Measuring Innovation – the UK?
(An updated extract from a presentation to the Thai Government 2013)
David Dent
Chief Technical Officer, Azotic Technologies Ltd
Special Advisor, Parliamentary & Scientific Committee, Thai Government S&TI Office
Introduction
When it comes to consideration of a nation’s innovation policy there are numerous
questions that will come to mind but I always feel compelled to ask, “how well do the
measures and indicators used to set policy, properly and effectively reflect the actual
drivers, processes and types of individuals involved in the delivery of innovation?”
Innovation is such a key component of economic growth that we really cannot afford
to be complacent about the assumptions that underlie our approaches to it. Having
been involved with innovation in a range of different types of businesses and advising
governments on innovation policy, I feel fairly well positioned to question the
relevance of some of the indicators and policies enacted in the UK and to suggest
areas where we may seek to make improvements.
Measuring Innovation
International indicators are important for Governments, because they set
benchmarks by which they may be publicly judged. So being able to satisfactorily tick
the appropriate boxes or explain why one does not, is important. So just how do we
measure innovation? The OECD and the EU run systems with a variety of
measurements that they consider as good general indicators of innovation applicable
across a broad spectrum of economies. The EU - Innovation Union Scoreboard in
2014 had a measurement framework based on the use of three main Indicators:
Enablers, Firm Activities and Outputs.
The Enablers category refers to the human resources, the extent of open excellent
research systems and systems of finance and support available, while Firm/company
activities include; firm investments, the extent and nature of linkages &
entrepreneurship and measures of intellectual assets. Last but not least, Outputs
consider measures relating to innovators and their economic effects and impacts.
Having a mind to making this article a readable length, and having a passion for
understanding the conditions necessary for innovators and entrepreneurs to flourish,
I propose to focus the rest of the article on the Enabler indicators.
So, if we explore the Enabler indicators in a bit more depth we find that the ‘Human
Resources’ category refers to measures of the number of new doctorate graduates,
the population aged 30-34 with tertiary (University) education and the proportion of
youth with an upper tertiary education; while the ‘Open excellent research systems’
considers measures of the number of international scientific co-publications that are
achieved by a nation, the top 10% most cited scientific publications, and the
contribution of non EU Doctorate students to the overall academic population. Finally
the ‘Finance and Support’ category considers overall levels of R&D expenditure in
the public sector and the extent of Venture Capital investments that are made.
Innovators and Entrepreneurs
The emphasis on new doctorate graduates, the population aged 30-34 with tertiary
education, and the youth having an upper tertiary education (higher university
degrees) is interesting because it implies that an Masters degree, a PhD or a
University Degree are useful indicators of innovation and/or the likelihood that
entrepreneurism will flourish. However, in my own experience, the people I know
who are innovators, I question whether this is likely or true - that a higher education
qualification or University degree is a good indicator of innovator capability? If we
look at SMEs and some of the entrepreneurs that play the essential role in
transforming invention into innovation and investigate their qualifications it may give
us some insight into the qualifications of an entrepreneur.
Firstly – a dictionary definition of an innovator, is ‘a person who does not mind
introducing a new way of doing things to others’. The Harvard Business Review
consider the key attributes of innovators, referred to as an ‘Innovators DNA,’ as the
ability to be:
 Associating
 Questioning
 Observing
 Experimenting
 Networking
What is interesting about this list is that there is not a single attribute that is exclusive
to skills secured at a tertiary level education or above? So how do the qualifications
of those business leaders of the most entrepreneurial sector (SMEs) measure up to
the requirement for a tertiary level of education? According to a Barclays Bank 2007
study only 46% of SME Chief Executives had a University degree, with 20% of small
business owner-managers only educated to GCSE level or below and when asked,
only 11% of UK CEOs believe achieving a good education is crucial to business
success (Barclays 2007). Figures from Startup (2013) show that the highest
qualification held by SME owner managers tends to be A-Level or equivalent (29.4%)
followed by a degree or equivalent (21.8%). However, a significant minority of owner
managers – 11% – has no educational qualifications whatsoever. It is perhaps also
surprising, that 10% of FTSE100/250 Company CEOs did not attend University in
2013 (HR Review, 2013) and only 28% have an MBA and one in ten a PhD (Robert
Half, 2014). However, the SME figures are particularly telling when one realises that
such small businesses provide >67% of the UK’s private sector jobs and >50% of UK
GDP.
