Decision Support Systems Course

Decision Support Systems Course
Dr. Aref Rashad February 2013 Decision Support Systems Course

Course Goals To become familiar with the goals and different forms of decision support. Explore approaches to decision making Explore the various decision support system components together with a detailed illustration of Decision support system analysis, design and development Implementation and Applications of Decision Support Systems. The actual and potential impact of the technology together with the challenges associated with this kind of application will be examined. February 2013 Decision Support Systems Course

References: Decision Support Systems for Business Intelligence, 2nd Edition, Vicki L. Sauter, January 2011, ©2010 Decision support systems and intelligent systems, Efraim Turban. Jay E. Aronson, Prentice Hall, 1998 Lecture Notes February 2013 Decision Support Systems Course

Course Requirements Lectures Notes Project Assignment Grades Distribution Final Exam Midterm Assignment Attendance Classroom activities Practice & Project February 2013 Decision Support Systems Course

Course Requirements Project: Each group shall submit a project showing real implementation of DSS based on using Excel and Visual Basic. (Week 10) Assignment: Each student shall submit a paper at least 5 pages on DSS application on certain domain (industry, Education, Health, Government….etc.) (Week 8) February 2013 Decision Support Systems Course

Course Contents Decisions and Decision Making Support. DSS Data Component. DSS Model Component. DSS User Interface. DSS Application Example Designing a Decision Support System. Development and Implementation Strategy. Intelligence and Decision Support Systems. February 2013 Decision Support Systems Course

“Virtually everyone makes hundreds of decisions each day” Decisions made up of a composite of information, data, facts and belief. Data by itself does not constitute useful information unless it is analyzed and processed. "Good decision making" means we are informed and have relevant and appropriate information on which to base our choices among alternatives. February 2013 Decision Support Systems Course

Quality of decisions Quality of decisions depend on : The adequacy of the available information The quality of the information, the number of options The appropriateness of the analysis effort available at the time of the decision February 2013 Decision Support Systems Course

Organizations Organizations are systems Involve people, structure and a common purpose Have limited resources Need to perform a series of functions to meet its objectives February 2013 Decision Support Systems Course

Managers Managers are responsible for effective and efficient execution of these organizational functions. A typical manager performs a number of functions that are categorized as: Interpersonal Informational Decisional One of the key traits that distinguish managers from operatives is the ability to make independent decisions. February 2013 Decision Support Systems Course

Types of Problems Structured: situations where the procedures to follow when a decision is needed can be specified in advance Repetitive Standard solution methods exist Complete automation may be feasible Unstructured: decision situations where it is not possible to specify in advance most of the decision procedures to follow One-time No standard solutions Rely on judgment Automation is usually infeasible Semi-structured: decision procedures that can be prespecified, but not enough to lead to a definite recommended decision. February 2013 Decision Support Systems Course

Decision Types Effective managers make various kinds of decisions. In general, these decisions are either: Programmed decisions Non-programmed decisions

Programmed Decisions Examples: Pricing standard customer orders,
A decision that is repetitive and routine A definite method for its solution can be established Does not have to be treated a new each time it occurs Procedures are often already laid out Examples: Pricing standard customer orders, Determining billing dates, Recording office supplies etc.

Non-programmed Decisions
A decision that is novel (new or unique) or Ill structured No established methods exist, because it has never occurred before or because it is too complex Are “tough” decisions that involve risk and uncertainty and call for entrepreneurial abilities Such decisions draw heavily on the analytical abilities of the manager Examples: Moving into a new market, Investing in a new unproven technology, Changing strategic direction

Level of Decision Making Strategic Managerial Operational More Structured February 2013 Decision Support Systems Course

Non-programmed Decisions
Organizational Levels Nature of Problems Nature of Decision-making Organizational hierarchy

Decision Levels Type of Control Type of Decision: Operational Control Managerial Control Strategic Planning Structured (Programmed) Accounts receivable, accounts payable, order entry Budget analysis, short-term forecasting, personnel reports Investments, warehouse locations, distribution centers Semistructured Production scheduling, inventory control Credit evaluation, budget preparation, project scheduling, rewards systems Mergers and acquisitions, new product planning, compensation, QA, HR policy planning Unstructured (Unprogrammed) Buying software, approving loans, help desk Negotiations, recruitment, hardware purchasing R&D planning, technology development, social responsibility plans February 2013 Decision Support Systems Course

