Developing Methods to Enhance the Organisational Management of Ambiguous Risks. Tom Horlick-Jones, Risk Research Group, Centre for Environmental Strategy, University of Surrey, Guildford, UK; and Jonathan Rosenhead, Department of Operational Research, London School of Economics & Political Science, London, UK
INTRODUCTION
Ambiguous risks, combining irreducible
uncertainties and diverse assessments, hamper decision-making
processes in many public and private corporate arenas. To be
adequate to such situations, analytical approaches to decision
support must take account of differences of perception and conflict
between multiple actors, encompass the plausibility of alternative
possible futures, encourage creativity and generate decisions
with flexible capacities.
Classical approaches to both planning
and decision-making are inappropriate in theory, and have proved
inadequate in practice for the management of such ambiguous risks.
In order to address this problem, recent research into risk management
has argued for a broadening of the knowledge-base which it employs.
What seems to be needed is a form of analysis which, effectively,
operationalises Funtowicz and Ravetz's concept of "Post-normal
Science" in the context of risk management.
This paper examines the potential
of a group of analytic approaches, collectively known as "Problem
Structuring Methods," to fulfill this role, and so provide
planning and decision support for the management of ambiguous
risks in organisational settings.
ORGANISATIONAL RISK MANAGEMENT
Organisational risk management involves
a number of interlocking processes including assessing and seeking
to control the physical and environmental risks of commercial
activities and managing financial and business risks. It also
means managing the interactions with the organisation's market,
political, social and technological environments (Mercer, 1992)
in increasingly turbulent and unpredictable times (Giarini and
Stahel, 1991; Beck, 1995).
At the corporate level, risk management
therefore becomes a key part of strategic management, as a multiplicity
of individual risk management decisions are integrated together.
This process involves different types of risk and their associated
uncertainties, and the expert knowledge and experience of a large
number of individuals and groups within the corporation, resulting
in a complex mixture of symbolism, micro-politics and negotiation
between culturally diverse parties (e.g. Dawson, 1992).
Considerable scope therefore exists
within such corporate arenas for the generation of range of risk
management problems characterised by uncertainty and plural perspectives.
Such ambiguity generates serious difficulties for organisational
planning and decision-making, with significant operational and
commercial implications (e.g. Kunreuther et al, 1995).
The range of operational risk management
contexts which exhibit such ambiguity is wide. These range from
situations where decisions are made over very short time scales
such as emergency management or the management of novel financial
instruments such as swaps and derivatives, to longer-term decision-making
processes involving environmental risks or those concerned with
commercial decisions such as the allocation of insurance cover.
The theoretical assumptions of traditional
rational comprehensive planning are not fulfilled by the characteristics
of this context; and, as is well known, decision-making in conditions
of uncertainty can be severely affected by biases arising from
subjective factors. Recent research into high-pressure decision
processes in environments characterised by uncertainty and plurality
(e.g. Klein et al, 1993) has shown that such real-world
decision making processes are embedded in wider tasks and concerns.
Decision-makers draw heavily on their knowledge and experience
to assess situations and select satisfactory, rather than optimal,
courses of action.
The work of Funtowicz and Ravetz
(e.g. 1992; 1995) is of much relevance here. They have recognised
the emergence of a class of contemporary problems with a number
of common features - typically facts are uncertain, values in
dispute, stakes high and decisions urgent. They identify a need
for new forms of scientific practice to be developed, which they
call "Post-normal Science", characterised by the integration
of an extended range of types and sources of knowledge, in order
to enhance the quality of associated decision-making. We will
now proceed to examine a possible approach to operationalise these
theoretical insights in the context of organisational risk management.
PROBLEM STRUCTURING METHODS
The classical analytic methods of
operational research were predicated on the existence both of
objective data and of value consensus. On these foundations a
range of methods were developed for finding optimal solutions,
either by explicit formulae or by efficient algorithms. Risk
could be accommodated within this framework only in the quantitative
form of objective probabilities.
These strict assumptions excluded
the analytic treatment of many risk management situations. One
response has been the development of the field of decision analysis,
in which the subjectivity of both preferences and probability
estimates is accepted. In one variant of decision analysis, decision
conferencing, these are elicited in a facilitated group exercise.
Problem structuring methods (e.g.
Rosenhead, 1989) are a set of methods designed to assist management
groups to agree the nature and boundaries of the problem which
they must tackle, and to secure shared commitment to action.
Their distinctive feature is that they are model-based. In general,
they incorporate processes for eliciting perceptions of relevant
factors and cause-effect links, relating or contrasting these
perceptions, and focusing managerial attention on key areas for
commitment or further exploration. Their mode of operation is
thus group-based, participative and iterative. Particular PSMs
have different emphases - e.g. conflict, alternative perspectives,
future uncertainties.
Problem structuring methods make
two further relaxations of the assumptions held to govern decision-making.
Firstly, uncertainties may be captured as alternative possibilities
rather than by numerical probabilities. Secondly, PSMs do not
require the formulation of an additive value function incorporating
explicit trade-offs between different objectives. This latter
feature of decision analysis in principle (although not necessarily
in practice) limits it to decisions by an individual, or at most
by a group with a unitary value structure.
The absence of this requirement in
problem structuring methods enables them to structure and display
features of the decision situation as perceived by multiple decision
makers whilst using a reduced level of formal quantification.
While this limits the mathematical operations which can be performed,
it greatly assists the involvement of decision makers and their
'ownership' of the outputs of the process.
Notable applications of PSMs include
the use of the Strategic Choice Approach to formulate national
policy on the storage, handling, transport and use of Liquid Petroleum
Gas in the Netherlands; the use of a range of PSMs (Cognitive
Mapping, Soft Systems Methodology, Strategic Choice Approach)
to determine an IT strategy for Sainsbury plc; and the use of
Cognitive Mapping in conjunction with a more conventional method,
System Dynamics, to support a successful legal action arising
out of delays and disruption to a major component of the Channel
Tunnel project (see Rosenhead and Horlick-Jones, 1995). Additionally,
an investigation conducted for the UK Home Office (Horlick-Jones,
Dewar, Rosenhead et al 1994; Horlick-Jones, 1995) demonstrated
the feasibility of using Soft Systems Methodology to provide an
enhancement of the cognitive environment of emergency managers
by means of planning and training initiatives.
DISCUSSION
Recent research into risk management
has recognised the need to contextualise expert knowledge and
to extend the range of knowledge that are seen to constitute "expertise"
(Wynne, 1991; Beck, 1995; Horlick-Jones, 1995; Horlick-Jones and
De Marchi, 1995). By assessing a wider range of both expert and
tacit knowledge, it can be argued, both contested values and sources
of uncertainty, as well as and the possible impacts on related
policy areas, can be incorporated into the decision-making process.
We have suggested (e.g. Rosenhead
and Horlick-Jones, 1995) that there is considerable potential
for application of PSMs to risk management problems in organisational
and interorganisational settings. The methods are predicated
on the need to address uncertainty and plurality, and their interactive
and transparent mode of operation provides a powerful means to
promote integration of knowledge, to build trust and understanding
between culturally distinct groups, and to enhance the quality
of decision-making.
ACKNOWLEDGEMENTS
We are pleased to acknowledge that
this paper draws on work conducted in collaboration with Jerry
Ravetz and Ragnar Löfstedt.
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