• Introduce and examine the concept of “wicked” problems
• Understand the importance of a systems approach to decision-making
• Explore multiple paradigms, perspectives, frameworks and approaches to decision-making
• Understand the role of stakeholders in decision-making processes
• Introduce and examine the concept of decision support systems
• Explore the role and application of decision support systems in organizational decision-making
• Discuss knowledge management systems from a decision-support context
Systems-oriented decision-making, in contrast, focuses on how the decision elements under consideration interact with all parts of the system. By considering the system interconnections and feedbacks, it encourages decision-makers to think about problems and solutions holistically and with due regard toward the long-term view.
Due to human cognitive limitations, as well as other constraints such as a lack of sufficient data on which to base informed decision-making, it is not easy to take the systems route. However, a number of analytical approaches have been proposed and refined over the years to facilitate this process. Using these decision analysis approaches enables stakeholders and decision-makers to incorporate systems thinking in the evaluation of very complex “wicked” problems. These are often characterized by uncertain data and information, and for which “cause” and “effect” are not closely related and the long-term consequences of short-term tradeoffs are not readily apparent.
Seeing the problem in its proper full context will facilitate identifying its stakeholders, who are the people involved, and come up with a definition of the problem and its elements.
A full grasp of the problem situation and its stakeholders is also a prerequisite in our critical search for setting appropriate boundaries to both the narrow system of interest with its relevant environment and the wider system of interest. All this provides the basis for defining a relevant system, in terms of both its focus and its detail.
The problem situation, or context within which a problem occurs, is the sum or aggregate of all aspects that can or may affect or shape the problem or issue of concern. It is the complex of:
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However, not all problems are decision problems!
However, not all problems are decision problems!
• The individual or group has alternative courses of action available,
• The choice of which alternative to take can have a significant impact. That is, not all the alternatives will yield the same outcome,
• The individual or group is uncertain a priori as to which alternative should be selected.
At one extreme are opportunities, those initiated on a purely voluntary basis, to improve an already secure situation.
At the other extreme are crises, where organizations respond to intense pressures.
A severe situation, which demands immediate action, can occur in crises.
Most decision problems fall in between the two extremes, being evoked by milder pressures than crises. During the development of a solution, however, a given decision process can shift along this continuum. For example, an ignored opportunity can later emerge as a problem or even a crisis or a manager may convert a crisis to a problem by seeking a temporary solution and in some cases a manager may use a crisis or problem situation as an opportunity to innovate.
References: to Mintzberg et al. (1976). Simon (1960)
Secondly, based on early work by Simon in 1960, decision problems may also be classified by their nature into three types, namely:
• Unstructured problems: For these, none of the phases of decision-making can be formalized, and no pre-established procedures exist. These types of problems are difficult to support with models and computerized decision-making processes.
• Structured problems:
Here, all phases of decision-making can be formalized, and it is possible to develop standard operating procedures for addressing the problems. The decision-making process can easily be delegated or even automated.
• Semi-structured or Ill-structured problems: These are somewhere intermediate between the above two types. The main challenge here is to find structure in problems that seem to have no structure. Such problems are also referred to as “wicked problems”, as discussed in a subsequent slide. Most systems analysis approaches are aimed at finding solutions to these types of problems.
Click on the link of each to learn more.
The Rational Model proposes that people follow a rational, four-step sequence when making decisions. The four steps are:
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In this model, the following assumptions are made:
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Evidently, in real-life problem situations most of the above assumptions do not hold true. Thus, some of the limitations faced by this model are issues such as not having enough information relevant to the problem and the fact that problems can evolve within a short period of time.
The Normative Model, which is based on the notion of Bounded Rationality, takes into account the fact that decision-makers are bound by certain constraints when making decisions. These constraints include personal and environmental factors that reduce rationality, such as time, complexity, uncertainty and resources. A decision-maker will only be able to manage a certain amount of information at any one time, so they make judgments based on their previous experiences wherever possible to speed up the decision making process. Often, choosing a solution that is "good enough" is considered effective when there are multiple solutions that will produce similar outcomes.
