PLAUSIBLE
FUTURES
SCENARIOS
Morphological Analysis Methodology
Centre for Environmental Risks and Futures
Department of Environmental Science and Technology
School of Applied Sciences
March 2012
1
Can we predict the future?
“No”, says the chaos theorist.
“Yes”, responds the astrophysicist.
“To an extent”, says the economist.
“Usually”, says the meteorologist.
(Pillkahn 2008, p. 29)
2
1.
Introduction
Project Background
Plausible futures scenarios aim to develop a set of plausible, internally
consistent ‘pictures of the future’ to be used to aid long-term planning and
strategic decision making.
The process is based on a strong evidence base, utilising existing evidence
and scenarios and futures studies, as well as internal and external expertise.
The aim is to realise a highly collaborative, systematic and transparent project
that will bring together participants from all areas of required expertise. Expert
input will primarily be gathered through workshops, interviews and online
surveys. In some cases scientific reviews may be conducted.
Timescale and Scope
A project of this type will require c. 12 months to complete. Prior to this there
will be a number of intermediate deliverables, including a report that will
summarize the main scenario drivers (i.e. key factors shaping the system that
is being analysed). The Centre will provide and support evidence analysis,
key factor descriptions, software based scenario construction, workshop
facilitation and reporting.
3
2.
Scenario Method – The Basics
“The purpose of scenarios is to inspire change. They encourage one to
intentionally depart from the comfort zone. They are provocative and they
serve as a basis for discussion.” (Pillkahn 2008, p. 287)
What are scenarios?
In what follows, the term ‘scenario’ will be used in accordance with the
following partial definitions:
 Scenarios are hypothetical illustrations of the future that describe a
cross-section in an established context. They include qualitative and
quantitative elements and are intentionally applied in multiples to show
indeterminacy and possible alternatives.
 Scenarios are plausible descriptions of how the future may develop,
based on a coherent set of assumptions about key relationships and
driving forces. They are neither predictions nor forecasts, but plausible
chains of cause and effect; clusters of plausible assumptions and
environmental changes and trends, combined to develop a set of
alternative, internally consistent future worlds. Scenarios can be based
on quantitative, scientific evidence as well as qualitative information
and opinions.
Why are scenarios useful?
“The dilemma of complexity consists in our tendency to demand and strive for
simple solutions at the same moment that we perceive the nature of our
environment becoming more complex”. (Pillkahn 2008, p. 59)
Scenarios are all about understanding complex systems and exploring the
way these systems may change and evolve over time, in particularly
challenging our tendency towards favouring the ‘business as usual’ future and
not adequately exploring viable alternatives.
Most issues or areas of investigation are shaped by a wide range of social-,
technological-, economic-, environmental-, political-, legislative- and valuerelated factors. Scenarios help us to: recognise the multitude of these factors,
4
identify the most important ones, explore the interactions between, identify the
key drivers, review what we know about them, project probable and disruptive
development paths into the future, paint consistent pictures of the future and
thereby develop a better understanding of what we should do today and in the
coming years.
If we want to ensure that our strategies, policies and resources are channelled
into the right direction, we need to have a tangible understanding of where we
can and want to be in the decades ahead. We need to a have a common
vision, an understanding of key uncertainties and a guide to what we need to
do, and who we need to interact with, in order to shape the future of our
customers.
In summary, scenarios are useful for…
 The exploration of alternative development paths towards the future
 Conditioning people for possible future changes to an organisation’s
environment
 Understanding complex systems and the interactions between
underlying entities
 The identification of critical decision points and strategic options
 Development of a clear context for future strategies and planning
 Exploring the strengths and weaknesses of current strategy and
planning approaches, e.g. testing the robustness of strategies and
planning against the key long-term changes and uncertainties
 Engaging internal and external customers in a dialogue about change
 Create a clear vision of where the an organisation wants to be
 Provide a long-term vision independent of any political timetable
For strategy making and planning, specific outputs include:
 A comprehensive list of the key studies, research and evidence on
relevant futures information customers can draw from.
