Building and Building and Implementing Decision Implementing Decision

Support SystemsSupport Systems

Week 6Week 6

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DSS Examples

Bank Rate Monitor Car Point

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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”

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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.

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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

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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

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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.

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Generalized DSS Development Process

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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.

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DSS Development Process

The remaining steps are:4. System design – the determination of

components, structure, and platform5. 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.

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Tools for DSS Development

There are a variety of tools available, roughly falling into three categories:

1. Primary development tools – these include programming languages and database query mechanisms.

2. DSS generators – at a higher level of technology, these possess integrated, diverse functionality, including decision modeling, sophisticated reporting, and database management.

3. Specific DSS applications – for some problem types there may be a commercially available package that can be acquired and customized.

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DSS Development Tool Classification

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Development Tool Selection Criteria

These criteria are particularly important in selection of a DSS generator :

1. Data management functions2. Model management functions3. User interface capabilities4. Compatibility and degree of connectivity5. Available hardware platforms6. Cost7. Quality and availability of vendor support

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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.

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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?

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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?

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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)

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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

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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

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Direct conversion

Four basic conversion strategies Direct conversion Parallel conversion Pilot conversion Phased conversion

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Direct conversion

Stop old system, start new system Need to keep the old system in

place

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Parallel conversion

Run both old system and new system and compare the results

Pointless for data-oriented DSS Acceptable for suggestion DSS

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Pilot conversion

Introduce the system to a small part of the organization

Not feasible for group DSS

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Phased conversion

Introduce the system in stages Good for DSS that can be divided

into several modules (GDSS) Start with most important modules

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System Conversion Viability

TPS DSSDirect conversion Usually

unacceptable risk

Usually acceptable risk

Parallel conversion

Usually impractical

Usually practical

Pilot conversion Generally first choice

May raise operational issues

Phased conversion

Requires large effort to interface 2 DBs

Good choice for usually read only systems

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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

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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)

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Managing Change

Deals with people, not technology Organizational culture Lewin-Schein Theory of Change

Unfreezing Moving Refreezing

Mostly applies to institutional DSS

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Unfreezing Create a strong motivation for

change Create a vision Based on justification of the system Clearly define the benefits 3 ways to unfreeze

1. Increase the forces that motivate change2. Reduce forces that motivate resistance3. Adjust the existing force

Should start when the project starts

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Moving

Most visible component Training

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Refreezing

Internal commitment to use the systems on an ongoing basis

Particularly important in DSS

3 factors that have positive effects1. Strong project champion2. Sufficient time for each change stage3. Make sure each stage a success

before continuing

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DSS Implementation Issues

Technical User-related

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Technical Implementation Issues

Unfamiliarity with this type of system

Response time Reliability and Availability Poor data quality

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User-related Implementation Issues

User and Management Support Unstable user community Response time Training Availability of support Voluntary or Mandatory Use

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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

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Ethical Issues in DSS Implementation

Storage of Information Use of Information Sharing of Information Human Judgment Combining Information Error Detection and Correction

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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

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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

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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)

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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