Manufacturing Statistics Current trends and challenges United Nations Statistics Division.
R&D and Innovation Statistics, challenges of interpretation
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Transcript of R&D and Innovation Statistics, challenges of interpretation
A story about research policy and numbersOn research assessment
Per M. KochDirector for Analysis and Strategic DevelopmentThe Research Council of Norway
6th Elsevier Nordic Librarian Forum, Helsinki, Nov 6th 2008
Research and innovation policy assessment for librarians
Universities, colleges and research institutes are policy organizations in their own right
Politicians, civil servants, industrialists and NGO staff ask for such information
A lesson in how to wake up a policy maker
Lesson 1: Give her a simple story that anybody can understand
The linear model works perfectly in a policy setting Research and
technological development in universities, RTOs and companies gives birth to an idea and relevant new knowledge
Companies make use of these ideas in the development of new products and processes
The company brings the new product to the market
Why?
It is a good story:
The unselfish scientist striving for the common good
It is simple: Give us the money and we will give you the results
By black boxing the whole process it communicates easily.
You don’t need to know how the computer works to make use of it
It works well with many of the traditional macroeconomists
The systemic model of learning and innovation is not easily reduced to a one minute sound bite
Knowledge of customer and market needs
In-house learning
market pull
New or improved products, processes or services
User input
Marked knowledge
Tacit knowledge
Acquired technology
Literature
Conferences and fairs
New employees
Commissioned R&D
In-house R&D
Rogers 1995
Klein
Havelock/Przybylinski
…because social reality is very complex
Lesson number 2: Policy makers are number fetishists
The policy game is based on indicators
1. Numbers make things true
There are limits to how much info policy makers can absorb, and they have to make a leap of faith
Since Newton, mathematics is understood as the best tool for describing the world. Numbers give legitimacy
Economists are powerful in this field, and their science ideal is physics
The number game part 2
2. You can choose the numbers that proves your point
(and disregard the rest)
Compare government budget meeting memos from various ministries
3. You can use the lack of indicators to kill a competitor
“It has not been documented that this policy has an effect…”
The numbers game part 3
Politicians and policy makers know the system. To get something done, you need a concrete commitment, and guess what?
You need a number!
3% objective
Policy makers are not stupid
But they know that they will have to make decisions based on less that perfect information.
They have to persuade!
Numbers make you look good.
There is a whole advisory industry that thrives on numbers.
Experts inside government
Consultants and researchers
Cynical? Not me!
This is the setting in which indicators are used.
There is no point in denying it.
There remains more than enough policy-makers and politicians that are genuinely interested in how the world really works!
How to Thomas Kuhn STI indicators
As long as the indicators do not diverge to much from “the facts on the ground” a “story” might survive.
When the epicycles become too complex the story becomes a political burden instead of a useful tool.
Then there is a need for a new “story” – a new interpretation of the numbers.
The Norwegian puzzle, a case study
The Norwegian Paradox
NO SE DK FI EU25
R&D/GDP
2005
1.5% 3.9% 2.4% 3.5% 1,9%
GDP per capita 2005
172 115 122 110 100
Unem-ployment 2006
3.5% 7,0% 3,9% 7,7% 7,9%
Low R&D InvestementsExtreme wealth creation
The Swedish and Norwegian paradoxes Sweden
Huge investments in R&D and high tech companies do not lead to more innovation, productivity or profit
Norway
Seemingly low R&D investments
Nevertheless the richest and most productive country in Europe
EUs innovasjonsindeks 2004
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
EU Innovation Scoreboard indicates a poor innovation capacity
Kilde: EU Innovation Scoreboard, 2004
Summary Innovation Index, 2004
But Norway has an extremely high productivity
EU 25
FinlandEU 15
USA
Luxem-burg
Norway with oil
Sweden
MainlandNorway
Denmark
There seems, in fact, to be no clear correlation between national R&D investments and economic growth.
So now what do we do? We are convinced
R&D in a narrow sense and learning in a broad sense explains growth.
But where is the convincing story that makes sense to our policy audience?
The Research Council of Norway and Innovation Norway have brainstormed a lot!
We are slowly developing a new story that makes sense to us, working with researchers and ministries
But the new story brings up new questions with no answers
This is not a unique phenomenon. It seems the consequences of a systemic approach to learning and innovation is finally catching up with us.
(Vinnova of Sweden is also taking part)
The main explanation
OECD and EIS indicator sets are misused both by the OECD and the EU and national governments.
