R&I foresight policy and practice : futures studies, disruptions and the twin transition : fourth thematic report.
Date: 2023-09-05
Institutions: Directorate-General for Research and Innovation
Subjects: EU policy, EU research policy, Framework Programme for Research and Development, environmental indicator, forward studies, innovation, learning, policymaking, report, risk management

R&I Foresight Policy and Practice:  
Future Studies, Disruptions and 
Twin Transition 

               Fourth thematic report 

 
 
 
 
 
 
 
R&I Foresight Policy and Practice: Futures Studies, Disruptions and the Twin 
Transition 

European Commission 
Directorate-General for Research and Innovation 
Directorate A — ERA & Innovation 
Unit A.1 — Semester & Country Intelligence 
Contact   (Horizon Europe PSF coordination team):  

Magda De CARLI, Head of Unit A.1 
Stéphane VANKALCK, PSF Head of Sector, Unit A.1 
Annamaria ZONNO, PSF Team Leader & Coordinator of the PSF MLE on R&I Foresight, Unit A.1 

Email   Magda.DE-CARLI@ec.europa.eu 

Stephane.VANKALCK@ec.europa.eu 
Annamaria.ZONNO@ec.europa.eu 
RTD-PUBLICATIONS@ec.europa.eu 

European Commission 
B-1049 Brussels 

Manuscript completed in August 2023 
1st edition 

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EUROPEAN COMMISSION 

R&I Foresight Policy and 
Practice: 

Futures Studies, Disruptions 
and the Twin Transition 

Fourth Thematic Report 

Edited by 

Paulo Soeiro de Carvalho 

2023 

Directorate-General for Research and Innovation 
Horizon Europe Policy Support Facility

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table of Contents 

EXECUTIVE SUMMARY .....................................................................    5 

1.  Foresight and Scanning .........................................................................    6 

 Foresight with a strategic focus                                                                           6 

 Horizon and Environmental Scanning                                                                 7 

2.  Driving forces and signals in Foresight ................................................    9 

 Megatrends                                                                                                             9 

2.1.1 Definitions of Megatrends                                                                                      9 

 Trends                                                                                                                   10 

2.2.1.Key differences between megatrends and trends                                               11 

 Weak signals                                                                                                        11 

2.3.1. Defining weak signals                                                                                         11 

2.3.2. Weak signals in science and technologies - An example                                   14 

 Wildcards and black swans                                                                                15 

2.4.1. Wildcards                                                                                                            15 

2.4.2. Black Swans                                                                                                       16 

 Uncertainties                                                                                                        16 

2.5.1. Defining uncertainty                                                                                         16 

2.5.2. Critical uncertainties                                                                                        17 

3.  Disruption and the twin transition                                                           17 

 Defining the concept of disruption                                                                    18 

3.1.1. Disruption as a form of crisis                                                                              18 

3.1.2. Disruptions versus wildcards                                                                              19 

3.1.3. Disruption, risk and uncertainty                                                                          19 

 Disruption in the context of the European policy making                               20 

3.2.1. European institutions exploring the concept of disruptions                       20 

 The twin transition framework                                                                            21 

  Potential disruptions in the twin transition in Europe                                     22 

3.4.1. Member States examples                                                                                   23 

3.4.1.1. Austria 

 23 

2 

 
3.4.1.2. Findland 

3.4.1.3. Portugal 

3.4.1.4. Belgium 

3.4.1.5. Czechia 

3.4.1.6. Estonia 

23 

24 

24 

25 

25 

4.  Concluding remarks ............................................................................... 26 

5.  References .............................................................................................. 28 

3 

 
 
 
 
List of Figures and Tables 

Figure 1: Weak signals in science and technologies ................................................................... 14 

Figure 2: Radar territories (EU, US, UK, China, South Korea, Japan and ROW) for medicine and 
biotechnology weak signals ......................................................................................................... 15 
Figure 3: 12 Potential future disruptions ...................................................................................... 24 

Table 1: Characteristics allowing qualifying a signal as weak ..................................................... 13 

4 

 
 
 
 
 
EXECUTIVE SUMMARY 

This thematic paper was drafted in preparation of the fourth seminar of the  Horizon Europe 
Policy  Support  Facility  (PSF)  Mutual  Learning  Exercise  (MLE)  on  Research  and  Innovation 
(R&I)  foresight,  policy  and  practice,  held  on  26-27  April  2023  in  Bucharest,  Romania.  The 
seminar addressed the topic of futures studies, disruptions and the twin transition.  

The thematic paper explores the relevance and role of the concept of disruptions in foresight 
with a focus on the application of driving forces for the twin transition framework. 

To this end, the paper begins by explaining briefly the foresight concept with a focus on the 
scanning activities that are one of the most important stages in any foresight project.  

The differences between horizon scanning and environmental scanning are highlighted, even 
if for the purpose of this paper, these distinctions are not so relevant given the focus on the 
different types of driving forces and signals that are usually captured and analysed in scanning 
activities. 

In  fact,  to  understand  what  disruptions  are  and  why  they  are  relevant  and  can  be  used  in 
foresight, it is important to distinguish the concept from the most common driving forces and 
signals that are found in most horizon and environmental scanning projects. 

Hence, megatrends are distinguished from more specific trends. The paper also defines weak 
signals  and  wildcards  and  explains  why  uncertainties  are so  important  and  can  be  used  as 
inputs to build scenarios. 

The  next  step  is  to  define  the  concept  of  disruptions  and  make  clear  the  differences  and 
similarities with other types of driving forces and signals of change. 

In  the  final  chapter,  a  number  of  projects  and  reports  are  assessed  that  have  made  use  of 
disruptions in the context of European policy making, with a focus on the application for the 
twin transition.  The paper argues that the twin transition framework can be thought  of  as a 
system and highlights some of the most important trade-offs when exploring the evolution of 
the system. This deeper understanding of the twin transition helps to identify and make sense 
of potential disruptions, notably in the R&I area. 

5 

 
 
 
1.  Foresight and Scanning  

  Foresight with a strategic focus  

Foresight can be understood as a process to anticipate, explore and imagine the future in an 
organised, structured and systematic way that should be useful or have some sort of value. 
According to the OECD, strategic foresight is “a structured and systematic way of using ideas 
about  the  future  to  anticipate  and  better  prepare  for  change.  It  is  about  exploring  different 
plausible futures that could arise and the opportunities and challenges they could present. We 
then use those ideas to make better decisions and act now”.1  

In  a  similar  vein,  the  European  Parliament  defines  strategic  foresight  as  a  “framework  for 
identifying  and  evaluating  future  possibilities  and  determining  the  best  course  of  action.  It 
serves as an input to strategic planning, not an alternative; it helps uncover opportunities and 
threats that traditional processes might miss” (Van Woensel, 2021). 

The  European  Commission  considers  strategic  foresight  as  a  policy  making  approach  that 
“builds  on  collective  intelligence  in  a  structured  and  systematic  way  to  help  better  develop 
possible  transition  pathways,  prepare  the  EU  to  withstand  shocks  and  shape  the  future  we 
want”.2 In this respect, strategic foresight: 

•  Anticipates trends, risks, emerging issues, and their potential implications and opportunities 
in order to draw useful insights for strategic planning, policy making and preparedness; and 

• 

Informs  the  design  of  new  European  Commission  initiatives  and  the  review  of  existing 
policies in line with the revamped Commission Better Regulation toolbox. 

Although there are a number of definitions, there are some basic principles, assumptions and 
concepts about foresight that are fundamental. 