5
 An analysis of what impacts different scenarios have on the realisation
of: strategic objectives, future investment strategy, human resources
requirements, evidence demands (i.e. type and focus of evidence
gathered), planning development and capability requirements of key
customers
 A framework for analysing the resilience of objectives towards longterm change
Five rules for scenario development
- Customised Design
Close and direct relation to guiding question/research topic at any given
time of the scenario process
- Participation and Communication
Focussing on the “strategic conversation”, not the tool
- Transparency and Documentation
Producing usable results, not secret knowledge; thorough documentation of
process for reconstruction
- Keep it Simple (but not stupid)
Using robust methodology, designed for practical usage, no overengineering of the process
- Feasibility of Results
Graspable presentation of results is key for diffusion of results and further
strategic planning
Setting up the process
“The countless and disparate techniques and methods of examining the future
that have been proposed by various scholars and enterprises has regrettably
led to considerable chaos.” (Pillkahn 2008, p. 162)
The methodology behind the construction of scenarios has been around for a
long time. However, it is still evolving and varies significantly between
organisations and fields of application. The methods individual organisations
6
chose are influenced by a wide range of factors such as habit, previous
experiences and budget.
Some scenarios are developed in a single workshop and are only based on
the ideas and knowledge of the people present, while other scenarios take
months or years to construct, using dedicated software tools. Due to the
breath of approaches used, the quality of existing scenarios and the
understanding of what scenarios can and should be, also varies significantly.
We aim to create evidence-based, high quality scenarios that are internally
consistent and have been developed by a careful analysis of existing
evidence as well as the integration of qualitative evidence from key customers
and stakeholders. We are committed to using the methodology most suitable
to achieving our goal, while at the same time considering such factors as
budget and timescale.
Table 1 – The development of scenarios can be sub-divided into five key steps:
Step
1
Question
What is the purpose of the endeavour?
What are we attempting to explain?
Focus
Orientation: From the real world to
the object of investigation
2
How are we to represent the object of
investigation?
Gathering of future elements
3
What do we know as a matter of fact about
the future?
Information about the future
4
What might the framework of the picture of
the future look like?
System architecture, construction of
future pictures
5
How can we represent pictures of the future
so as to make them broadly accessible?
Illustration and visualization
We are using UK food security as the focus for investigation. Clarity must be
established from the very outset among all participants about three factors
beyond the goal and expectations. In this example these include:
A. Focus
Scenarios will focus on the relationship between UK agriculture, UK
food consumption and the state of the UK environment
7
B. Timeframe
Scenarios will focus on the year 2030
C. Geographical scope
Scenarios will focus on the UK, but will not ignore how the UK is
affected by global changes.
Table 2 – Three approaches to drafting the scenario framework
Minimal
Approach
Standard
Approach
Maximum
Approach
Number of
Uncertainties
2
Around 3 to 8
>8
Deployed
Tools and
Methods
Four-quadrants
(Axis of
Uncertainty) matrix
Wilson matrix,
morphological analysis
Wilson matrix
morphological analysis,
cross-impact analysis,
consistency analysis
Simple description
of the enquiry
Description of the
inquiry with a
manageable number of
uncertainties and
elements
Complex subjects with
many degrees of freedom
and unknown variables
Application
8
3.
Methodology – Morphological Analysis
Like other scientific and non-scientific disciplines, futures research (such as
scenarios planning) is subject to constant technological change. With the
availability of new, innovative software tools, the morphological approach is
fast gaining popularity across private and public sector organisations in
Europe, North America and Asia.
The morphological approach is generally favoured in situations and inquiries
that are characterised by a large number of elements and uncertainties. The
method is more laborious, time consuming and expensive than using a 2x2
Axis of Uncertainty matrix often used in the UK, but ultimately also more
advanced, structured and transparent, with additional levels of analysis, such
as e.g. the cross-impact analysis, active-passive map, and consistency
analysis (all described below).
The morphological approach and use of software tools does not in itself
guarantee the development of good scenarios. This method, like any other,
depends on the quality of the input and attention to detail. However, the
method does allow for a more structured and formalised analysis and should
thereby counteract a lack of transparency or internal inconsistencies
(contradictions within individual scenarios) that other methods can fail to
address.
Below is a step by step guide on how the method would be used, using the
example of scenarios for UK food security in the year 2030. This subject has
been picked to display the utility of the morphological approach when
investigating an issue with a high number of interrelated variables, coupled
with complex global supply chains.
9
Table 3 – Overview of key advantages and disadvantages of morphological
analysis compared to the four quadrants matrix
Advantages
Disadvantages
 Highly structured, multi-step process
 More laborious
 Transparent process
 Less simple
 Additional levels of analysis
(cross-impact analysis and consistency
analysis)
 Not so well known in the UK (where the
Axis of Uncertainty approach is more
often used)
 Structured integration and evaluation of
expertise
Step 1: System analysis and identification of key factors
“Once we determine the structure of an enterprise’s environment, we can
move forward and conduct an efficient search for information about various
segments.” (Pillkahn 2008, p. 84)
1.1 Analysing and Mapping the System
Question: What are the important trends/driving forces for future
development?