Information Characteristics for Different Types of Decisions February 2013 Decision Support Systems Course

Management Problems Most management problems can be represented by : Provide earliest entry into market Minimize employee discomfort/turnover Objective Maximize profit Determine length of time tests should be run on a new product/service Determine the responsibilities to assign to each worker Determine price to use Decision variables Ensure responsibilities are at most shared by two workers Test enough to meet minimum safety regulations Can’t charge below cost Constraints February 2013 Decision Support Systems Course

Problem Solving Steps Systematic Approach Six Steps Define The Problem
Analyze The Problem Generate Possible Solutions Select The Best Solution Plan For Implementation Implement And Evaluate The Solution

Problem Solving Steps 1. Step One : Define The Problem
Identify the problem Develop an accurate problem statement: Too general or misleading: - - Too broad. . . “Reduce the quality problems in our area”. - - Implies a cause or suggests a solution “There are not enough forklifts to service the assembly line”. Accurate and Appropriate: “Reduce the downtime of the assembly line due to parts problems caused by inadequate restocking”.

2. Step Two : Analyze The Problem
Problem Solving Steps 2. Step Two : Analyze The Problem Don’t rush to a wrong solution. Highly critical step. Common mistake to immediately begin generating solutions. Must identify and eliminate root causes of problem.

Problem Solving Steps 2. Step Two : Analyze The Problem
Getting to the Root Cause of the Problem Five “Whys” equal one “How-To” (5W=1H) Why did the machine stop? An overload caused the fuse to blow. Why did the overload occur? The bearing was not sufficiently lubricated. Why was it not lubricated sufficiently? The lubrication pump was not pumping sufficiently. Why was it not pumping? The shaft of the pump was worn and rattling. Why was the shaft worn? Metal scraps got to the pump because no strainer was attached. This helps uncover the root problem and correct it.

Diagnostic Tools Brainstorming Flow Diagrams Cause and Effect Diagrams Pareto Charts Check Sheets

Data Collection Steps to Data Collection: Identify what information to collect Decide how to collect the information. Decide when to collect the information Design which tools you will use to collect the information Collect the data. Identify what information to collect. When a cause/effect is occurring. How frequently it is occurring. Where it is occurring. What is the magnitude of the occurrence?

Steps to Data Collection: 2. Decide how to collect the information. Interviews and questionnaires (Technical Specialists, Supervisors and Managers, other Employees) Look at records (Past/ recent information, quality productivity, safety, inventory, maintenance records). Direct observation (Make your own records, use those involved in the problem). 3. Decide when to collect the information. Decide what is a reasonable time. Consider when you are most likely to get the information.

Problem Solving Steps 2. Step Two : Analyze The Problem Design which tools you will use to collect the information. Interviews or questionnaires Decide from whom you need information, what questions to ask. Use checklists to collect two kinds of information at the same time. Think of combinations that show when and where the cause is happening. - Number of times and places occurring - Length of time and type of thing - Cost and type - Machine and/or type of system 5. Collect the data. February 2013 Decision Support Systems Course

Problem Solving Steps 3. Step Three : Generate Alternative Solutions How to Develop Alternatives: Look at the data. What does it tell you? Question each aspect of situation. Use all idea sources available. Apply some appropriate action Apply creativity to the situation Brainstorm for alternative solutions. February 2013 Decision Support Systems Course

Problem Solving Steps 3. Step Three : Generate Alternative Solutions
How to Develop Alternatives: Data will lead to some ideas Data may not lead to best idea Look at the data. What does it tell you? What is the job to be done Why is the job to be done? Who should do the job? Where should the job be done? When should the job be done? How should the job be done? Question each aspect of situation. The worker involved In-house experts Written material Outside experts Use all idea sources available.

Problem Solving Steps 3. Step Three : Generate Alternative Solutions
How to Develop Alternatives: Eliminate (part, reason, job, activity) Combine (parts, forms, jobs, functions) Rearrange (sequence, location) Simplify (make obvious, provide , remove steps, reduce physical effort) Apply some appropriate action Making new ways Rearranging old ways Form novel and useful ideas Apply creativity to the situation Brainstorm for alternative solutions.

