ch3 Decision Support Systems Concepts, Methodologies, and Technologies

DSS Classifications (DSS Categories)

(1) institutional and ad hoc DSS (2) the personal, group, and organizational support (3) individual support system versus GSS (4) custom-made systems versus ready-made systems.

MBMS

1- Model creation, using programming languages, DSS tools and/or subroutines, and other building blocks 2- Generation of new routines and reports 3- Model updating and changing 4- Model data manipulation

The key characteristics and capabilities of DSS

1- SemiStructured or unstructured problems: Support for decision-makers, mainly in semistructured and unstructured situations, by bringing together human judgment and computerized information. Such problems cannot be solved (or cannot be solved conveniently) by other computerized systems or through the use of standard quantitative methods or tools. Generally, these problems gain structure as the DSS is developed. Even some structured problems have been solved by DSS. 2- Support managers at all levels: Support for all managerial levels, ranging from top executives to line managers. 3-Support individuals and groups: Support for individuals as well as groups. Less-structured problems often require the involvement of individuals from different departments and organizational levels or even from different organizations. DSS supports virtual teams through collaborative Web tools. DSS has been developed to support individual and group work, as well as to support individual decision making and groups of decision-makers working somewhat independently. 4-Interdependent or sequential decisions: Support for interdependent and/or sequential decisions. The decisions may be made once, several times, or repeatedly. 5-support intelligence, design, choice, and implementation: Support in all phases of the decision-making process: intelligence, design, choice, and implementation. 6-Support variety of decision processes and styles 7-Adaptable and flexible: The decision-maker should be reactive, able to confront changing conditions quickly, and able to adapt the DSS to meet these changes. DSS is flexible, so users can add, delete, combine, change, or rearrange basic elements. They are also flexible in that they can be readily modified to solve other, similar problems 8- Interactive, ease of use: User-friendliness, strong graphical capabilities, and a natural language interactive human-machine interface can greatly increase the effectiveness of DSS. Most new DSS applications use Web-based interfaces or mobile platform interfaces. 9-Effectiveness and efficiency: Improvement of the effectiveness of decision making (e.g., accuracy, timeliness, quality) rather than its efficiency (e.g., the cost of making decisions). When DSS is deployed, decision making often takes longer, but the decisions are better. 10-Humans control the process: The decision-maker has complete control over all steps of the decision-making process in solving a problem. A DSS specifically aims to support, not to replace, the decision-maker. 11-Ease of development by end-users: End users are able to develop and modify simple systems by themselves. Larger systems can be built with assistance from the information system (IS) specialists. Spreadsheet packages have been utilized in developing simpler systems. OLAP and data mining software, in conjunction with data warehouses, enables users to build fairly large, complex DSS. 12-Modeling and analysis Models are generally utilized to analyze decision-making situations. The modeling capability enables experimentation with different strategies under different configurations. 13-Data access Access is provided to a variety of data sources, formats, and types, including GIS, multimedia, and object-oriented data 14-Stand-alone, integration, and Web-based The DSS can be employed as a stand-alone tool used by an individual decision-maker in one location or distributed throughout an organization and in several organizations along the supply chain. It can be integrated with other DSS and/ or applications, and it can be distributed internally and externally, using networking and Web technologies.

Holsapple and Whinston's Classification

1- The text-oriented DSS 2-The database-oriented DSS. 3-The spreadsheet-oriented DSS 4-The solver-oriented DSS 5-The rule-oriented DSS (include most knowledge-driven DSS 6-data mining, management, and ES applications) 7-The compound DSS

Institutional DSS

A DSS that handles situations or decisions that occur more than once, usually several times per year or more. An institutional DSS is used repeatedly and refined over the years. example: is a portfolio management system (PMS), which has been used by several large banks for supporting investment decisions. It is important to remember that an institutional DSS may not be used by everyone in an organization; it is the recurring nature of the decision-making problem that determines whether a DSS is institutional versus ad hoc.

Web analytics

Is an approach to using business analytics tools on real-time web information to assist decision making. most application is related to e-commerce, especially CRM. most have been in SCM.