Thus, the normative model suggests that decision making is characterized by:
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In this model, the decision-making process is not regarded as a sequence of steps that begins with a problem and ends with a solution. Instead, decisions are the outcome of independent streams of events within an organization. The organization is a “garbage can” where these streams are stirred. There are four possible consequences to this approach:
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• Resolving a problem involves selecting a course of action that yields an outcome that is good enough, or “satisfices”. It is a qualitatively oriented or clinical” approach rooted in common sense and subjectivity. Ackoff points out that most managers are problem resolvers, citing a lack of information and time to do otherwise.
• Solving a problem, on the other hand, involves selecting a course of action that is believed to yield the best possible, or most optimal, outcome. This is referred to as a research approach which is preferred by technologically oriented managers whose organizational objective is growth rather than mere survival. The research approach mainly employs scientific tools, techniques and methods.
• Dissolving a problem involves changing the nature and environment of the entity in which the problem is embedded so as to remove the problem. Considered a “design” approach, it aims at changing the characteristics of the larger system into a state in which the problem cannot or does not arise. The designer makes use of the methods, techniques and tools of both the clinician and the researcher. He uses them synthetically rather than analytically. This approach is preferred by managers whose principle organizational goal is development and not just growth or survival.
References:
Ackoff (1981)
Here:
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The alternative that yields the highest rate of return while satisfying the requirement of at least 18% before taxes would then be selected as the best solution.
The context of the problem consists of all aspects that directly or indirectly affect the measure of performance and over which the decision-maker has no control, or which are considered to be “givens”. In the above example, this could consist of the current location of the firm, the potential sources of raw materials, the demand for the products, etc.
For this particular example, an alternative decision criterion could be that “annual profits are maximized”. This would also yield the desired result of achievement of a satisfactory rate of return on investment. In this scenario, the measure of performance that would distinguish one alternative course of action from another would be the annual level of profit.
It is also possible that there may be only one relevant criterion to evaluate how well an objective has been achieved. An example of such an objective may be “to achieve the highest profits”, for which the decision criterion would be “profits are maximized”. As seen in this example, the decision criterion and objective coincide.
There are also decision problems where more than one objective exists. These are referred to as multiple- objective decision problems.
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Conflicting objectives may have to be resolved through a process of negotiation and compromise. Attaining even a partial consensual understanding of the problem situation will allow agreement on a choice of action, even if no consensus can be reached on objectives.
In most real-life applications, problem definition will not be achieved in a single pass. The initial definition usually goes through a series of progressively more detailed reformulations and refinements, as deeper insight into the problem is gained. In fact, to some extent problem formulation continues until a project ends. It is, however, in the early problem-structuring stages where the ultimate success or failure of a project most often has its roots!
The term was originally coined by Horst Rittel and Melvin Webber in 1973, and refers to a problem for which each attempt to create a solution changes the understanding of the problem.
Wicked problems always occur in a social context. The wickedness of the problem reflecting the diversity among the stakeholders is the problem. Wicked problems cannot be solved in a traditional linear fashion, because the problem definition evolves as new possible solutions are considered and/or implemented.
• You don't understand the problem until you have developed a solution. Indeed, there is no definitive statement of "The Problem." The problem is ill-structured, an evolving set of interlocking issues and constraints.
• Wicked problems have no stopping rule. Since there is no definitive “Problem", there is also no definitive “Solution." The problem solving process ends when you run out of resources.
• Solutions to wicked problems are not right or wrong, simply "better," "worse," "good enough," or "not good enough."
• Every wicked problem is essentially unique and novel. There are so many factors and conditions, all embedded in a dynamic social context, that no two wicked problems are alike, and the solutions to them will always be custom designed and fitted.
• Every solution to a wicked problem is a "one-shot operation," and every attempt has consequences. As Rittel says, "One cannot build a freeway to see how it works." This is the "Catch 22" about wicked problems: you can't learn about the problem without trying solutions, but every solution you try is expensive and has lasting unintended consequences which are likely to spawn new wicked problems.
• Wicked problems have no given set of alternative solutions. There may be no solutions, or there may be a host of potential solutions that are devised, and another host that are never even thought of.
As Laurence Peter put it, ““Some problems are so complex that you have to be highly intelligent and well informed just to be undecided about them!”