Problem Solving Steps 4. Step Four : Select A Solution
Refer back to original problem statement. Consider: - - Safety Cost - - Product performance Better management information - - Improved Technology Time - - Quality Appearance Some questions to ask: - - Will this completely resolve the problem? - - Will this only satisfy part of the problem? - - Will this prevent future occurrences? - - Will this have little or no impact on the problem? - - Do we have the authority to implement? - - Do we have the necessary resources? - - How long will it take to implement?

Problem Solving Steps 5. Step Five : Plan and Implement Solution
Steps to ensure successful implementation: - Prepare an action plan: ... What will be done? ... How will it be done? ... Where will it be done? ... Who will do it? ... When will it be done? - Develop a tracking system: ... Identify milestones or events ... Assign completion dates ... Identify reporting systems - Design evaluation procedures - Implement the procedures

Problem Solving Steps 6. Step Six : Evaluate The Solution
Measure results using procedures established during implementation Use data gathering: - check sheets - control charts - time studies - Pareto analysis

Forms of Rationality February 2013 Decision Support Systems Course

Rational Decisions The situation where a decision maker selects a vehicle from a range of automobiles. Economic rationality Costs of the various automobiles Technical rationality Engine size, Horsepower, Better grade wheels and tires Legal Rationality Car seats, Societal rationality air or noise pollution Procedural rationality Fare away Service center, Rare unique type of fuel Political issues car purchased for an elected official conveys to his or her constituency. February 2013 Decision Support Systems Course

Causes of Satisficing Behavior
Decision makers do not optimize their decisions. Rather, these decision makers generally satisfies; February 2013 Decision Support Systems Course

Decision Styles Decision-making, though a rational process does include some subjective elements Thus in real organizational settings, the quality of decision does depend on the ability, style and approach of the manager

Decision Styles: Vroom and Yetton Model
Vroom and Yetton have identified five decision styles for managers, and are classified as follows: Autocratic : AI The decision is made individually, using the information available to the individual only AII The manager obtains information from subordinates and himself makes the decision May or may not share with subordinates, the purpose of questions or the nature of problem Subordinates do not play any role in problem definition or selection of alternatives

Vroom and Yetton Model Consultative: CI The manager shares the problem with relevant subordinates individually Getting their input individually and not as a group. The manager then makes the decision independently, and may or may not be influenced by the subordinates’ suggestions CII The problem is shared to subordinates in a group Their ideas and suggestions are sought in a group meeting The decision is then made by the manager which May or may not reflect the subordinates’ influence

Vroom and Yetton Model Group Consensus: GI
The problem is shared to subordinates as a group Alternatives are generated and evaluated collectively Effort is made to reach a consensus The decision is made collectively and the manager functions as a coordinator Does not “press” the group in adopting the manager’s “solution” The manager is willing to accept and implement the decision of the group

Decision Support System Definition DSS are computer-based systems that: Bring together information from a variety of sources Assist in the organization and analysis of information Facilitate the evaluation of assumptions underlying the use of specific models. February 2013 Decision Support Systems Course

DSS allow decision makers to: Access relevant data across the organization as they need it to make choices among alternatives. Analyze data generated from transaction processing systems and other internal information sources easily. Access to information external from the organization Analyze the information in a manner that will be helpful to that particular decision and will provide that support interactively. February 2013 Decision Support Systems Course

The analyses can help decision makers understand: What is happening in their organization, Why problems or trends occur, What trends are likely to continue, What actions are best, and how to take advantage of situations in the future. February 2013 Decision Support Systems Course

Evolution of DSS Goal: Use best parts of IS, OR/MS, AI & cognitive science to support more effective decision February 2013 Decision Support Systems Course

Functions of a DSS February 2013 Decision Support Systems Course

Uses of DSS in Business February 2013 Decision Support Systems Course

Pressure to Build DSS February 2013 Decision Support Systems Course

Continuum of IS Products
Structured Semistructured Unstructured February 2013 Decision Support Systems Course

