engleski

From analytic to predictive digital performance measurement - Big Data challenge for controlling

The aim of this research is to present possibilities for controlling regarding digitally oriented performance measurement and a proactive role in decision making. The goal is to develop a conceptual model of “digital proactive/prospective controlling” useful for predictive analysis in private and public- oriented organisations using a range of “information literacy ”. Due to digital technology, data, and information explosion, we need to develop analytical methods and models that will satisfy efficient business decision making. Controlling as one of the important functions in an organisation that provides analytical processing and creation of information for decision making purposes is now deeply affected by the challenges of digital technologies. Analytic or retrospective view of performance measurement is changing to predictive or proactive. Big Data enables controllers to use more accurate data and develop advanced measures. The emphasis is on the prediction of future problems or identification of potential opportunities which will lead to the growth of added value. As a result, the role of controllers as business partners needs to be further strengthened through its holistic analytical prospective thinking that will contribute to more efficient decision making. To find out the current state of controllers' digital development, a desk research of the existing scientific literature has been conduceted followed by interviews with controllers and responsible management in key positions of the selected organisations. Although the research was limited to a small group, primary findings show that the controller’s role will partially change in the future. Based on theoretical background and empirical research, we proposed the conceptual DPC model for the new era of controlling.

controlling ; Big Data ; digitalization ; performance measurement ; prediction

Cjeloviti rad objavljen u 2019. godini u Zborniku radova konferencije (Pogledati rad CROSBI ID: 937326)