effectiveness and curriculum review process, and students retention, success and dropout rates but the centralization of power, technological tools, lack of skilled personnel, administrative workload, political interference, data verification, limited ICT infrastructure, insufficient financial resources and leadership commitment are the barriers to implement data driven decision making. The results also reveal an important gap between the availability and use of technological tools. There is no statistical difference among the perceptions of heads of department, deans of faculty and administrative officers.  The findings may help university administrators and higher education policymakers to promote systematic and evidence based decision making practices in public sector universities.