SD Course in Kyiv Polytechnic Institute, 12-23 Febraury 2006

1. From forecasting to Backcasting:
Developing Shared Future Visions for
Sustainable Development
February 21, 2007
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Faculty of Technology, Policy and Management

2. Why forecasting?
• Improves quality of debate?
• Suspect: technocracy?
• Control dilemma
- the earlier a debate takes place, the more options
there are for technological steering
entrenchment
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3. Control dilemma for new technology
Control dilemma with forecasting of impacts?
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4. Forecasting possible?
• Fundamental problem: non-linearities
• Problem of Induction
• Historic empiric correlations are insufficient if there is
no clear causal relationsship
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5. EXAMPLE OF A NON LINEAR
PHENOMENON
Who is the first to buy a telephone?
Some products become more attractive
as others buy similar products:
especially high-tech products:
(computer, fax, phone, car, video)
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6. Foresight instead of forecasting, but how?
* Monitoring, trend watching
* ’historic’ methods
* ’expert’ methods
* experiments
* modelling
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7. Monitoring
study of
- professional journals
- patents/patent trends searches
- meetings
- Web searches
- annual reports/media
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8. ‘historic’ methods
presupposition: historic parallels
historic analogy
diffusion curves
S-curves
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10. Extrapolations
• Based on hypotheses such as
• Linear growth
• S-curve
• Envelope curve
• Fisher-Prey, Gompertz diffusion
models
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11. February 21, 2007 11