Foresight is an exploration of the future as a space of possibilities and not an attempt to predict 
a specific outcome. Foresight usually focusses on the long term, or the “long view”, and should 
adopt a holistic, contextual and global view. Additionally, it is important to have a multitude of 
perspectives  and  stakeholders,  so  that  individual  and  group  biases  can  be  considered  and 
ensure foresight is a co-creative and participatory process.  

From a conceptual perspective, it is important to keep in mind the critical importance of scoping 
the strategic focus of a foresight exercise and strongly connected with this, the definition of the 
time horizon. These two decisions form the anchor of a foresight project in the sense that they 
allow  for  strategic  conversations  to  happen  and  allow  divergent  and  creative  stages  of  the 
foresight process to be linked with the objectives and purposes of the project. 

Given these principles and basic decisions that help to frame the rationales and objectives, one 
of most important stages or steps in any foresight project is termed scanning. Various terms in 
foresight  literature  and  practice  are  related  with  these  scanning  activities  such  as 
environmental scanning or horizon scanning which help identify specific driving forces, trends 
or signals of change. The differences between foresight and horizon scanning are discussed 
in more detail by, for example, Cuhls (2020). 

1 https://www.oecd.org/strategic-foresight. 
2 https://commission.europa.eu/strategy-and-policy/strategic-planning/strategic-foresight_en 

6 

 
 
 
 
 
 
 
 
Scanning in foresight refers to the capability to capture, identify, categorise and make sense of 
a multitude of drivers of change, insights or signals that can be relevant when exploring the 
future of a specific topic. Some of these elements can include megatrends or more  specific 
trends, weak signals or early warnings, or wildcards and uncertainties, which can be used as 
inputs to build and describe scenarios. These concepts are explained in more detail in the next 
chapter. 

These scanning activities can be organised in many ways, but it is important to be as broad 
and deep as possible concerning the participants involved, the sources used, the amount and 
kind of data analysed. 

  Horizon and Environmental Scanning  

Horizon scanning and environmental scanning are related concepts in the field of foresight and 
organisational planning, sharing similarities and also distinctive features in terms of focus and 
scope. 

Horizon scanning is usually defined as a systematic process of identifying and monitoring early 
signs  of  change  in  the  external  environment  to  anticipate  emerging  trends,  threats  and 
opportunities  that  could  potentially  impact  an  organisation's  future.  It  often  focuses  on  long-
term developments and seeks to recognise weak signals that may indicate significant future 
changes (Coates et al., 2001; Hiltunen, 2008). 

As mentioned above, horizon scanning aims to collect data and make sense of it so that people 
can think about the future in new and diverse ways. That information could come from humans, 
records and artefacts, or a combination of the two. The data could be analysed qualitatively, 
quantitatively, or both. However, data must be analysed, evaluated and used in ways that make 
sense to the organisation int he context of their strategy processes. The information retrieved 
through  this  study  and  its  interpretation  help  to better  understand  the  past  and  present 
developments and to prepare for the application of foresight tools to look into possible futures. 

Horizon scanning frameworks developed by the European Environmental Agency  (EEA) aim 
to  identify  and  analyse  emerging  environmental  issues  that  can  affect  European  policies, 
strategies and decision-making. This process is structured in the following steps: 

•  Define  the  scope:  The  first  step  is  to  establish  the  scope  and  objectives  of  the  horizon 
scanning  process.  This  involves  determining  the  key  topics,  sectors  and  time  horizons 
relevant to the environmental issues under consideration. 

•  Establish a network of experts: Engage a network of experts from various disciplines and 
countries  to  ensure  a  comprehensive  understanding  of  the  environmental  issues  and 
trends. These experts contribute their knowledge and perspectives, helping to identify and 
assess potential threats and opportunities. 

•  Collect and gather information: This step involves gathering data from multiple sources, 
including  research  papers,  reports,  news  articles,  and  other  relevant  documents.  The 
information is collected systematically to cover a wide range of topics and perspectives. 

•  Screening and prioritisation: The collected information is screened and prioritised based 
on relevance, novelty, and potential impact. The experts evaluate the identified issues and 
trends and rate them according to their perceived importance. 

7 

 
 
 
•  Analyse and synthesise: The identified trends and issues are analysed to understand their 
potential implications for European environmental policies and strategies. This may involve 
exploring the drivers and root causes of the issues, as well as potential future developments 
and consequences. 

•  Disseminate findings: The results of the horizon scanning process are communicated to 
relevant stakeholders, such as policymakers, environmental managers, and researchers. 
This may involve producing reports, policy briefs, or other forms of communication to ensure 
that the findings are accessible and actionable. 

•  Monitor and update: The horizon scanning process is continuously updated and refined 
as new information and insights become available. This involves monitoring changes in the 
environmental landscape and updating the analysis to reflect emerging trends and issues. 

Environmental scanning, on the other hand, refers to the continuous collection, analysis, and 
interpretation  of  information  on  an  organisation's  external  environment  (Choo,  2001).  This 
process  helps  organisations  identify  trends,  events,  and  developments  that  may  affect  their 
operations, strategies, and market position.  

In  this  sense,  environmental  scanning  generally  covers a  broader range  of  factors,  such  as 
Political, Economic, Social, Technological, Legal, and Environmental (PESTLE) aspects, and 
typically focuses on the near- to mid-term future (Aguilar, 1967; Choo, 2001), when applied to 
organisations. 

Various  methods  and  projects  have  been  developed  to  conduct  environmental  scanning 
effectively, with some common steps presented below providing a general framework. 

• 

Identify key factors and variables: The first step in environmental scanning is to identify 
the  most  relevant  factors  and  variables  that  may  impact  the  organisation's  operations, 
strategies,  and  market  position.  These  factors  often  include  PESTLE  aspects  (Aguilar, 
1967; Choo, 2001). 

•  Select appropriate information sources: After identifying key factors and variables, it is 
essential  to  choose  appropriate  information  sources  that  provide  reliable  and  up-to-date 
data  on  these  aspects.  Sources  may  include  academic  literature,  news  articles,  industry 
reports,  patents,  government  publications,  and  expert  opinions  (Choo,  2001;  Albright, 
2004). 

•  Collect and organise information: The next step is to systematically collect and organise 
information from the selected sources. This process may involve the use of various data 
collection techniques, such as content analysis, interviews, surveys and online monitoring 
tools (Choo, 2001; Fahey, King, 1977). 

•  Analyse and interpret the information: Once the information is collected and organised, 
it  needs  to  be  analysed  and  interpreted  to  understand  the  potential  implications  for  the 
organisation's strategies, operations and market position. This step may involve techniques 
such as trend analysis, scenario planning, SWOT analysis or cross-impact analysis (Choo, 
2001; Lenz, Engledow, 1986). 

•  Communicate the findings: The final step is to effectively communicate the findings and 
insights derived from the environmental scanning process to decision-makers and relevant 

8 

 
stakeholders within the organisation. This step is essential for facilitating informed decision-
making and strategic planning (Choo, 2001). 

Despite the differences, both horizon scanning and environmental scanning are essential for 
organisations to understand current developments in the context of complexity, anticipate and 
adapt  to  changes,  mitigate  risks  and  seize  opportunities  in  an  increasingly  dynamic  and 
uncertain world. In addition, it is important to underline the focus, which is on the different types 
of driving forces and signals that are usually captured and analysed in scanning activities. 

2.  Driving forces and signals in Foresight  

As mentioned above, in the foresight field, scanning refers to the capability to capture, identify, 
categorise, and make sense of a multitude of drivers of change, insights or signals that can be 
relevant when exploring the future of a specific topic or issue. In this sense, it is critical not only 
to  incorporate  a  diverse  typology  of  drivers  and  signals  but  also  to  clearly  understand  the 
differences between megatrends or more specific trends, weak signals or early warnings, as 
well as wildcards and critical uncertainties that can be used to build and describe scenarios. 