Stories about successful innovators and entrepreneurs abound but I always find it
striking how so many of the internationally renowned individuals have, one way or
another, failed to complete school or university. These include but are not limited to:
 Michael Dell; billionaire founder of Dell Computers, dropped out of college
 Ray Kroc; founder of McDonald’s dropped out of high school
 Richard Branson; billionaire founder of Virgin Records, Virgin Atlantic
Airways, Virgin Mobile, dropped out of school at the age of 16
 Simon Cowell; TV producer, music judge, American Idol, The X Factor, and
Britain’s Got Talent dropped out of high school.
 Steve Wozniak, and Steve Jobs; co-founders of Apple - billionaires who did
not complete college.
 Tom Anderson; co-founder and “friend” of MySpace dropped out of high
school.
 Bill Gates started university but then decided to leave to found Microsoft.
Further study is clearly required in this area, to discover how and where
entrepreneurism and innovative capability manifests itself, but I have found
surprisingly little evidence that such capability is dominated by the highly educated. It
may be wishful thinking by Government or those with vested interests, and act as a
justification for investment in higher education and academic research but, as a
genuine indicator of human resource capacity for innovation, the use of measures of
tertiary education, especially higher tertiary university education, leaves in my opinion
a great deal to be desired.
Excellent Open Innovation Systems
Everyone talks freely about ‘innovation’ but sometimes there is confusion as to what
constitutes innovation as opposed to invention. The process of invention involves the
generation of new concepts, methodologies or devices that derive from individual’s
ideas or sometimes, through the outputs of scientific or technical research. In
marked contrast, to invention, innovation addresses the commercialization or the
bringing to market (applied also to social or charitable products or services) of an
invention. An invention on its own has little economic or social value – to monitize
and/or for society to gain value from an invention, it needs to be transformed through
innovation! Interestingly the creative process that leads to invention may be
‘technology supply-led’ or ‘market-gap led’ (Dent, 2010). For the most part the
former rather than the latter is emphasised in the use of indicators for innovation (see
the article on this website for an explanation of the implications of this approach).
The indicator for assessing the effectiveness of open, excellent research systems
relates to the number of international scientific co-publications, top 10% most cited
scientific publications and engagement of non EU Doctorate students within the
country. This implies that a formal high quality academic research capability,
particularly scientific research and its publication in high impact academic journal
should be a pre-requisite for, or a good indicator of, innovation?
Universities are seen as a key driver of innovation in the UK, but the reality is that
University IP and innovation outputs tend to be modest and in fact better perhaps
relate to some limited measure of invention as a precursor of innovation than
anything else!
The UK Government has for many years prioritised and championed the excellence,
particularly the world-class nature of our science, and this emphasis has yielded very
positive results. For example, according to BIS (2011), by 2010 UK researchers
generated more articles per researcher, citations per researcher, and usage per
article than US, China, Japan and China, and in a more recent report (BIS, 2014) the
UK research base is described as continuing “…to produce a large output for our
moderate size, with a sustained track record of high quality research. With just 4 per
cent of the world’s researchers, the UK account for 6 per cent of world articles, 12
per cent of citations (a key measure of research excellence) and 16 per cent of the
most highly cited articles.”
But does research excellence actually relate to innovation potential? To address this
question we have to understand something of the hopes and aspirations of
Government in their support of research in our universities. Highly cited publications
in high impact academic journals usually (but not always), come about from research
that addresses fundamental scientific, technical and methodological issues. This type
of research is capable of generating radical new concepts, methods, or devices that
can be regarded as General Purpose Technologies (GPT’s). From a government
perspective a GPT represents the ‘holy grail’ of technologies because of the
significant impact they potentially can have on a national economy, but also
internationally. The primary feature of general ‘purposeness’ of a GPT, is their role in
performing some generic function that is vital to the functioning of a large segment of
existing or potential products and production systems. A secondary characteristic is
their technological dynamism: continuous innovational efforts, as well as learning,
increase over time the efficiency with which the generic function is performed
(Bresnahan and Trajtenberg, 1995).