The first step focuses on analysing and mapping the system under
investigation, in this example UK food security. For the purpose of this paper,
UK food security will be defined as factors affecting the availability,
accessibility, affordability and quality of food in the UK.
The process starts with a period of desk research and environmental
scanning to identify factors (trends, drivers, developments) that are likely to
shape or influence the future of UK food security (e.g. food security is shaped
by climate change, demographics, consumption behaviours, etc.). There are a
variety of methods that may be used for this step. They include: collaborative
brainstorming sessions, surveys, expert interviews and analysing existing
research papers.
The result of this step is a broad overview of trends and topic areas, research
papers and expert knowledge to consider when building our scenarios.
10
1.2 Identification of Key Factors
The initial environmental scanning provides the basis for the selection of key
factors; essentially those factors considered to be most influential in shaping
the future of UK food security. The preliminary selection of factors is designed
to paint ‘the big picture’; all the things we could potentially consider when
constructing our scenarios. This step is usually performed in a participatory
workshop or via an online survey.
The preliminary list of key factors for UK food security towards 2030 is set out
in Diagram 2 below.
Diagram 1 – Key Factors for UK Food Security
“While total representation is never possible, the inclusion of more elements
in case of doubt will usually lead to a better picture.” (Pillkahn 2008, p. 179)
Step 2: Cross-impact analysis and selection of key factors
Question: What are the key driving forces for future development and
how are they linked?
In a cross-impact analysis we map the interactions between individual factors.
In a participatory workshop, connections are made to establish if, and to what
degree, one factor is driven by, or drives, another factor. This involves an
analysis of the relationships and the impact each factor has on one another.
A key benefit of this exercise is that it forced participants to consider
relationships that may have previously not been considered as relevant. It
11
also highlights those factors that are driving the system, the active factors,
and those that are influenced by developments in other factors, i.e. the
passive factors.
In the exercise, each combination is investigated separately and assigned a
score based on a scale of 0 (independent) to 3 (powerful driver). The active
sum allows the determination of the factors that have an especially strong
impact on (and essentially drive) the other factors.
Diagram 2 – Cross-Impact Analysis UK Food Security
The analysis creates an active-passive map, which highlights the driving
forces as well as those factors that are primarily driven by others. It allows us
to identify those factors that are most influential (active) in shaping the future
and therefore most relevant to the construction of scenarios.
12
Diagram 3 – Active - Passive Map UK Food Security
Factors which have a high number of links can be found in the red area.
Step 3: Description of key factors and development of evidence
base
Step two resulted in a selection of the most important factors. These ‘key
factors’ are now described in more detail to establish their most important
aspects and build an evidence base around them.
Picture 1 – Example of a key factor descriptor
The evidence presented for each key factor should be based on a broad
range of scientific and non-scientific sources as well as expert opinions,
workshops and surveys. For factors where insufficient internal or external
13
evidence is available, expert interviews, surveys and/or science reviews
should be conducted.
The quality of the input information (rich, diverse, and neutral) plays a crucial
role in the quality of the scenarios.
Step 4: Development of projections
Question: What alternative projections are possible?
The evidence base around the key factors will provide the basis for the
development of projections. Where possible, projections will be based on or
supported by evidence and expectations established in existing futures
studies. For this example, for climate change we are using existing projections
from UKCP09, IPCC and the Stern Review. The projections for climate
change could thus be based on different degrees of warming and the effects
currently anticipated with this. The same can be done for expectations on, e.g.
the global economy, availability of energy resources. Using existing evidence
to formalise individual projections, will ensure that we make maximum use of
existing research and assumptions, to develop scenarios that are based on
the expectations of key organisations, researchers and thinkers from both
within and beyond our own research. Crucially, using the morphological
approach to scenario making enables us to perform a structured analysis of
existing information, with a high level of transparency in terms of where
information was used to support a given assumption (projection).
For each key factor the set of projections should all depict a distinctly different
state of the future and cover the breath of probable possibilities. The key
factors and projections collectively make up the morphological box.
14
Diagram 4 – Morphological Box: Key Factors and Projections for UK Food
Security
Key factors are blue boxes with the individual projections below each key factor represented
as the grey boxes.
For each factor a set of three to five projections is developed ensuring that the
chosen projections are distinct enough and do not overlap.
Another possible input is to conduct an expert survey asking participants to
rate the probability of each projections, allowing a subsequent analysis of the
most probable scenario (in the eyes of the experts) as well as an analysis of
key expectations about the future that are incompatible (identification of
inconsistencies in business as usual expected by experts).
Step 5: Consistency analysis
Question: Can the projections occur together? Can they coexist
and, if so, how well?