  Megatrends  

Megatrends can be defined as large-scale, long-term shifts that significantly impact societies, 
economies, and cultures. These trends are characterised by their profound and far-reaching 
effects,  and  they  typically  result  from  the  convergence  of  social,  economic,  political, 
technological, and environmental forces. 

The  concept  of  megatrends  first  emerged  in  the  early  1980s,  with  the  publication  of  John 
Naisbitt's  book  "Megatrends:  Ten  New  Directions  Transforming  Our  Lives."  Naisbitt  defined 
Megatrends as “(…) large, transformative global forces that define the future by having a far-
reaching impact on business, economies, industries, societies, and individual lives" (Naisbitt, 
1982). 

Other influential authors and reports that have used the concept of megatrends include Alvin 
Toffler, whose book "The Third Wave" identified a series of megatrends related to the transition 
from an industrial to an information-based economy, or Peter Drucker, who wrote about the 
megatrends of globalisation and the rise of the knowledge worker in his book "Post-Capitalist 
Society". 

2.1.1.  Definitions of Megatrends 

European Commission 

The  European  Commission  has  decided  to  monitor  14  Global  Megatrends  relevant  for  the 
future of the world, with some focus on Europe. These megatrends are regularly updated and 
are not” static” and are accompanied by an engagement tool which supports the use in policy 
making. 

“Megatrends  are  long-term  global  driving  forces  that  are  observable  in  the  present  and  are 
likely to continue to have a significant influence for a few decades. 

9 

 
Megatrends are defined as long-term driving forces that are observable now and will most likely 
have a global impact. They can help you to identify probable and preferable futures. Use them 
to reflect on the future in a systemic way!”3  

SITRA (Finland) 

“A  Megatrend  is  a  general  direction  of  development, consisting  of several  phenomena,  or a 
wide-ranging process of change. They are often considered to occur at the global level and 
development is often believed to continue in the same direction.  

Megatrends are not surprising: they are familiar things, changes that are already happening 
today and highly likely to continue happening tomorrow. They provide a useful view of broad 
future changes that can be narrowed down by focusing on more detailed trends, weak signals 
and the analysis of tensions.”4 

CIFS (Copenhagen Institute For Future Studies) 

“Megatrends  are  the  big  drivers  of  change.  They  have massive  consequences  for  all 
important  megatrends  are 
organisations 
automation, urbanisation,  population  growth,  ageing,  greater 
interconnectedness, 
globalisation, environmental change, and environmentalism. 

term.  Amongst 

the medium 

the  most 

in 

Knowing and understanding the trajectories of  megatrends is crucial for any decision-maker 
seeking to make more futures-informed decisions in an increasingly complex world.”5 

  Trends 

The distinction between megatrends and trends is not always straightforward as both concepts 
refer to significant changes in a specific direction that happen over time. However, megatrends 
and  trends  tend  to  vary  in  terms  of  scale,  duration,  and  impact.    A  number  of  definitions  of 
trends are available from the foresight and policy making literature, including: 

•  A trend is a pattern of gradual change in a condition, output, or process, or an average or 
general  tendency  of  a  series  of  data  points  to  move  in  a  certain  direction  over  time, 
represented by a line or curve on a graph (OECD, 2001). 

•  Trends are large-scale, long-term shifts in social, economic, technological, environmental, 
or political conditions that influence a wide range of activities, processes, and perceptions 
(European Environment Agency, 2009). 

•  Trends are characterised as “(...) ongoing, fundamental societal change over an extended 

period (...) [or] a short-term phenomenon, e.g. in fashion or music” (Schwarz, 2005).  

•  A trend is a direction towards which an industry or market is moving. Hence, a trend can be 
understood as a significant development of one or more variables in the same direction that 
are constant over a certain period of time. Trends are medium to long-term developments 
in the corporate environment. Compared to so-called "fashions" or "hypes", trends last at 

3 https://knowledge4policy.ec.europa.eu/foresight/tool/megatrends-hub_en 
4 https://www.sitra.fi/en/topics/megatrends/ 
5 https://cifs.dk/global-megatrends 

10 

 
 
least five years and have a significant impact on the corporate environment. A trend exists 
outside of the company and independently from it. (Itonics6). 

2.2.1.  Key differences between megatrends and trends 

The following key differences between megatrends and trends can be highlighted: 

Scale  and  scope:  megatrends  are  typically  characterised  by  their  global  scale  and  far-
reaching impact, affecting multiple industries, economies, and societies. Trends, on the other 
hand, may have a more limited scope, often influencing specific sectors, regions, or populations 
(OECD, 2001; EEA, 2009). 

Duration and persistence: megatrends are generally long-term phenomena that can unfold 
over several decades or even centuries (Gupta, Vegelin, 2016).  Trends, in contrast, have a 
shorter time horizon, with their effects being felt over a number of years (Hines, Bishop, 2006). 

Impact and implications: due to their global scale and persistence, megatrends can generate 
profound  and  transformative  changes  in  societies,  economies,  and  individual  lives  (Naisbitt, 
1982).  Trends,  while  still  significant,  may  have  a  more  modest  impact  on  the  areas  they 
influence (EEA, 2009). 

  Weak signals 

Igor Ansoff was one of the first authors to put the concepts of turbulence and uncertainty in the 
firm’s environment in the agenda of strategic management, defending the use of information 
on  the  type  of  weak  signals  as  mechanisms  or instruments  capable  of  helping  to  anticipate 
future events. Ansoff used the term strategic surprises to define these future events, which can 
assume the form of threats or opportunities (Ansoff, 1975, 1984). According to Ansoff, the weak 
signals theory is linked to the time scale of management by flexible/rapid response in the form 
of weak signal issue management.  

In order to improve the traditional strategic planning methods of the 1960s and 1970s, Ansoff 
presented his weak signals theory in business economics in the middle of the 1970s, with the 
aim of addressing the inability of these approaches to deal with turbulent environments marked 
by the acceleration of change and frequent discontinuities in the firm’s environment (Ansoff, 
1975). One of the premises of the theory developed by Ansoff relates to the fact that strategic 
surprises give advanced information of their appearance. The author argues that although this 
information  is  initially  inexact,  i.e.,  signals  are  vague,  fuzzy,  and  difficult  to  interpret,  they 
gradually become more distinct and easier to understand. 

2.3.1.  Defining weak signals 

Although the term weak signal was used for the first time by Igor Ansoff in 1975, it was only 
later that he developed a more rigorous and complete definition of the concept (Lesca, Blanco, 
2002).  In 1982 Ansoff defined weak signals as warnings, which can be found inside or outside 
the company, events or developments that, due to being incomplete, do not allow for any type 
of estimation of their impacts and rigorous answers (Ansoff, 1982). 

6 https://www.itonics-innovation.com/knowledge/innovation-glossary 

11 

 
 
Some years later he presented the following definition of weak signals as “a development about 
which  only  partial  information  is  available  at  the  moment  when  response  must  be  launched 
(…).” (Ansoff et al., 1990, in Lesca, Blanco, 2002) 

In 1997, Bryan Coffman published several non-scientific articles about weak signals, relating 
them  to  information  theory,  cybernetics,  and  complexity.  He  defended  the  possibility  for 
organisations  to  develop  and  implement  models  that  allow  them  to  obtain  competitive 
advantages through the exploration of this type of information. Coffman presented the following 
definition of weak signals in changing environments and organisational dynamics as (Coffman, 
1997): 

•  an  idea  or  trend  that  will  affect  how  we  do  business,  what  business  we  do,  and  the 

environment in which we will work; 

•  new and surprising from the signal receiver's vantage point (although others may already 

perceive it)  

•  sometimes difficult to track down amid other noise and signals  

•  a threat or opportunity to your organisation  

•  often scoffed at by people who "know"  

•  usually has a substantial lag time before it will mature and become mainstream  

• 

therefore, represents an opportunity to learn, grow and evolve.  

