Decision Support and Business Intelligence Systems(9th Ed.,
Prentice Hall)Chapter 2:Decision Making, Systems, Modeling, and
Support
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Learning ObjectivesUnderstand the conceptual foundations of
decision makingUnderstand the need for and the nature of models in
decision makingUnderstand Simon's four phases of decision making:
intelligence, design, choice, and implementation
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Learning ObjectivesRecognize the concepts of rationality and
bounded rationality and how they relate to decision
makingDifferentiate between the concepts of making a choice and
establishing a principle of choiceLearn how DSS provide support for
decision making in practiceUnderstand the systems approach
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Opening Vignette:Decision Modeling at HP Using
SpreadsheetsCompany backgroundProblemProposed solutionResultsAnswer
and discuss the case questions
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Decision Support Systems (DSS)Dissecting DSS into its main
concepts
Building successful DSS requires a through understanding of
these concepts
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Characteristics of Decision MakingGroupthinkEvaluating what-if
scenariosExperimentation with a real system!Changes in the
decision-making environment may occur continuouslyTime pressure on
the decision makerAnalyzing a problem takes time/moneyInsufficient
or too much information
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Characteristics of Decision MakingBetter decisionsTradeoff:
accuracy versus speedFast decision may be detrimentalAreas
suffering most from fast decisions personnel/human resources
(27%)budgeting/finance (24%)organizational structuring
(22%)quality/productivity (20%)IT selection and installation
(17%)process improvement (17%)
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Decision MakingA process of choosing among two or more
alternative courses of action for the purpose of attaining a
goal(s)Managerial decision making is synonymous with the entire
management process - Simon (1977)e.g., PlanningWhat should be done?
When? Where? Why? How? By whom?
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Decision Making and Problem SolvingA problem occurs when a
systemdoes not meet its established goalsdoes not yield the
predicted results, ordoes not work as plannedProblem is the
difference between the desired and actual outcomeProblem solving
also involves identification of new opportunities
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Decision Making and Problem SolvingAre problem solving and
decision making different? Or, are they the same thing?Consider
phases of the decision process Phase (1) Intelligence Phase (2)
DesignPhase (3) Choice, andPhase (4) Implementation(1)-(4): problem
solving; (3): decision making(1)-(3): decision making; (4): problem
solvingThis book: decision making problem solving
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Decision-Making DisciplinesBehavioral: anthropology, law,
philosophy, political science, psychology, social psychology, and
sociologyScientific: computer science, decision analysis,
economics, engineering, the hard sciences (e.g., biology,
chemistry, physics), management science/operations research,
mathematics, and statisticsEach discipline has its own set of
assumptions and each contributes a unique, valid view of how people
make decisions
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Decision StyleThe manner by which decision makers think and
react to problemsperceive a problemcognitive responsevalues and
beliefsWhen making decisions, peoplefollow different
steps/sequencegive different emphasis, time allotment, and priority
to each steps
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Decision Style Personality temperament tests are often used to
determine decision styles There are many such
testsMeyers/Briggs,True Colors (Birkman),Keirsey Temperament
Theory, Various tests measure somewhat different aspects of
personalityThey cannot be equated!
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Decision Style Decision-making stylesHeuristic versus
AnalyticAutocratic versus DemocraticConsultative (with individuals
or groups)A successful computerized system should fit the decision
style and the decision situationShould be flexible and adaptable to
different users (individuals vs. groups)
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Decision MakersSmall organizationsIndividualsConflicting
objectivesMedium-to-large organizationsGroupsDifferent styles,
backgrounds, expectationsConflicting objectivesConsensus is often
difficult to reachHelp: Computer support, GSS,
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ModelA significant part of many DSS and BI systemsA model is a
simplified representation (or abstraction) of realityOften, reality
is too complex to describeMuch of the complexity is actually
irrelevant in solving a specific problemModels can represent
systems/problems at various degrees of abstraction
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Types of ModelsModels can be classified based on their degree of
abstraction
Iconic models (scale models)
Analog models
Mental Models
Mathematical (quantitative) modelsDegree of
abstractionLessMore
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The Benefits of ModelsEase of manipulationCompression of
timeLower cost of analysis on modelsCost of making mistakes on
experimentsInclusion of risk/uncertaintyEvaluation of many
alternatives Reinforce learning and trainingWeb is source and a
destination for it
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Phases of Decision-Making ProcessHumans consciously or sub
consciously follow a systematic decision-making process - Simon
(1977) IntelligenceDesignChoiceImplementation(?) Monitoring (a part
of intelligence?)