References: Horst Rittel and Melvin Webber in 1973
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Since stakeholders are roles, a person may assume more than one role at the same time.
How problem owners and/or analysts perceive the problem situation involves a fair degree of arbitrariness. It is strongly affected by the purpose of the analysis, the world views of the analysts and/or problem owners, and the resources available for the analysis. A sufficient degree of shared appreciation of the various views is needed to reach a partial consensus on the problem situation. Only then is it likely that an agreement will emerge as to which issue is to be studied and how.
A problem situation summary should not be in the form of a systems description, since this may impose a given structure that may bias the analysis. At the initial problem-structuring stage, it is crucial to keep an open mind. Acquiring a sufficiently complete and detailed understanding of the problem situation is a necessary condition for a successful system intervention. The analyst must get a thorough “feel” for anything that may impact the outcome.
Boundary selection will largely fix the scope, direction, and focus of all subsequent analysis. It not only determines which inputs are considered controllable, but also which benefits and costs are included in the performance measure, and which potential stakeholders are reduced to problem customers or possibly mere victims without any say or recourse.
Inappropriate boundary selection often means that the benefits or advantages derived for the narrow system of interest are partially or completely negated by losses or disadvantages in the wider system. Selecting the wrong boundaries may result in solving the wrong problem. It may make it difficult or even impossible to implement the solution or it may reduce the potential benefits that could have been derived.
Based on earlier work by Herbert Simon (1960), Sharifi et al. (2004) propose a framework for a systematic approach to decision-making, consisting of three phases namely:
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References:
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As previously discussed, however, problem-solving within a systems context almost invariably involves a diverse set of stakeholders, whose views and preferences need to be taken into account in the decision-making process if the decisions or outcomes are to gain validity or acceptance.
For this reason, the traditional linear paradigm is modified as shown in the diagram, to cater for the following processes:
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The seven stages are:
1. Entering the problem situation
2. Expressing the problem situation
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4. Building conceptual models of human activity systems
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6. Defining changes that are desirable and feasible
7. Taking action to improve the real world situation
The dynamics of the method come from the fact that stages (2) through (4) are always an iterative process.
The stake-holders who are defined as Client, Actors and Owner, engage in a debate guided by the analyst/facilitator. During this debate various root definitions which are succinct statements of appropriate systems and conceptual models are put forward, modified and developed until a desirable model is achieved by consensus. This model then forms the basis for real world changes.
The mnemonic CATWOE shown in the diagram represents several criteria that should be specified to ensure that a given root definition is rigorous and comprehensive. It stands for:
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1) The problem might simply disappear as the result of reaching a consensus or a realization that, actually, the problem never was;
2) A fairly unstructured solution might result, such as agreement to adopt a new role for the organization;
3) The problem might become more structured. In this case the “soft” problem resolves into an identifiable "hard" problem that can be tackled through traditional means.
Click each tab to learn more.
Clients - Who are the beneficiaries or victims of this particular system? (Who would benefit or suffer from its operations?)
Actors - Who are responsible for implementing this system? (Who would carry out the activities which make this system work?)
Transformation - What transformation does this system bring about? (What are the inputs and what transformation do they go through to become the outputs?)
Worldview - What particular worldview justifies the existence of this system? (What point of view makes this system meaningful?)
Owner - Who has the authority to abolish this system or change its measures of performance?
Environmental constraints - Which external constraints does this system take as a given?
In order to ensure the objectives set out by the Directive are achieved by 2015, the links between the pressures exerted by society and their environmental impact have to be understood and projected to the time frame available for achieving the Directive’s objectives. In practice this means identifying the origins of pressure or driving forces represented by social, demographic and economic developments in societies; modelling the effects caused by the pressures on the state of water bodies; and finally evaluating the impacts of the changed state of the water bodies.
In order to organize the causal relations between the various elements, work has been carried out on producing conceptual frameworks which are suitable for structuring, organizing and relating the indicators collected to describe and quantify interactions between society and the environment.
The DPSIR framework is one such framework.