Components of a DSS February 2013 Decision Support Systems Course

Database Management System (DBMS) Provides access to data as well as all of the control programs necessary to get those data in the form Data include facts about internal operations, trends, market research and/or intelligence, and generally available information. User Interface Represents all of the mechanisms whereby information is input to the system and output from the system. It includes all of the input screens by which users request data and models. In addition, it includes all of the output screens through which users obtain the results. February 2013 Decision Support Systems Course

. Model Base Management system (MBMS) A component that consists of models used in computational and analytical routines that mathematically express relations among variables It controls running the models Examples: Linear programming models Multiple regression forecasting models Capital budgeting present value models February 2013 Decision Support Systems Course

February 2013 Decision Support Systems Course

The Characteristics and Capabilities of DSS are: 1. Support for decision makers (mainly in semi- and un-structured situation) by bringing together human judgment and computerized information. 2. Support for all managerial levels, ranging from top executives to line managers. 3. Support for individuals (from different departments, organizational levels or different organizations) as well as groups of decision makers working somewhat independently – virtual teams through collaborative Web tools. 4. Support for independent or sequential decisions that may be made once, several times or repeatedly. 5. Support in all phases of decision-making process (intelligence, design, choice, implementation). 6. Support for a variety of decision-making process and style. February 2013 Decision Support Systems Course

7. The decision maker should be reactive, able to confront changing conditions quickly and able to adapt the DSS to meet these changes. DSS are flexible, so users can add, delete, combine, change or rearrange basic elements. 8. User-friendliness, strong graphical capabilities and natural language interactive human-machine interface can greatly increase the effectiveness of DSS, Most new DSS application use Web-based interfaces. 9. Improvement the effectiveness of decision making rather than its efficiency. When DSS are deployed, decision making often takes longer but the decisions are better. 10. The decision maker has complete control over all steps of the decision-making process in solving a problem – a DSS aims to support not to replace the decision maker. 11. End users are able to develop and modify simple systems by themselves. Larger systems can be built with assistance from information system specialist. Online analytical process (OLAP) and data mining software, with data warehouses, allow users to build very large and complex DSS. . February 2013 Decision Support Systems Course

12. Models are generally utilized to analyze decision-making situations. The modelling capability enable experimentation with different strategies under different configurations 13. Access is provided to a variety of data sources, formats and types, including GIS, multimedia and object oriented. 14. Can be employed as a standalone tool used by an individual decision maker in one location or distributed throughout an organisation and in several organizations along the supply chain. It can be integrated with other DSS or applications and it can be distributed internally and externally using networking and Web technologies. These key DSS Characteristics and Capabilities allow decision makers to make better, more consistent decision in a timely manner and they are provided by the major DSS components. February 2013 Decision Support Systems Course

Types for DSS based on mode of assistance Data-driven DSS Model-driven DSS Communication-driven DSS Document-driven DSS Knowledge-driven DSS As with the definition, there is no universally accepted taxonomy of DSS either. Different authors propose different classifications. February 2013 Decision Support Systems Course

Data-driven DSS Emphasize access to and manipulation of a time series of internal company data and, sometimes, external data . Simple file systems accessed by query and retrieval tools provides the elementary level of functionality. Data warehouses provide additional functionality. OLAP provides highest level of functionality. Examples: Accessing data base for a certain subject in a certain time period Accessing database for all incidents in a specified Sector in a certain period February 2013 Decision Support Systems Course

Model-driven DSS Emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation They are not necessarily data intensive. Examples: A spread-sheet with formulas A statistical forecasting model An optimum routing model February 2013 Decision Support Systems Course

Communication-driven DSS
Use network and comminication technologies to faciliate collaboartion on decision making . It supports more than one person working on a shared task. Examples: Group Decision Making Vide conferencing. February 2013 Decision Support Systems Course

Document-driven DSS Uses storage and processing technologies to document retrieval and analysis. It manages, retrieves and manipulates unstructured information in a variety of electronic formats. Document database may include: Scanned documents, hypertext documents, images, sound and video. Example: Library System February 2013 Decision Support Systems Course

Knowledge-driven DSS Provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures. It suggest or recommend actions to managers. Example: MYCIN: A rule based reasoning program which help physicians diagnose blood disease. February 2013 Decision Support Systems Course