Hiltunen (2001: 3), after the identification and analysis of different definitions of weak signals 
presented  by  several  authors,  suggested  the  existence  of  two  distinct  ways  to  define  the 
concept.  On  the  one  hand,  they  can  be  understood  as  anticipative  information  (early 
information) on future trends or changes. Ansoff’s approach fits this perspective, as he argues 
that the existence of turbulence in one specific area does not mean that the phenomenon  is 
identifiable in its final form. For that, it is necessary to detect and explore gradual responses to 
weak signals, building on the understanding of these as anticipative information. On the other 
hand, weak signals can be considered as the first symptoms of change. According to Hiltunen, 
the approach of Aberg fits this perspective, highlighting that: 

“If a company wants to examine its quality level, it should consider what are the first symptoms 
or Weak Signals that are raised if the quality level decreases. Another example is an autumn 
flue. The first symptom could be tiredness. The next thing to come is sore throat and rhinitis 
and there are no more doubts what caused the tiredness. It was the first symptom or Weak 
Signal of the flue.” (Hiltunen, 2001) 

Lesca and Blanco (2002) present the features that weak signals should have, namely that they 
are fragmented; with a weak visibility; with a weak meaning and strong ambiguity (not evident); 
not (or vaguely) familiar; have an apparent weak utility; fleeting; and with an apparent weak 
feasibility. 

Adopting  Ansoff’s  approach  as  the  foundational  support,  Humbert  Lesca  and  Sylvie  Blanco 
(Lesca, Blanco, 2002) identify a set of dimensions that must exist as conditions for us to classify 
a signal as weak (see Table 1).  

12 

 
CHARACTERISTICS 
OF THE WORD 
WEAK 

FRAGMENTED 

COMMENTS 

We are not in a situation of complete information about the event to be 
anticipated. On the contrary, we only have a fragment of information with 
which we can risk making some inductions in a holistic demarche, for 
example. We focus on what weak signals are in a very small number. We 
are not in a case where there is a great volume of information, needing, 
for that matter, processing software of great volumes. 

OF A WEAK VISIBILITY  Mingled among a multitude of useless information, data that “produce 
noise” the weak signal becomes unseen. Most people don’t recognise 
this information. 

OF A WEAK AND 
AMBIGUOUS 
SIGNIFICATION, NON-
EVIDENT 

The weak signal is often poorly audible (or, on the opposite, too 
ambiguous). There isn’t an evident relation of cause and effect. 
Moreover, this information is probably not very clear and not univocal (we 
refer to ambivalence or possibility of equivocation). For a weak signal to 
emit signification, it is essential to make an effort guided by a 
methodology.  

POORLY OR NOT 
FAMILIAR 

The characteristics of non-familiar information make its awareness more 
difficult. We do not focus on this type of information; we don’t find or use 
it in a repetitive way. This line is closer to what we know about cognitive 
biases, either individual or collective. 

OF AN APPARENTLY 
WEAK USEFULNESS  

The same information may be very important for an individual and 
apparently of no interest for his or her professional environment. It is 
apparently devoid of operational signification. Its utility is not evident, the 
consequences of the event it refers to don’t have meaning by 
themselves. 

OF A WEAK 
“PALPABILITY”, 
FLEETING 

Metaphorically, we can say that a weak signal, even when identified, can 
easily slip through our fingers. It’s a sensation, a word listened to, a 
sentence, an image, etc. 

OF A WEAK 
PERTINENCE 

We don’t know what to link the information to, into what frame we should 
classify the information, according to the ongoing concerns.   

OF AN APPARENTLY 
WEAK RELIABILITY  

This is about information concerning eventual future events – so, the 
information is not factual, not countable, but perceived as subjective, 
potentially erroneous. 

Table 1: Characteristics allowing qualifying a signal as weak 
Source: Lesca, Blanco, 2002: 6-7 

13 

 
 
 
 
2.3.2.  Weak signals in science and technologies - An example. 

Figure 1: Weak signals in science and technologies 
Source: Eulaerts et al., Weak signals in Science and Technologies in 2021, Publications Office of the European Union, 
Luxembourg. 

The figure below presents an example of radar territories (EU, US, UK, China, South Korea, 
Japan and the Rest of the World (ROW)) for medicine and biotechnology weak signals. 

14 

 
 
 
 
Figure 2: Radar territories (EU, US, UK, China, South Korea, Japan and ROW) for medicine and biotechnology weak signals 
Source: Eulaerts et al., Weak signals in Science and Technologies in 2021, Publications Office of the European Union, 
Luxembourg. 

  Wildcards and black swans  

2.4.1.  Wildcards 

In the 1960s Herman Kahn emphasised the need to think the unthinkable, which is the question 
to  ask  when  searching  for  wildcards  Although  he  did  not  provide  a  specific  definition  of  a 
wildcard in  his  published  works,  he  often  used  it  in  a  broader  sense  to  refer to  unexpected 
events or developments that could have a significant impact on the future.  

In this sense, wildcards are events or developments that have a very low probability to occur, 
but that could have significant impacts on a particular system, organisation, or society. They 
are often used in the fields of foresight, planning and policy making to help decision-makers 
anticipate and prepare for unexpected events.  

According to John Petersen, wildcards are defined as "low probability, high impact events that, 
were they to occur, would severely impact the human condition." (Petersen, J. L., 1999) 

Mendonça, Kaivo-oja and Ruff (2004) define wildcards as “sudden and unique incidents that 
can constitute turning points in the evolution of a certain trend or system.”  

15 

 
 
 
The authors argue that organisations should put in place a two-component wildcard system. 
The first component being a weak signal methodology to take into account those wildcards that 
can be anticipated by scanning the decision environment. The second component is to nurture 
of improvisation capabilities, which are designed to deal with ongoing crisis.  

In a similar way, Barber presents the concept of wildcard analysis defined as a conceptual tool 
to support the contemplation of  alternatives beyond the present state of the art, the existing 
framework and the contemporary thinking (Barber, 2006). 

2.4.2.  Black Swans  

The term black swans derive from the belief, prevalent before 1697, that all swans were white. 
When black swans were identified in Australia, the concept of “black swans” was considered a 
metaphor for unexpected events that can have a significant impact on a system or organisation. 
According to Taleb (2007), a black swan is an event or occurrence that deviates from what is 
normally  expected  in  a  situation  and  is  at  the  same  time  extremely  difficult  to  predict. 
Furthermore, black swan events are characterised by their extreme rarity, their severe impact, 
and the widespread insistence that they were obvious in hindsight. 

However, there are some differences between the two concepts, which are related to the level 
of predictability, impact, and probability. While both wildcards and black swans describe low-
probability and high-impact events, wildcards are generally considered to be conceivable and 
can be identified through systematic analysis (Petersen,1997; Mendonça et al.,2004). Black 
swans,  however,  are  extremely  difficult  to  predict  and  are  often  characterised  by  their 
unexpectedness (Taleb,2007). 

Black swan events are  typically distinguished through their strong sense of hindsight bias – 
meaning that after these unexpected events occur, people frequently believe that they should 
or could have anticipated them (Taleb,2007). Wildcards, while also classified as low-probability, 
high-impact events, may not necessarily induce this same bias of perceived predictability after 
the fact (Petersen,1997). 

