DSS for Integrated
Water Resources
Management (IWRM)
Success and failure
DDr. Kurt Fedra
[email protected]
ESS GmbH, Austria
http://www.ess.co.at
Environmental Software & Services A-2352 Gumpoldskirchen
SUCCESS AND FAILURE OF
DECISION SUPPORT SYSTEMS
FOR INTEGRATED WATER
RESOURCE MANAGEMENT
Presented at:
Palazzo Zorzi, Venice, Italy
5-7 October 2005
DSS for water resources management
DSS success measure and
end user satisfaction
Apparent assumptions:
1. We can measure the success of a DSS
2. We can measure user satisfaction
3. Success and user satisfaction is not
necessarily the same.
3
Level of information on consequences of actions
Degree of consensus on actions
LOW
HIGH
LOW
HIGH
problematic
DSS
domain
support-oriented
activities
Formal
decision
taken
Framework for water management
(after Verbeek & Wind, 2001)
4
DSS for water resources management
Some experiences :
1. Nature of application unclear:
– Policy/DM process to be supported unclear
– most DSS provide “only” scenarios
– assumption of chronology designimplementation incorrect
– “work-flow” users not involved in design
– no continuous involvement of users
5
DSS for water resources management
2. Conflict science vs policy
– DSS built on “state-of-the-art” science
models, research oriented
Resulting problems:
– Lack of system consistency
– Lack of flexibility to change
– Little room for uncertainty
– Models/data limiting factors
– Technology driven design
– Lack of long-term support
6
DSS for water resources management
Possible solutions:
- embedding in policy process
- continuous user involvement
- science  engineering
- science of integration, both :
Technological: alternative tools, hierarchical
structure, uncertainty propagation
Institutional: actor analysis, participation
7
DSS for water resources management
DSS success measure and
end user satisfaction
Apparent assumptions:
1. We can measure the success of a DSS
2. We can measure user satisfaction
3. Success and user satisfaction is not
necessarily the same.
8
DSS for water resources management
Proposition:
1. We can NOT measure the success of a DSS
in terms of making “better” decisions;
2. We can measure user satisfaction by
traditional psychometric methods (uncertain)
OR measure it in quantitative terms of
frequency and extent of use;
3. Therefore, success and user satisfaction is
the same: success is being used.
9
DSS for water resources management
Lemmata:
1. Basic objective of a DSS is to
influence decision making
processes, educate and
empower participants
2. Education needs a happy and
attentive audience (satisfied
users)
10
DSS for water resources management
Corollary:
Users are happy if they get what
they want which is NOT ONLY a
better decision in some (naïve
neopositivist) objective sense
meeting expressed aspirations
but includes diverse, usually
hidden agenda.
11
Measuring success
Lemma:
Success is difficult to measure:
Compared to WHAT ??
Only one decision gets
implemented – there is nothing
to compare the outcome with.
12
Measuring success
Success is difficult to measure:
It may be easier to establish failure cases:
• Mismatch of expectations and resources
• Mismatch of expectations and product
• Institutional change, priorities shift
• People change (retire, get promoted, leave)
Indication of failure: to be ignored
14
Success: building consensus
How to motivate a group to cooperate:
1. Demonstrate the potential for an
increase in overall net benefit
(through optimization)
2. Demonstrate allocation of the net benefit
in a “win-win game”
3. Use a DSS for that …..
15
IWRM Decision Problems
Problems:
–
–
–
–
Too much, not enough
Wrong time and place
Insufficient quality
Prohibitive costs ?
16
Overall objective:
Every use including the
environment gets the water
needed (in terms of quantity
and quality) wherever,
whenever, at an affordable
price or cost to the public,
sustainably.
17
Overall objective:
• Supply meets demands
• Demands (expectations) are well
balanced with all supplies
• Benefits exceed costs
• System is sustainable, equitable
(everybody happy)
ELSE THERE IS CONFLICT
18
Overall objective:
More formally:
• Maximise a social
utility function subject
to some equity
constraint
19
If there is conflict: Which decisions ??
1. Supply management incl. quality
– Alternative sources, water allocation,
– Structures, technologies
– Investment, OMR, economic incentives
2. Demand management
– Pricing, economic incentives
– Technologies (economics, efficiency, reuse)
3. Regulatory framework (affects all)
– Policy and decision making process
– Market mechanisms
20
Thesis:
Water resources problems require a
new approach to decision support
and decision making because:
• it is impossible to solve the
inverse problem (HOW TO)
unambiguously due to the
complexities of systems;
21
Thesis:
As a consequence, any practical
DSS approach has to be
– iterative
(multi tiered)
– adaptive
(learning)
– interactive (end user involvement)
22
Conclusions
Paradigm change:
• more complex problems
(increasing pressures, demands)
• participatory processes, civic
society, diverse audience
• increasing demand for
information
23
Conclusions
Paradigm change:
• information technology promises
instantaneous and ubiquitous
access to information
• research results and tools are
directly accessible beyond the
academic community
24
Conclusions
Paradigm change:
• changed nature of discourse from
scientific correctness, precision,
verification, formal proof
to political feasibility, acceptability,
Mehrheitsfähigkeit;
• from abstract optimality to an
evolutionary: good enough.
25
Conclusions
Paradigm change:
DSS do not offer optimal solutions
(given a set of preferences) but a
mechanism to make the process
open, accessible, and the solution
acceptable to a majority.
26
Concluding assumption:
• improvements to the
DM process will lead to
• improvements of the
DM results.
(an ISO 9000 approach).
27