The need for benchmarking leads to the idea of “best practice” and model countries (Finland, US, Ireland and Israel)
The heterogeneity of national innovation systems is ignored
Model based on old fashioned health care. One treatment fits all.
Countries may vary a lot as regards industrial structure
Sweden and Finland has some large high tech companies that explain the R&D investment levels
Nokia, Ericsson, Volvo, ABB)
Norway and Iceland are dominated by traditional industries that do not normally invest much in R&D
Fisheries, aquaculture, oil and gas
Denmark is somewhere in between
Note also that the Norwegian GDP is extremely large
A nagging suspicion
Companies may not fully have grasped the Frascati manual.
The understanding of basic concepts like research, (experimental) development and innovation may vary from
Industry to industry (e.g. manufacturing vs. services)
Company to company (different reporting practices)
Country to country (different incentives, e.g. tax)
The main problem: Developmental work“That’s just what we do!”
Norway EU Innovation ScoreboardEIS 2005 Innovation performance (relative to EU average) - NORWAY
76148150
193124
11987
8296
87
111137
65128
9890
12121
3260
69
9877
10827
49
0 20 40 60 80 100 120 140 160 180 200
INNOVATION DRIVERSS&E graduates
Tertiary educationBroadband penetration
Lifelong learningYouth education
KNOWLEDGE CREATIONPublic R&D exp
Business R&D expMed/hi-tech manuf R&D
Public funding innovationUniv R&D financed by bus
ENTREPRENEURSHIPSMEs innovating in-house
% all SMEs collab. on innovationInnovation expenditures
Early stage venture capitalICT expendituresNon-tech change
APPLICATIONEmploym hi-tech services
Hi-tech exportsNew-to-mark product salesNew-to-firm product sales
Employm med/hi-tech manufINTELLECTUAL PROPERTY
EPO patentsUSPTO patents
Triad patentsCommunity Trademarks
Community Designs
Low Medium-low Average Medium-high High
We need to shift from a technology push perspective to a vision of learning
The 3 percent objective is based on a linear model
1. Increase national investments in R&D
2. Produce more knowledge
3. Apply that knowledge to industrial production
4. Result: innovation
5. and wealth creation
There is nothing wrong in having increased investments in R&D as a policy objective, but here it is used as a proxy for innovation
Focus on other aspects of learning
R&D embedded in technology and human capital
Design
Branding
Organisational change
Management practices and types of ownership
A new focus on research as a learning tool
The effects of R&D products on the innovation system
Company profits as result of sales of new or improved products, processes or services
Spillover effect 1: the new products leads to increasing productivity among customers
Spillover effect 2: the new products leads to innovation among customers and suppliers
The effects of R&D on learning in the innovation system
Research builds competences that can be used to absorb knowledge and technologies developed elsewhere
Research may lead to network building
University research teaches students how to use the tools of science
Do we have indicators for learning?
The numbers of students
The size of faculty
The number of Ph.D’s
The size of R&D budgets
These are all input-indicators that say nothing about outcome.
What about research output indicators?
Publications
Citations
• These are important as they are measures of research productivity and quality, • But they are not measuring the effects this research has on society
• Different publication practices in different disciplines• Publish or perish hysteria•Bottom-up perspective on research
Indicators for the interaction with society
Patents
Licenses
Co-publication
Popularization and communication
Income from commissioned research
Collaboration agreements
Participation in the EU Framework Programme
These are measures of interaction, but not of the effect on society.
We have to connect research input to social, economical and environmental output Now research is seen as one
of many “deserving causes”, and it lose out if set up against health, poverty or the environment.
Have to communicate that research is part of the solution of major social challenges.
One example: Connect company R&D investments with accounting data
The Nordic advantage: The autonomous workers make the bumblebees fly
The Nordic advantage: staff that solves problems independently and finds competences outside the organization.
Connected to educational level and research as a learning tool.
(Source: Åge Mariussen, NIFU STEP)
-1,00000 0,00000 1,00000
Market learning
10,00
20,00
30,00
40,00
Denmark
Germany Finland
Sw edenUK
Norw ay
Slovenia
Spain
Hungary
France
Austria
Be lgium
Czech R
Sw itzerlan
Turkey
GreeceIta ly
Netherland
Poland
Portugal
Slovak R
Ire land
Europe: market learningGDP/ capita
Source:Fourth European Working Conditions SurveyOECD
Concepts like “high tech” and “low tech” makes little sense
Understanding innovation in resource based industries Resource-based industries
may be knowledge-intensive and profitable, but not R&D intensive
Farming, aquaculture fisheries, petroleum and mining
The word “high tech” is misleading, as it refers to R&D as a percentage of company turn-over, and not to the company’s use of advanced technology and knowledge
Low tech, but knowledge intensive
A high tech company is per definition a company that invests much in R&D.