  Uncertainties 

In a Harvard Business Review article from 1985, Pierre Wack sates that:  

“Most managers know from experience how inaccurate forecasts can be. My thesis – on which 
agreement may be less general—is this: the way to solve this problem is not to look for better 
forecasts by perfecting techniques or hiring more or better forecasters. Too many forces work 
against the possibility of getting the right forecast. The future is no longer stable; it has become 
a moving target. No single “right” projection can be deduced from past behaviour. The better 
approach,  I  believe,  is  to  accept  uncertainty,  try  to  understand  it,  and  make  it  part  of  our 
reasoning. Uncertainty today is not just an occasional, temporary deviation from a reasonable 
predictability; it is a basic structural feature of the business environment.” (Wack, 1985)  

This text highlights the importance of the concept of uncertainty in the field of futures studies 
and foresight.  

2.5.1.  Defining uncertainty  

Although we can identify a multitude of definitions of uncertainty in the literature, the following 
definitions allow us to understand the basic features of the concept. 

16 

 
•  According to Kees van der Heijden, uncertainties are aspects of the future that are unknown 
or unknowable, which can result from a lack of information, conflicting information, or the 
inherent unpredictability of complex systems. In this sense, uncertainty refers to the degree 
of doubt about the future and the level of unpredictability that exists in relation to events or 
phenomena  that  may  occur  (van  der  Heijden,  1996).  This  approach  emphasises  the 
concepts of doubt and unpredictability in looking to the future and is widely cited in scenario 
planning literature. 

•  Joseph  Voros  defines  uncertainty  as  the  degree  to  which  the  future  is  unknowable.  He 
distinguishes  between  so-called  'probable',  'possible',  and  'preferable'  futures,  each  with 
different degrees of uncertainty (Voros, J, 2003). 

•  Schoemaker describes uncertainty as a state where the decision-maker does not know all 
possible outcomes or their probabilities. Uncertainty, in Schoemaker's view, is not just about 
risk,  where  probabilities  of  outcomes  are  known,  but  also  about  ambiguity  (where  the 
probabilities are not known). This perspective emphasises that uncertainty can arise from 
a lack of information, complexity, and unpredictability in the environment. 

2.5.2.  Critical uncertainties  

Critical uncertainties are a key concept in foresight, particularly in scenario planning, as they 
help to identify the drivers of the future and develop a range of plausible futures. 

Critical uncertainties are key variables that are highly uncertain and they can have a significant 
impact  on  the  factors  used  to  develop  a  range  of  alternative  futures  by  exploring  different 
combinations of possible outcomes (configurations) for these variables. 

According to Schwartz (1996), "critical uncertainties are factors that have both a high degree 
of  uncertainty  and  a  high  potential  impact  on  the  organisation,  industry,  or  issue  under 
consideration" (Schwartz, 1996). 

Schwartz  and  Bradfield  state  that  "critical  uncertainties are the  most  important  uncertainties 
that drive the differences between alternative future scenarios, shaping the future landscape in 
ways  that  can  significantly  affect  an  organisation's  strategy  and  success"  (Bradfield  et  al., 
2005). 

These uncertainties may arise from technological, economic, social, political, environmental, 
or other factors that have the potential to significantly alter the future landscape, and to identify 
critical uncertainties. A range of methods can be used, such as environmental scanning, expert 
interviews,  trend  analysis,  and  stakeholder  consultations  (Schoemaker,  1991).  Once  these 
uncertainties are identified, they are assessed in terms of their level of uncertainty and their 
potential  impact  on  the  future.  Scenarios  are  developed  through  the  exploration  of  different 
combinations of outcomes for those critical uncertainties, although this can be done differently 
depending  on  the  type  of  scenario  methodology  applied.  By  doing  so,  they  create  a  set  of 
plausible  futures  that  can  help  decision-makers  to  develop  strategies  and  policies  that  are 
robust across a range of possible futures. 

3.  Disruption and the twin transition  

Disruption is a central concept in the fields of foresight and innovation, as it refers to events or 
developments  that  significantly  change  the  status  quo,  often  leading  to  the  creation  of  new 

17 

 
markets or displacing established incumbents. In this chapter, we provide a synthetic analysis 
of the concept of disruption, its historical background, and similarities and differences with other 
relevant concepts in the fields of foresight and innovation. 

  Defining the concept of disruption  

The concept of disruption has its roots in the work of Joseph Schumpeter, an economist who 
introduced the idea of creative destruction to describe the process by which new innovations 
can displace existing economic structures (Schumpeter, 1942).  

This  notion  laid  the  foundation  for  later  work  on  disruption,  including  Christensen's  seminal 
book,  "The  Innovator's  Dilemma,"  which  explored  how  disruptive  innovations  can  challenge 
established businesses. According to Christensen, disruptive innovation refers to innovations 
that  create  new  markets  or  redefine  existing  ones  by  delivering  new  value  propositions  to 
customers (Christensen, 1997).  

Both disruption and disruptive innovation focus on the transformative potential of new ideas 
and technologies to reshape markets and industries. However, the term "disruption" can have 
different definitions and interpretations depending on the context in which they are used.  

Christensen defines disruption as “a process whereby a smaller company with fewer resources 
is  able  to  successfully  challenge  established  incumbent  businesses  by  targeting  overlooked 
segments or employing a different approach that is more suitable to the market" (Christensen, 
1997).  

Similarly, "disruption is a transformation that occurs when new products, services, or business 
models  displace  existing  market  leaders,  often  by  fundamentally  changing  the  way  value  is 
created and delivered to customers" (Bower, Christensen, 1995).  This kind of disruption often 
requires a new way of thinking and can result in significant market share gains. For example, 
Uber disrupted the traditional taxi industry by introducing a new business model that leverages 
mobile technology. 

3.1.1.  Disruption as a form of crisis 

In  a  broader  context,  disruption  refers  to  events  or  developments  that  create  significant 
instability,  uncertainty,  or  a  breakdown  in  the  normal  functioning  of  systems,  industries,  or 
societies.  Disruptive  crises  can  have  substantial  consequences  and  often  require  adaptive 
measures to overcome or mitigate their impact.  It is possible to apply and explore the concept 
of disruption in a multitude of areas or domains, including: 

•  Technological  disruption:  rapid  advancements 

the 
obsolescence of existing systems, products, or services, causing economic instability or job 
loss  for  those  who  depend  on  them.  For  example,  the  rise  of  automation  and  artificial 
intelligence has the potential to displace many workers, leading to unemployment and social 
unrest. 

technology  can 

lead 

to 

in 

•  Economic disruption: sudden economic shocks, such as financial crises or recessions, 
can disrupt the normal functioning of markets and lead to widespread job losses, business 
closures, and negative social consequences. For example, the 2008 global financial crisis 
disrupted economies worldwide, resulting in high unemployment rates and creating lasting 
economic consequences. 

18 

 
•  Political  disruption:  political  instability,  regime  changes,  or  conflicts  can  disrupt  the 
stability of a nation and create uncertainty for citizens and businesses. Examples include 
the Arab Spring, Brexit, or the ongoing crisis in Venezuela, which have all had far-reaching 
social, economic, and geopolitical consequences. 

•  Environmental disruption: natural disasters, climate change, and resource scarcity can 
lead  to  disruption  in  the  form  of  crises  that  require  immediate  response  and  long-term 
adaptation.  For  example,  hurricanes,  floods,  droughts,  or  wildfires  can  displace 
communities, damage infrastructure, and disrupt supply chains. 

