Cambridge report explores the Future of Patent Analytics


Our new report on “Exploring the Future of Patent Analytics” 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.Capture2

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.

Report download link:

Jeremiah Chan (Google) live broadcast from Silicon Valley in Cambridge IP management lecture

Massive thanks to Jeremiah Chan, Legal Director for Global Patents at Google for joining us today live on video from the Silicon Valley in the fourth lecture of the Innovation & Strategic Management of Intellectual Property module @Cambridge_Eng.


For engineering students the University of Cambridge launches new course on Innovation and Strategic management of Intellectual Property

Very pleased to see the launch of the new eight-week course on „Innovation and Strategic management of Intellectual Property“ (4E1) on Wednesday this week. The course is taught at the University’s Department of Engineering attended by approximately 60 undergraduate, graduate and postgraduate / PhD students from different programmes. The course is mandatory for the IfM’s MPhil ISMM programme (Industrial Systems, Manufacture and Management) as part of this year’s redesigned curriculum.


The IP management module covers topics such as protection, enforcement and risk management, markets for technology and licensing, open innovation and appropriation strategies, but as well as insights into how firms organize for effective IP management and IP analytics for technology intelligence.

The course is taught by Dr Frank Tietze, head of the Innovation and IP Management (IIPM) research group, based within the Centre for Technology Management, Institute for Manufacturing. The module is supported by guest speakers from the UKIPO and EPO as well as senior IP managers from ARM, Google and ThyssenKrupp.

Further details are available here:

Isn’t this a bit funny? A Research Policy article with the same top level title as our Technovation paper from 2015

A current, in press RP paper is titled “To own, or not to own? A multilevel analysis of intellectual property right policies‘ on academic entrepreneurship„. Sounds to me quite similar to our 2015 Technovation paper with the title „To own or not to own: How ownership impacts user innovation–An empirical study„. Maybe our choice for the title was not too bad then.

How innovation research can create more impact – reflections on this year’s #Druid17 conference in New York

Over the last two days I attended the DRUID conference in New York. It has been an excellent experience. While this might be partially explained by the unbeatable location, I found the intellectual conversations and particularly the DRUID debates extremely inspiring and on a fantastic high level.

The conference features two debates, with the first one on engaging with practice (and the problem to create impact) and the second on focused on theoretical and empirical contributions in academic papers.

Particularly when I was listening to the second DRUID debate it struck me that the debate circled around a particularly view of what must be considered one particular way to understand what theory is. It seems to me that most colleagues (possibly mostly the younger ones) understand theory predominantly as an instrument to provide explanations of existing phenomenon, particularly of those which warrant explanation (i.e. are relevant). Accordingly, the type of theory to be developed and tested usually seeks to explain ‘why’, in other words to explain the causalities within and around certain phenomenon (i.e. interrelations of constructs). From my understanding, such an understanding essentially forces researchers to become concerned with existing (ex post) conceptual or empirical phenomenon and will inevitable aim at developing explanatory theories. Let me try to explain why I think this approach is linked the problem that the community faces about creating impact through research (i.e. discussed during the first debate) and how this could possibly be changed.

There is an alternative way of thinking about what theory is, which was briefly touched upon by Martin Kilduff during the second debate. One may want to consider whether to disregard the phenomenon focused approach and substitute it with a focus on economic or managerial problems (e.g. the strategic alignment problem). Focusing on a problem (instead of phenomenon) offers a different cognitive space and thus a way for the field to create the impact it deserves with all the intellectually power of extremely capable colleagues behind it. Let me try to explain how I see it.

Focusing on problems will drive researchers to theorize solutions, some of which might be sub-optimal, but through empirical testing, validation and refinement one may (eventually) arrive at a fairly optimal solution to a certain problem. Hence, when focusing on problems the type of theory to be developed will be of inherently different nature than the theorizing that takes place when aiming to explain phenomenon. Instead of taking an ex-post observatory approach researchers will be forced to develop theories, i.e. an understanding of causalities that need to be set in action for solving a problem. These kind of theories can likewise be tested empirically, even though we may need slightly different methods (e.g. simulations). The next step would then be to develop policy frameworks (which can turn out to be highly relevant policy implications) as well as tools and techniques (to be put forward as managerial implications), which in turn can be tested empirically (i.e. their performance). We may also need to develop particularly skills, if not guidelines to frame and define problems.

Taking such an approach to empirically supported theory development may contribute to changing the research conducted in the community towards a way that creates impact, while being rigorous. Research will then become a creative (problem solving) endeavour with relevance and impact.