Decision Making Process

A compelling representation of the Decision Making Process was proposed in the early 1960s, and still remains today a major methodological reference. The model includes three phases :

termed intelligence,
design and
choice.

Figure dss.04 shows an extended version of the original scheme, which results from the inclusion of two additional phases, namely implementation and control.

Figure dss.04 Phases of the Decision Making Process
Each step in the decision-making process may include social, cognitive and cultural obstacles to successfully negotiating dilemmas. It has been suggested that becoming more aware of these obstacles allows one to better anticipate and overcome them.

Intelligence
In the intelligence phase the task of the decision maker is to identify, circumscribe and explicitly define the problem that emerges in the system under study. The analysis of the context and all the available information may allow decision makers to quickly grasp the signals and symptoms pointing to a corrective action to improve the system performance. For example, during the execution of a project the intelligence phase may consist of a comparison between the current progress of the activities and the original development plan. In general, it is important not to confuse the problem with the symptoms. For example, suppose that an e-commerce bookseller receives a complaint concerning late delivery of a book order placed on-line. Such inconvenience may be interpreted as the problem and be tackled by arranging a second delivery by priority shipping to circumvent the dissatisfaction of the customer. On the other hand, this may be the symptom of a broader problem, due to an understaffed shipping department where human errors are likely to arise under pressure.

Design
In the design phase actions aimed at solving the identified problem should be developed and planned. At this level, the experience and creativity of the decision makers play a critical role, as they are asked to devise viable solutions that ultimately allow the intended purpose to be achieved. Where the number of available actions is small, decision makers can make an explicit enumeration of the alternatives to identify the best solution. If, on the other hand, the number of alternatives is very large, or even unlimited, their identification occurs in an implicit way, usually through a description of the rules that feasible actions should satisfy. For example, these rules may directly translate into the constraints of an optimization model.

Choice

Once the alternative actions have been identified, it is necessary to evaluate them on the basis of the performance criteria deemed significant. Mathematical models and the corresponding solution methods usually play a valuable role during the choice phase. For example, optimization models and methods allow the best solution to be found in very complex situations involving countless or even infinite feasible solutions. On the other hand, decision trees can be used to handle decision-making processes influenced by stochastic events.

Implementation
When the best alternative has been selected by the decision maker, it is transformed into actions by means of an implementation plan. This involves assigning responsibilities and roles to all those involved into the action plan.

Control
Once the action has been implemented, it is finally necessary to verify and check that the original expectations have been satisfied and the effects of the action match the original intentions. In particular, the differences between the values of the performance indicators identified in the choice phase and the values actually observed at the end of the implementation plan should be measured. In an adequately planned DSS, the results of these evaluations translate into experience and information, which are then transferred into the data warehouse to be used during subsequent decision-making processes.

The most relevant aspects characterizing a Decision Making Process can be briefly summarized as follows:

Decisions are often devised by a group of individuals instead of a single decision maker.
The number of alternative actions may be very high, and sometimes unlimited.
The effects of a given decision usually appear later, not immediately.
The decisions made within a public or private enterprise or organization are often interconnected and determine broad effects. Each decision has consequences for many individuals and several parts of the organization.
During the decision-making process knowledge workers are asked to access data and information, and work on them based on a conceptual and analytical framework.
Feedback plays an important role in providing information and knowledge for future decision-making processes within a given organization.
In most instances, the decision-making process has multiple goals, with different performance indicators, that might also be in conflict with one another.
Many decisions are made in a fuzzy context and entail risk factors. The level of propensity or aversion to risk varies significantly among different individuals.
Experiments carried out in a real-world system, according to a trial and error scheme, are too costly and risky to be of practical use for decision making.
The dynamics in which an enterprise operates, strongly affected by the pressure of a competitive environment, imply that knowledge workers need to address situations and make decisions quickly and in a timely fashion.

Choice

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