•  Social  disruption:  social  movements  or  cultural  shifts  can  challenge  the  status  quo, 
leading  to  conflict  or  upheaval.  Examples  include  the  civil  rights  movement,  the  feminist 
movement,  or  the  Black  Lives  Matter  movement,  which  have  led  to  significant  societal 
changes and, in some cases, political and legal reforms. 

•  Health disruption: disease outbreaks, pandemics, or other public health crises can disrupt 
societies  by  causing  widespread  illness,  death,  and  economic  hardship.  The  COVID-19 
pandemic, for example, led to the significant loss of life, closure of businesses, , and travel 
restrictions , forcing governments and societies to adapt to new ways of living and working. 

In  each  of  these  cases,  the  concept  of  disruption  can  be  applied  as  a  form  of  crisis  that 
challenges existing systems, institutions, or norms. Responding to these crises often requires 
innovative solutions, collaboration, and adaptability to mitigate impacts and build resilience for 
the future. 

3.1.2.  Disruptions versus wildcards 

Disruption is closely related to the concepts of wildcards in the field of foresight, with both being 
related  to  unexpected  or  unforeseen  events  or  developments  that  have  significant 
consequences.  Regarding  similarities,  the  two  concepts  involve  events  that  are  difficult  to 
predict and can catch individuals, organisations, or societies off guard. Additionally, disruptions 
and wildcards can all have substantial consequences, affecting various aspects of life, such as 
the  economy,  technology,  politics,  or  the  environment.  Finally,  these  events  often  require 
individuals, organisations, or societies to adapt and respond to the changes they bring, which 
can involve modifying existing practices, developing new strategies, or embracing innovation. 
However,  disruptions  and  wildcards  differ in  terms  of  their  origins,  predictability,  and scope. 
Disruptions are typically driven by innovations or business models that transform industries or 
markets and can often be anticipated or identified as emerging trends. In contrast, wildcards 
are  low-probability,  high-impact  events  that  are  difficult  to  predict  and  have  the  potential  to 
cause significant changes across various domains of society. 

3.1.3.  Disruption, risk and uncertainty 

Disruption, risk, and uncertainty are all related concepts that deal with change and its potential 
consequences, while representing distinct aspects of decision-making and planning.  

In his influential contribution to the field of economics, "Risk, Uncertainty, and Profit" (1921), 
Frank H. Knight makes a fundamental distinction between risk, as referring to events subject 
to a known or knowable probability distribution, and uncertainty, as referring to events for which 
it was not possible to specify numerical probabilities. 

19 

 
Knight characterises risk as a situation where outcomes are indeterminate, yet they adhere to 
a  known  probability  distribution.  This  essentially  means  that  while  we  do  not  have  absolute 
certainty  about  the  specific  outcome  of  an  event,  we  possess  knowledge  about  the  relative 
frequencies  of  the  possible  outcomes  as  quantified  through  statistical  probabilities.  In  this 
context,  risk  can  be  statistically  quantified  and  managed  through  techniques  such  as 
diversification, insurance, and hedging. 

Uncertainty,  on  the  other  hand,  represents  a  higher  degree  of  indeterminacy,  in  which  the 
underlying  probability  distribution  of  outcomes  itself  is  unknown  or  non-quantifiable.  This 
situation arises when we lack sufficient information to assign reliable probabilities to different 
outcomes or when the event in question is so unique that there are no precedents or parallels 
to inform judgement. This type of uncertainty is inherently immeasurable and thus cannot be 
managed or mitigated through conventional risk management strategies. 

These  concepts  share  a  common  characteristic  in  that  they  all  refer  to  situations  where  an 
unexpected event or outcome may occur, resulting in significant consequences (Schoemaker, 
1995).  Additionally,  managing  and  mitigating  the  effects  of  disruption,  risk,  and  uncertainty 
demands  proactive  measures,  which  frequently  require  creative  thinking,  flexibility,  and 
adaptability. 

  Disruption in the context of the European policy making  

In the context of European policy making, the concept of disruption has gained prominence in 
supporting the understanding of the transformative potential of new ideas, technologies, and 
societal developments that can reshape existing policy frameworks and governance structures.  

In  this  sense,  disruptions  can  challenge  the  assumptions  and  objectives  underlying  current 
policies,  requiring  policymakers  to  reassess  their  goals  and  strategies.  The  concept  of 
disruption is applied in policy making in several ways, including: 

•  Anticipating  disruptions: policy makers can anticipate disruptions by monitoring trends 
and developments in technology, business models, and social movements. This can help 
them  identify  potential  disruptions  and  develop  policies  that  can  address  emerging 
challenges. 

•  Adapting to disruptions: policymakers must adapt to disruptions by revising existing or 
developing new policies that can address emerging challenges. This can involve engaging 
with  stakeholders,  such  as  industry  representatives,  civil  society  groups,  and  citizens  to 
ensure that policies are responsive to their needs. 

•  Embracing  disruptions:  policymakers  can  also  embrace  disruptions  by  leveraging new 
technologies or business models to achieve policy objectives. For example, policymakers 
may  use  data  analytics  to  develop  more  effective  policies  or  promote  innovation  in  the 
development of new products or services. 

3.2.1.  European institutions exploring the concept of disruptions 

There are a number of studies and reports that explore the concept of disruptions and their 
implications  for various  industries  and  sectors.  Focusing  on  EU-level  literature  the  following 
reports can be highlighted: 

20 

 
• 

• 

• 

"Disruption by Technology, Impacts on Politics, economics and society”, 2020, European 
Parliamentary  Research  Service.  This  report  explores  the  potential  of  disruptive 
technologies  to  drive  innovation  and  economic  growth  in  Europe.  It  identifies  the  key 
technologies that are likely to have the greatest impact on economics, politics and society 
and provides insights into the challenges of adoption. 

"Late  Lessons  from  Early  Warnings:  Science,  Precaution,  Innovation"  (EEA,  2013).  This 
report examines the lessons learned from past disruptive events and their implications for 
future policy and decision-making. It provides insights into the importance of early warning 
systems  and  precautionary  measures  to  prevent  or  mitigate  the  negative  effects  of 
disruptive events. 

"Strategic  Agenda  2019-2024",  (European  Council,  2019).  This  document  outlines  the 
priorities and objectives of the European Union for the next five years. It identifies disruptive 
technologies as a key area of focus and highlights the need for policies and investments to 
support innovation, research, and education. 

“Industrial Innovation for Competitive Sustainability” (JRC, 2021). This background note 
published by the Joint Research Centre describes five core global disruptions affecting the 
world economy in the context of industrial innovation for competitive sustainability. 

  The twin transition framework  

The twin transition refers to the simultaneous transformation of the European economy towards 
climate neutrality and digitalisation (the so-called green and digital transitions). It is a strategic 
framework for achieving a sustainable, low-carbon, and digitalised economy in Europe.  

In this sense, the twin transition recognises the interdependence between the two transitions, 
as digital technologies can support the decarbonisation of the economy, and the transition to a 
low-carbon economy can create new opportunities for innovation and growth. 

The European Commission and several European agencies have produced reports on the twin 
transition, including: 

• 

• 

• 

"The European Green Deal" (EC, 2019). The European Commission presented in 2019 The 
European Green Deal – a roadmap for making the EU's economy sustainable by turning 
climate and environmental challenges into opportunities across all policy areas and making 
the transition just and inclusive for all. This report outlines the European Commission's plan 
for  achieving  climate  neutrality  and  the  twin  transition  towards  a  sustainable,  digitalised 
economy.  

