A study of enablers that facilitate successful data driven performance management systems

Data driven decision making commonly known as analytics in performance management is one of the crucial areas for an employee and the organisation. This paper attempts to study the enablers or the variables that facilitate the implementation of analytics in performance management systems (PMS). The researchers have adopted the total interpretative structural modelling (TISM) approach for the study. The methodology started with extant literature review to identify enablers which were validated through expert opinion. The expert opinion was converted into structural self interaction matrix, reachability matrix and the model was derived. The findings of the study showed that governance is important to smoothly implement data driven PMS. Knowledge management practices helped capture information related to key result areas, it also supported future functions. A competent HR professional, strong data infrastructure support, strategic cascading for clear well-defined goals and organisational culture were also responsible for enabling data driven PMS.