The effective use of digital technologies to create business value has generated enormous data, and using data in decision-making is vital. Although there is growing empirical evidence in favour of a positive association between informed decision-making and firm performance in developed countries, there is little to no evidence of a large-scale study in an emerging economic context. Moreover, there has been scant empirical evidence on how DDDM affects productivity in the banking sector of developing countries. This study examined the impact of DDDM on the productivity of Pakistan’s banking sector from 2016 to 2020 based on primary and secondary data collected from banks registered in Pakistan. The findings suggest that banks who adopt DDDM practices show a 4–7% increase in productivity depending on adjustment to change. We believe this study would shed light on the importance of DDDM in the banking sector of developing countries.

The increased access and availability of information technology solutions have brought structural shifts in traditional business models, processes, and activities worldwide. As a result, the innovative ways of doing business and practices have disrupted the traditional businesses and technologies. This study investigates the impact of investment in data analytics on the financial performance of banks in Pakistan. A sample of 32 banks including commercial and microfinance banks for 2010 to 2019 was selected. Random effect panel estimation and instrumental variable two-stage least square were employed to quantify the impact of data analytics on firm performance. The results indicate that investment in data analytics increases the productivity of banks by 10%. However, the impact of investment in DA on profitability measures including return on assets, return on equity, and net interest income was negative, reflecting the “profitability paradox.” In the current era of digitalization, the banks need to invest in innovative technologies which have analytical capabilities to remain competitive and sustainable.

This research stems from the disturbing phenomenon known as digital transformation and the colossal data creation. A vast amount of data has been produced as a result of increased usage of digital technologies to generate commercial value. However, data does not hold any value, so organizations are motivated to invest in data analytics and make informed decisions to enhance their performance. Against this backdrop, this study investigates the impact of data-driven decision-making (DDDM) on productivity in the presence of data analytics capability of Pakistan’s banking sector. We explore this link based on innovation diffusion theory using Instrumental Variable Two-Stage Least Square. A composite index of DDDM was developed based on primary data collected through online survey. This index is then regressed on actual productivity measures for 2016–2020. The findings suggest that banks exploiting analytics and adopting DDDM methods results in an increase in productivity of about 9–10%. It further indicates that DDDM adoption with an investment in data analytics leads to enhanced productivity.

Digitalisation is portrayed as a transformative force, remodelling the way we live and businesses operate. In today's unprecedented business environment, the survival of organisations is in technological advancement and online presence. When masses rely on digital financial payments, there is a pressing need for the financial sector to offer innovative products and services to meet customers’ needs and achieve sustainable performance. This paper aims to investigate the impact of data analytics on the productivity of banks in Pakistan and employed two-step system generalised methods of moments for estimation. The findings suggest that 5.9% productivity is increased for banks that invested in data analytics on average. It was also found that productivity increase is associated with an investment in data analytics compared to a mere investment in any software. However, the moderating role of dynamic capabilities on the relationship between data analytics and banks’ productivity is insignificant, which raises a question on the relevance of research and development expense with human capital development. It is recommended that banks should invest in those analytics that have predictive, visualising and analytical capabilities. The use of these innovative technologies should be combined with training and human capital development to ensure sustainable firm performance.