"The European Environment - State and Outlook 2020" (EEA, 2020).  Published by the EEA 
every five years as mandated in its regulation, the State of the Environment Report (SOER) 
2020 is its 6th edition. It offers solid, science-based insights on how to respond to the huge 
and complex challenges faced, such as climate change, biodiversity loss and air and water 
pollution.  The  SOER  2020  has  been  prepared  in  close  collaboration  with  the  EEA’s 
European Environment Information and Observation Network (Eionet). 

“2022  Strategic  Foresight  Report,  Twinning  the  green  and  digital  transitions  in  the  new 
geopolitical context” (EC, 2022). A comprehensive, future-oriented and strategic approach 
to the twin transitions, recognising their inherently geopolitical nature, is necessary to further 
reinforce their synergies and address tensions.  

21 

 
• 

“Towards a Green and Digital Future” (JRC, 2022). Analyses how current and future digital 
technologies  could  become  key  enablers  for  the  green  transition  by  2050.  The  report 
examines tension points between the twin transitions, and assesses how economic, social, 
and political factors will impact the twin transitions. 

These studies and reports provide valuable insights into the implications of disruptive events 
for  the  twin  transitions  and  the  need  for  proactive  policies  and  measures  to  support  the 
transformation  of  the  European  economy  towards  climate  neutrality  and  digitalisation.  They 
highlight  the  potential  of  disruptive  technologies  to  support  the  transition  to  a  sustainable, 
digitalised economy and the role of finance, innovation, and education in supporting the twin 
transition. 

  Potential disruptions in the twin transition in Europe  

While  the  twin  transition  concept  designed  by  the  European  Commission  presents  a 
comprehensive and integrated approach to addressing the challenges of climate change and 
resource depletion, there are also potential disruptions that could impact its implementation. 
Some of the most important disruptions include: 

•  Political and regulatory instability: the twin transition will require sustained and stable 
political and regulatory support to be successful. Changes in government or shifts in public 
opinion  could  lead  to  changes  in  policy  and  regulation,  impacting  the  stability  of  the 
transition. 

•  Technological disruptions: the twin transition relies heavily on technological innovation 
to achieve its goals. Disruptions in technology, such as the emergence of new low-carbon 
or  circular  technologies,  could  impact  the  viability  of  existing  technologies  and  require 
significant adjustments to the strategy underlying the transition. 

•  Economic  disruptions:  the  twin  transition  will  require  significant  investments  in  new 
infrastructure,  technologies,  and  skills.  Economic  disruptions,  such  as  recessions  or 
financial crises, could impact the availability of financing and investments for the transition. 

•  Social  disruptions:  the  twin  transition  will  have  significant  impacts  on communities  and 
individuals, particularly those in industries that may be impacted by  the transition. Social 
disruptions, such as protests or strikes, could impact the political and social support for the 
transition. 

•  Climate disruptions: the impacts of climate change, such as extreme weather events and 
natural  disasters,  could  disrupt  the  implementation  of  the  twin  transition  by  damaging 
infrastructure or disrupting supply chains. 

•  Global disruptions: the twin transition is a global challenge that will require coordinated 
action  across  countries  and  regions.  Global  disruptions, such  as  geopolitical  tensions  or 
conflicts, could impact the ability of countries to work together towards the common goal of 
the transition. 

22 

 
 
 
3.4.1. 

Member States examples  

A number of foresight projects developed by Member States (MS) relate to the twin transition 
and  its  role  vis-à-vis  disruptions  relevant  for  the  future  of  R&I  policy.  The  cases  of  Austria, 
Finland, Portugal, Belgium, Czechia and Estonia outlined below are drawn from a survey of the 
MLE participants. 

3.4.1.1.  Austria 

The  Austrian  Federal  Ministry  for  Climate  Action,  Environment,  Energy,  Mobility,  Innovation 
and Technology commissioned a meta-study using around 45 international trend analyses as 
a part of a foresight activity on topics related to applied research topics in 2016. This was an 
internal strategic activity of the Directorate General Innovation and Technology of the ministry. 
It included an analysis on possible future disruptions. Issues addressed included:  

•  Environment and resource use, climate change; 

•  Mobility and infrastructure, smart cites; 

•  Technological change: rapid digitisation, new production technologies such as 3D-printing, 

automation, autonomous systems, nanotechnologies and their application; 

•  Politics: towards a multipolar world order. 

From  several  projects  undertaken  in  the  last  years  in  these  fields  (although  not  foresight 
activities  in  the  narrower  sense)  future  disruptions  identified  include  climate  change,  the 
scarcity of resources, and disruptions in energy supply, as well as issues related to digitisation 
such as the internet of things, new forms of work and the overall impact of digitalisation.  

3.4.1.2.  Findland  

Recent  foresight  projects  developed  by  Business  Finland  have  identified  future  growth 
opportunities within focus areas which are connected to twin transition, including: 

•  Digitalisation to boost productivity; 

•  Digital transition enables a more transparent and equal world; 

•  Merging  the  physical  and  virtual  worlds  will  revolutionise  services  industry  and  everyday 

life; 

•  Carbon neutral and crises-resistant energy solutions ensure a stable society; 

•  Zero waste and a circular economy enable sustainable economic growth. 

Business Finland have made in-depth future-related studies on certain critical topics that have 
potential  future  consequences  for  Finland  and  are  related  to  the  twin  transition,  notably  the 
study of “Overcoming critical material dependences”, and the “Digitalisation and Electrification” 
project.  12  Potential  future  disruptions  were  identified  as  critical  and  relevant  for  the  next 
decades with the potential to create long-term market shifts and with clear implications for R&I 
policy, as outlined in the figure below. 

23 

 
Figure 3: 12 Potential future disruptions 
Source : Business Finland 

3.4.1.3.  Portugal 

Portugal has been implementing several projects7 using horizon scanning techniques funded 
under the EEA Grants schemes. From these we can highlight the following studies: 

•  Growing Circle project, led by Instituto da Construção (IC) partnering with Norway (NTNU) 
and Iceland. Promoting circular approaches, prioritising re-usable products and sustainable 
and non-toxic reusable systems instead of single use products, targeting the reduction of 
generated waste, are at the heart of the Growing Circle pilot project. The expected outcome 
is the promotion of awareness and education of construction industry stakeholders, on the 
relevance  and  role  of  data  templates  for  construction  processes  and  as  tool  to  foster 
efficiency and circularity. 

• 

“The Future of the Open Strategic Autonomy”: Portugal is part of the project, led by Spain, 
which aims to understand the main international vulnerabilities for the EU in the near future, 
and  identify  effective  forms  to  tackle  them,  with  no  prejudice  regarding  the  Union  basic 
values  and  social  and  environmental  aspirations.  In  particular  the  work  focuses  on  the 
identification of the main strategic dependencies in the digital tech area. 

3.4.1.4.  Belgium 

The  Flemish  Government  through  the  Department  Chancellery  and  Foreign  Affairs  have 
recently  started  a  horizon  scanning  project  focused  on  recovery  and  resilience.  The  main 
purpose  of  the  project  is  to  provide  quantitative  insights  for  the  Flemish  resilience  progress 
reporting, for which the Strategic Dossiers and Projects unit within the Flemish Chancellery and 
Foreign Office is responsible. The horizon scan has been launched in 2023 to be implemented 

7 See https://www.eeagrants.gov.pt/pt/programas/ambiente/resultados-dos-projetos/ 

24 

                                                                                                                                                                                                                                                                                                                                                                                                                                                                       
 
 
 
  
until  2024,  including  testing  digital  data  tools  for  horizon  scanning  (e.g.,  through  a  futures 
platform). 

