Exploring the future of patent analytics


Leonidas Aristodemou and Frank Tietze

Download the report here.


In a connected world, where successful technological development increasingly depends on collaboration between different partners, effectively utilising patent data analytics has significant, yet untapped, potential. Given the right analytics solutions, this high-quality data can be used for decision-making at a strategic level in a variety of organisation types.


This report contributes to expanding the field of patent analytics for more effective exploitation of the largest worldwide repository of technological information. The report may further help to facilitate collaboration and coordinated action within the patent analytics community. 


The report presents a domain-level technology roadmap following a three-stage technology roadmapping and problem-solving approach involving a substantial amount of key stakeholders from the patent analytics community. This research was funded by the United Kingdom Engineering Physical Science Research Council (EPSRC), through the Cambridge Big Data initiative as part of an EPSRC Institutional Sponsorship Grant 2016 – Small Partnership Awards, supported by Aistemos Ltd as the industrial partner.



The research identifies 11 priority technologies, such as artificial intelligence and neural networks, 5 additional technologies, such as technologies for linking databases, and 15 complementary technologies, such as block chain, to be adopted in the IP field. Also, 21 enablers are identified for potential breakthrough progress in the field that cluster around 4 themes: technology development cycles and methodologies; legislation and standardisation for patent data quality; continuous professional development; and cooperation between industry and academia.




The report was prepared by Leonidas Aristodemou and Dr Frank Tietze from the Innovation and IP Management (IIPM) research group, which is part of the IfM’s Centre for Technology Management at the Department of Engineering, University of Cambridge.



Download the report here.

For further information please contact:

Dr Frank Tietze

T: +44 (0) 1223 338083

E: frank.tietze@eng.cam.ac.uk