Presentation on Foresight for Science, Technology & Innovation by Dr. Ozcan Saritas IFI Seminar - 30 Aug 2018, Bangkok Thailand

1. Foresight
for Science, Technology & Innovation - ForSTI
Dr. Ozcan Saritas
osaritas@hse.ru
National Research University Higher School of Economics

2. 2
Why are we concerned about Foresight?
Setting priorities
Optimizing resource use
Building visions
Thinking out of the box
Detecting Weak Signals of emerging trends
Giving lead time for innovators
Enabling innovation
Preparing for Wild Cards
Exploring alternative futures
Formulating policies & strategies
Networking stakeholders
Mutual learning
Collecting intelligence
Making evidence-based decisions
Simply because it is too costly not to do so!!!

3. 3
What is Foresight?
“the application of
 ‘systematic’,
 ‘participatory’,
 ‘future-intelligence-gathering
and medium-to-long-term
vision building process’ to
 ‘informing present-day
decisions and mobilising joint
actions’”

4. 4
Forecasting vs. ‘Foresight’
 Futures thinking: Single vs. Multiple
 Nature of situations: Simple, Complicated vs. Complex
 Nature of systems: Technological and Economic only vs. STEEPV
 Nature of problems & approaches: Positivist vs. Constructivist &
Critical
 Level of participation: Expert driven vs. participative & inclusive
 Level of uncertainty & Time horizons: Low uncertainty, short term
vs. High uncertainty, long term
 Taking into account of Wild Cards / Surprises / Shocks: No
contingency vs. High contingency
 Use of techniques: Quantitative vs. Quan. & Qual. and their
combinations

5. 5
Evolution of Foresight practice
Early
Foresight
1950s 1960s 1970s 1980s
1990s 2000s 2010s 2020s Future
Beginning of Civilization Post World War Recurrent oil
shocks
Emergence of
Innovation as an
economic driver
Economic crises &
climate change,
energy, and security
issues
S&T as a strategic
instrument with
economic & social
benefits
Increasing frequency
of disasters, shocks,
surprises
Rapid technological
advancements

6. 6
Foresight from the past
Jean-Marc Côté's Visions of the Year 2000 (1899)
http://www.paleofuture.com/blog/category/1890s
6

7. 7
Trends in the use of ForSTI methods
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1991 1992 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
technology foresight Scenario analysis Delphi method
Perfect foresight Technology forecasting Strategic foresight
Decision making Technology road map Mental time travel
System Dynamics Models hindsight bias game theory
multi-criteria decision analysis policy analysis risk assessment
science and technology policy Simulation bibliometric analysis
Adaptive foresight Emerging technology Expert panel
Weak signal Text mining Case study
cluster analysis Network analysis nonlinear systems
patent analysis Stochastic model trend research
Autobiographical memory Early warning Horizon scanning
Megatrends path dependence priority setting
Survey agent-based modeling Analytic hierarchy process
cross-impact analysis Dynamic programming Future-oriented technology analysis
Metacognition monitoring Neuroimaging
Portfolio management Strategic decision making workshop
Alternative futures Bayesian estimation Benchmarking
benefit-cost analysis content analysis Evidence-based policy
Saritas, O. and Burmaoglu, S. (2015). The evolution of the use of Foresight methods: a scientometric analysis of global FTA research output, Scientometrics, 105, 1, 497-508.

8. 8Saritas, O. and Burmaoglu, S. (2015). The evolution of the use of Foresight methods: a scientometric analysis of global FTA research output, Scientometrics, 105, 1, 497-508.
1991-2000
2001-2010 2010-present
Integration of ForSTI methods

9. MappingofForesightactivities
9

10. Sectors focused
Scope of Foresight activities
10

11. Foresight outputs
11

12. 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014
Pre
Foresight Technology
Foresight –
Foresight First
Cycle Foresight
Second
Cycle
Foresight Third Cycle ????
Office of S&T (1992-2006) of Science & Innovation (2006-7)
Located: till 1995 Cabinet Office
Department of Trade and Industry till 2006
Department of Innovation, Universities and Skills till 2007..
Office of
Chief
Scientist
D.E.S.
Science
Office
Govt. Office for Science.
Located: Department of
Business, Innovation & Skills
Party in Power:
Coalition:
Conservative (Major) Labour (Blair to 2007, then Brown) Con-Dem
Three cycles of Foresight in the UK
12