The morphological box is the basis for a consistency analysis. Using another
matrix, the compatibility of projections is checked step by step. As part of the
analysis, each combination of projections is evaluated according to the
following scheme:

Total inconsistency (impossible combination)

Partial inconsistency (includes contradictions)

Low inconsistency (includes few contradictions)

Neutral (no cross impact)

Low promotion (limited impact)
15

Mutual promotion (positive impact)

Mutual dependency (both projections are linked)
The procedure is highly laborious and repetitive and therefore, is not always
suitable for a workshop situation. However, it is sufficient to have a small team
of project members to collaboratively perform the analysis in a smaller circle
and then present the results to a wider steering group.
Diagram 5 – Consistency Analysis
16
Diagram 6 – Cluster Analysis of Consistent Scenario Combinations
The consistency analysis calculates the most consistent scenario
combinations, i.e. combination of projections. A cluster analysis can help to
identify groups of projections that are distinctly different from each other. This
information allows us to indentify the most suitable combination of projections
to make up a set of distinctly different but internally consistent raw scenarios.
Crucially the analysis allows the “locking” (making sure that the projection is
included as part of the scenario calculation) of individual projections (or
groups or projections). For example, the projection for climate change “climate
change above 4°C with high impact on agricultural productivity” can be locked
to allow an analysis of the most consistent combination of projections around
the chosen selection. The system can thus provide a system analysis to
assess what impact individual assumptions have on the system. This is
particularly useful for analysing the most important drivers of a system.
Diagram 7 – Logging and System Analysis via Individual Factors
17
Step 6: Selection of raw scenarios
Questions:
Which combination of projections will result in consistent scenarios
(and differ distinctly from one another)?
Which combination of projections is consistent and highly probable?
(Robust scenario)
The consistency analysis lists the most consistent scenario combinations. The
software does not provide finished scenarios, but gives an indication on which
parts of the story best fit together.
Identification of Raw Scenarios
The consistency and cluster analysis resulted in six potential scenarios for the
future of UK food security. They are:
Climate change significantly impacts global food and energy supplies. The
production and distribution of staple crops is severely disruptive. With
increasing demand for meat and agricultural products, prices are high and
extremely volatile. Key economies and growing regions stop their exports as
the global food market shifts towards protectionism and self-sufficiency.
Worldwide, governments take control of their agricultural sectors. Food and
agriculture policies are highly fragmented. The triad nations benefit from
technological capabilities and social change. European citizens are forced to
embrace GM in order to continue their lavish hedonistic lifestyles. By 2030,
the UK has turned into a country dominated by GM and new technological
solutions, such as advanced hydroponics and urban agriculture.
18
Climate change gives agriculture a rough ride. Extreme weather, droughts
and heavy rains severely disrupt the production and distribution of staple
crops. Prices are high and extremely volatile. Globally, protectionist measures
increase. As markets collapse, governments argue about sharing
responsibilities. In response, key economies forge strategic alliances to
collectively ensure food security. A south-north divide emerges with China
forging strategic alliances with Africa and South America. The UK engages in
a partnership with the US, Europe and Russia. A lack of reliable import
sources forces an EU policy shift towards embracing GM. Food consumption
becomes turns into a highly strategic activity with governments and retailers
working together to supply consumers with available produce, while
minimizing waste and excess consumption. By 2030 50% of crops grown in
the EU are GM. Large-scale, high productivity agriculture dominates, while
environmental concerns are often overlooked.
The overall impacts of climate change are positive, as the world agricultural
system learns to adapt to the challenges climate change poses. Water
scarcity is overcome with the invention of cheap and easy to use
nanotechnology based desalination technologies. The global food system
19
turns into a highly flexible, adaptive system where certain types of food are
grown only in the most suitable areas, while overall global trade and supply
benefits from the greater integration of small farmers and developing
countries. With greater productivity, global supply of food is stable and can
keep up with growing demand from emerging economies. Overall, GM
continues to be restricted to certain regions. The UK turns into a region
focussed on the production of value-added, GM-free, specialist produce,
which is exported throughout the world. Examples are high-tech organic
produce grown in specialised hydroponics and rare breads of meat.
Climate change severely disrupts global agriculture. The production and
distribution of staple crops is severely affected. The situation is worsened by
tightening supplies of oil. With growing global demand, prices for oil and food
are high and extremely volatile. Globally, protectionist measures increase, as
governments’ fights over the resources needed to feed their own people.
Global food and energy markets collapse and regional conflicts break out. The
world enters another economic crisis, where only the rich can buy the food
they want, while most of the population are forced to eat what they can get.
