DECISION SUPPORT
&
ARTIFICIAL INTELLIGENCE
The New Science of Management Decision
young
field
TEDSS Case

still
dynamic
Herbert Simon (1960)
Wall Street Journal -Exodus (30Sep05)
Wall Street Journal -Terrorist (17Feb06)
Caspian Sea Pipeline Project (2012)
ProQuest assignment: analytic hierarchy process
TEDSS, Decision Types, Phases & DSS
day.1
1b TEDDS illustrates decision types supported by DSS (details: More Efficient Exodus, WSJ)
13 benefits of building DSS (similar: regression)
S-1 the journey into decision making will lead to a major revolution in
management and organization
(observed in CIO cases)
2
TERRAIN MAP of decision making is needed because:
S-2 different (IT) techniques are required for different phases of the journey
3
TYPES OF DECISIONS
S-3a Programmed (routine sequence of responses so studied / programmed)
S-3b opportunity use ITS to program decisions (TPS, MIS JIT)
S-3a Nonprogrammed (unique & ill-structured)
S-3c require flexible / interactive (IT) techniques (DSS, AI)
4
In reality, decisions exist in continuum requiring a complement of ITS:
PG &Vanity Fair used DSS (Stonyfield : Access) to access & analyze
information from TPS & IOS
5.a PHASES OF DECISIONS
S-6.2 complex / unstructured problems are typically encountered in design
& choice phases of nonprogrammed decisions  DSS(AI) useful
 Build:Buzzsaw; Dock:Sparks; Home:TEDDS,PredictTerrorist,N-Site;
Indian:Covisint,DBMS; Jackpot:WiNet,Celtics; Rx:CPOE-EMR
S.4
Assignment:
proquest search
(analyic hierarchy process)
day.2
2 WHAT IS A DSS?
6.1 flexible/interactive ITS support complex/ill-structured DM
6.2 typically applied to design/choice in nonprogrammed decisions
6.3 AHP is an example
8 momentous changes for (complex/ill-structured) DM
ProQuest shows applied to many diverse decisions
9 AHP developed to assist DM evaluate (design / choice phases of)
complex judgmental (involving qualitative criteria) problems
7 Analytic (decompose into components)
design
Hierarchy (organize into hierarchical structure)
Process (simpler pair-wise comparisons)
choice
13 Simple, Intuitive, Powerful
9 understanding (components of decision)
10 management of complexity (hierarchical structure, simpler choices)
11 sophistication / speed of information processing (infers priorities
from series of simple choices)
14a EC applied to spouse choice demonstrates DSS & components
assignment: use EC to weight presentation criteria
16 integrated into GDSS (Ranking Technical Managers)
DSS extended by groupware & telecommunications
GDSS
16.a What is GDSS?
17
18
22
Hiring technical manager is complex, ill- structured, team
decision
Design and choice phases of GDSS
H relate to table handouts
Benefits of GDSS
day.3
A Decision Support System to Save Lives
day.1
1. You cannot see, hear, or smell nuclear radiation, but it’s deadly all the
same. In 1986 about 3.5 million people in Belarus, Russia, and Ukraine were
exposed to it when there were two explosions in Unit 4 of the Chernobyl Nuclear
plant. Some of the effects are only now emerging, like the high incidence of thyroid
cancer in children. Experts agree that many health problems would have been
avoided if an evacuation plan had been in place.
2. To avoid such a human tragedy in Virginia, power plant administrators
commissioned the development of TEDSS to assist in creating an evacuation plan
in case of a nuclear power plant disaster there. TEDSS is a special type of IT
system called a decision support system. If a nuclear disaster were to occur,
planners can use TEDSS to quickly (speed) determine the best evacuation routes
(force) and how best to notify the public of those routes
3. For TEDSS to help determine the best evacuation strategies, it uses
information on multiple variables that include
The behavior of radioactive gasses, such as dispersion rates
Highway system characteristics, such as number of lanes
Population distributions, such as densities and the location of people with
disabilities
Current weather conditions, such as wind direction
4. If this information were static, administrators would have no need for a
decision support system because the evacuation route would be developed once and
the job would be done. However, the information fluctuates constantly depending
on the time of day, time of year, and meteorological and economic conditions.