13. Foresight
Horizon
Scanning
UK Foresight - organizational structure
13

14. © Copyright Higher School of Economics , Moscow 2013
14
UK Foresight - completed projects

15. S&T Foresight
System
•Evidence -based analysis
•Integration of quantitative
and qualitative methods
•Prioritizing
•Communication and
networking
•Stakeholder engagement
•Integration to policy
Global Challenges 
Grand Responses
Demand for new
skills
Policy mix
New economic
paradigm
New
instruments
for STI policy
Changing
society
Multidisciplinary
and multicultural
research
Changing National
Innovation Systems
Enhancing Infrastructure,
networks
Changing global value
chains and traditional
leaders
Globalization vs
localization
Increasing
influence of
technologies
Russian Foresight system
15

16. Evolution of Foresight activities in Russia – with a
boost
2008 2009 2010 2011 2012 2013 20142006 2007
Critical
technologies
(national)
S&T Foresight 2025 S&T Foresight 2030
STI priorities for natural resources
Foresight for nanoindustry markets
Foresight for ICT
and mass-media
2030
STI priorities for
Bashkortostan
STI priorities for
Moscow
STI priorities for
Samara
Tomsk
innovation
infrastructure
STI priorities
for Tula
Regional clusters
Roadmap for power
engineering equipment
Sectoral roadmaps for new materials
(space, aircraft, nuclear energy)
Roadmap for medicine &
pharmaceutical industry
Roadmap for water purification
Roadmap for composite materials
Roadmaps for energy efficiency
Roadmaps for oil & gas sector: upstream & downstream
Roadmaps for technology platforms
Programmes of innovative development of
state-owned companies: priorities,
roadmaps, technology audit, et al.
Foresight for
shipbuilding
Critical technologies (national)
Software – Interaction with expert network
Online database on global technology trends
Software – Interactive
technology roadmaps
Demand for future skills
Foresight for civil society
Federal level
Regional level
Sectoral and
corporate level
Foresight
infrastructure
1996 – 1997: Initiation of
Foresight projects in Russia
(HSE team)
Roadmap
for space
navigation
S&T Foresight for
aircraft sector
Concept of a
roadmap for
automotive
industry: FCVRoadmap for LED manufacturing
Regional
Foresight
(education)
2015-2018
National technology
Foresight system
Critical technologies
(national)
S&T Foresight
2040
Roadmaps for aviation
Sectoral Foresight
systems
Critical technologies
(sectoral)
Network of
sectoral S&T
Foresight centres
Foresight for
National
universities
(5/100)
Evolution of Foresight activities in Russia
16

17. Russian S&T Foresight system
Russian S&T Foresight
Forecast of socioeconomic
development
Budget forecast
Socioeconomic
development strategy
for Russia
Strategic goals and priorities of
socioeconomic and S&T
development (President’s
addresses)
Strategies for macroregions
State S&T development programme
Strategic Foresight
Priority S&T areas and critical technologies for Russia
Spatial development strategies
Programmes for
regional clusters
Regionallevel
Sectoral strategies
Sectoral S&T priorities
and critical technologies
Sectoral S&T Foresight studies
Sectorallevel
State regional programmes
Companies’
programmes
and target
documents
Strategic R&D
programmes for
technology
platforms
Technology
roadmaps Sectoral state
programmes
Nationallevel
Russian S&T Foresight system
17

18. More than 150 global
trends in the
economy, science,
politics and society
Assessments of
effects and
periods of
maximal
manifestation of
challenges and
windows of
opportunities
More than 1000
specific priority
R&D tasks
Characteristi
cs of more
than 80
prospective
markets and
250 product
groups
Priority S&T areas Key sectors of the economy Publications
Russian Foresight outputs
18

19. 19
Global Trends
Growing up: global demand for products and
services
Getting scarce: water, food, energy, natural
resources
Gaining value: scarce resources become more
expensive as they are finite and shared
Giving rise to: sustainability and security
concerns problems with potential social,
economic and political conflicts
Going technological: Advancements in STI
and increasing public and private R&D are
providing opportunities for addressing global
challenges

