DSS Lectures - Decision Support Systems Explained PDF

Making Decisions in the Decision Support Systems Environment - Activities in the Decision Support Systems Environment. - The Decision Making process. - Information Use for strategic management. Learning Objectives Learn the basic concepts of decision making. Understand systems app...

Making Decisions in the Decision Support Systems Environment - Activities in the Decision Support Systems Environment. - The Decision Making process. - Information Use for strategic management. Learning Objectives Learn the basic concepts of decision making. Understand systems approach. Learn Simon’s four phases of decision making. Understand the concepts of rationality and bounded rationality. Differentiate between making a choice and establishing a principle of choice. Learn which factors affect decision making. Learn how DSS supports decision making in practice. Decision Making Process of choosing amongst alternative courses of action for the purpose of attaining a goal or goals. The four phases of the decision process are: – Intelligence – Design – Choice – implementation Systems Structure – Inputs – Processes – Outputs – Feedback from output to decision maker – Separated from environment by boundary – Surrounded by environment Figure 1: Structure of the System 1  Figure 2: The System and Its Environment System Types Closed system – Independent – Takes no inputs – Delivers no outputs to the environment Open system – Accepts inputs – Delivers outputs to environment Models Used for DSS Iconic – Small physical replication of system – Iconic model may be three-dimensional, such as that of an airplane, car, bridge, or production line. Analog – Behavioral representation of real system but does not look like it. – Models of this type are usually two-dimensional charts or diagrams. Some examples include: Organization charts that depict structure, authority, and responsibility relationships ‫ والمسؤولية‬،‫ السلطة‬،‫رسوم البيانية للمنظمة التي توضح العالقات بين الهيكل‬ Maps on which different colors represent objects, such as bodies of water or mountains ‫ مثل المسطحات المائية أو الجبال‬،‫خرائط الملونة لتمثل الكائنات‬ 2  Stock market charts that represent the price movements of stocks ‫الرسوم البيانية لسوق األوراق المالية التي تمثل حركة أسعار األسهم‬ Blueprints of a machine or a house ‫مخططات اآللة أو المنزل‬ Quantitative (mathematical) – Most DSS analyses are performed numerically with mathematical or other quantitative models. Phases of The Decision-Making Process Simon’s original three phases: – Intelligence – Design – Choice He added fourth phase later: – Implementation Book adds fifth stage: – Monitoring Figure 3: Phases of The Decision-Making Process Intelligence Phase Searching for conditions that call for decisions: Scan the environment Analyze organizational goals Collect data Identify problem Categorize problem – Programmed and non-programmed – Decomposed into smaller parts Assess ownership and responsibility for problem resolution ‫ويتم‬.‫يشمل الذكاء مسحا للبيئة وتنفيذا جلملة من األنشطة اليت تستهدف حتديد املشكلة وتعيني أسباهبا وتصنيف املشكلة طبقا لدرجة هيكلتها‬.‫كذلك جتزأة املشكلة الواحدة املعقدة إىل مشاكل فرعية للمساعدة يف حل املشكلة املعقدة عن طريق تبسيطها‬ 3  Design Phase Inventing, developing, analyzing solutions: Develop alternative courses of action Analyze potential solutions Create model Test for feasibility Validate results Select a principle of choice – Establish objectives – Incorporate into models – Risk assessment and acceptance – Criteria and constraints.‫وتشمل إنتاج وتطوير وحتليل احللول البديلة املمكنة وتتضمن كذلك أنشطة مثل فهم املشكلة واختيار جدوى احللول وبناء النموذج اخلاص باملشكلة‬ Choice Phase Selecting a course of action Principle of choice – Describes acceptability of a solution approach Normative Models – Optimization Effect of each alternative – Rationalization More of good things, less of bad things Courses of action are known quantity Options ranked from best to worse – Suboptimization Decisions made in separate parts of organization without consideration of whole.