Examples of GPT’s include electricity, computers, lasers, the internet, biotechnology,
nanotechnology and most recently from the UK, graphene. GPT’s are often
generated in multinational collaborative programmes. For this reason and a number
of others, the development and specifically, the exploitation of GPT’s, is particularly
difficult. Firstly such inventions are rare, and when they do occur in order to secure
sufficient IP protection their value must be immediately recognised, secured and
resourced. The UK has a very, very poor track record in this area – and sadly
graphine is yet another example of this continuing failure. In 2010 the Nobel Prize in
Physics was awarded to Andre Geim and Konstantin Novoselov of the University of
Manchester “for groundbreaking experiments regarding the two-dimensional material
graphene”. In terms of scientific and engineering excellence for the UK, the award of
the Nobel Prize enhances the UKs reputation, however reputations do not
necessarily create jobs or wealth!
The worldwide dataset for ‘graphene’ published between 2005 and 2014 contains
over 25,000 published patents, equating to over 13,000 patent families. However
almost half of graphene patents were ‘first filed’ in China, with less than 1% of the
total graphene-related patents having been ‘first filed’ in the UK! This startling fact
means that the UK has effectively lost any control and access to the vast majority of
potential commercial benefits that could have arisen from this technology, simply by
failing to quickly recognise the inventions potential and its value to the UK’s
economy. The subsequent availability of investment and creation of the National
Graphene Institute was a brave but belated step by the UK Government to recover
lost ground – but it is ground that will never be recovered, and the manufacturing
companies, the employment and growth in the economy that could have been
secured for the UK has been lost to China, Korea and the USA!
Such failures should be regarded as national disasters, but they are symptomatic of a
wider malaise in the UK’s National Innovation System: the emphasis on Universities
as the main source of invention (not just GPTs) may itself be seriously flawed.
There is evidence to suggest that the vast majority of inventions that drive a nations
economic growth are not actually delivered through fundamental research from our
Universities: a point that was emphasised in a report published in 2011 produced for
Mobius, at BioCity in Nottingham. The authors of this report, Connell and Probert,
went as far as to say “The over-glamourised notion of the University boffin as the
prime source of inventions that can rebuild the UK’s scientific industrial base is
seriously misleading.” The duo’s research demonstrated that many of the largest and
most successful science and technology businesses in the South East England did
not owe their origins to University IP but rather to what they referred to as Soft
Companies - science/technology based companies whose business model is to
provide R&D services (e.g. technical consulting, contract R&D). Such companies
draw on its internal expertise and/or proprietary technologies to provide bespoke
offerings for a range of customers and applications.
The primary income source of Soft Companies is from commercial customers with
some form of innovation requirement. Their economic contribution comes from
scaling-up, developing spin-outs and exploiting their own IP through licensing. In SE
England around 50 Soft Companies employed >3,500 people and generated
>£400m/yr. One of the great advantages of the Soft Company is its suitability as an
easy start-up model as well as a business growth model (developing capability,
market understanding, technical staff & IP). The model also works for a wide range of
industries e.g. drug development, engineering, medical devices, agri-technology,
software & ICT, consultancy and instrumentation.
Interestingly, productive interactions between Soft Companies and Universities are
largely restricted to the provision by Universities of trained PhD qualified scientists
and engineers, with only a low transfer of University IP to Soft Companies.
Collaborative research programmes while possible were deemed too complex, time
consuming and unproductive in terms of Soft Company requirements “dysfunctional”, “takes our researchers further from the market”, and “time scales are
too long” (Connell and Probert, 2011).
Overall the measurement of ‘excellent open innovation systems’ utilizing information
on academic publications and its use as an indicator of a nation’s innovation health,
is at best misleading and at worst involves an over emphasis and unrealistic
expectation of academic outputs in terms of innovation capacity. There also appears
to be too little emphasis or recognition given to supporting and measurement of Soft
Companies as a means of boosting innovation - an area that could benefit from
Government intervention.
