pom class6
TRANSCRIPT
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Positioning the Firm: Cost
Waste elimination relentlessly pursuing the removal of all waste Examination of cost structure
looking at the entire cost structure for reduction potential
Lean production providing low costs through disciplined operations
1-1
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Positioning the Firm: Speed
Fast moves, Fast adaptations, Tight linkages Internet Customers expect immediate responses
Service organizations always competed on speed (McDonalds, LensCrafters,
and Federal Express)
Manufacturers time-based competition: build-to-order production and
efficient supply chains
Fashion industry two-week design-to-rack lead time of Spanish retailer, Zara
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Positioning the Firm: Quality
Minimizing defect rates or conforming to designspecifications
Ritz-Carlton - one customer at a time
Service system designed to move heaven and earth
to satisfy customer
Employees empowered to satisfy a guests wish
Teams set objectives and devise quality action plans
Each hotel has a quality leader
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Positioning the Firm: Flexibility
Ability to adjust to changes in product mix,production volume, or design
Mass customization: the mass production ofcustomized parts
National Bicycle Industrial Company offers 11,231,862 variations
delivers within two weeks at costs only 10% abovestandard models
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Policy Deployment
Policy deployment translates corporate strategy into measurable
objectives
Hoshins
action plans generated from the policydeployment process
1-5
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Policy Deployment
Derivation of an Action Plan Using Policy Deployment
1-6
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Balanced Scorecard
Balanced scorecard measuring more than financial performance
1. finances
2. customers
3. processes
4. learning and growing
Key performance indicators
set of measures to help managers evaluateperformance in critical areas
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Balanced Scorecard Worksheet
1-8
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Balanced Scorecard
1-9
Radar Chart Dashboard
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Copyright 2011 John Wiley & Sons, Inc.Copyright 2011 John Wiley & Sons, Inc.
Operations Strategy
Products
1-10
Services Process
and
Technology
Capacity
Human
Resources Quality
Facilities Sourcing Operating
Systems
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Copyright 2011 John Wiley & Sons, Inc.Copyright 2011 John Wiley & Sons, Inc.
Decision Analysis
Quantitative methods a set of tools for operations manager
Decision analysis
a set of quantitative decision-makingtechniques for decision problems in whichuncertainty exists
Example of an uncertain situation
demand for a product may vary between 0 and200 units, depending on the state of market
Supplement 1-11
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Problem Formulation
A decision problem is characterized by decision
alternatives, states of nature, and resultingpayoffs.
The decision alternatives are the differentpossible strategies the decision maker canemploy.
The states of nature refer to future events, notunder the control of the decision maker, whichmay occur in the future. States of nature shouldbe defined so that they are mutually exclusiveand collectively exhaustive.Examples,
high or low demand for a product
good or bad economic conditions
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Payoff Tables
The consequence resulting from a specificcombination of a decision alternative and astate of nature is a payoff.
A table showing payoffs for all combinations
of decision alternatives and states of nature isa payoff table.
Payoffs can be expressed in terms of profit,cost, time, distance or any other appropriate
measure.
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Payoff Table
Payoff table method for organizing and illustrating payoffs from
different decisions given various states of nature
Payoff
outcome of a decision
Supplement 1-14
States Of Nature
Decision a b
1 Payoff 1a Payoff 1b2 Payoff 2a Payoff 2b
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Copyright 2011 John Wiley & Sons, Inc.Copyright 2011 John Wiley & Sons, Inc.
Decision Making
Decision making under risk probabilities can be assigned to the
occurrence of states of nature in the
future Decision making under uncertainty
probabilities can NOT be assigned to the
occurrence of states of nature in thefuture
Supplement 1-15
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Decision Trees
A decision tree is a chronologicalrepresentation
of the decision problem. Each decision tree has two types of nodes;
round nodes correspond to the states of naturewhile square nodes correspond to the decision
alternatives. The branches leaving each round node
represent the different states of nature while thebranches leaving each square node representthe different decision alternatives.
At the end of each limb of a tree are the payoffsattained from the series of branches making upthat limb.
