12.1 © 2007 by prentice hall 12 chapter enhancing decision making

12.1 © 2007 by Prentice Hall

1212ChapterChapter

Enhancing Enhancing Decision MakingDecision Making

Enhancing Enhancing Decision MakingDecision Making


LEARNING OBJECTIVES

Management Information SystemsManagement Information SystemsChapter 12 Enhancing Decision MakingChapter 12 Enhancing Decision Making

• Describe different types of decisions and the decision-making process.

• Assess how information systems support the activities of managers and management decision making.

• Demonstrate how decision-support systems (DSS) differ from MIS and how they provide value to the business.


LEARNING OBJECTIVES (cont’d)

• Demonstrate how executive support systems (ESS) help senior managers make better decisions.

• Evaluate the role of information systems in helping people working in a group make decisions more efficiently.



Procter & Gamble Restructures Its Supply Chain

• Problem: Cost pressures, complex supply chain.

• Solutions: Deploy modeling and optimization software to maximize return on investment and predict the most successful supply chain.

• Modeling software fueled with data from Oracle data warehouse improved efficiency and reduced costs.

• Demonstrates IT’s role in restructuring a supply chain.

• Illustrates digital technology improving decision making through information systems.



Business Decision Making and the Decision-Making Process Business Decision Making and the Decision-Making Process

• Senior management

• Middle management and project teams

• Operational management and project teams

• Individual employees

Decision-Making Levels:

DECISION MAKING AND DECISION-SUPPORT SYSTEMS




Information Requirements of Key Decision-Making Groups in a Firm

Figure 12-1

Management Information SystemsManagement Information SystemsChapter 12 Enhancing Decision Making Chapter 12 Enhancing Decision Making


Unstructured decisions:

Types of Decisions



• Novel, non-routine decisions requiring judgment and insights

• Examples: Approve capital budget; decide corporate objectives


Structured decisions:



• Routine decisions with definite procedures

• Examples: Restock inventory; determine special offers to customers

Semistructured decisions:

• Only part of decision has clear-cut answers provided by accepted procedures

• Examples: Allocate resources to managers; develop a marketing plan

Types of Decisions (Continued)


• Management Information Systems (MIS)

• Decision-Support Systems (DSS)

• Executive Support Systems (ESS)

• Group Decision-Support Systems (GDSS)

Systems for Decision SupportSystems for Decision Support

There are four kinds of systems that support the different levels and types of decisions:




Stages in Decision Making

Figure 12-2




• Information quality: Accuracy, integrity, consistency,

completeness, validity, timeliness, accessibility

Decision Making in the Real WorldDecision Making in the Real World

In the real world, investments in decision-support systems do not always work because of

Management Information SystemsManagement Information SystemsChapter 12 Enhancing Decision Making for the Digital Firm Chapter 12 Enhancing Decision Making for the Digital Firm



• Management filters: Biases and bad decisions of managers

• Organizational inertia: Strong forces within organization that resist change



Decision Making in the Real World (Continued)


• Primarily address structured problems

• Provides typically fixed, scheduled reports based on

routine flows of data and assists in the general control

of the business

SYSTEMS FOR DECISION SUPPORT

The Difference between MIS and DSS The Difference between MIS and DSS

Management Information SystemsManagement Information SystemsChapter 12Enhancing Decision MakingChapter 12Enhancing Decision Making

Management Information Systems:


• Support semistructured and unstructured problems

• Greater emphasis on models, assumptions, ad-hoc queries, display graphics

• Emphasizes change, flexibility, and a rapid response



Decision Support Systems:


Model-driven DSS:


Types of Decision-Support Systems Types of Decision-Support Systems


• Primarily stand-alone systems

• Use a strong theory or model to perform “what-if” and similar analyses


Data-driven DSS:



• Integrated with large pools of data in major enterprise systems and Web sites

• Support decision making by enabling user to extract useful information

• Data mining: Can obtain types of information such as associations, sequences, classifications, clusters, and forecasts


• DSS database: A collection of current or historical data from a number of applications or groups

• DSS software system: Contains the software tools for data analysis, with models, data mining, and other analytical tools

• DSS user interface: Graphical, flexible interaction between users of the system and the DSS software tools


Components of DSS Components of DSS





• Statistical models

• Optimization models

• Forecasting models

• Sensitivity analysis (“what-if” models)

Model: An abstract representation that illustrates the components or relationships of a phenomenon


Overview of a Decision-Support System


Figure 12-3



• Data Visualization: Presentation of data in graphical forms, to help users see patterns and relationships

• Geographic Information Systems (GIS): Special category of DSS that display geographically referenced data in digitized maps



Business Value of DSS


• DSS based on the Web and the Internet can support

decision making by providing online access to various

databases and information pools along with software for

data analysis

• Some of these DSS are targeted toward management,

but many have been developed to attract customers.