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Simons Decision-Making Process
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Decision-Making: Intelligence PhaseScan the environment, either
intermittently or continuouslyIdentify problem situations or
opportunitiesMonitor the results of the implementationProblem is
the difference between what people desire (or expect) and what is
actually occurringSymptom versus ProblemTimely identification of
opportunities is as important as identification of problems
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Decision-Making: Intelligence PhasePotential issues in
data/information collection and estimationLack of dataCost of data
collectionInaccurate and/or imprecise dataData estimation is often
subjectiveData may be insecureKey data may be qualitativeData
change over time (time-dependence)
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Decision-Making: Intelligence PhaseProblem
ClassificationClassification of problems according to the degree of
structuredness Problem Decomposition Often solving the simpler
subproblems may help in solving a complex problemInformation/data
can improve the structuredness of a problem situationProblem
OwnershipOutcome of intelligence phase:A Formal
ProblemStatement
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Decision-Making: The Design PhaseFinding/developing and
analyzing possible courses of actionsA model of the decision-making
problem is constructed, tested, and validatedModeling:
conceptualizing a problem and abstracting it into a quantitative
and/or qualitative form (i.e., using symbols/variables)Abstraction:
making assumptions for simplificationTradeoff (cost/benefit): more
or less abstractionModeling: both an art and a science
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Decision-Making: The Design PhaseSelection of a Principle of
ChoiceIt is a criterion that describes the acceptability of a
solution approachReflection of decision-making objective(s) In a
model, it is the result variableChoosing and validating
againstHigh-risk versus low-riskOptimize versus satisficeCriterion
is not a constraint
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Decision-Making: The Design PhaseNormative models (=
optimization)the chosen alternative is demonstrably the best of all
possible alternativesAssumptions of rational decision makersHumans
are economic beings whose objective is to maximize the attainment
of goalsFor a decision-making situation, all alternative courses of
action and consequences are knownDecision makers have an order or
preference that enables them to rank the desirability of all
consequences
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Decision-Making: The Design PhaseHeuristic models (=
suboptimization)the chosen alternative is the best of only a subset
of possible alternativesOften, it is not feasible to optimize
realistic (size/complexity) problemsSuboptimization may also help
relax unrealistic assumptions in modelsHelp reach a good enough
solution faster
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Decision-Making: The Design PhaseDescriptive modelsdescribe
things as they are or as they are believed to be (mathematically
based)They do not provide a solution but information that may lead
to a solutionSimulation - most common descriptive modeling method
(mathematical depiction of systems in a computer environment)
Allows experimentation with the descriptive model of a system
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Decision-Making: The Design PhaseGood Enough, or
Satisficingsomething less than the bestA form of
suboptimizationSeeking to achieving a desired level of performance
as opposed to the bestBenefit: time saving
Simons idea of bounded rationality
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Decision-Making: The Design PhaseDeveloping (Generating)
AlternativesIn optimization models (such as linear programming),
the alternatives may be generated automatically In most MSS
situations, however, it is necessary to generate alternatives
manuallyUse of GSS helps generating alternativesMeasuring/ranking
the outcomes Using the principle of choice
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Decision-Making: The Design PhaseRiskLack of precise knowledge
(uncertainty)Risk can be measured with probabilityScenario (what-if
case)A statement of assumptions about the operating environment
(variables) of a particular system at a given time Possible
scenarios: best, worst, most likely, average (and custom
intervals)
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Decision-Making: The Choice PhaseThe actual decision and the
commitment to follow a certain course of action are made hereThe
boundary between the design and choice is often unclear (partially
overlapping phases)Generate alternatives while performing
evaluationsIncludes the search, evaluation, and recommendation of
an appropriate solution to the modelSolving the model versus
solving the problem!
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Decision-Making: The Choice PhaseSearch approachesAnalytic
techniques (solving with a formula)Algorithms (step-by-step
procedures)Heuristics (rule of thumb)Blind search (truly random
search)Additional activitiesSensitivity analysisWhat-if
analysisGoal seeking
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Decision-Making: The Implementation PhaseNothing more difficult
to carry out, nor more doubtful of success, nor more dangerous to
handle, than to initiate a new order of things. - The Prince,
Machiavelli 1500sSolution to a problem = Change Change
management?Implementation: putting a recommended solution to
work
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How Decisions Are Supported
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How Decisions Are SupportedSupport for the Intelligence
PhaseEnabling continuous scanning of external and internal
information sources to identify problems and/or
opportunitiesResources/technologies: Web; ES, OLAP, data
warehousing, data/text/Web mining, EIS/Dashboards, KMS, GSS,
GIS,Business activity monitoring (BAM)Business process management
(BPM)Product life-cycle management (PLM)
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How Decisions Are SupportedSupport for the Design PhaseEnabling
generating alternative courses of action, determining the criteria
for choiceGenerating alternativesStructured/simple problems:
standard and/or special models Unstructured/complex problems: human
experts, ES, KMS, brainstorming/GSS, OLAP, data/text miningA good
criteria for choice is critical!
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How Decisions Are SupportedSupport for the Choice PhaseEnabling
selection of the best alternative given a complex constraint
structureUse sensitivity analyses, what-if analyses, goal
seekingResourcesKMSCRM, ERP, and SCM Simulation and other
descriptive models
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How Decisions Are SupportedSupport for the Implementation
PhaseEnabling implementation/deployment of the selected solution to
the systemDecision communication, explanation and justification to
reduce resistance to changeResourcesCorporate portals, Web
2.0/Wikis Brainstorming/GSS KMS , ES
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New Technologies to Support Decision MakingWeb-based
systemsm-CommercePDA, Cell phones, Tablet PCsGSS with
visual/immersive presenceRFID and other wireless technologiesFaster
computers, better algorithms, to process huge amounts of
heterogeneous/distributed data
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End of the Chapter
Questions / Comments
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