Population densities also change, as does the highway system. The task, then, is to
analyze all the information given the specific conditions of the moment, find the best
solution, and find it quickly.
5. Some of the information that TEDSS needs resides within the power plant
organization, such as the layout of the power plant, information on deadly gasses,
and the escalation rate of the accident. Other information is supplied by state
agencies and other external sources.
6. By processing this information in its simulation models, TEDSS provides
output — some of it in graphic form — on the following factors:
Evacuation routes and paths from any origin to assigned shelters
Projected volumes of traffic on the highway system
Highways that may become severely blocked by radiation
The time that will have elapsed before the last vehicle clears the area
7. With these outputs produced by TEDSS, planners can evaluate traffic
management strategies, such as one-way operation of highways, shoulder use, and
flashing signals to reduce traffic congestion and to improve evacuation time.
A Decision Support System to Save Lives
1. You cannot see, hear, or smell nuclear radiation, but it’s deadly all the same. In 1986 about 3.5 million people in Belarus,
Russia, and Ukraine were exposed to it when there were two explosions in Unit 4 of the Chernobyl Nuclear plant. Some of the
effects are only now emerging, like the high incidence of thyroid cancer in children. Experts agree that many health problems
would have been avoided if an evacuation plan had been in place.
2. To avoid such a human tragedy in Virginia, power plant administrators commissioned the development of TEDSS to
assist in creating an evacuation plan in case of a nuclear power plant disaster there. TEDSS is a special type of IT system called a
decision support system. If a nuclear disaster were to occur, planners can use TEDSS to quickly determine the best evacuation
routes and how best to notify the public of those routes
3. For TEDSS to help determine the best evacuation strategies, it uses information that includes
The behavior of radioactive gasses, such as dispersion rates
Highway system characteristics, such as number of lanes
Population distributions, such as densities and the location of people with disabilities
Current weather conditions, such as wind direction
4. If this information were static, administrators would have no need for a decision support system because the
evacuation route would be developed once and the job would be done. However, the information fluctuates constantly depending
on the time of day, time of year, and meteorological and economic conditions. Population densities also change, as does the
highway system. The task, then, is to analyze all the information given the specific conditions of the moment, find the best
solution, and find it quickly.
5. Some of the information that TEDSS needs resides within the power plant organization, such as the layout of the
power plant, information on deadly gasses, and the escalation rate of the accident. Other information is supplied by state agencies
and other external sources.
6. By processing this information in its simulation models, TEDSS provides output—some of it in graphic form—on the
following factors:
Evacuation routes and paths from any origin to assigned shelters
Projected volumes of traffic on the highway system
Highways that may become severely blocked by radiation
The time that will have elapsed before the last vehicle clears the area
7. With these outputs produced by TEDSS, planners can evaluate traffic management strategies, such as one-way
operation of highways, shoulder use, and flashing signals to reduce traffic congestion and to improve evacuation time.
DSS-1.b
Introductory Case
A Decision Support System (DSS) to Save Lives
illustrates types of decisions supported by DSS
Evacuation planning for nuclear power plant disaster
multi-factor
TEDSS.3&5
complex
+
High
Cost &
Benefit
dynamic
TEDSS.4
non-routine
unstructured
 TEDSS.2&7
best
solution
Force
TEDSS
Speed

quickly at
the moment
TEDSS.6
simulation: regression
color graphics output (N-GAGE, Sparks, Celtics-HO)
Details: Modeling…more efficient exodus. WSJ.30Sep05
Figure 2: The presentation of the Surry Power Station area consists of the highway
network and the protective action zones (PAZs).
NBC10.com/traffic
Provides similar graphic output (based multi-variate
model) that assists decision maker in selecting best route.
