A short interview with Patrick Mikalef, Professor of Computer Science and Information Systems, who has written this report.

How would you summarize the main take-aways from the results of the literature review?

– After a decade of research on the business value of big data analytics, there are several important take-aways. I would say that the most important result is that value from big data analytics is not technology-driven, but organizational driven. Studies emphasize key components as the skills of employees at different firm levels, breaking down data silos, enabling cross-departmental collaboration, establishing a data-driven culture, and fostering an environment of experimentation. Studies also show that it requires time to experiment, scale-up and deploy applications to create value.

How would you characterize the policy perspectives being discussed in the literature?

– Studies usually over-emphasize the research and practical recommendations, and misses the opportunity to discuss policy perspectives. However, we know for example that certain industries are lagging in the use less big data analytics, which is primarily due to the lack of know-how, and the unclear understanding of what value it would bring. It is thus important to have precise incentives in order to aid small and medium firms, or companies in industries not tech-oriented. It is surprising that there are no comparisons between countries’ different policy approaches, which increase knowledge about which incentives are useful and how their outcomes are identifiable.

Do you see any low hanging fruit for either firms or policy makers to facilitate for firms to reap the benefits from BDA?

– Struggling firms usually lack the know-how and availability of data in order to create value from big data analytics. By encouraging more tightly-knit collaborations between clusters of firms and academic and research institutions would greatly help in transferring this know-how. Also industry-research funding incentives can be helpful, either through formalized joint ventures or even as something as informal as more academia-industry collaboration in education. Financial support can prompt firms to experiment with these technologies without having to deal with the risk of uncertainty that comes with adopting such technologies.

Now switching gears, and taking a forward-looking perspective, what do you suggest should be the main areas of focus for the research community, policymakers and private actors in order to take advantage of the digital technologies that are being developed at a rapid pace such as BDA, AI, etc.)

– A core barrier for many firms, although basic and fundamental, is how to manage corporate and open data. Firms do usually not have a good understanding of what data they possess, it’s value, and how to manage it effectively. So both data literacy as well as corporate and industry governance of data is key. Opening up the discussion about data availability and data sharing in entire ecosystems in which firms operate is very important and ultimately enables economies to grow.