20. Foresight
Foresight landscape
20

21. Foresight
21

22. 22

23. 23
A set of ambitious goals for 2030

24. 24
ForSTI: a systemic process
Miles, I., Saritas, O. and Sokolov, A. (2016). Foresight for Science, Technology and Innovation, Springer Verlag, Berlin.
Initiation: establishing the purpose of the activity, its scope and
intended uses and users, and the resources that are available
Intelligence: Scanning the focal object and its context,
establishing basic knowledge about trends, about the results of
other studies and the views of major stakeholders, etc.
Imagination: Involving efforts to grasp the underlying dynamics of
the focal object, to map and model it for the future
Integration: Delineating and appraising possible futures that can
arise from the dynamics considered
Interpretation: Examining the implications of the analysis, and
suggesting relevant strategies and priorities for achieving the
major objectives of the sponsor and other stakeholders
Intervention: Communicating these interpretations and steps that
follow to key actors
Impact: Evaluating the extent to which the ForSTI activity has
achieved its objectives and been of use, and examining follow-up
and the scope for embedding such activity in the organisations
concerned
Interaction: an activity that early on particularly involves
recruitment of stakeholders, and later engages them in
participation in successive phases of the process

25. 25
A Systemic Foresight process
Initiation
Intelligence
Imagination
Integration
Intervention
Impact
Interaction
Horizon Scanning
Literature review
Big Data & STI mining
Social Network Analysis
Systems Mapping
Scenario Planning
ModellingGaming
Delphi
Multi-criteria analysis
Success scenarios
SWOT analysis
Visioning
Roadmapping
Backcasting
Strategic planning
Critical/key technologies
Forecasting
Scoping
Priority-setting
Policy assessment
Survey
Interviews
OR methods
Stakeholder mapping
Expert panels
Workshops
Action planning
Environmental Scanning
Voting
Polling
Indicators
Brainstorming
Interpretation
FORSTAR – Foresight process & methods
Miles, I., Saritas, O. and Sokolov, A. (2016). Foresight for Science, Technology and Innovation, Springer Verlag, Berlin.

26. ForSTI
Processes
Qualitative
methods
Quantitative &
SQ methods
26

27. 27
Initiation
Interaction
WAS
IS
SOON
Foresight & Technological Convergence

28. 28
Using Big Data for Foresight
Data is our major asset!!!
Analysis of scientific
literature & media
Patent analysis
Big data intelligent analysis system –
intelligent FOResight Analytics (iFORA)
Scientific
publications
> 2 mln
Scientific articles
> 10,000
Research fronts
Experts
> 10,000
Patents
> 500,000
Analytical
reports &
Forecasts
> 50,000
News feeds
> 1000
International
conferences
> 150
Combination of
quantitative &
qualitative methods
Analysis of networks &
clusters
Focus groups and in-
depth interviews
Biblio-/Sciento-metric
analysis
Semantics &
Text mining
Expert consultations
STEEPV analysis
Funding
NSF, DARPA,
EC, ESRC…
Stock Exchange
DJ, FTSE,
NIKKEI…
Mergers &
Acquisitions
Thomson
Reuters

29. 29
How the Victorians invented the future…
http://aeon.co/magazine/society/how-the-victorians-imagined-and-invented-the-future/

30. 30
Second mission of Foresight:
Analyzing wider impacts of change
Revolutions in machinery,
manufacturing &
transportation  Slum
days, many suffered ill
health due to starvation in
Victorian Britain, such as
these London children in
1860…
Enormous expansion of rail
and telegraph lines,
unprecedented movement of
people and ideas, a new
wave of globalization  and
destruction…
Increased access to goods
and services  stress on
natural resources,
demographic change &
the emergence of
megacities…
1st Industrial revolution 2nd 3rd

31. 31
The 4th Industrial Revolution: Some consequences –
a day in Futurama!

32. 32
Unexpected consequences!
Knightscope claims the security robot
is better than a human guard, because
it never gets bored of its job
but!!

33. 33
Science &
Ecology
Technology
& Economics
Socioeconomics
Politics & Values
What is
possible?
What is
desirable?
What is
feasible?
Systemic
Foresight

34. osaritas@hse.ru
www.systemicforesight.com
www.fb.com/ozcan.saritas.3
@FuturesDesign
https://uk.linkedin.com/in/ozcan-saritas-9852225
Designing
scientifically possible,
economically feasible &
socially desirable
futures
Dr. Ozcan Saritas