Building and Implementing Decision Support Systems

1. Building and Implementing Decision Support Systems Week 6

2. DSS Examples • Bank Rate Monitor • Car Point

3. Development Process Review • SDLC • Advantages: standardized steps, formal documentation, no important area overlooked • Disadvantages: too rigid, poor user-developer communication • Prototyping • Advantages: improved user-developer communication • Disadvantages: can extend development, user misperceptions • End-User Development • Advantages: user control, time & cost savings • Disadvantages: distraction, not training in systems development, “playing graphic designer”

4. The DSS Analysis and Design Process • Functional category analysis – the developer identifies the specific functions necessary for a specific DSS from a broad list of available functions.

5. Functional Categories • 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

6. Functional Categories • Equalization – creation of knowledge regarding conditions necessary to maintain consistency • Optimization – discovering what set of parameter values best meet a set of performance measures

7. 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.

8. Generalized DSS Development Process

9. 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). • Problem diagnosis – formal identification of the problem context • Identification of objectives and resources – specific objectives must be described and available resources identified • System analysis – three categories of requirements (functional, interface, and coordination) are established.

10. DSS Development Process The remaining steps are: • System design – the determination of components, structure, and platform • System construction – an iterative prototyping approach, with small but constant refinement employed • System implementation – where testing, evaluation, and deployment occurs • Incremental adaptation – this final stage is a continual refinement of the activities of the earlier six stages.

11. Tools for DSS Development There are a variety of tools available, roughly falling into three categories: • Primary development tools – these include programming languages and database query mechanisms. • DSS generators – at a higher level of technology, these possess integrated, diverse functionality, including decision modeling, sophisticated reporting, and database management. • Specific DSS applications – for some problem types there may be a commercially available package that can be acquired and customized.

12. DSS Development Tool Classification

13. Development Tool Selection Criteria These criteria are particularly important in selection of a DSS generator : • Data management functions • Model management functions • User interface capabilities • Compatibility and degree of connectivity • Available hardware platforms • Cost • Quality and availability of vendor support

14. DSS User Interface Issues The unique characteristics of a DSS user interface stem from the unique characteristics of typical end users: • They play an organizational role based on something other than computing skills. • They have latitude in exercising judgment. • Their decisions have impact. • They spend more time on tasks that do not need a computer than do. • The unique nature of the decisions they make means their personal preferences must be accommodated.

15. Factors Related to the Quality of the User Interface • Learning curve – how fast does the user learn? • Operational recall – how long does it take the user to recall how to use the DSS? • Task-related time – how long is the typical task? • System versatility – does it support a variety of end user tasks?

16. Factors Related to the Quality of the User Interface • Error-trapping and support – what type of errors will users make? • Degree of system adaptability – will it adjust to individual use? • Management of cognitive overload – to what extent does the DSS reduce the need to remember things while using it? • Degree of personal engagement – to what extent is the DSS enjoyable to use? • Degree of guidance and structure – to what extent does the interface guide the user?

17. Implementation Stage • “The process of assuring that the information system is operational and then allowing the users to take over its operation for use and evaluation” (Kendell and Kendell, 1988)

18. Implementation Stage Activities • Obtaining and installing the DSS hardware • Installing the DSS and making it run on its intended hardware • Providing user access to the system • Creating and updating the database • Training the users on the new system

19. Implementation Stage Activities • Documenting the system • Making arrangements to support the DSS • Transfer from developers to operations • Changing previous methods • Evaluating the operation and use

20. Direct conversion • Four basic conversion strategies • Direct conversion • Parallel conversion • Pilot conversion • Phased conversion

21. Direct conversion • Stop old system, start new system • Need to keep the old system in place

22. Parallel conversion • Run both old system and new system and compare the results • Pointless for data-oriented DSS • Acceptable for suggestion DSS

23. Pilot conversion • Introduce the system to a small part of the organization • Not feasible for group DSS

24. Phased conversion • Introduce the system in stages • Good for DSS that can be divided into several modules (GDSS) • Start with most important modules

25. System Conversion Viability

26. Resistance to Change • “There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things.” (Machiavelli, 1532) • Few will gain • Many will lose

27. Resistance to Change • “The design and implementation of a DSS is an example of planned technological change. The success or failure of a proposed DSS depends on how well this change process is managed.” (Chervany & Palvia, 1990)

28. Managing Change • Deals with people, not technology • Organizational culture • Lewin-Schein Theory of Change • Unfreezing • Moving • Refreezing • Mostly applies to institutional DSS

29. Unfreezing • Create a strong motivation for change • Create a vision • Based on justification of the system • Clearly define the benefits • 3 ways to unfreeze • Increase the forces that motivate change • Reduce forces that motivate resistance • Adjust the existing force • Should start when the project starts

30. Moving • Most visible component • Training

31. Refreezing • Internal commitment to use the systems on an ongoing basis • Particularly important in DSS • 3 factors that have positive effects • Strong project champion • Sufficient time for each change stage • Make sure each stage a success before continuing

32. DSS Implementation Issues • Technical • User-related

33. Technical Implementation Issues • Unfamiliarity with this type of system • Response time • Reliability and Availability • Poor data quality

34. User-related Implementation Issues • User and Management Support • Unstable user community • Response time • Training • Availability of support • Voluntary or Mandatory Use

35. User-related Implementation Issues • Change in job content • Loss of status • Change in interpersonal relationships • Loss of power • Change in decision-making approach • Uncertainty or unfamiliarity or misinformation • Job security

36. Ethical Issues in DSS Implementation • Storage of Information • Use of Information • Sharing of Information • Human Judgment • Combining Information • Error Detection and Correction

37. Measuring Implementation Success • 1. Ratio of actual project execution time to the estimated time • 2. Ratio of actual project development cost to budgeted cost • 3. Managerial attitudes toward the system • 4. How well managers' information needs are satisfied • 5. Impact of the project on the computer operations of the firm

38. Other MSS Success Measures • System Use • User satisfaction • Favorable attitudes • Degree to which system accomplishes its original objectives • Payoff to the organization • Benefit-to-cost ratios • Degree of institutionalization of DSS in the organization

39. Contributing Factors to DSS Success • User involvement • User training • Top management support • Information source • Level of managerial activity being supported • Characteristics of the tasks involved (structure, uncertainty, difficulty, interdependence)

40. MSS Implementation Failures • Usually a closely held secret in many organizations • Expected synergy of human and machine not developed • Managers unwilling to use computers to solve problems • Not much formal data on MSS failures • Many informal reports on unsuccessful implementation