Model directory

Its role is similar to that of database It's a catalog of all the models and other software in the model base Contains definitions and its main function to answer questions about the availability and capabilities of the models

Custom-Made Systems / Ready-Made Systems

Many DSS are custom made for individual users and organizations. However, a comparable problem may exist in similar organizations. For example, hospitals, banks, and universities share many similar problems. Similarly, certain nonroutine problems in a functional area (e.g., finance, accounting) can repeat themselves in the same functional area of different areas or organizations. Therefore, it makes sense to build generic DSS that can be used (sometimes with modifications) in several organizations. Such DSS is called ready-made and are sold by various vendors (e.g., Cognos, MicroStrategy, Teradata). Essentially, the database, models, interface, and other support features are built-in: Just add an organization's data and logo. The major OLAP and analytics vendors provide DSS templates for a variety of functional areas, including finance, real estate, marketing, and accounting. The number of ready-made DSS continues to increase because of their flexibility and low cost. They are typically developed using Internet technologies for database access and communications, and Web browsers for interfaces. They also readily incorporate OLAP and other easy-to-use DSS generators. The DSS exhibits the traits of ad hoc and institutional systems and also of custom and ready-made systems. Several ERP, CRM, knowledge management (KM), and SCM companies offer DSS applications online. These kinds of systems can be viewed as a ready-made, although typically they require modifications (sometimes major) before they can be used effectively.

Model execution, integration and command

Model execution is the process of controlling the actual running of the model Model integration involves combining the operations of several models when needed or integrating the DSS with other applications A model command processor is used to accept and interpret modeling instructions from the user interface component and route them to the model execution or model integration functions

Personal, Group, Organizational support

Personal: here the focus is an individual user performing an activity in a discrete task or decision. the task is fairly independent of other tasks. Group: the focus is on a group of people. all of them are engaged in a separate but interrelated task. example: the finance department in which one DSS can serve many employees working in preparing budget. if the use of ad hoc it will be group support DSS. Organizational support: the focus on an organizational task or activity involving a sequence of operations, different functional areas at a different location and massive resources.

DSS Description

The early definitions of a DSS identified it as a system intended to support managerial decision makers in semistructured and unstructured decision situations. DSS were meant to be adjuncts to decision makers, extending their capabilities but not replacing their judgment. They were aimed at decisions that required judgment or at decisions that could not be completely supported by algorithms. Not specifically stated but implied in the early definitions was the notion that the system would be computer based, would operate inter- actively online, and preferably would have graphical output capabilities, now simplified via browsers and mobile devices.

Knowledge Base Management Subsystem

The knowledge-based management subsystem can support any of the other subsystems or act as an independent component. It provides intelligence to augment the decision mak- er's own. It can be interconnected with the organization's knowledge repository (part of a knowledge management system [KMS]), which is sometimes called the organizational knowledge base. Knowledge may be provided via Web servers. Many artificial intelligence methods have been implemented in Web development systems such as Java and are easy to integrate into the other DSS components. Incorporation of intelligence and expertise Because many semistructured and unstructured problems are so complex Knowledge components: Expert systems, Knowledge management systems, Neural networks, Intelligent agents, Fuzzy logic, Case-based reasoning systems, and so on

Model Management Subsystem

The model management subsystem is the component that includes financial, statistical, management science, or other quantitative models that provide the system's analytical capabilities and appropriate software management. Modeling languages for building custom models is also included. This software is often called a model base management elements: 1-model base 2-MBMS 3-Modeling language 4-model directory 5-model execution, integration, command processor

User Interface Subsystem

The user communicates with and commands the DSS through the user interface subsystem. The user is considered part of the system. Researchers assert that some of the unique contributions of DSS are derived from the intensive interaction between the computer and the decision-maker. The Web browser provides a familiar, consistent graphical user interface (GUI) structure for most DSS. For locally used DSS, a spreadsheet also provides a familiar user interface. User Interface (Dialog) Subsystem: The term User Interface covers all aspects of communication between a user and the DSS or any MSS It includes H\W and S\W and all factors that deal with ease to use, accessibility, and human-machine interaction. User Interface Management System (UIMS) Software(Composed of several programs) that managed the user interface subsystem the User Interface Process DSS User Interfaces Access provided through Web browsers including ( Voice input, portable devices) Web browsers provide a portal or dashboard to access the system