Unfortunately, GM technology fails to provide a solution to overcome the
crisis. The world enters a long period of stagflation, where food is the key
currency. Where possible, people apply new technological solutions to feed
themselves and their neighbours. In the UK, local food networks emerge,
where people grow their own food in villages and cities, trading it on the black
market.
20
Over the next decade advances in GM technology manage to convince even
the strongest opponents of its benefits. By 2020, GM foods dominate the
shelves. Most types of bread now come with omega3. A range of other GM
enabled functional food products greatly enhance the health of citizens in both
the developed and developing world, while ate the same time allowing major
growing regions to overcoming some of the key challenges of climate change
such as water scarcity and droughts. The UK agricultural system too switches
to large-scale high tech GM foods. The UK is part of a concerted global policy
effort that allows us to overcome the challenges of a growing world population
and increased consumption of meat and diary, by providing affordable GM
food and open markets for all.
The emerging economies fail to sustain their rapid economic growth. As a
result, the global middle class does not expand as rapidly as previously
anticipated, reducing demand growth for agricultural products, in particular
meat and dairy. At the same time consumption in developed regions is
significantly optimised. The UK and EU are boosted by pay offs from vast
investments in clean tech and renewable energy. Europe now focuses all its
attention towards creating a sustainable food system, with GM-free high tech
21
agriculture that can feed the region without compromising on the health of the
environment. As consumers learn how to use food more effectively, food
waste is reduced and vegetarian consumption increases. By 2030, European
society has fully embraced sustainability for both its economy and its
agricultural system.
The above represents a draft of raw scenarios and not the final
scenarios. The illustrations are merely designed to show possible
results that can be generated from the method described.
Step 7: Final scenarios and communication
The scenarios strands act as the guide to the ‘story telling’, the narrative
elements and a ’road-maps of change’ that will make up the final scenarios.
As such, the final scenarios contain both narrative and evidence based
components (such as indicators etc.), combining all the information collected
and created in the previous steps.
Scenarios need to be presented in an attractive and informative format to
engage with the reader. A report should include an overview of the key
factors, a description of the projections and the set of final scenarios.
For effective communication, the value of good design should not be
underestimated. At the outset of the project, a budget is allocated for creating
a set of intelligently designed and attractive reports as well as other
supportive products such as posters and brochures (if required).
Step 7: Results and impact analysis
“If it is clear right from the outset that the client within the enterprise has
neither the power nor the motivation to implement change, success will be
very modest and will likely be limited to mini projects.” (Pillkahn 2008, p. 291)
In order to be successful and have an impact, the scenario process will need
to engage with key customer decision makers. By engaging these people
throughout the research process, our aim is that later they will act as
22
champions, helping us to communicate the findings within their organisation
and beyond by working with us in:
 Selecting a set of indicators for monitoring
 Analysing the impact of the scenarios on strategy and decision making
 Identifying the key driving points and action
Conclusion
“The development of scenarios is an especially intense process, a process
that includes reflection, speculation, discussion, comparison, rejection, and
analysis, to name just a few of the related activities. Logic and scientific
methods alone are not enough. Creativity, fantasy, knowledge, experience
and powers of imagination are vitally important to shaping the future. It would
be more apt to describe the activity behind the development of good,
provocative, challenging and refreshing scenarios as an art than as a
science.” (Pillkahn 2008, p. 227-228)
The success of any scenario process is dependent on the level of
participation. It is crucial that any scenario process is an interactive process
that involves all the key stakeholders from the receiving organisation.
The somewhat formalised approach using a morphological analysis is the
most elaborate of all the approaches to scenario-building. Its key advantage is
that it is highly formalised and structured, allowing transparent and structured
integration of existing knowledge and expertise. It also offers additional levels
of analysis and thereby discussion that other methods cannot offer.
Main references
Pillkahn, U. (2008) Using Trends and Scenarios as Tools for Strategy
Development: Shaping the Future of Your Enterprise, Wiley-VCH Verlag
GmbH & Co.: Weinheim
Richey, T (2011). Wicked Problems – Social Messes. Decision support
modelling with morphological analysis (risk, governance and society).
Springer, London
Richey, T. (2011). Modelling Alternative Futures with General Morphological
Analysis World Future Review, Spring 2011, pp. 83-94.
23
Habegger, B. (2010) Strategic foresight in public policy: Reviewing the
experiences of the UK, Singapore, and the Netherlands, Futures: Volume 42,
Issue 1, February 2010, Pages 49-58
Richey, T. (2009), Future Studies using Morphological Analysis. Futures
Research Methodology Series V3.0
24