‫وتشمل البحث والتقومي والتوصية حبل مناسب للنموذج وبالتايل تنفيذ القرار ومتابعة النتائج وحتليل هذه النتائج عن طريق نظام التغذية العكسية‬ Implementation Phase Adapting the selected course of action; Figure 4: Phases of The Decision-Making Process and Problem Solving 4 Classification of Problems The decision-making process may be range from highly structured (programmed - with standard solution methods, because is possible to abstract, analyze, and classify into specific categories for which we have a model and a solution – management science (MS) / operation research (OR) ) to highly unstructured (non-programmed- fuzzy, complex problems there are no cut and dried solution methods). Definitions: Nature of problem determines the approach to decision making to be followed to solve it. There are three – An unstructured problem: all phases are unstructured, – A structured problem: all phases are structured, the procedures for obtaining the best solution are known, – Semi structured problem: has structured and also unstructured phases. Decision Support Frameworks Type of Control Type of Decision: Operational Control Managerial Control Strategic Planning Structured Accounts Budget analysis, Investments, (Programmed) receivable, short-term warehouse locations, accounts payable, forecasting, distribution centers order entry personnel reports Semistructured Production Credit evaluation, Mergers and scheduling, budget preparation, acquisitions, new inventory control project scheduling, product planning, rewards systems compensation, QA, HR policy planning Unstructured Buying software, Negotiations, R&D planning, (Unprogrammed) approving loans, recruitment, technology help desk hardware development, social purchasing responsibility plans 5  Technologies for Decision-Making Processes Type of Decision Technology Support Needed Structured MIS, Management Science Models, (Programmed) Transaction Processing Semistructured DSS, KMS, GSS, CRM, SCM Unstructured GSS, KMS, ES, Neural networks (Unprogrammed) Technology Support Based on Anthony’s Taxonomy Type of Control Operational Managerial Strategic Control Control Planning Technology MIS, Management GSS, CRM, Support Needed Management Science, DSS, ES, EIS, ES, neural Science EIS, SCM, CRM, networks, KMS GSS, SCM 6  Introduction to Decision Support Systems - Characteristics. - Application of Decision Support Systems. - Capabilities of Decision Support Systems. - Benefits of Using Decision Support Systems. - Evaluating the Success/Failure of Decision Support Systems. Learning Objectives Understand DSS configurations. Learn characteristics and capabilities of DSS. Understand DSS components. Describe structure of DSS components. Understand how DSS and the Web interact. Learn the role of the user in DSS. Understand DSS hardware and integration. Learn DSS configurations. 1) Decision Support System Decision Support Systems (DSS) are a specific class of computerized information system that supports business and organizational decision-making activities. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions. 2) Why DSS? Because A DSS is a methodology that supports decision-making. It is: – Flexible; – Adaptive; – Interactive; – GUI-based; – Iterative; and – Employs modeling. 7 3) Characteristics. Figure 5: Characteristics and capabilities of DSS 4) Business Intelligence Proactive Accelerates decision-making Increases information flows Components of proactive BI: – Real-time warehousing – Exception and anomaly detection – Proactive alerting with automatic recipient determination – Seamless follow-through workflow – Automatic learning and refinement 5) Components Of DSS There are three fundamental components of DSS : – Data Base Management System (DBMS) – Model Based Management System (MBMS) – Dialog Generation & Management System (DGMS) – User Interface – Knowledge Management and organizational knowledge base. 8 6) Architecture Of DSS Figure 6: Architecture of DSS Figure 7: A schematic View of DSS 9 6.1) Data Management Subsystem Components: – Database – Database management system – Data directory – Query facility Figure 8: The Structure Of Data Management Subsystem Database Interrelated data extracted from various sources, stored for use by the organization, and queried: – Internal data, usually from TPS – External data from government agencies, trade associations, market research firms, forecasting firms – Private data or guidelines used by decision-makers Database Management System Extracts data Manages data and their relationships Updates (add, delete, edit, change) Retrieves data (accesses it) Queries and manipulates data Employs data dictionary 11 Data Directory Catalog of all data – Contains data definitions – Answers questions about the availability of data items – Source – Meaning – Allows for additions, removals, and alterations 6.2) Model Management Subsystem Components: – Model base – Model base management system – Modeling language – Model directory – Model execution, integration, and command processor Models  Strategic – Supports top management decisions  Tactical – Used primarily by middle management to allocate resources  Operational – Supports daily activities  Analytical – Used to perform analysis of data Model Base Management System  Functions: – Model creation – Model updates – Model data manipulation – Generation of new routines  Model directory: – Catalog of