Finance and Support
As an Enabling indicator, Finance and Support addresses measures of R&D
Expenditure in the Public Sector and Venture Capital Investments. R&D investment
from Government in the UK has long been an issue of debate. Unfortunately the UK
is one of 3 countries in the top 20 GDP nations that have decreased R&D intensity
between 1993-2009 (WIPO, 2011) and in 2012 the UK’s R&D intensity decreased by
further 2% to £27 billion compared to 2011 (ONS, 2014). The UK’s Government R&D
expenditure to Universities was 27% (£7.2 bn) of the total expenditure, while
Research Council funding and National Research Institutes decreased 8% in 2012 to
£2.2 bn (ONS, 2014). So by these measures the UK is a relatively poor performer
and further investment could be justified by international measures!
The emphasis given to Venture Capital (VC) investments as a key innovation
indicator is also interesting, not least because generally VCs only provide a financing
option in less than 0.1% of firms, predominantly during their start-up phase (OECD,
2015). As a proportion of GDP in the UK, VC funding represents only 0.035%
compared to all private equity investments at 0.72% (EVCA, 2015). Hence, it is
perhaps difficult to understand why the extent of VC investments is taken as such an
important measure of innovation.
The reason is most likely based on the success of VC funding for USA companies.
Despite the niche-funding role of VC investments, their inclusion as a key indicator of
innovation is based on the potential role that venture-capital-funded companies can
go-on to play in the wider economy. For example, in the USA, by 2003, companies
that had been backed by venture capital employed around 10 million people, just
under 10% of the US private sector labour force (Shane, 2008). Given that VC
investment in any given year in the USA is normally less than 0.2 per cent of GDP,
this is an astonishing figure.
In a typical VC portfolio, most of the returns are made from 20% of the investments.
This is just a statistical average but it is treated as a law of nature. Thus if a VC
makes ten investments, two will be winners and create most of the gains in the fund.
These statistics inevitably then mean that the remaining 80% are either missing
expected revenue targets, are only breaking even or have made a loss or failed
altogether! According to Shikhar Ghosh, a senior lecturer at Harvard Business
School more than 95% of start-ups fail in the USA (Cage, 2012).
While the 20% rule may be sufficient to guarantee a return for a fund, governments
should surely be asking the question whether such a strategy is delivering the best
result for developing a nation’s economy – given that funding from VCs will be
cherry-picking the most innovative (although higher risk) of our technologies,
business opportunities etc. What is happening to those 80% of businesses if they
have been rated as failed by their VC investor. Forrest (2014) quotes Tomasz
Tunguz, a partner at Redpoint Ventures in the USA, "Typical portfolio company
failure rates across the industry defined as either shutdowns or returning capital, are
roughly 40%-50%." This is staggeringly and worryingly high with regard to a national
innovation strategy, especially given the relative success of VC investment in the
USA compared to the UK.
The UK Venture Capital system is less mature than the US and hence, is further
limited by its (Pierrakis, 2010; Demos, 2010):
 Small fund size
 Limited funding offers
 Limited size of offer
 Lack of syndication and clustering of funds
 Conservative approach to risk
 Small size and scale of market requires internationalisation
Although, the UK Government has taken measures to redress some of these factors
my own and colleagues experience would suggest there is still some way to go. The
implications of which, are that UK companies seeking VC investment find it difficult to
secure funds from more than one VC (or consortium of VCs), the terms are punitive,
a general lack of funding from start-up through to profitability, and hence, the need
for follow-on funds (thereby forcing further dilution of founders equity). No wonder
then that the VCs are known in some quarters as ‘Vulture Capitalists’, an opinion
substantiated by an article (3 July 2014) in The Times Higher Education: David
Latchman set-up a biotech company in the UK in 1999, called BioVex that was very
successful and subsequently 12 years later the company was bought out for £600
million. David Latchman had originally owned 25% of the company which upon sale
was potentially worth £150m. However, his original 25% share ownership had over
the 12 years been reduced by successive investments made by Venture Capital
Companies to the extent that the Founder Director made the grand sum of £423
upon sale of his company!