TEDDS: 2,7
DSS-1.b
Introductory Case
A Decision Support System (DSS) to Save Lives
Evacuation planning for nuclear power plant disaster (terrorism)
+
multi-factor
TEDSS.3&5
complex
High
Cost &
Benefit
dynamic
N-Site
(AHP)
TEDSS.4
non-routine
unstructured

best
solution
DSS
benefits
Force
TEDSS
TEDSS.2&7
Speed

quickly at
the moment
color graphics output (N-GAGE, Sparks, Celtics-HO)
Tools to Predict Likely Teroritst Moves. WSJ.30Sep05
DSS-13
DSS
What are the benefits of a DSS?
involves interaction between decision maker and IT system that
supplements & enhances human decision making by increasing:
V understanding of the problem/decision by examining force
intuition/judgment/experience of decision makers (spouse
choice, accounting policy, terrorist activity, pipeline path)
V management of complexity & lack of structure Excel
V sophistication of processing capabilities
Access
N-GAGE(AHP)
V speed of access to & processing of information
u
for an organization, the enhancement of human decision making
contributes to:
V increasing flexibility & productivity (Dock:Sparks, DHS:N-Site)
V decreasing costs (Jackpot : Celtics, Rx:CPOE)

u
Introduction
S-1
New Science of Management Decision
Herbert Simon (1960)
u …this journey (into the decision making process) is going to
lead…(to) a major revolution in the art and science of
management and organization (observed in CIO cases)
S.7.4
u …the computer and the new decision-making techniques
associated with it are bringing momentous changes like
machinery brought to manual jobs
S.xi.1
Proquest
u In 1960, described a terrain map of decision making that
provides a framework the discussion in new millennium
S.7.5
DSS.2
Types of Decisions
DSS-3
What types of decisions do you face?
Structured
Processing specific
info. in specified way
Recurring
repeatedly or
periodically
Programmed
TPS & MIS
Non-recurring
infrequently
Unstructured
No precise way to
get a right answer
AI (DSS)
CIO assessments (N-Gage)
Celtics Analytics Slam Dunk
Non-programmed
Plant Layout
Line Balancing
Spouse Choice (N-Gage)
Hiring Technical Managers
… or University Faculty
Accounting Policy
Caspian Sea Pipeline Path
Types of Decisions
S-2
Different Processes for Programmed vs
Nonprogrammed Decisions
u My reason for making the distinction is that
different techniques are used for handling the
programmed and the nonprogrammed aspects
of decision making
S.5.3
S-3.a
Types of Decisions
Two Polar Types of Decisions
u Programmed
V to the extent repetitive and routine so that a definite procedure
has been developed
S.5.4
V the name is from the computer field indicating a detailed
sequence of responses exists to a complex task environment S.6.2
u Nonprogrammed
V to the extent novel and unstructured so that no specific
procedures have been developed to respond to the situation S.6.1
V general problem solving capacities (judgment, creativity,
heuristics) are used to respond
S.6.3
V frequently ineffective and high cost so focus of DSS and AI S.6.4
S-3.b
Types of Decisions
Different Processes for Programmed vs
Nonprogrammed Decisions
u Programmed decisions are frequently observed so they can be
studied and better understood (sales, purchases, inventory,
registration, grades)
V traditionally, organizations use SOP (habit) and structure
(departments & committees)
S.9-10
V opportunity to use IT (TPS, MIS, JIT) so focus on
nonprogrammed (Gresham’s Law)
S-3.c
Types of Decisions
Different Processes for Programmed vs
Nonprogrammed Decisions
u Nonprogrammed decisions occur infrequently so they are less
studied and less understood (spouse choice, team project
assessments, accounting policy decisions, Caspian Sea pipeline path)
Vtraditionally, organizations use general problems solving
capabilities (judgment, heuristics, task forces, selection
/training)
Vopportunity to use IT (DSS &AI ) to study & improve
Human thinking, problem solving & learning have been
mysterious processes that have been labeled but not explained
S.13.1
nonprogrammed decision making will soon undergo as
fundamental a revolution as the one currently transforming
programmed decisions in business organizations
S.21.1
DSS-4
Continuum of decisions,
Complement of ITS
Recurring
Nonrecurring
Structured
Nonstructured
Which supplier to use, based Probably recurring
only on price
In between, if consider
factors other than price
Which car insurance to buy
at renewal time
In between
(Continuum / Not
discrete)
Mostly unstructured
Recurring
Whether to expand business Nonrecurring
into Eastern Europe
What plants to include in the Nonrecurring
landscaping around a new
building
How to use tax regulations Recurring
to fill out an income tax
form
How many lanes to put into Nonrecurring
a new bowling alley
In between
(Continuum / Not
discrete)
Unstructured if
consider ethical &
legal issues
In between
Types of Decisions
S-4
A Continuum of Decisions,
A Complement of ITS
u They are not really distinct types, but a whole continuum.
