The figure provides an overview of decision making along with two dimensions i.e. problem structure and the nature of the decision.
The figure below
The first dimension is problem structure, where decision-making processes fall along a continuum ranging from highly structured to highly unstructured (see the left column in Figure).
Structured decisions deal with routine and repetitive problems for which standard solutions exist, such as inventory control.
In a structured decision, the first three phases of the decision process-intelligence, design, and choice-are laid out in a particular sequence, and the procedures for obtaining the best (or at least a good enough) solution are known.
Two basic criteria used to evaluate proposed solutions are minimizing costs and maximizing profits. These types of decisions are candidates for decision automation.
At the other extreme of complexity are unstructured decisions. These decisions are intended to deal with “fuzzy,” complex problems for which there are no cut-and-dried solutions.
An unstructured decision is one in which there is no standardized procedure for carrying out any of the three phases.
In making such a decision, human intuition and judgment often play an important role.
Typical unstructured decisions include planning new service offerings, hiring an executive, and choosing a set of research and development (R&D) projects for the coming year.
Although BI cannot make unstructured decisions, it can provide information that assists decision makers.
Located between structured and unstructured decisions are semistructured decisions, in which only some of the decision process phases are structured.
Semistructured decisions require a combination of standard solution procedures and individual judgment.
Examples of semistructured decisions are evaluating employees, setting marketing budgets for consumer products, performing capital acquisition analysis, and trading bonds.
The Nature of Decisions
The second dimension of decision support deals with the nature of decisions. All managerial decisions fall into one of three broad categories:
- Operational control: Executing specific tasks efficiently and effectively.
- Management control: Acquiring and using resources efficiently in accomplishing organizational goals.
- Strategic planning: The long-range goals and policies for growth and resource allocation.
These categories are displayed along the top row of Figure. Note that strategic decisions define the context in which management control decisions are made. In turn, management control decisions define the context in which operational control decisions are made.
The Decision Matrix
The three primary classes of problem structure and the three broad categories of the nature of decisions can be combined in a decision-support matrix that consists of nine cells, as diagrammed in Figure.
Lower-level managers usually perform tasks in cells 1, 2, and 4. The tasks in cells 3, 5, and 7 are usually the responsibility of middle managers and professional staff. Finally, tasks in cells 6, 8, and 9 are generally carried out by senior executives.
Computer Support for Structured Decisions
Examples of computer support that might be used for the nine cells in the matrix are displayed in the right-hand column and the bottom row of Figure.
Structured and some semistructured decisions, especially of the operational and management control type, have been supported by computers since the 1950s.
Decisions of this type are made in all functional areas, but particularly in finance and operations management.
Problems that lower-level managers encounter on a regular basis typically have a high level of structure.
Examples are capital budgeting (e.g., replacement of equipment), allocating resources, distributing merchandise, and controlling inventory.
For each type of structured decision, prescribed solutions have been developed, which often include mathematical formulas.
This approach is called management science or operations research, and it also is executed with the aid of computers.