Looking at companies like Google and Amazon innovating new services for consumers or the ability for doctors to detect cancer cells more precisely from through creating massive training data on what is a cancerous cell, we are very much in the cusp of creating a broad utility of “Big data”. This being said, public policy is not at the forefront of utilizing “Big data” in decision making. We know that novel big data and analytics based methods can have a significant impact to public policy-making and BIGPROD addresses the issues by adopting big data measures on understanding the “productivity paradox”. In the communication from the European Commission (26.2.2020) on the 2020 European Semester it is noted that "“[p]roductivity growth remains a challenge, even more so in the light of demographic change…" In addition, "…[t]here are multiple causes for this weak performance…" and "…[p]olicies to foster productivity need to be tailored to national circumstances…”. This highlights the importance of the BIGPROD project.
However, adopting big data measures is not simply a question of technical capability to create novel measures. Big data and analytics comes with new challenges involving reproducibility, complexity, security, and risks to privacy, as well as a need for new technology and human skills. We know that, institutional capacities have a significant role to play in the use of “Big data” in public policy, particularly on what will be the impact “Big data” information on the policy cycle. We need to better explain and make transparent the utility and complementarity of “Big data” driven analysis into the policy cycle. In the case of productivity, “Big data” per se can not solve the productivity challenge. Rather the question at hand is if novel measures can create additional vantage point to understand an important question in our society and if we then can integrate it with the policy cycle.
The objective of the BIGPROD project is to extend existing econometric approaches on productivity with a theoretically sound “Big data” measures that can be operationalized and validated through pilots. In addition we are addressing issues beyond the technical capability of creating new metrics. This is achieved through deep stakeholder consultation mitigating the skills gap, creating transparency, enabling stakeholder influence in sources and tools and enabling policy makers being informed on tools and pilots. The goal of the project is to 1) create tools for utilising “Big data” for innovation and productivity assessment, 2) extended econometric framework for the evaluation of the productivity-innovation link based on “Big data”, 3) build a large-scale data platform, 4) create policy-relevant pilots that measure the impact of proposed changes, and 5), use the most effective tools available to effect stakeholder engagement and co-creation, while simultaneously ensuring the dissemination of the knowledge gained in this process to the wider public.