Web-Based Customer Decision-Support Systems Web-Based Customer Decision-Support Systems



• Customer decision making has become increasingly

information intensive, with Internet search engines,

intelligent agents, online catalogs, Web directories, e-

mail, and other tools used to help make purchasing

decisions.

• Customer decision-support systems (CDSS) support

the decision-making process of an existing or potential

customer.



Web-based Customer Decision-Support Systems (Continued)


• Group Decision-Support System (GDSS) is an interactive

computer-based system used to facilitate the solution of

unstructured problems by a set of decision makers

working together as a group.

GROUP DECISION-SUPPORT SYSTEMS

What Is a GDSS? What Is a GDSS?



• Hardware (conference facility, audiovisual equipment, etc.)

• Software tools (Electronic questionnaires, brainstorming tools, voting tools, etc.)

• People (Participants, trained facilitator, support staff)

Three Main Components of GDSS: Three Main Components of GDSS:




• In a GDSS electronic meeting, each attendee has a workstation.

• The workstations are networked and are connected to the facilitator’s console, which serves as the facilitator’s workstation and control panel, and to the meeting’s file server.

• All data that the attendees forward from their workstations to the group are collected and saved on the file server.

Overview of a GDSS Meeting




• The facilitator is able to project computer images onto the projection screen at the front of the room.

• Many electronic meeting rooms have seating arrangements in semicircles and are tiered in legislative style to accommodate a large number of attendees.

• The facilitator controls the use of tools during the meeting.



Overview of a GDSS Meeting (Continued)Overview of a GDSS Meeting (Continued)


Group System ToolsGroup System Tools

Figure 12-9

The sequence of activities and collaborative support tools used in an electronic meeting system facilitate communication among attendees and generate a full record of the meeting.

Source: From Nunamaker et al., “Electronic Meeting Systems to Support Group Work,” Communications of the ACM, July 1991. Reprinted by permission.


Group Decision-Support Systems (GDSS)


• Traditional decision-making meetings support an optimal size of three to five attendees. GDSS allows a greater number of attendees.

• Enable collaborative atmosphere by guaranteeing contributor’s anonymity.

• Enable nonattendees to locate organized information after the meeting.

Business Value of GDSS




• Can increase the number of ideas generated and the

quality of decisions while producing the desired results in

fewer meetings

• Can lead to more participative and democratic decision

making



Business Value of GDSS (Continued)Business Value of GDSS (Continued)


• ESS can bring together data from all parts of the firm

and enable managers to select, access, and tailor

them as needed.

• It tries to avoid the problem of data overload so

common in paper reports.


The Role of Executive Support Systems in the Firm

EXECUTIVE SUPPORT IN THE ENTERPRISE


• The ability to drill down is useful not only to senior

executives but also to employees at lower levels of

the firm who need to analyze data.

• Can integrate comprehensive firmwide information

and external data in timely manner

• Inclusion of modeling and analysis tools usable with a

minimum of training



The Role of Executive Support Systems in the Firm (Continued)


• Ability to analyze, compare, and highlight trends

• Graphical interface enables users to review data

more quickly and with more insight, speeding

decision making.

• Timeliness and availability of data enables more

timely decision making, helping businesses move

toward a “sense-and-respond” strategy.


Business Value of Executive Support Systems



• Increases upper management span of control, better

monitoring

• ESS based on enterprise-wide data can be used for

decentralization of decision making or increase

management centralization.



Business Value of Executive Support Systems Business Value of Executive Support Systems (Continued)(Continued)


• Decision-support systems provide opportunities for

increasing precision, accuracy, and rapidity of

decisions and thereby contributing directly to

profitability


Management Opportunities:

MANAGEMENT OPPORTUNITIES, CHALLENGES AND DECISIONS

12.1 © 2007 by prentice hall 12 chapter enhancing decision making

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