12. Expert judgment
• If there are no reference points for extrapolation
• To check a quantitative forecast
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13. experts
• Are always biased
• Positive in regard to technology in general IEEE onderzoek
• Positive in regard to the area of expertise (nuclear fusion, self
selection)
The social structure of disciplines prohibits
open communication regarding the future
(interdependencies, prejudices, publication priorities)
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14. Delphi method
Delphi:
• survey among experts in several rounds
• anonymous feed back of arguments & estimates
• Revision of judgments
• Consensus in 3-4 rounds
Criticism:
• group bias remains
• strategic behavior by mutual contact
• Only for experts within a discipline
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15. Experiences Delphi
• Used since 1959
• Good results,
• Not just forecasting: it is also intervention in a
discipline
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16. Example: External propulsion of
vehicles
- 50 experts (global, 50% return, variatie)
• 14 technologies
• 4 technologies were promising
• Many experts changed their view during Delphi
process
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17. Failed Forecasts
• Misjudgement of
• Speed of Technological change: (1950s, flying cars)
• expert assessment of technologies (eg the forecast
regarding superiority of synthetics, 1970)
• citizens judgments (nuclear power)
• Public policy (glass recycling)
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18. Scenarios:
To paint the various possible and
consistent futures in a complex
situation:
-not: emergency scenarios
-but: credible stories that stimulate the
creativeness of people in thinking of
future threats and opportunities
- Robust options
- cheap precautions
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19. During stable times, the mental
model of a successful decision
maker and unfol-ding reality match...
In times of rapid change and
increased complexity, how-ever, the
manager's mental model beco-mes a
dangerously mixed bag: rich detail
and understanding can coexist with
dubi-ous assumptions .. and illusory
projec-tions (Wack, 1985)
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20. ingredients
- technology
- economy
- demographics
- culture
- regulation
- the (global) environment
- competitors actions
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21. Scenario Results: Stimulating creative discussion
- in all scenario's, the corporation meets its goals.
- in all scenario's, the corporation does not meet its
goals.
- in a surprise free scenario, the corporation meets its
goal, but not in other scenarios.
- in a surprise free scenario the corporation does not
meet its goals, in alternative scenarios, it does.
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22. Backcasting: Looking back from the
future to design actions now
• Involve various stakeholders
• Start with needs, not with technology
• Analyze the need, what do stakeholders really want?
• Build consensus
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23. Backcasting: from vision to action
Intermediate steps
E Future-
C oriëntation
ing
O Backcast
E
F
F g
I stin
C k ca
I B ac
E
N
C
Y
2000 TIME 2050
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24. Why Backcasting?
• Clear future visions have a strong guiding power: Man
on the Moon,
• Defining and clarifying an attractive sustainable future
• It forces to specify norms and values
• Alternative for traditional forecasting
• Fit for ‘wicked problems’
• Experiences:
• The Natural Step
• Netherlands: Sustainable Technology Development
program
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25. Backcasting: characteristics
• From future vision to action by design and
analysis
• Organize the process carefully, the process is
important,
• Facilitate learning of participants
• Facilitate the social embedding of the results
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26. Stakeholder Involvement
INDUSTRY
SCIENCE
GOVERNMENT AND
TECHNOLOGY
OPTIONS
SOCIETAL
ORGANISATIONS EDUCATION
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27. Backcasting in 5 steps
Step 1 Strategic Problem orientation Analysis
Step 2 Prepare a vision of a desirable future Vision
Step 3 Back-casting What do we need to make this
come true?
Step 4 Further elaboration, detailing
Step 5 Implementation, Policy implications,
organizing embedding & follow-up
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28. Toolkit for Backcasting:
4 kinds of methods
• Participation and interaction
• workshops, visioning, creativity stimulation, brain storms
• Design- and scenario-methods: modeling, forecasting
• Analysis- and modeling-methods
• LCA, effect analysis, stakeholder analysis
• Management-methods for Process-, Project-, and Network
management
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29. Step 1
Strategic Problem orientation
• Which needs to fulfill?
• Trends, and possible changes that are relevant for this
need?
• What is the problem, how is this problem perceived by
various groups?
• What are the unsustainabilities and what are the causes?
• Who are the stakeholders?
• What are potentially directions to seek solutions?
Methods
• Actor/Stakeholder analysis, socio-technical map
• Interactive methods (interviews, workshops, etc)
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30. Example: Soy Fodder - pigs – meat
products
The Netherlands is importing large amounts of Soy
fodder from Brazil, where it is often grown in areas
that were cleared from tropical rainforest.
The soy fodder is used to feed pigs in a specific region.
Pigs manure creates local ammonia contamination.
The pigs (or the pigs meat) is often transported to Italy.
Some of the meat is afterwards returned as real
‘Parma Ham’.
The proteins that are actually consumed only account for
a few percent of the plant proteins in soy fodder.
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31. Strategic Problem Orientation
• What is the need?
• What are the current unsustainabilities?
• What will probably be stakeholders?
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32. Step 2
Prepare a desirable future
• Terms of Reference?
• What socio/technical options are available?
• Are the unsustainabilities solved?
• Which technology is needed?
• How does it affect culture and structure of society?
• What are important trends, and events?
• Could we make the future vision even more sustainable?
Methods
• workshops
• Creativity stimulation, designing
• Consensus formation
• Illustrations
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33. Step 3
Back-casting What do we need?
• Which changes are needed to make the future vision come
true (technologic, cultural, organization/structure)?
• Who can implement the changes. How could the changes
be made attractive for these actors?
• Could we define stepping stones?
Methods
• Analysis and modeling
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34. Step 4
Elaboration, analysis
• A possible design of a socio-technical system
• Effects of these systems for various stakeholders?
• What are drivers, barriers?
• What need to be in follow-up (policy, research,
development, publicity)?
Methods
• Methods for Environmental Impact Analysis, consumer
studies, economic analysis of elements of system
• Technology Assessment methods (checklist, cost/benefit,
etc)
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35. Step 5
Agenda, embedding & follow-up
• What should be done to guarantee successful further
activity after a backcasting project has been carried out?
• How to embed specific projects and proposals?
• Agreements on further process and conflict resolution.
Methods
• Communication
• Management
General
• Project management, team building, communication
• (process) evaluation
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