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Decision Making Criteria UnderUncertainty
Maximax choose decision with the maximum of the
maximum payoffs
Maximin choose decision with the maximum of the
minimum payoffs
Minimax regret choose decision with the minimum of the
maximum regrets for each alternative
Supplement 1-17
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Decision Making Criteria UnderUncertainty
Hurwicz
choose decision in which decision payoffs areweighted by a coefficient of optimism, alpha
coefficient of optimism is a measure of adecision makers optimism, from 0(completelypessimistic) to 1(completely optimistic)
Equal likelihood (La Place)
choose decision in which each state of nature isweighted equally
Supplement 1-18
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Southern Textile Company
Supplement 1-19
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive Conditions
Expand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
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Maximax Solution
Supplement 1-20
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive ConditionsExpand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
Expand: $800,000
Status quo: 1,300,000 Maximum
Sell: 320,000
Decision: Maintain status quo
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Maximin Solution
Supplement 1-21
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive ConditionsExpand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
Expand: $500,000 Maximum
Status quo: -150,000
Sell: 320,000
Decision: Expand
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Minimax Regret Solution
Supplement 1-22
States of NatureGood Foreign Poor Foreign
Competitive Conditions Competitive Conditions
$1,300,000 - 800,000 = 500,000 $500,000 - 500,000 = 0
1,300,000 - 1,300,000 = 0 500,000 - (-150,000)= 650,0001,300,000 - 320,000 = 980,000 500,000 - 320,000= 180,000
Expand: $500,000 Minimum
Status quo: 650,000
Sell: 980,000Decision: Expand
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Hurwicz Criteria
Supplement 1-23
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive ConditionsExpand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
= 0.3 1 - = 0.7
Expand: $800,000(0.3) + 500,000(0.7) = $590,000 Maximum
Status quo: 1,300,000(0.3) -150,000(0.7) = 285,000Sell: 320,000(0.3) + 320,000(0.7) = 320,000
Decision: Expand
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Equal Likelihood Criteria
Supplement 1-24
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive ConditionsExpand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
Two states of nature each weighted 0.50
Expand: $800,000(0.5) + 500,000(0.5) = $650,000 Maximum
Status quo: 1,300,000(0.5) -150,000(0.5) = 575,000
Sell: 320,000(0.5) + 320,000(0.5) = 320,000
Decision: Expand
Decision Making under Risk
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Copyright 2011 John Wiley & Sons, Inc.Copyright 2011 John Wiley & Sons, Inc.
Decision Making under Risk(with Probabilities)
Risk involves assigning probabilities tostates of nature
Expected value
a weighted average of decision outcomesin which each future state of nature isassigned a probability of occurrence
Supplement 1-25
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Copyright 2011 John Wiley & Sons, Inc.Copyright 2011 John Wiley & Sons, Inc.
Expected Value
Supplement 1-26
EV (x) = p(xi)xin
i =1
xi = outcome i
p(xi) = probability of outcome i
where
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Decision Making with Probabilities
Supplement 1-27
STATES OF NATURE
Good Foreign Poor Foreign
DECISION Competitive Conditions Competitive ConditionsExpand $ 800,000 $ 500,000
Maintain status quo 1,300,000 -150,000
Sell now 320,000 320,000
p(good) = 0.70 p(poor) = 0.30EV(expand): $800,000(0.7) + 500,000(0.3) = $710,000
EV(status quo): 1,300,000(0.7) -150,000(0.3) = 865,000 Maximum
EV(sell): 320,000(0.7) + 320,000(0.3) = 320,000
Decision: Status quo
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Expected Value of Perfect Information
Frequently, information is available which can
improve the probability estimates for the states ofnature.
The expected value of perfect information (EVPI) isthe increase in the expected profit that would result
if the decision maker knew with certainty whichstate of nature would actually occur.
The EVPI provides an upper bound on the
expected value of any sample or surveyinformation. Thus, it is the maximum amount thatmight be paid to gain information that would resultin a decision better than the one made without
perfect information.
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EVPI
Good conditions will exist 70%of the time choose maintain status quo with payoff of$1,300,000
Poor conditions will exist 30%of the time choose expand with payoff of $500,000
Expected value given perfect information=$1,300,000 (0.70) + 500,000 (0.30)= $1,060,000
Recall that expected value without perfectinformation was $865,000 (maintain status quo)
EVPI=$1,060,000 - 865,000 = $195,000
Supplement 1-29
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Sequential Decision Trees
A graphical method for analyzing decisionsituations that require a sequence of decisionsover time
Decision tree consists of
Square nodes - indicating decision points Circles nodes - indicating states of nature Arcs - connecting nodes
Supplement 1-30
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Risk Analysis
Risk analysis helps the decision maker
recognize the difference between:
the expected value of a decisionalternative, and
the payoff that might actually occur The risk profile for a decision alternative
shows the possible payoffs for the decisionalternative along with their associatedprobabilities.
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Sensitivity Analysis
Sensitivity analysis can be used to determine
how changes to the following inputs affectthe recommended decision alternative:
probabilities for the states of nature
values of the payoffs If a small change in the value of one of the
inputs causes a change in the recommendeddecision alternative, extra effort and careshould be taken in estimating the input value.