Types of DSS Text-oriented DSS Includes catalog books, periodicals, reports, memos, and other written documents so that their contents can be made available to decision makers. The system allows you to categorize, consolidate, and merge documents as well as to write comments about the contents and the value thereof. Database-oriented DSS It provides descriptive information that is of relevance to a choice under consideration. Focus on discrete data that are stored in a database. February 2013 Decision Support Systems Course

Spreadsheet-oriented DSS Use the tools available in a spreadsheet to summarize and analyze the data. Instead of just providing access to data, Allow the decision maker to create some basic models and to evaluate those models in a quick and efficient manner. Solver-oriented DSS Provide some kind of modeling package as the basis of the DSS. Allow decision makers to identify more varied and sophisticated relationships among the data. The modeling package may be integrated into the DSS or simply used by the DSS depending on the architecture of the system February 2013 Decision Support Systems Course

Rule-oriented DSS Provides advisory support to decision makers. Provides some cognitive functions and prove something to be true (or sometimes false) or reason as far as the data allowed toward a conclusion. Compound DSS Hybrid combinations of the individual types of DSS. Such hybrid designs are the most common form of DSS today systems have mixed capabilities February 2013 Decision Support Systems Course

DSS Advantages Look at more facets of a decision • Generate better alternatives • Respond to situations quickly • Solve complex problems • Consider more options for solving a problem • Utilize multiple analyses in solving a problem • Have new insights into problems • Implement a variety of decision styles and strategies • Use more appropriate data • Better utilize models • Consider "what if?" analyses February 2013 Decision Support Systems Course

Decision Style Impact on DSS Knowledge of different decision-making styles tells the designer of a decision support system how to: Present information Incorporate models Develop Interface The system must have the flexibility to change with the decision maker and accommodate changes in both the information sought and the models employed. February 2013 Decision Support Systems Course

People develop in their information processing as a function of their maturation, experience, education, and self-regulation. Inexperienced decision makers : Seek more concrete information More comfortable with methods drawn from their own personal experiences. Prefer very explicit, quantitative data regarding the resources available Tend to prefer more qualitative information and even speculations regarding the past performance Need a great deal of structure in system February 2013 Decision Support Systems Course

As decision makers become more experienced Seek possibilities they have not considered previously. Imagine other options and other information to support their hypotheses about options Seeking information about the performance of alternatives under consideration. Seek quantitative, factual information regarding the process or internal operations of an alternative. Need a great deal of flexibility February 2013 Decision Support Systems Course

Car-purchasing example: Novice users: Provide limited Information May not be aware of the details (e.g extras associated with options of prices as sales tax or interest ) The system might ask questions such as: what car they drive now what things they like about it or not like about Make a recommendation based upon limited information. DSS must provide unknown information explicitly and help the user apply it appropriately Master decision makers can handle more abstract questions such as the desirability of new options on a car. February 2013 Decision Support Systems Course

Ingredients for DSS Success or Failure For DSS Success Management Support Users Involved in Design & Development Early Benefits Shown For DSS Failure Lack of Management Support Users Ignored in Design & Development No Early Benefits Shown February 2013 Decision Support Systems Course

DSS Applications 1. Corporate Functional Management
1.1 Accounting/Auditing 1.2 Finance 1.3 Human Resources Management 1.4 International Business 1.5 Information Resources Management 1.6 Marketing 1.7 Production and Operations Management 1.8 Strategic Management 1.9 Multifunctional Management 2. Education 3. Government 4. Hospital and Health-Care 5. Military 6. Natural Resources 7. Urban and Community Planning February 2013 Decision Support Systems Course February 2013 Decision Support Systems Course 71

America Airlines DSS Improves productivity and Profitability The problem: maintenance scheduling of 660 aeroplanes in 10 different fleet types is a nightmare. Each type goes through 30 different maintenance check-ups. The solution: a DSS takes all the variables, including many models such as programming and simulation. It allows the airline to generate a maintenance plan and perform various what-if analysis. It react to the changes rapidly. The Result: improved productivity; reduced maintenance costs by as much as $454m over the active life of 227 wide-body aircraft alone; generated revenues by reducing the time that aeroplanes are not flying. February 2013 Decision Support Systems Course

Decision Support Systems Course

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