Intelligent Support Systems.

Answer: Intelligent support systems (ISS) are systems that facilitate decision requiring the use of knowledge, intuition and experience.

Systems that fall into this category are:

A. Decision support systems (DSS):
Decision support systems (DSS) a re interactive, well-integrated systems that provide managers with data, tools and models to facilitate semi-structured decisions or tactical decisions. Or Decision support systems are computerized systems that provide managers with internal and external data and decision making models that facilitate semi-structured decision making.  As you may recall, a tactical decision is partly structured and partly unstructured.

An example of tactical decision is bidding on a contract. Part of the task is structured—for example, considering standard operational costs and overheads—while part is unstructured, since the bidder must take into account the way competitors may bid on the same contract. DSS provide the decision maker with a set of tools and techniques that can be “mixed and matched” in creative ways to solve semi-structured problems.

How a DSS works?
A DSS accesses and processes large volumes of internal and external data and integrates them with various decision-making models.

• Internal data are often downloaded form the TPS or form other information systems. (Downloading means moving data from a larger system, such as a mainframe, to a smaller system such as a PC).

• External data may come a wide variety of sources, such as the Dow Jones, The Wall street Journal, or other external databases maintained by government agencies or private companies.

Analysis of DSS

• The alternative generated by a decision maker can be further analyzed using “what if” analysis, which assesses the impact of changes, made to input or output variables. For example, producing pricing is a complex decision that takes into account a number of internal factors such as material costs, production costs, labor costs, and external factors such as competitor pricing and product demand.

• A DSS can present a manager with different pricing alternatives and help answer “what if” questions such as these; “what if the price of raw materials increases by 3.6% a year?” “What if demand for a product increases by 10%?” “What if a competitor reduces its price for a similar product by 20%?”

• A DSS also allows managers to perform goal-seeking, which specifies the actions a manager should take in order to accomplish a certain goal. For example, suppose the goal of the company is to increase sales of product A by 10%. A DSS can help a marketing manager decide on the course of action to take regarding operating costs, product pricing, advertising and other related issues in order to achieve the goal.

• Group decision support system: GDSS are a set of interactive, well-integrated systems that facilitate and support group decision making. DSS is a tool that facilitates the process of decision making more than simply solving a given problem.

B. Executive information systems (EIS):
A second type of ISS, used primarily by top management, is the Executive information system (EIS). It is a user-friendly, interactive system, designed to meet the information needs of top management engaged in long-range planning, crisis management and other strategic decisions.

The primary difference between DSS and an EIS is that the goal of an EIS is not so much to generate alternatives for a given problem as it is to integrate data from different sources and present it in a useful format to the decision maker. An EIS is user-friendly and almost intuitive to use; it has excellent menus and graphic capabilities. Another special characteristic of an EIS is its drill-down capability, which is the ability of the system to provide information at any level of detail desired by the decision maker. For example, the CEO of a company may want a breakdown of sales figures on a regional basis or on a store-wide basis. The drill down facility can provide both. A drill-down is a feature that allows the user to get information at any desired level of detail from an EIS.

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Characteristics of DSS and EIS:

• DSS and EIS are intelligent support systems designed to provide middle and top managers with information necessary to make decisions that require intuition and judgment.

• Both DSS and EIS are intuitive, interactive, user-friendly systems that augment the decision-making capabilities of a manager. They are menu-driven and often have excellent color and graphic capabilities.

• Both systems use internal and external data to solve problems. Managers at this level tend to rely more on external data than on internal data.

• A DSS also uses various decision-making models to provide managers with alternative solutions to a given problem. An EIS provides managers with information integrated from a variety of sources.

• Both systems are equipped with decision-making tools such as “what-if” analysis and goal seeking. In addition to these tools an EIS is equipped with drill-down capabilities.

• A DSS can support both individual decision making and group decision making. Decision support systems that support group decision making are referred to as group decision support systems. (GDSS).

C. Artificial intelligence and expert systems (AIES):
Artificial Intelligence: The third type of ISs is artificial intelligence (AI), a branch of computer science whose goal is to design and develop computer systems that emulate human intelligence. AI attempts to endow machines with capabilities and characteristics that would indicate intelligence if found in a human being.

Expert systems: Expert systems (ES) are a branch of AI. It is software designed to capture the knowledge and problem-solving skills of a human expert. Expert systems are good solving semi-structured and unstructured problems and can solve problems that require theoretical knowledge and practical experience. More important, they help organizations acquire and retain knowledge that is vital to the competitiveness and the success of the company.

An expert system has three main components:

• A knowledge base: The knowledge base, as its name implies, serves as a storehouse of knowledge and experience gathered from experts in a given field, including facts, theorems, and principles related to a given area of knowledge or field of study. For example, an expert car mechanic would be the source of knowledge for an expert system designed to solve car problems.

•  An inference engine: The second component of an expert system is the inference engine, which uses rules of behavior and interrelationships between different pieces of knowledge to solve the given problem. It selects the appropriate knowledge, applies it to the problem and resolves any conflicts that may arise in the process.

•  A user interface: The user interface consists to tools, such as menus, graphics, and explanation facilities that help users to interact with system. Of particular importance is the explanation module in an expert system, which provides explanations as to how a problem was solved and how the knowledge was used to solve the problem.

Characteristics of expert systems:

• An expert system is a program designed to capture the knowledge and problem solving skills of a human expert. Expert systems are a branch of artificial intelligence.

• Expert systems handle problems that require knowledge, intuition and judgment.

• Expert systems, unlike DSS and EIS, can replace decision makers.

• An expert system has three main components; the knowledge base, which stores the knowledge, the inference engine, which stores the reasoning principles used by the expert, and the user interface which allows the user to interact with the system.

• Expert systems are not designed for any one level of management; their primary function is to disseminate expertise throughout the organization.