Decision Support Systems Concepts Week 5 DSS

Decision Support Systems Concepts Week 5

DSS Configurations Many configurations exist; based on management-decision situation specific technologies used for support DSS have three basic components Data 2. Model 3. User interface 4. (+ optional) Knowledge 1. 2

DSS Configurations Each component Typical types: 3 has several variations; are typically deployed online Managed by a commercial of custom software Model-oriented DSS Data-oriented DSS

DSS Description An early definition of DSS 4 A system intended to support managerial decision makers in semistructured and unstructured decision situations meant to be adjuncts to decision makers (extending their capabilities but not replacing their judgment) aimed at decisions that required judgment or at decisions that could not be completely supported by algorithms would be computer based; operate interactively; and would have graphical output capabilities…

DSS Description A DSS is typically built to support the solution of a certain problem (or to evaluate a specific opportunity). This is a key difference between DSS and BI applications 5 BI systems monitor situations and identify problems and/or opportunities, using variety of analytic methods The user generally must identify whether a particular situation warrants attention Reporting/data warehouse plays a major role in BI DSS often has its own database and models

DSS Description DSS is an approach (or methodology) for supporting decision making 6 uses an interactive, flexible, adaptable computerbased information system (CBIS) developed (by end user) for supporting the solution to a specific nonstructured management problem uses data, model and knowledge along with a friendly (often graphical; Web-based) user interface incorporate the decision maker's own insights supports all phases of decision making can be used by a single user or by many people

A Web-Based DSS Architecture 7

DSS Characteristics and Capabilities 8

DSS Characteristics and Capabilities 9 Business analytics implies the use of models and data to improve an organization's performance and/or competitive posture Web analytics implies using business analytics on real-time Web information to assist in decision making; often related to e-Commerce Predictive analytics describes the business analytics method of forecasting problems and opportunities rather than simply reporting them as they occur

DSS Classifications AIS SIGDSS Classification for DSS 10 Communications-driven and group DSS Data-driven DSS Document-driven DSS Knowledge-driven DSS Model-driven DSS

Communications-Driven and Group DSS Use computer, collaboration, and communication technologies to support groups in tasks that may or may not involve decision making Examples: 11 Support meetings KMS developed around communities of practice

Data-Driven DSS 12 Primarily involved with data and processing DB organization plays a major role in structure Features strong report generation and query capabilities

Document-Driven DSS 13 Rely on knowledge coding, analysis, search and retrieval for decision support KMS

Knowledge-Driven DSS and ES 14 Involve the application of knowledge technologies to address specific decision support needs Example: AI-based DSS and ES

Model-Driven DSS 15 Developed around one or more optimization or simulation models Most common end-user tool Excel

Compound (or Hybrid) DSS 16 Include 2 or more of the major categories Data-driven can feed a model-driven DSS

DSS Classifications Holsapple and Whinston's Classification 1. 2. 3. 4. 5. 6. 17 The text-oriented DSS The database-oriented DSS. The spreadsheet-oriented DSS The solver-oriented DSS The rule-oriented DSS (include most knowledge-driven DSS, data mining, management, and ES applications) The compound DSS

Brief Example: Advanced Scout 18 Allows NBA coaches and league officials organize and interpret the data collected at every game Can review countless stats: shots attempted, shots blocked, assists made, personal fouls, etc. Can detect patterns; patterns found are linked to video of the game Helps coaches mine through and analyze a lot of data

Components of DSS Data Management Subsystem Model Management Subsystem Model base management system (MBMS) User Interface Subsystem Knowledgebase Management Subsystem 19 Includes the database that contains the data Database management system (DBMS) Can be connected to a data warehouse Organizational knowledge base

Design and Development of DSS Focus on the decision, then build or buy? 20

Overview of Design and Development Approaches 21 Traditional system analysis and design, SDLC An iterative, rapid prototyping, or “quickhit” approach Managers develop their own personal DSS, End-User DSS Development Design and Development of DSS, D. J. Power 21

Investigate Alternative Design and Development Approaches 22 Building effective DSS is important and expensive Choose an approach that increases the chances the DSS will be used Building a DSS is a difficult task; people vary so much in terms of their personalities, knowledge and ability, the jobs they hold, and the decision they make Design and Development of DSS, D. J. Power 22

Methodology SDLC the standard Alternatives 23 Prototyping End-user development Involve quickly constructing a portion of the DSS then testing, improving, and expanding

A Decision-Oriented Design Approach 24 Pre-design description and diagnosis of decision making Diagnosis of current decision – making Identification of problems or opportunities for improvement in current decision behavior Determine how decisions are currently made Design and Development of DSS, D. J. Power

Decision – orientation is the key 25 Specify changes in decision processes Determine what specific improvements in decision behavior are to be achieved Flowchart the process Design and Development of DSS, D. J. Power

3 Diagnostic Steps 26 Collect data on current decision-making Use interviews, observations, and historical records Establish a coherent description of the current decision process Specify a norm for how decisions should be made Design and Development of DSS, D. J. Power

Decision Process Audit Plan 27 Step 1: whom Step 2: Step 3: Step 4: Step 5: What will be audited and by Examine and diagram process Observe and collect data Assess performance Reporting and recommendations Design and Development of DSS, D. J. Power

DSS Audit Plan Step 1 28 Define the decisions, decision processes and related business processes that will be audited. Define the authority of the auditor, purpose of the audit, scope of the audit, timing of the audit, and resources required to perform the audit. Identify a primary contact.