V We can find decisions of all shades of gray along the
continuum, the terms programmed and nonprogrammed are
concepts that define the range
S.5.3
V The obvious reason why repetitive decisions tend to be
programmed, and vice versa, is that if a particular problem
recurs often enough, a routine procedure will usually be
developed for solving it.
S.6.0
u Not all IT systems and strategies are appropriate for every
company or set of circumstances, but they are complementary
BroadVision @CIO.com (092101)
DSS-5.a
Figure 4.3
Phases of the Decision Making Process
Spouse
Choice
N-GAGE
(AHP)
GDSS [ DSS (AI )]

Complex
Ill-structured
Subjective
Examples
Hire technical manager
Accounting Choices
Access Assessment
Spouse Choice
N-Site
Pipeline
DSS-5.b
Decision Process
What is the Decision Making Process?
u
Intelligence - find what needs fixing
V recognizing a threat or opportunity
u
Design - find fixes
V developing possible solutions
u
Choice - pick a fix
V selecting the best solution
u
Implementation - apply the fix
V carrying out the solution, monitoring results & adjusting
Figure 4.3
S-5
Decision Process
Three Principal Phases of Decision Making
u Decision Making Comprises Three Phases
S.2.1
The first phase of the decision-making process searching the environment for conditions requiring a
decision - I shall call intelligence (borrowing the
military meaning).
The second phase inventing, developing and analyzing
possible courses of action - I shall call design activity.
The third phase - selecting a particular course of action
- I shall call choice activity.
S-6
Decision Process
Phases of Decision Making
u Generally, intelligence activity precedes design, and design
precedes choice.
S.3.2
u The cycle of phases is, however, far more complex than this
sequence suggests.
Figure 5.3
V Each phase in making a particular decision is itself a
complex decision-making process.
V The design phase may require new intelligence activities
V Problems at any given level generate subproblems that, in
turn, have their intelligence, design and choice phases.
DAY 2
N-GAGE
ENGAGEMENT
for
SPOUSE CHOICE
day.2
1.b WHAT IS A DSS?
