Good decisions are the ones that resolve the problem identified. Not all decisions will have this intended outcome. No manager always makes the right decision. Factors that are unforeseeable or over which the decision maker has no control assure some wrong decisions, for example, bad weather, disease, changing economic conditions, false information received, bad luck and changes in laws and regulations.
According to Trull (1966) the success of a decision is a function of its quality and of how it is implemented. Decision quality is judged by a decision's compatibility with existing constraints, its timeliness, its incorporation of the optimal amount of information. A successful implementation of a decision results when managers avoid conflict of interest, make sure the decision is understood by those who must carry it out, and perceive the rewards of successful implementations are worth the risks of implementing the decision. Decision success is a measure of whether objectives sought when making a decision have been partially or completely attained.
The distinction between effectiveness of decision-making and efficiency in decision-making helps DSS analysts understand the impact of DSS on decision behavior. Keen and Scott Morton (1978) present the following explanations of these important concepts:
"Effectiveness in decision-making requires us to address the process of identifying what should be done. Effective decision-making requires consideration of the criteria influencing the decision. Thus, in this view, we need to discover the decision maker's perception of the decision situation in order to increase the decision maker's effectiveness. This is fully as important as identifying the surface "facts" of the situation. It is often the case that the "facts" which initially appear important when working within a semistructured or unstructured decision situation are not the ones that, after they are explored by the decision maker, turn out to be the most influential in affecting decision outcome."
"Efficiency in decision-making addresses the means for performing a given defined task in order to achieve outputs as well as possible, relative to some predefined performance criteria. The definition of efficiency used here is closely related to the term's use in physics and engineering: an output value divided by a value for the input resources used to obtain that output."
Increasing efficiency typically takes the form of minimizing time, cost or effort to complete an activity. Effectiveness focuses on what activities should occur. A focus on effectiveness requires decision-makers to adapt and learn, to make a responsive adjustment to changes in the environment for and within which they make decisions (after Bennett 1983, p. 2).
There are some known impediments to "good" decisions over which a manager does have some control. Some examples include tradition and bias, lack of experience and lack of knowledge and improper use of decision aids.
Tradition and Bias Impediment
"We have always done it that way." The finality and implied end of discussion suggested by this statement means that tradition is at work. Approaching alternatives with prejudice means that an otherwise good alternative is not given serious consideration because of bias. Tradition and bias reflect fear of change and fear of failure. Comfort with the known and confidence in what has worked before are understandable. But when tradition and bias prevent brainstorming for new ideas, consideration of off-the-wall ideas, making mistakes and experimenting with new ideas, they are impediments to good decision-making. This impediment can hinder the implementation of DSS and DSS can do little to reduce this impediment. Managers need to be conscious of the problem and overcome it as best they can.
Lack of Knowledge Impediment
For routine, recurring decisions knowledge and experience are very important. DSS and expert systems can capture some managerial knowledge and reduce the impediment of inexperience and lack of knowledge.
Improper Use of Decision Aids Impediment
It is discouraging to realize that some of the decision aids and DSS that have been created and implemented in organizations can actually hinder "good" and successful decision-making. DSS can provide a false sense of confidence that information is complete or that data is accurate. Completeness and accuracy are essential activities of the DSS analyst. These attributes of information are not guaranteed because the data is in a DSS. DSS need to be designed to positively impact decision behavior for an individual or for a group. In Decision Support Systems it is hard to support qualitative issues; managers are encouraged to place the most emphasis on numbers; also DSS usually neglect political issues; and DSS users may not explicitly consider their values and use their general knowledge and common sense.
Simon (1965) argued that we need to understand the thought process that computerized decision aids will support if we are to create effective support systems. Our understanding of decision and thought processes remains incomplete and we need to be especially cautious in assessing when and how a DSS will be used prior to its design and implementation.