DSS Audit Plan Step 2 29 Examine the formal design of the process. Diagram the process and specify criteria, etc. Is the design effective and efficient?

DSS Audit Plan Step 3 30 Examine the actual use of the decision process. Observe the process. Interview decision makers and collect data. Is the process implemented and used as intended?

DSS Audit Plan Step 4 31 Assess performance of the actual decision process. What works? Can cycle time be reduced? Are decisions appropriate? Timely? Cost effective? Is the process producing value in meeting business objectives? If not, why?

DSS Audit Plan Step 5 32 Reporting and recommendations. Summarize steps 1 -4 in a written report. Discuss what is working well and what needs to be improved. Develop recommendations for improving the process. Hold an exit meeting with decision makers.

Reaching a Diagnosis 33 Focus on identifying what is assumed by decision-makers in the decision situation Focus on what is defined by decisionmakers as the range of available remedial actions How can decision-making be improved? Design and Development of DSS, D. J. Power

Critical Success Factors Design Method for a Data-Driven DSS 34 Focus on individual managers and on their current hard and soft information needs It identifies "the limited number of areas in which results, if they are satisfactory, will insure successful competitive performance for the organization" (Rockart, 1979) If organizational goals were to be attained, then these key areas of activity - usually three to six factors - would need careful and consistent attention from management.

Conduct a feasibility study 35 Issues Objectives DSS Scope and Target Users Anticipated DSS Impacts Major Alternatives Conclusions Build versus Buy Design and Development of DSS, D. J. Power

If build, then choose a DSS Development Approach SDLC A rapid prototyping approach End-user DSS development Decision. Oriented Design Systems Development Life Cycle 36 Rapid Prototyping End-User Development Design and Development of DSS, D. J. Power

7 Step SDLC Approach 37 Confirm user requirements Systems analysis System design Programming Testing Implementation Use and Evaluation Design and Development of DSS, D. J. Power

SDLC 38 Project plans must be carefully prepared Determine the needs of potential users Identify the outputs that fulfill those needs Technical requirements should follow logical requirements and design steps If in-house development is not chosen, a request – for – proposal [RFP] may be required Design and Development of DSS, D. J. Power

SDLC 39 In many situations a full-scale SDLC is too rigid for DSS, especially a DSS where requirements are changing rapidly User requirements agreed upon at the first stage of the process are hard to change Design and Development of DSS, D. J. Power

5 Step Rapid Prototyping Process 40 1. Identify user requirement 2. Develop a first iteration DSS prototype 3. Evolve and modify the next DSS prototype 4. Test and return to step 3 if needed 5. Full-scale implementation Design and Development of DSS, D. J. Power

How is a prototype developed? 41 DSS analyst sits down with potential users and develops requirements Analyst develops a prototype User use the prototype, react to, comment on, and eventually approve Missing features are added later Design and Development of DSS, D. J. Power

More on Prototyping 42 Once approved, the prototype can be expanded in the development environment or used as a specification for a DSS developed in a language like Java, C, or C++ Compared with the SDLC approach, prototyping seems to improve userdeveloper communication Design and Development of DSS, D. J. Power

End-User DSS Development 43 Puts the responsibility for building and maintaining a DSS on the manager who builds it Major advantages 1) person who wants computer support will be involved in creating it 2) fast 3) lower cost Design and Development of DSS, D. J. Power

End-User Development Concerns 44 End-users may select an inappropriate software development product End-user may have limited expertise in the use of the product and the IT group may have limited ability to support End-user development Errors during End-user DSS development are common Design and Development of DSS, D. J. Power

End-User Development Concerns 45 Unnecessary databases are sometimes developed by the end-users for their DSS may have limited testing and limited documentation End-user databases may be poorly constructed and difficult to maintain End-users rarely follow a systematic development process Design and Development of DSS, D. J. Power

DSS project Management 46 Assign DSS project manager Tasks include diagnosis, a feasibility study, and a definition of the objectives and scope of the proposed project The larger the scope of the project the more important it is to receive widespread agreement and sponsorship of the project Design and Development of DSS, D. J. Power

DSS Project Management 47 Once the project is approved then a methodology and project plan needs to be developed Outsourced – process needs to be developed for creating RFP’s and then evaluating proposals In-house – development and technical tools need to be resolved Design and Development of DSS, D. J. Power

DSS Project Management 48 DSS project manager should identify tasks that need to be completed, resources that are needed and project deliverables Deliverables are especially important for monitoring the progress of the project Design and Development of DSS, D. J. Power

DSS Project Participants DSS Project Manager or DSS analyst Expert who makes the technical decisions about the software and hardware to use Executive Sponsor Senior manager who has the influence to help resolve major resource issues and potential problems Potential DSS users 49 Users are often non-technical people in functional areas of a business like marketing and finance Design and Development of DSS, D. J. Power

DSS Project Participants 50 DSS Builder or analyst Technical Support Staff DW Architect, Data Quality Analyst Toolsmith/Specialist Focus on the tools and technologies that will be used in the construction of the DSS Network Specialists, Database Administrator Design and Development of DSS, D. J. Power