So as a measure of innovation, the presence of a VC industry might seem an
appropriate indicator of risk capital but whether that industry is actually working in the
best interests of a nation, its innovators and economy is another matter entirely. The
VC industry is cherry-picking the best technologies and entrepreneurial management
teams but potentially leaving 80% to ‘whither and die’, simply because they do not
meet stringent ‘unrealistic’ funding criteria that ensures success of a fund.
Since there are strong reasons for believing that left to its own devices the market will
invest less in venture capital than the level that is socially optimal, (because of the
potential social returns to innovation arising from venture-capital-backed firms which
are not captured by private investors), government intervention to support some of
the VC fund ‘failures’ would seem a logical step. Given also, the due diligence
process that the VCs have been through in selecting the companies in the first place,
plus the initial investment from the VC should give Government some assurance of
the potential value of the businesses in the 80% category and the availability of
appropriate follow-on funds to these companies should be a high priority.
In addition, in looking to determine which ventures are those most likely to succeed,
while it is difficult to identify specific technologies as winners, it may be easier to back
winning teams. Public funds could be effectively used to prime/underpin new types
of venture funds that back serial innovators and entrepreneurs (much the same as
government grant awards support successful Professors). Administering funds based
on track record of individuals is easier than decision-making based on technology
and market risk.
The emphasis placed on VC funding as an indicator of thriving innovation is
misguided given its current business model – it may even be counterproductive for
sustained economic growth.
Financing and support for innovation should focus on the following:
 Identify young early stage innovators and entrepreneurs and nurture them
 Identify innovators and entrepreneurs with a successful track record and
support them
 Support the entrepreneurs in identifying the best technologies and build top
teams around the plans produced for their commercial exploitation
 Invest in winning teams and create serial entrepreneurs who keep finding,
developing and taking new technologies, ideas, processes to market
In conclusion
From this discussion we can conclude that the Enablers indicator of innovation
highlights technically well qualified human resources, evidence of excellent research
reflected in highly cited academic publications, and venture capital funding systems
that cherry pick and undermine sustainable business growth. However, it is my belief
that there exist alternative approaches and indicators that create and recognise
national systems of innovation that match and are relevant to the real needs of those
who actually innovate and generate wealth, whether individuals or organisations.
Firstly, secondary education is more ubiquitous and provides the largest pool from
which to harness entrepreneurial talent. There is a need to focus greater efforts in
schools to identify and support potential innovators and entrepreneurs. These may
not be the individuals who readily excel at school and/or learning in the conventional
sense but rather the more rebellious, tenacious, dynamic, risk-taking individuals who
do not fit the system!
There is a need to accept that for the large part Universities are only ‘ok’ at invention,
that GPTs are rare events and it is difficult to secure their value (although better
mechanisms must be introduced), and they are less successful at innovation and
fund the sector accordingly. Within Universities, spin-out companies based on
provision of innovation services to industry should be encouraged and provide the
main focus of support. These then are the Soft Companies that have a larger than
realised role in innovation and can provide a more focused and direct route to
technological development, generation of IP and spin-offs than through Universities.
Soft Companies offer great potential for creating and exploiting invention, and for
subsequent promotion of economic growth. Create mechanisms to invest in Soft
Companies, since they are relatively cheap to support, are private, work on a
commercial basis, are close to market, generate IP and technologies – none of which
requires massive infrastructure investment. Target contracts and funds at building
Soft Companies to provide a more focused, direct means of generating new
technologies/products/services of commercial value relevant to local market need
and to provide the base for economic growth.
Public funds could be effectively used to prime/underpin new types of venture funds
that back serial innovators and entrepreneurs If only because administering funds
based on track record of individuals is easier than decision-making based on
technology and market risk. We need to create a culture of serial entrepreneurism.
From these changes will flow new and more relevant indicators of innovation that will
include:
 Number of school leavers setting-up businesses

Number of entrepreneurs who have taken more than one business to
profitability

Number of Soft Companies (including those spun-out from universities) and
established within each industry sector

Value of VC funds directed toward entrepreneurial teams rather than
technology, and their success rate in terms of generating profits rather than
returns to funds.
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