IMG Source: http://www2.epa.gov/sites/production/files/styles/large/public/2013-06/dpsir-flowchart.jpg?itok=8FU-zlPx
WSR sees management decisions as involving multiple relations: relations with the world, relations with the mind, and relations with others. The WSR approach presents a conceptual framework and an operable methodology for integrating wuli, shili and renli considerations into a differentiated or interconnected whole, as the context, content and process of decision making.
Shi in Chinese means: affairs, events; trouble, accident; job, work, business; responsibility, involvement, engagement, service.
Renli denotes patterns of human behaviour and interaction, effects of encounters among different value and belief systems, as well as preferences in tackling those patterns, effects and encounters.
Thus, “Wuli” refers to investigation of the facts of a situation, sometimes with modelling of future scenarios.
“Shili” implies enough knowledge of different theories and methods to allow informed choices about which methods to choose, and which paths of action to follow.
While “Renli” concerns the ability to deal with human relations.
WU: The notion of wu therefore covers the decision context (natural resources, physical environment, population, transportation and communication facilities, financial resources, available technology and data, time scale, production capacity, manpower, pollution, etc., as well as existing organizational structures, regulations and reporting systems). Accordingly, wuli are the principles that form and govern the relations among these objective wus.
Shi: Shili is used to denote patterns of engagement between ”the human mind” and “the world”, i.e. the ways we choose to see, to think, and to act. In studying shili, the focus is on understanding how “the world”, i.e. problems, issues, options and choices can be better investigated, formulated, modelled, evaluated, compared and managed.
Renli: The concept of ren concerns the socio-political aspects of reality and decision-making. Renli denotes patterns of human behavior and interaction, effects of encounters among different value and belief systems, as well as preferences in tackling those patterns, effects and encounters. Renli highlights the importance of human relations, which in most circumstances shape the process and outcome of human activities.
The implications of thinking of systems in organizations as work systems include the following:
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The work system approach for understanding systems includes both a static view of a current or proposed system in operation and a dynamic view of how a system evolves over time through planned change and unplanned adaptations.
This model encompasses both planned and unplanned change. Planned change occurs through a full iteration encompassing the four phases; starting with an operation and maintenance phase, flowing through initiation, development, and implementation, and arriving at a new operation and maintenance phase. Unplanned change occurs through fixes, adaptations, and experimentation that can occur within any phase.
Once a decision problem is understood and the ways in which performance measures are to be calculated have been agreed, data is collected on system performance under different solutions, decision variables are adjusted and scenarios are modeled. Further evaluation that takes into consideration other stakeholder requirements leads to the selection of one option for implementation that is acceptable to all stakeholders. As with the problem-definition process, this evaluation and selection process is often iterative in nature.
Thus, effective tools to assist in such decision processes must have the ability to represent critical aspects of the system, to compare the performance of different options against competing objectives through simulation of the various options, to consider scientifically verified or calibrated model outputs alongside diverse stakeholder views and interests, and to present model outputs in ways that are relevant to the decision context and are easily understood by all stakeholders, including those with non-technical backgrounds.
The models are:
A process/behavioral model
A planning model
An evaluation model
Click the link to learn more about each.
A process/behavioral model describing the existing functional and structural relationships among elements of the system and its environment, to help analyze the actual state of the system and identify the existing problems or opportunities.
A planning model, which integrates potential and capacity of resources, socio-economic information, goals, objectives, and concerns of the different stakeholders to simulate the behavior of the system. Conducting experiments with such a model helps to understand the behavior of the system and allows generation of alternative feasible scenarios to address the existing problems.
An evaluation model, which allows the evaluation of impacts of various strategies/scenarios and supports selection of the most acceptable solution that improves the management and operation of the system and is acceptable to all stakeholders.
In relation to the classical decision-making framework discussed earlier, models are primarily useful at the design and choice phases of the decision making process, while the intelligence phase largely depends on people’s intuition and experience. Intuition is good at identifying and defining important factors but poor at combining that information; mathematical models, on the other hand, are good at combining factors but poor at defining them.
In 2004 Bruen also notes that modelling tools or evaluation techniques can be applied by an experienced practitioner in a “stand-alone” manner to address a particular aspect of a decision problem. However, if these tools and techniques are to be used as part of interaction amongst both technical and non-technical players then their use and interpretation must be made as simple as possible.