6.1 flexible/interactive ITS support complex/ill-structured DM
6.2 typically applied to design/choice in non-program. decisions (Spouse Choice)
6.3 AHP is an example
8 momentous changes for (complex/ill-structured) DM
ProQuest shows applied to many diverse decisions
9 AHP developed to assist DM evaluate design / choice phases of
complex judgmental (qualitative criteria) problems
7 Analytic (decompose into components)
design
Hierarchy (organize into hierarchical structure)
Process (simpler pair-wise comparisons)
choice
13 Simple, Intuitive, Powerful
9 understanding (components of decision)
10 management of complexity (hierarchical structure, simpler choices)
11 sophistication / speed of information processing (infers priorities
from series of simple choices)
14a EC applied to spouse choice demonstrates DSS & components
assignment: use EC to weight presentation criteria
16 integrated into GDSS (Ranking Technical Managers)
DSS extended by groupware & telecommunications
Psychological Foundation:
Approach – Avoidance principle
Analytic: decompose
into components
(more complete analysis)
Hierarchical Structure
(smart people organize)
ABCDEF
ABCDEF
ABCDEF
ABCDEF
Process of pairwise comparisons: (easier 2 @ time, on all criteria)
N-GAGE PROCEDURES
►
►
►
►
►
►
Go to kennedyonline.us
Select N-Gage
Run
Run
File
New
► Enter file name & description
► Next
► Enter # of levels under the goal ( goal is
level 0)
► Next
► Enter goal name & description
► Done
► Select Design tab
► Select Criteria
Select level 1
► Name & describe criterion
► OK
► Name & describe other criteria as
previously until finished level 1
Select Criteria
► Select next level (2)
► Name & describe elements (alternatives)
► OK
► Name & describe other alternatives as
previously until finished level 2
► Select goal
► Select arrow button
to draw relationships
► Draw arrows from the goal to each criterion in
level 1
► When finished drawing arrows to define
relationships at level 1, select a criterion
► Draw arrows from the criterion in level 1 to
each alternative in level 2 to be rated on that
criterion
► Repeat the process for each criterion
N-GAGE PROCEDURES
► Select the Compare tab
► Double click the Goal (a pair-wise
comparison – PWC – table appears)
Select the first row in the table
► Compare (approach : avoidance) the
criteria using the number line
► Select the next row in the table
► Repeat the comparison process
► OK when the comparisons are finished in
the last row of the table
► Double click a criterion in level 1 (a pairwise comparison table appears)
► Select the first row in the table
► Repeat the comparison process in the table
just as previously
► Repeat the process for each criterion
► Select the Goal when finished the
comparison process for each criterion
► Select the Solution tab
► The hierarch of criteria & alternatives appears
with the weights derived from the PWC
process on the arrows and an IR
(inconsistency ratio) in each box
► If the IR > 0.10 a “Revise IR!” statement
appears in the box
► To revise the inconsistent comparisons,
select the compare tab
► Then, double click on the box with the
inconsistency message
► Redo the comparison process as before
► When all the inconsistencies have been
resolved, select the Goal and the select the
Solution tab
► Print the hierarchy (if the hierarchy does not
print on a single page, use print screen PrtSc – to copy and past into PowerPoint or
Word)
DSS-5.a
Figure 4.3
Phases of the Decision Making Process
Spouse N-GAGE
Choice (AHP)
GDSS [ DSS (AI )]

Subjective
Complex
Ill-structured
Examples
Hire technical manager
Accounting Choices
Access Assessment
Spouse Choice
N-Site
Pipeline
DAY 3
DECISION SUPPORT SYSTEMS
1.b WHAT IS A DSS?
6.1 flexible/interactive ITS support complex/ill-structured DM
6.2 typically applied to design/choice in non-programmed decisions (Spouse Choice)
6.3 AHP is an example
8 momentous changes for (complex/ill-structured) DM
ProQuest shows applied to many diverse decisions
9 AHP developed to assist DM evaluate design / choice phases of
complex judgmental (qualitative criteria) problems
7 Analytic (decompose into components)
design
Hierarchy (organize into hierarchical structure)
Process (simpler pair-wise comparisons)
choice
13 Simple, Intuitive, Powerful
9 understanding (components of decision)
10 management of complexity (hierarchical structure, simpler choices)
11 sophistication / speed of information processing (infers priorities
from series of simple choices)
14a EC applied to spouse choice demonstrates DSS & components
assignment: use EC to weight presentation criteria
16 integrated into GDSS (Ranking Technical Managers)
DSS extended by groupware & telecommunications
DSS-2
What is a DDS?
