1. Decision Support Systems Concepts
Week 5

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

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

4. DSS Description An early definition of DSS
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…

5. 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
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

6. DSS Description
DSS is an approach (or methodology) for supporting decision making
uses an interactive, flexible, adaptable computer-based 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

7. A Web-Based DSS Architecture

8. DSS Characteristics and Capabilities

9. DSS Characteristics and Capabilities
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

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

11. 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:
Support meetings
KMS developed around communities of practice

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

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

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

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

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

17. DSS Classifications Holsapple and Whinston's Classification
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

18. Brief Example: Advanced Scout
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

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

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

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

22. Investigate Alternative Design and Development Approaches
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

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

24. A Decision-Oriented Design Approach
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

25. Decision – orientation is the key
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

26. Design and Development of DSS, D. J. Power
3 Diagnostic Steps
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

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

28. DSS Audit Plan Step 1
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.

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

30. DSS Audit Plan Step 3
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?

31. DSS Audit Plan Step 4
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?

32. DSS Audit Plan Step 5
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.

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

34. Critical Success Factors Design Method for a Data-Driven DSS
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.

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

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

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

38. Design and Development of DSS, D. J. Power
SDLC
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

39. Design and Development of DSS, D. J. Power
SDLC
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

40. 5 Step Rapid Prototyping Process
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

41. How is a prototype developed?
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

42. Design and Development of DSS, D. J. Power
More on Prototyping
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 user-developer communication
Design and Development of DSS, D. J. Power

43. End-User DSS Development
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

44. End-User Development Concerns
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

45. End-User Development Concerns
Unnecessary databases are sometimes developed by the end-users for their DSS
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

46. DSS project Management
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

47. DSS Project Management
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

48. DSS Project Management
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

49. 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
Users are often non-technical people in functional areas of a business like marketing and finance
Design and Development of DSS, D. J. Power

50. DSS Project Participants
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