MIS Decision Support System, Knowledge Management System

Decision support systems (DSS) are interactive software-based systems intended to help managers in decision-making by accessing large volumes of information generated from various related information systems involved in organizational business processes, such as office automation system, transaction processing system, etc.

DSS uses the summary information, exceptions, patterns, and trends using the analytical models. A decision support system helps in decision-making but does not necessarily give a decision itself. The decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.

Programmed and Non-programmed Decisions

There are two types of decisions – programmed and non-programmed decisions.

Programmed decisions are basically automated processes, general routine work, where:

• These decisions have been taken several times.
• These decisions follow some guidelines or rules.

For example, selecting a reorder level for inventories, is a programmed decision.

Non-programmed decisions occur in unusual and non-addressed situations, so:

• It would be a new decision.
• There will not be any rules to follow.
• These decisions are made based on the available information.
• These decisions are based on the manger’s discretion, instinct, perception and judgment.

For example, investing in a new technology is a non-programmed decision.

Decision support systems generally involve non-programmed decisions. Therefore, there will be no exact report, content, or format for these systems. Reports are generated on the fly.

Attributes of a DSS

• Adaptability and flexibility
• High level of Interactivity
• Ease of use
• Efficiency and effectiveness
• Complete control by decision-makers
• Ease of development
• Extendibility
• Support for modeling and analysis
• Support for data access

Standalone, integrated, and Web-based

Characteristics of a DSS

Support for decision-makers in semi-structured and unstructured problems.

• Support for managers at various managerial levels, ranging from top executive to line managers.
• Support for individuals and groups. Less structured problems often requires the involvement of several individuals from different departments and organization level.
• Support for interdependent or sequential decisions.
• Support for intelligence, design, choice, and implementation.
• Support for variety of decision processes and styles.
• DSSs are adaptive over time.

Benefits of DSS

• Improves efficiency and speed of decision-making activities.
• Increases the control, competitiveness and capability of futuristic decision-making of the organization.
• Facilitates interpersonal communication.
• Encourages learning or training.
• Since it is mostly used in non-programmed decisions, it reveals new approaches and sets up new evidences for an unusual decision.
• Helps automate managerial processes.

Components of a DSS

Following are the components of the Decision Support System:

• Database Management System DBMSDBMS: To solve a problem the necessary data may come from internal or external database. In an organization, internal data are generated by a system such as TPS and MIS. External data come from a variety of sources such as newspapers, online data services, databases financial,marketing,humanresourcesfinancial,marketing,humanresources.
• Model Management System: It stores and accesses models that managers use to make decisions. Such models are used for designing manufacturing facility, analyzing the financial health of an organization, forecasting demand of a product or service, etc.

Support Tools: Support tools like online help; pulls down menus, user interfaces, graphical analysis, error correction mechanism, facilitates the user interactions with the system.

Classification of DSS

There are several ways to classify DSS. Hoi Apple and Whinstone classifies DSS as follows:

Text Oriented DSS: It contains textually represented information that could have a bearing on decision. It allows documents to be electronically created, revised and viewed as needed.

• Database Oriented DSS: Database plays a major role here; it contains organized and highly structured data.
• Spreadsheet Oriented DSS: It contains information in spread sheets that allows create, view, modify procedural knowledge and also instructs the system to execute self-contained instructions. The most popular tool is Excel and Lotus 1-2-3.
• Solver Oriented DSS: It is based on a solver, which is an algorithm or procedure written for performing certain calculations and particular program type.
• Rules Oriented DSS: It follows certain procedures adopted as rules.
• Rules Oriented DSS: Procedures are adopted in rules oriented DSS. Export system is the example.
• Compound DSS: It is built by using two or more of the five structures explained above.

Types of DSS

Following are some typical DSSs:

• Status Inquiry System: It helps in taking operational, management level, or middle level management decisions, for example daily schedules of jobs to machines or machines to operators.
• Data Analysis System: It needs comparative analysis and makes use of formula or an algorithm, for example cash flow analysis, inventory analysis etc.
• Information Analysis System: In this system data is analyzed and the information report is generated. For example, sales analysis, accounts receivable systems, market analysis etc.
• Accounting System: It keeps track of accounting and finance related information, for example, final account, accounts receivables, accounts payables, etc. that keep track of the major aspects of the business.
• Model Based System: Simulation models or optimization models used for decisionmaking are used infrequently and creates general guidelines for operation or management.

Knowledge Management System (KMS)

All the systems we are discussing here come under knowledge management category. A knowledge management system is not radically different from all these information systems, but it just extends the already existing systems by assimilating more information.

As we have seen, data is raw facts, information is processed and/or interpreted data, and knowledge is personalized information.

What is Knowledge?

• Personalized information
• State of knowing and understanding

An object to be stored and manipulated

• A process of applying expertise
• A condition of access to information
• Potential to influence action

Sources of Knowledge of an Organization

• Intranet
• Data warehouses and knowledge repositories
• Decision support tools
• Groupware for supporting collaboration
• Networks of knowledge workers
• Internal expertise

Definition of KMS

A knowledge management system comprises a range of practices used in an  organization to identify, create, represent, distribute, and enable adoption  to insight and experience. Such insights and experience comprise knowledge,  either embodied in individual or embedded in organizational processes and  practices.

Purpose of KMS

• Improved performance
• Competitive advantage
• Innovation
• Sharing of knowledge
• Integration
• Continuous improvement by:

o Driving strategy o Starting new lines of business o Solving problems faster o Developing professional skills o Recruit and retain talent

Activities in Knowledge Management

• Start with the business problem and the business value to be delivered first.
• Identify what kind of strategy to pursue to deliver this value and address the KM problem.
• Think about the system required from a people and process point of view.
• Finally, think about what kind of technical infrastructure are required to support the people and processes.
• Implement system and processes with appropriate change management and iterative staged release.

Level of Knowledge Management