Artificial Intelligence
Excel
Access
Expert
Choice
( AHP)
N-Site
networks
Recurring
Programmed Structured
{
Non-recurring
Non-structured
}
Nonprogrammed
(qualitative)
DSS-6
DSS
What is a Decision Support System (DSS)?
u
u
u
DSS is a flexible and interactive IT system designed to support
decision making when problem is complex / unstructured
V frequently includes AI models like N-GAGE (AHP)
V must be flexible / interactive in response to / because of
problems that are complex / unstructured
usually involves qualitative criteria
typically in design / choice phases of decisions
ACCESS
Examples:
PROJECTS
V
V
V
Excel – statistical & what-if analysis (flexible budgets)
MS Access –data mining tools like queries and reports
N-GAGE – employs AHP to evaluate complex hierarchical
problems involving qualitative criteria
DSS-7
DSS-6
DSS
What is a Decision Support System (DSS)?
u
u
u
DSS is a flexible and interactive IT system designed to support
decision making when problem is complex / unstructured
V frequently includes AI models like N-GAGE (AHP)
V must be flexible / interactive in response to / because of
problems that are complex / unstructured
usually involves qualitative criteria
typically in design / choice phases of decisions
ACCESS
Examples:
PROJECTS
V
V
V
Excel – statistical & what-if analysis (flexible budgets)
MS Access –data mining tools like queries and reports
N-GAGE – employs AHP to evaluate complex hierarchical
problems involving qualitative criteria
DSS-7
A-12
Select Access Projects
Choice: order CIO.1 presentations (Rx
Tentative
dates
T
TH
CIO Team
Access Project
800
A:
Build)
930
Data Definition
(cradling : relevance)
B: Application Generators
(capturing : reliably)
BRING
C: Application Generators
(capturing : reliably)
FLASH
D: Application Generators
(capturing : reliably)
DRIVE
E:
Data Manipulation
(creating : analysis)
F:
Data Manipulation
(creating : analysis)
THURSDAY
200
DSS-7
DSS: AHP
Analytic Hierarchy Process
u
is an AI that models how experts approach complex
hierarchical decisions involving qualitative criteria
H
H
H
Analytic - decompose complex problems into components
(criteria / alternatives)
Hierarchy - organize into meaningful structure
Process of pair-wise comparisons involving trade-offs
assigns weights to the criteria and preferences to the
alternatives
more natural to compare two things than numerous
elements
(Saaty 2000, 1990, 1977)
Analytic: decompose
into components
Hierarchical Structure
B D H I J Rx
B D H I J Rx B D H I J Rx
Process of pairwise comparisons
B D H I J Rx
ASSIGNMENT: N-GAGE (ASSESS CIO.1)
DSS-8
DSS: AHP
Simple,
Intuitive…Powerful
AHP has been applied to many diverse decisions:
(ProQuest)
V Strategic Planning for a Caspian Sea Pipeline Project
2012
V AHP-Delphi GDSS for Locating Whey Processing Facility
2008
u
V N-Site: An Anti-terrorist Distributed Consensus Building and
Negotiation Support System across the WWW
2006
► Evaluating Characteristics of Financial Information
2004, 1995
V TQI Benchmarking Tools for Evaluating TQM programs
2003
V Translating Financial Phrases into Numerical Probabilities
1997
V
Consensus Ranking of Technical Manager Candidates
1996
Qualitative Characteristics
of Financial Information
Decision Usefulness
design
Analytical: decompose into components
RELEVANCE
RELIABILITY
Hierarchical Structure
Predictive
Value
Feedback
Value
Timeliness
Verifiability Neutrality
Process of pairwise comparisons
choice
FASB: SFAC2
understanding
Comparability
(including Consistency)
Representational
Faithfulness
manage complexity
Similar to:
Choice spouse &
CIO/Access assessments
DSS-10
AHP QUESTIONNAIRE
Concept A
o
o
Extreme
o
Very
strong
o
o
Strong
o
o
o
Moderate
o
Equal
o
o
o
Moderate
o
Strong
o
o
Very
strong
o
o
Extreme
Concept B
Reliability
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Relevance
Reliability
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Cost
Reliability
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Materiality
Reliability
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Comparability
Relevance
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Cost
Relevance
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Materiality
Relevance
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Comparability
Cost
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Materiality
Cost
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Comparability
Materiality
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Comparability
DSS-12.