models – Definitions Model Management Activities  Model execution – Controls running of model  Model command processor – Receives model instructions from user interface – Routes instructions to MBMS or module execution or integration functions  Model integration – Combines several models’ operations 11 6.3) User Interface System Figure 9: Schematic View of the User Interface User Interface Management System  GUI  Natural language processor  Interacts with model management and data management subsystems  Examples – Speech recognition – Display panel – Tactile interfaces – Gesture interface 6.4) Knowledge-Based Management System Expert or intelligent agent system component Complex problem solving Enhances operations of other components May consist of several systems Often text-oriented DSS 7) DSS Hardware De facto standard Web server with DBMS: – Operates using browser – Data stored in variety of databases – Can be mainframe, server, workstation, or PC – Any network type – Access for mobile devices 12 8) DSS Classifications Alter – Extent to which outputs can directly support or determine the decision – Data oriented or model oriented Holsapple and Whinston – Text oriented, database oriented, spreadsheet oriented, solver oriented, rule oriented, or compound Intelligent Donovan and Madnick – Institutional – Problems of recurring nature Ad hoc – Problems that are not anticipated or are not repetitive Hackathorn and Keen – Personal support, group support, or organizational support GSS v. Individual DSS – Decisions made by entire group or by lone decision maker Custom made v. vendor ready made – Generic DSS may be modified for use o Database, models, interface, support are built in o Addresses repeatable industry problems o Reduces costs 13 9) Web and DSS Data collection Communications Collaborations Download capabilities Run on Web servers Simplifies integration problems Increased usability features 14 10) Evaluating the Success/Failure of Decision Support Systems 10.1 ) Decision Making Under Certainty - Assume complete Knowledge available (deterministic environment) - Typically for structured problems with short time horizons 10.2 ) Decision Making Under Risk (Risk Analysis) - Probabilistic or stochastic decision situation - Must consider several possible outcomes for each alternative, each with a probability. - Long-run probabilities of the occurrences of the given outcomes are assumed known or estimated. - Assess the (calculated) degree of risk associated with each alternative. Risk Analysis: Calculate the expected value of each alternative Select the alternative with the best expected value. 10.3 ) Decision Making Under Uncertainty - Several outcomes possible for each course of action. - But the decision maker does not know, or cannot estimate the probability of occurrence. - More difficult – insufficient information. - Assessing the decision maker's (and/or the organizational) attitude toward risk. 10.4 ) Measuring Outcomes - Goal attainment - Maximize profit. - Minimize cost. - Customer satisfaction level (minimize number of complaints). 10.5 ) Other Important Decision Making Issues - Personality types. - Gender. - Human cognition. - Decision styles. 15 11) Decision Style - The manner in which decision makers think and react to problems. - Varies from individual to individual and from situation to situation. Types of Decision Styles Directive: Low tolerance of context ambiguity. Does not requires large volumes of information and verbal communication is preferable on writing methods for managers. Analytical: High tolerance of context ambiguity. Does not requires great values of information. Not quick in taking decision. Conceptual: The "people person" and they tend to be thinkers rather than doers. Behavioural.: It requires low amount of input data and demonstrate a short-range vision. 12) The Decision makers: 12.1) Individuals - May still have conflicting objectives. - Decisions may be fully automated. ‫اإلستخدام بواسطة شخص واحد‬ Software ‫ النظم الفرعية‬ ‫ النظام الفرعي إلدارة البيانات‬- ‫ النظام الفرعي إلدارة النماذج‬- ‫ النظام الفرعي إلدارة الحوار المبني مع المستفيد‬- Hardware ‫ األجهزة‬ 16  ‫‪12.2) Groups‬‬ ‫‪-‬‬ ‫‪Most major decision made by groups.‬‬ ‫‪-‬‬ ‫‪Conflicting objectives are common.‬‬ ‫‪-‬‬ ‫‪Variable size.‬‬ ‫‪-‬‬ ‫‪People from different departments.‬‬ ‫‪-‬‬ ‫‪People from different organizations.‬‬ ‫‪-‬‬ ‫‪The group decision-making process can be very complicated.‬‬ ‫نظم مساندة قرارات المجموعة ‪GDSS‬‬ ‫نظم مساندة القرارات الجماعية هي نظاما ً معتمداً على الحاسب يدعم مجموعات من األفراد المشمولين في مهمة أو‬ ‫أهدف مشتركة‪.