Imagine every Western economy is running on a treadmill — working harder but not actually moving faster. That's the productivity paradox. BIGPROD built new measurement tools that use big data from 160,000-200,000 European companies to figure out why this slowdown is happening and what policymakers can do about it. Think of it like upgrading from a bathroom scale to a full-body MRI — you finally see what's really going on under the surface of economic growth numbers.
Most Western economies are experiencing a productivity slowdown — companies invest more in technology and innovation, yet output per worker barely moves. Traditional economic models fail to capture the impact of digitalization and big data on real productivity, leaving policymakers and business leaders making decisions based on incomplete pictures.
BIGPROD built an extended version of the standard CDM econometric model incorporating big data measures, tested it on a sample of 160,000-200,000 European companies, and validated it through 3 pilot studies (high-tech, low-tech, and services sectors). The project produced 21 deliverables including validation workshops, expert consultations, and an expanded data architecture.
If you are an economic consulting firm struggling to explain productivity gaps to government clients — this project developed an extended econometric model validated across 160,000-200,000 European companies that measures how big data and digitalization actually drive (or stall) productivity. The 3 pilot studies cover high-tech, low-tech, and services sectors, giving you ready-made analytical approaches.
If you are a business intelligence provider looking for new analytical methods to benchmark company performance — this project created a tested data architecture that connects big data measures to productivity outcomes. The methodology was validated through 3 separate pilot studies and consultation workshops with domain experts.
If you are a government agency responsible for measuring economic performance and innovation outcomes — this project extended the standard CDM productivity model with big data indicators, tested on a sample of 160,000-200,000 companies across Europe. The multi-criteria impact assessment approach helps you validate results before integrating them into official indicator sets and observatories.
BIGPROD produced an academic methodology and data architecture, not a commercial software product. Adopting the extended CDM model would require econometric expertise and access to large-scale company datasets. Based on available project data, no pricing or licensing model was established.
The methodology was designed for and tested on a sample of 160,000-200,000 European companies, so it operates at a significant scale already. The 3 pilots covered high-technology, low-technology, and services sectors, suggesting broad applicability across industries.
As a publicly funded Research and Innovation Action with 6 academic and research partners, results are likely available through open access publications. Based on available project data, no commercial licensing terms were established. Contact the coordinator at VTT (Finland) for specific IP arrangements.
The project used a multi-criteria impact assessment approach with 3 pilot studies: high-technology and digitalization, low-technology and innovation outcomes, and services with incumbent-entrant dynamics. Validation workshops and expert consultations (including data science experts) were conducted as documented in the deliverables.
The model was operationalized using a random stratified sample of 160,000-200,000 European companies. Based on available project data, it combines traditional econometric data with big data measures, though the specific commercial data sources are detailed in the 21 project deliverables.
This is a research methodology, not a turnkey business tool. The 3 pilots demonstrate proof of concept, and the data architecture has been tested and expanded. However, translating this into a commercial product would require additional development and packaging.
The BIGPROD consortium consists of 6 partners across 5 countries (Germany, Finland, Lithuania, Netherlands, UK), led by VTT — Finland's leading applied research center. The consortium is entirely academic: 3 universities and 3 research organizations, with zero industry partners and zero SMEs. This 0% industry ratio signals that the project was designed for research and policy impact rather than commercial deployment. For a business considering adoption, this means the methodology is scientifically rigorous but would need a commercial partner to turn it into a usable product or service.
VTT Technical Research Centre of Finland — search for BIGPROD project lead at VTT
Want to understand how big data productivity insights could benefit your sector? SciTransfer can connect you with the BIGPROD research team and help translate their findings into actionable intelligence for your organization.