DSS: EC
Analytical Hierarchy Proces:
Decision Support for complex judgmental problems
u
While the applications of AHP appear different, each
“incorporated judgments on intangible criteria and other
elements alongside tangible ones which have known
measurements.”
Saaty 1987 p.157
u
N-GAGE & Expert Choice are an expert systems
(artificial intelligence) based on AHP designed
specifically to make explicit the judgments of experts in
evaluating complex unstructured problems involving
qualitative criteria
DSS-13
DSS
What are the benefits of a DSS?
u
involves interaction between decision maker and IT system
that enhances & supplements human decision making by
increasing:
V understanding of the problem/decision by examining
intuition/judgment/experience of decision makers
V management of complexity and lack of structure
V sophistication of processing capabilities
V speed of access to and processing of information
u
for an organization, the enhancement of human decision
making contributes to:
V increasing flexibility and productivity
V decreasing costs
DSS-14.a
What are the Components of a DSS?
Expert Choice
Prepares
Auditors
Users
Graphics
&
prompts
What makes
accounting data
decision useful?
What accounting
alternative should be
used to report these
events?
AHP
Figure 4.5
Pairwise
comparisons
DSS-14.b
What are the Components of a DSS?
Expert Choice
graphics & prompts
AHP
pairwise
comparisons
Figure 5.6
DSS-14.c
DSS
What are the components of a DSS?
DSSs vary in application and complexity, but all share specific
components:
u
user interface
V permits user to enter information, commands and models
V should be simple, flexible, consistent
u
model management
V stores and manages the DSS models
u
data management
V stores and maintains information
Relate to Expert Choice
DSS-15
DSS
What is the process of developing DSS?
u
Intelligence
V
examine the problem to determine if a DSS is needed
DSS if the problem is complex / unstructured
TPS, IOS or MIS if the problem is structured / routine
DSS.2-3
u
Design
identify what is available to buy as an alternative to building
V DSS generators: Excel, Expert Choice
(Research)
V
u
Choice
V
u
compare build to buy considering cost, fit with the
problem/decision, ease of use
Implementation
V
test, evaluate and revise the DSS
(Research)
Consensus Ranking Technical Manager:
similar spouse choice & CIO.1 ranking
DSS-16a
Facilitators:
Researchers
Team Members:
Nursing Directors
Nurse Managers
Staff Nurse
IT Tools
DSS supports team DM
when problem is
complex / unstructured
(qualitative criteria)
as in CIO.1 RANKING
}
GDSS supports
TEAM STRATEGY
Netscape/ Outlook
N-GAGE
LAN / internet
DSS-16.b
GDSS
What is Group Decision Support System (GDSS)?
DSS that is designed to support decision making by a team
especially when decision is complex /unstructured
DSS-2
typically involves qualitative criteria
DSS.17
H.135.6
GASB - setting accounting policies
N-Site – multi-national response to terrorism
Assign rankings to CIO.1 team presentations
Consensus Ranking of Technical Manager
Candidates
Omega v24 n5 pp523-538
DSS-16.c
GDSS
What are the components of a GDSS?
People
Team Members
H united by a common goal & task interdependence
H experience, perspective, judgment
Facilitators
H nontechnical role to conduct the meeting
H technical role related to IT tools
IT Tools
Omega
Groupware permit team to provide input
simultaneously/anonymously and view by others
DSS capabilities to classify, analyze, and rank ideas
Telecommunications hardware/software to network
team members (LAN, WAN, Internet)
DSS-17
Consensus Ranking
Consensus Ranking of
Technical Manager Candidates
u Hiring technical managers is:
Complex
H broad range of skills is required
H candidates have different skill sets
Unstructured
H qualitative criteria have no inherent scale / metric for
trade-offs between criteria or comparisons between
candidates
H DMs have implicit criteria that may not be appropriate (e.g.
religion, sex, race) and should be challenged
Team / Group Decision
H perceived importance of required skills (hiring criteria)
will vary within and between organizational levels
DSS-18
Consensus Ranking
What are the phases of
team/group decision making?