‬االستخدام بواسطة مجموعة أشخاص على إحدى الصور التالية‪:‬‬ ‫‪.1‬استخدام النظام بواسطة مجموعة أشخاص موجودين في حيز واحد‪:‬‬ ‫– في غرفة واحدة يحدد الكل شخص واحد جهاز ‪PC‬‬ ‫– يتراوح عدد المستخدمين من ‪ 03 – 21‬جهازاً وتسمى غرفة القرار ‪ Decision Room‬وتحتوى الغرفة‬ ‫على نظام عرض وتكبير إلكتروني مرئي ‪.‬‬ ‫– تعد غرفة القرار إطاراً لمجموعة صغيرة من الناس تلتقي وجها لوجه‪.‬‬ ‫ً‬ ‫– المسهل شخصا ً مهمته االحتفاظ بحط سير المناقشة المناقشة في مسار طبيعي‬ ‫‪.2‬ربط األجهزة على شبكة إتصال محلية ‪Local Area Network LAN‬‬ ‫ حيث ال يجتمع أعضاء الفريق في مكان واحد وإنما يتواجد هؤالء في عدة أماكن ولكن في مجال‬ ‫جغرافي محدود ‪.‬مثل حرم الجامعة ومن مزايا هذه الطريقة ‪:‬إعطاء قدر أكبر من المرونة والحرية‬ ‫ألعضاء فريق العمل مثل فريق الجودة ‪ ،‬فريق التسويق‪.....‬‬ ‫ يدخل العضو تعليقاته عن طريق لوحة المفاتيح ويرى التعليقات الخاصة باألعضاء اآلخرين على‬ ‫الشاشة‬ ‫‪.3‬غرف القرارات ‪Decision Rooms‬‬ ‫ ر بط غرف قرارات متعددة مع بعضها البعض باستخدام تقنية اإلتصاالت الحديثة ( التليفونات ‪،‬‬ ‫خطوط الهاتف ) ويحدث الربط والتشبيك اإللكتروني بين غرف القرارات وبخاصة في المؤسسات‬ ‫الكبيرة التي تضم عدداً كبيراً من الفروع أو الشركات‪.‬‬ ‫‪.4‬شبكة القرار واسعة االنتشار ‪wide Area Deaision Network.‬‬ ‫ يتم اإلتصال بدون وجود غرف قرارات من خالل قنوات شبكة اإلتصاالت الواسعة التي قد تمتد على‬ ‫أقاليم جغرافية متباعدة ‪.‬‬ ‫‪13) Benefits of DSS‬‬ ‫‪-‬‬ ‫‪Improving personal efficiency.‬‬ ‫‪-‬‬ ‫‪Expediting problem solving.‬‬ ‫‪-‬‬ ‫‪Facilitating interpersonal communication especially GDSS.‬‬ ‫‪-‬‬ ‫‪Promoting learning or training.‬‬ ‫‪-‬‬ ‫‪Increasing organizational control.‬‬ ‫‪17‬‬  Developing Decision Support Systems 1) Strategies for DSS Analysis and Design There are two common strategies for DSS development: Programming a customized DSS: Either a general purpose language like C++ or a fourth-generation language like Delphi or Visual C# can be used. This allows for development of special interfaces between the DSS and other applications. Employing a DSS generator: These range from spreadsheets such as Excel—perhaps with some add-ins—or a more sophisticated generator such as MicroStrategy’s DSS Architect. 2) DSS Analysis and Design Process Several approaches can be applied to the process of DSS development: System development life cycle: employs a series of recursive phases each with its own inputs, activities and outputs. These phases begin with “Problem definition” then “Feasibility Analysis” and finish with “Implementation” and “Maintenance” Four phases I. Planning (1) identify business value, (2) analyze feasibility, (3) develop work plan, (4) staff project, and (5) control and direct project. II. Analysis (6) analyze problem, (7) gather information, (8) model process(es), and (9) model data. In the design phase: (10) design physical system, (11) design architecture, (12) design interface, (13) database and files, and (14) design interface(s). In the implementation phase: (15) construction, and (16) installation III. Design IV. Implementation - The primary advantage of SDLC is the structure and discipline it brings. - The major complaint about SDL is its rigidity since requirements in a DSS can change rapidly. 18  ROMC analysis: This approach asks the developer to understand representations (R), operations (O), memory aids (M), and controls (C). Representations include charts and tables. Functional category analysis: The developer identifies the specific functions necessary for a specific DSS from a broad list of available functions. Selection: locating knowledge within the knowledge base for use as input Aggregation: creation or derivation of summary statistics, such as averages or totals Estimation: creation of model parameter estimates Simulation: creation of knowledge about expected outcomes or consequences of specific actions Equalization: creation of knowledge regarding conditions necessary to maintain consistency Optimization: discovering what set of parameter values best meet a set of performance measures Figure 10: Generalized DSS Development Process 19 2) DSS Development Process For unstructured problems, we employ an alternate development strategy. There are seven basic activities in this process (not all may be performed in every project). 1. Problem diagnosis: formal identification of the problem context 2. Identification of objectives and resources: specific objectives must be described and available resources identified 3. System analysis: three categories of requirements (functional, interface, and coordination) are established. The remaining steps are: 4. System design: the determination of components, structure, and platform 5. System construction: an iterative prototyping approach, with small but constant refinement employed 6. System implementation: where testing, evaluation, and deployment occurs 7. Incremental adaptation: this final stage is a continual refinement of the activities of the earlier six stages. 21