3.4.1.5.  Czechia 

Technology Centre Prague (TC Prague) implemented the national project Horizon Scanning 
for  Responsible  Research  and  Innovation  (HS4RRI)  via  the  agency’s  ETA  Programme  for 
applied social sciences research in 2019-2021. The objective of the project was to create and 
apply a functional horizon scanning system aimed at monitoring and evaluating technological 
and social trends and their potential impacts. The objectives of the project were to:  

•  Create a system for collecting and processing structured and unstructured data and sorting 

and analysing them by using appropriate software tools;  

•  Create an IT platform for methodologically led expert discussion on identified technological 
trends, their potential impacts on society and individual segments of the Czech economy 
(e.g. domains of smart specialisation), as well as on the overall readiness to capture and 
absorb these technological trends; and  

•  Verify the functionality of the system in the Entrepreneurial Discovery Process (EDP) while 
managing  the  National  Smart  Specialisation  Strategy.  A  publication  on  Trends  in  Key 
Enabling Technologies (KETs) was published in Czech in October 2020.  

This report presented the results of an analysis of structured and unstructured data from a large 
number of publicly available information sources carried out to identify technological trends and 
emerging technologies in the areas of the KETs.  

To identify trends and emerging technologies, a newly developed analytical tool was used that 
effectively combines different text mining methods in order to search, structure and filter a large 
number of documents. This tool was applied to a set of information sources covering research 
articles,  news  articles  and  expert  discussions  on  social  media.  The  study  identifies  163 
technologies grouped into 39 technology trends.  

This  was  the  first  comprehensive  identification  of  technology  trends  in  Czechia  based  on  a 
systematic analysis of a large set of global information sources. 

3.4.1.6.  Estonia 

The  main  foresight  activities  related  to  green  and  digital  transition  are  performed  by  the 
Foresight Centre of Estonia which advises the Parliament of Estonia. The Foresight Centre has 
three main areas of research that contribute to policy making in relation to the green and digital 
transitions. These areas are “Green Transition Scenarios in Estonia”, “Active Consumers in the 
Future Energy System”, and “The Future of Data Freedom”.  

The research area “Green Transition Scenarios in Estonia”8 considers the possible economic 
and  social  impacts  of  the  green  transition,  identifying  the  main  vulnerabilities.  What  could 
Estonia expect under different scenarios for the green transition? How might our understanding 
of  a  competitive  business  environment  change  during  the  green  transition?  The  research 
considers the central choices needed to make the green transition happen, and analyses what 

8 See: link: https://arenguseire.ee/en/green-transition-scenarios-in-estonia/  

25 

 
 
alternative scenarios would be created by the different choices and combinations of choices 
for executing the green transition in Estonia.  

The research area “The Future of Data Freedom”9 considers the central development trends 
and choices for the Estonian data economy and for the future progress of data-informed public 
governance,  and  their  economic  and  social  consequences  up  to  2035.  The  future  of  data 
management is considered from the perspectives of the data subject, the data holder, and the 
possible data user. The focus is on the collection, exchange, and use of data both within and 
between the public and private sectors. 

From those projects it was possible to identify potential future disruptions with clear implications 
for R&I policy. 

Report 

Report: The future of the data society. 
Scenarios up to 2035 
Year: 2023 
See: 
https://arenguseire.ee/en/reports/the-
future-of-the-data-society-scenarios-up-
to-2035/ 

Report: Data in Future Society 
Year: 2022 
See: 
https://arenguseire.ee/en/reports/data-
in-the-future-society/ 

Project: ADDVAL-BIOEC “Increasing 
added value and more efficient use of 
raw materials in the Estonian 
bioeconomy”. 
Year: 2021 

Implication of disruptors 
Two key unknowns that will steer the future course 
of the data society are the division of control over 
data, and whether private interests or public 
interests dominate in the future development of the 
data society. It is not directly stipulated which 
implications the unknowns might have for R&I policy, 
however, the above has a direct impact on the 
availability of data for innovation, challenges related to 
Intellectual Property (IP) and streamlining innovative 
solutions to everyday life. 
The creation of a universal quantum computer will 
bring about change to the entire e-cryptography 
system. The metaverse will change how the internet 
is perceived. 
It is not directly stipulated which implications the above 
might have for R&I policy, however, it has a direct 
impact on how to store, collect, and apply data, hence, 
also the creation of innovation and challenges related to 
it. 
We do not fully know how population growth 
combined with technological development, 
changing lifestyles and preferences, for example, 
will affect the demand for different types of food 
(meat vs. plant-based food, soil-based vs. soil-free 
food) and products (from clothes to medicines and 
housing). 
It is not directly stipulated what implications the above 
might have for R&I policy; however, it has a direct 
impact on the direction of innovation requirements. 

Table 2: Overview of reports that identify potential future disruptions 
Source: own compilation 

4.  Concluding remarks  

In the field of foresight, we are engaged in a conscious, organised and systematic exploration 
of possible alternative futures in order to facilitate well-informed decision-making in the present. 

9 See: link: https://arenguseire.ee/en/the-future-of-data-freedom/ 

26 

 
 
 
 
 
 
 
Strategic foresight, which is inherently multidisciplinary, is firmly embedded in the philosophy 
of co-creation, allowing a diverse pool of stakeholders to partake in the discourse. 

Central to the practice of foresight is the concept of scoping, which refers to the demarcation 
of a strategic focus and time horizon. This framework aids in fostering strategic conversations 
while ensuring that the creative and divergent stages align with the objectives and aims of the 
foresight  project.  The  act  of  scanning,  further  captures  and  contextualises  a  multitude  of 
change drivers, thus giving a sense of the potential futures. 

In the exploration of potential futures, it is essential to distinguish between various drivers of 
change. The notions of megatrends, trends, weak signals, wildcards, and uncertainties each 
bring  unique  perspectives  to  the  understanding  of  the  future.  While  megatrends  represent 
large-scale  shifts,  trends  refer  to  significant,  yet  typically  less  overarching  changes.  Weak 
signals, provide early warning signs of potential shifts, and wildcards denote low-probability yet 
high-impact  events.  Uncertainties,  however,  embody  the  inherent  unpredictability  of  future 
developments, emphasising the need to embrace and manage uncertainty rather than aiming 
for perfect predictions. 

Within  the  domain  of  foresight  and  innovation,  disruption  holds  significant  value.  Rooted  in 
Schumpeter's  creative  destruction  and  later  extended  by  Christensen's  work  on  disruptive 
ideas  and 
innovation,  disruption  underscores 
technologies.  The  concept  has  become  integral  to  policy  making,  as  these  high  impact  and 
system-changing driving forces can generate shifts in policy goals and strategies. 

transformative  potential  of  novel 

the 

The focus on the twin transition – a combined shift towards sustainability and digitisation – is 
of particular relevance in the European context, given the transformative potential of disruptions 
in these spheres.  

A multitude of foresight initiatives in various EU Member States have underscored this focus, 
illustrating the implications of such disruptions for policy planning. 

Strategic foresight, thus, has proven to be an invaluable tool in policy making, allowing us to 
prepare  for  a  future  that  remains  largely  uncertain  and  undefined.  By  recognising  and 
evaluating  the  broad  spectrum  of  drivers  and  potential  disruptions,  we  can  create  an 
anticipatory and adaptable decision-making framework that is better prepared to navigate the 
complexities and uncertainties of the future. 

27 

 
 
 
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31 

 
GETTING IN TOUCH WITH THE EU 

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This report has been prepared in the context of the Mutual 
Learning Exercise (MLE) on research and innovation 
foresight (R&I foresight), a process led by the European 
Commission DG RTD. The report aims to identify and 
discuss good practices in the use of Futures Studies, 
Disruptions and the Twin Transition. 

Studies and reports