Norwegian petroleum companies and Swedish and Finish mining companies do not invest much in R&D, but they do make use of advanced technologies) and they do employ highly competent engineers
A lot of process innovation
Companies make use of other forms of innovation: branding, marketing
Little R&D per company, but branches of industry as a whole may invest much (food)
Oil- and gas is defined as high tech, but is in fact veeeery advanced
Indirect use of research
MS Kristian With Refrigeration/containership built by Vaagland Båtbyggeri AS on the North-West Coast of Norway
Argon AS has installed the electronics
Radar, satellite phone and TV-antenna delivered by ProNav
Sonar, logg, radio and electronic map systems delivered by Furuno
Gyro compass and autopilot delivered by Simrad
The advanced technology has been “black-boxed”. You do not need to know how to build a TV to watch the Simpsons.
We need to get a better understanding of the role of services
The largest part of the economy
A very heterogeneous sector
A residual factor (what’s left when we leave out manufacturing and food)
We need a new categorization
Until now: Industrial policies have been focused on manufacturing, even if 70 percent are employed in services
Important service sectors
B2C services: non-R&D companies, including retail, people care and tourism
Retail: Innovation in transport, storage, delivery and customer care
Tourism: Innovation in product range, presentation, transportation and marketing
Services as partners and knowledge providers for industry
Advanced knowledge providers, e.g. R&D intensive B2B ICT companies (Knowledge intensive business services)
These companies may compensate for the lack of R&D in others.
Low R&D measurements in some industries may be an effect of outsourcing
Understanding the effects of public sector innovation
Innovation in the private sector is understood as an investment, in the public sector as an expense
Innovation in the public sector and the effect on industry
Public/private learning arenas
Public procurement
The effect of social welfare on risk taking and company behavior
We have no output indicators!
The Copenhagen Manual
New Nordic project aimed at developing a statistics manual for public sector innovation
Danish Agency for Science, Technology and Innovation, Denmark
Danish Centre for Studies in Research and Research Policy, CFA,
NIFU STEP, Norway
RANNIS, Iceland
Innovation Norway, Norway
The Research Council of Norway
DAMVAD, Denmark
Statistics Finland
Statistics Norway
Statistics Denmark
Statistics Sweden
In cooperation with: OECD NESTI NESTA UK
Company
LearningNetworksinnovation
Customers and users
Suppliers
Policy-institutions
FinancialInstitutions
R&DInstitutions
Consultants
Public policy Cultural framework
International framework Industrial structure
Understanding competence flows in the innovation system
The role of competence flows
The role of education
User-driven innovation
Customer/supplier relationships
“Open innovation” and industry collaboration
The role of KIBS
The role of public sector institutions
National innovation systems must have porous boundaries.The EU is not competing with the US or Japan. This is not a zero-sum game!
Understanding the heterogeneity of innovation systems
Norway, Sweden, Iceland, Finland, the Netherlands, Bravaria, Catalonia, Northern Italy and the UK have all successful innovation systems that produces wealth.
But they are all totally different from each other.
Unique historical trajectories.
Unique socio-cultural framework conditions
There is no best practice.
Finland and Ireland cannot be used as models for other countries!
Understanding socio-cultural framework conditions Stable macro-economic framework conditions
Disciplined fiscal policy
Competition policy encouraging innovation
Low taxes
An open economy
Socio-cultural framework conditions
Egalitarian culture with high social mobility
High wages for blue collar work gives impetus towards innovation (robots, internet banking)
High educational levels brings flexibility and labour mobility
An efficient public sector helps industry
A trustworthy welfare system reduces risk
Political and social stability engender trust
Where are we now?
The 2008 report on Norwegian innovation tells the new story in full: There is no paradox!
Increasing consensus: The Nordic success is competence based.
DG Enterprise and DG Research are working on more new nuanced interpretations of indicators
White papers in all the Nordic countries try to take the heterogeneity and complexity of innovation into consideration
Online R&D statistics and research and innovation policy information
Cordis http://cordis.europa.eu/indicators/
Pro Inno Europe http://www.proinno-europe.eu
Eurostat http://epp.eurostat.ec.europa.eu
OECD http://tinyurl.com/6dt2qn
Erawatch http://cordis.europa.eu/erawatch/
Worldbank: http://www.worldbank.org/kam
A Norwegian portal for R&D policy info: www.forinn.no