EVALUATING DATA ANALYTICS ADOPTION IN SELECTED COMPANIES OF THE FINANCIAL SECTOR IN THE REPUBLIC OF NORTH MACEDONIA

Abstract

Data analytics has become one of the driving forces for digital transformation efforts of companies around the world (Keary, 2019). Nowadays, in a highly digitized environment, companies generate data across different sources which is increasing rapidly in volume, variety and velocity. There is no doubt that companies can use these datasets for creating a more efficient services that deliver a more targeted customer experience. Hence, the importance of data analytics has become essential for organizations to find new opportunities and gain new insights to run their business efficiently. Emerging literature and the empirical evidence suggest that companies from the financial services sector have a lot to gain by adopting data analytics (minimize risks, detect fraud, improve credit risk management, improve marketing activities in real time etc.). In spite of that, companies in the country are still in the early stages of adoption of data analytics technologies. This research is a pilot study and represents the first attempt to assess the data analytics adoption maturity in selected companies of the financial sector in the country. The methodology used in this research for evaluating data analytics adoption is based on Maturity Model for Data and Analytics (IT Score for Data and Analytics) (Gartner, 2017), since it best describes maturity levels in service sectors. The assessment is founded on interviewing managers using questionnaire that guides respondents through all dimensions and levels proposed by the model. In the model four measurement areas are analyzed: Strategy, People, Governance and Technology. For each area, five maturity levels are defined: Basic, Opportunistic, Systematic, Differentiating and Transformational. Survey results confirmed that analyzed companies fully understand the benefits of data and analytics as valuable source to gain competitive advantage from data and the overall level of data and analytics maturity is set on level 2 for almost all dimensions.