I
Develop explicit functional criteria that reflect
organizational perspectives
Brainstorming (Table 1, Table 2)
Issue categorization & analysis (Table 3, Figure 1)
19.a-b
II Assign priority to criteria & preferences to candidates
Voting (Expert Choice, Figure 2)
20.a-b
III Achieve a consensus while minimizing the dysfunctional
effects of groups (groupthink, conflict, status)
Ranking of the Candidates (Tables 6 & 8)
21.a-b
DSS-19.a
Consensus Ranking: Phase I
(I) Developing the Hiring Criteria Hierarchy
Each Decision Maker (DM) develops a list of
criteria.
Facilitators aggregate individual lists of criteria
and develop a comprehensive list for each DM
group.
Table 1
Facilitators do a comprehensive literature search
to prepare operational definitions of the criteria.
Table 2
Omega: 525-8
DSS-19.b
Consensus Ranking: Phase I
(I) Developing the Hiring Criteria Hierarchy
Each DM identifies related criteria sets and rank
orders the criteria within each set.
Table 3
Facilitators collect the rankings and develop a
synthesized hierarchy of criteria for each DM
group.
Figure 1
Facilitators and each DM group meet to finalize
each group’s criteria hierarchy.
Omega : 525-8
DSS-20.a
Consensus Ranking: Phase II
(II) Assigning Importance to Criteria &
Preferences to Candidates
Facilitators familiarize DMs with principles of AHP
and suitable AHP software such as Expert Choice (EC).
DMs use EC for pairwise comparisons between criteria
in the hierarchy in Figure 1.
EC alerts DMs to logical inconsistencies and
encourages DMs to repeat the pairwise comparisons
process in the previous step.
HR does initial screening and identifies several eligible
candidates.
Omega: 528-30
DSS-20.b
Consensus Ranking: Phase II
(II) Assigning Importance to Criteria &
Preferences to Candidates
DM groups interview candidates using their criteria
hierarchy.
DMs use EC for pairwise comparisons to evaluate
candidates on each criterion at lowest level of
hierarchy.
EC alerts DMs to logical inconsistencies and
encourages DMs to repeat the
comparisons process in the previous step.
pairwise
Table 4
Omega: 528-30
DSS-21.a
Consensus Ranking: Phase III
(III) Identifying the Consensus Ranking
of the Candidates
Facilitators provide anonymous feedback to all
the DMs about each group’s average weights and
preferences.
Figure 2
If the DMs are satisfied that there is adequate
consistency within the group, the process
proceeds to Step 2 below
Otherwise, DMs to go back to Step 6 of
Phase 2.
Table 5
Omega: 530-34
DSS-21.b
Consensus Ranking: Phase III
(III) Identifying the Consensus Ranking
of the Candidates
Facilitators input the final data from Step 1 to
MAH and obtain a consensus ranking of the
candidates.
Tables 6
Facilitators meet with DMs. Unless unforeseen
dissatisfactions, the process of employment offers
begins in the order prescribed by the GDSS
(AHP & MAH).
Tables 8
Omega: 530-34
DSS-22.a
GDSS
What are the benefits of a GDSS?
u
Achieves the benefits of a team approach to a decision by:
V
compressing time /space so individuals can interact
V
brainstorming to share ideas, facilitate consensus and
achieve acceptance
V
perspectives from different organizational levels
revealing required expertise in candidates (nursing
directors, nurse managers, staff nurses)
V
explicit functional criteria are encouraged rather than
implicit / inappropriate criteria such as sex, race,
Omega
religion.
H.138.2
DSS-22.b
GDSS
What are the benefits of a GDSS?
u
minimizes the problems of group processes including:
V
groupthink in which different ideas are suppressed
V
conflict by keeping focus on problem not personalities
V
status differences that restrict participation (nursing
directors, nurse managers, staff nurses)
V
sequential interaction in face-to-face meeting,
Omega
H.138.2