Decision support system configuration

based on management-decision situation, specific technologies used for support DSS has three basic components: 1-data 2-models 3-interface + 4-knowledge Each component has several variations; are typically deployed online, Managed by a commercial of custom software Typical types: Model-oriented DSS Data-oriented DSS

Predictive Analytics

business analytics methods of forecasting problems and opportunities rather than simply reporting them as they occur. advanced forecasting and simulation models.

model base

contain routine and special tactical, financial, forecasting management science and other quantitative models that provide analysis capabilities in DSS. the ability to run invoke, change, combine and inspect models is a key DSS capabilities that make it different. it divided into 4 : strategic model: to support top managers. potential app includes e-commerce venture, developing a corporate objective, planning for acquisition, selecting plant location, analyzing the environmental impact, and budget. example: the southwest airline, FedEx tactical models: used by middle managers to assist in allocating the organization resources. webserver selection, labor requirement planning, sales promotion, plant layout, capital budgeting. only use as a subsystem like in the accounting department. they only use it for 1m to 2y use both internal and external data operational models: to support line managers from day to day activity. E.g., e-commerce transaction acceptance (e.g., purchases), approval of personal loans, production scheduling, inventory control, maintenance planning. only internal data. bank in giving loans. Analytic models: Used to perform analysis on data They include statistical models, management science models, data mining algorithms, financial models and more, They can be integrated with others They can be classified by functional areas or by discipline Model building blocks and Routines The model base can contain model building blocks and routines such as the functions and add-ins in excel. Modeling Tools For semistructured and unstructured problems: Programming tools and languages used to customize models such as .Net Framework, C++, Java For small and medium-sized DSS or less complex ones: Excel usually used.

ad hoc DSS

deal with specific problems that are usually neither anticipated nor recur- ring. Ad hoc decisions often involve strategic planning issues and sometimes management control problems Justifying a DSS that will be used only once or twice is a major issue in DSS development. Countless ad hoc DSS applications have evolved into institutional. DSS Either the problem recurs and the system is reused or others in the organization have similar needs that can be handled by the formerly ad hoc DSS.

Individual support system versus group support system (GSS)

group support system (GSS) used to be in the same room at the same time but now it a croce the world like blackboard

Data Management Subsystem

includes a database that contains relevant data for the situation and is managed by software called the database management system (DBMS).2 The data management subsystem can be interconnected with the corporate data warehouse, a repository for corporate relevant decision-making data. Usually, the data are stored or accessed via a database Web server. DSS database DBMS Data directory Query facility

Business Intelligence (BI)

systems monitor the situation and identify problems and opportunities using analytical methods. reporting is the most importing feature in BI. the user most identify if the situation needs attention after that they apply analytical tools. focus on reporting and identifying problems by scanning data stored in data warehouses (BI called business analytics systems Although some may run locally as a spreadsheet, both DSS and BI use Web

business analytics :

the use of models and data to improve an organization's performance or competitive posture. the focus of business analytics is the use of models even if it buried deep inside the system. extremely effective models are rarely used because managers and analysts don't know how and when to use models to describe and analyze a situation. data mining and OLAP have models in them but they are not well understood.

DSS application

why is DSS built? - to support the solution for a certain problem and evaluate an opportunity. have their own database and used to solve a problem or a set of problems. this is the key difference between DSS AND BI ---------------------------- DSS is an approach (methodology) to support decision making. it uses interactive, flexible, adaptable CBIS it was developed to support the solution of unstructured problems. developed (by end user) for supporting the solution to a specific nonstructured management problem it uses data, models, and knowledge. 1- use data, to provide a user-friendly interface and incorporate decision-maker insights. 2- it uses models, developed by end-users through an interactive and iterative process. 3- use knowledge, to support all phases of decision making. incorporate the decision maker's own insights the DSS can be a web-based used by multiple users or a single user. Although some may run locally as a spreadsheet, both DSS and BI use Web