Operations As A Basic Function OPERATIONS
MARKETING
© 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
FINANCE
Ch 1 - 5
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Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 2
Historical Events In POM • • • • • • •
Industrial Revolution Scientific Management Human Relations Management Science Quality Revolution Information Age Globalization
© 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 7
Historical Events In POM Industrial Revolution Steam engine Division of labor Interchangeable parts
1769 1776 1790
James Watt Adam Smith Eli Whitney
Scientific Management Principles Time / motion study Activity scheduling chart Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
1911 1911 1912
Frederick W. Taylor Frank & Lillian Gilbreth Henry Gant Ch 1 - 8
Human Relations Hawthorne studies Motivation theories
1930 1940s 1950s 1960s
Elton Mayo Abraham Maslow Frederick Hertzberg Douglas McGregor
Management Science Linear programming Digital computer Simulation, PERT/CPM, Waiting line theory MRP Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
1947 1951 1960
George Dantzig Remington Rand Research groups
1960s Joseph Orlicky, IBM Ch 1 - 9
Quality Revolution JIT TQM Reengineering
1970s Taiichi Ohno, Toyota 1980s W. Edwards Deming, Joseph Juran, et. al. 1990s Hammer, Champy
Information Age EDI, EFT, CIM Internet, World Wide Web
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
1970s Numerous 1980s individuals and 1990s companies 1990s Tim Berners-Lee
Ch 1 - 10
Globalization Worldwide markets and operations Supply chain management Electronic commerce Mass customization
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
1990s Numerous individuals and companies
Ch 1 - 11
Operations As The Technical Core
Operations
Workers
Finance
Personnel
Purchasing
Suppliers
Capital Markets, Stockholders
Marketing Customers
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 6
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Issues & Trends In Operations 1. Intense competition 2. Global markets, global sourcing, and global financing 3. Importance of strategy 4. Product variety and mass customization 5. More services Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 29
Issues & Trends In Operations 6. Emphasis on quality 7. Flexibility 8. Advances in technology 9. Worker involvement 10. Environmental and ethical concerns
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 30
ก ก =
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ภภ(Productivity Measurement) ภ=
(Total Productivity) % && ' + )*' + +* ,
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% && ' )*' +* ,
ภภ(Productivity Measurement) Years
Units produced Labour (man days) Raw materials(kg) Machine(hours) Total sales Profit
2000 1,250 800 300 750 10,000 1,400
2001 1,750 1,200 450 1,100 21,000 4,550
ภภ(Productivity Measurement) Years Units produced per man hour
2000
2001
1,250 800
= 1.56
1,750 1,200
= 1.46
Units produced per kg raw material 1,250 300
= 4.17
1,750 450
= 3.90
Units produced per machine hour
= 1.67
1,750 = 1.59 1,100
1,250 750
(OUTPUT) PRODUCT = NO&P Q กNR'S QUALITY = WX*YZ WNRS' COST = Q')*'\'ก DELIVERY = ก -.& O,P Q & SAFETY = X O Z \'ก )` & ' MORALE = N aก` &\ ENVIRONMENT = -Z % QO ETHIC = , Y
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Cost Product cost Design Productivity Delivery Speed On -time JIT Supply chain Quality Recognition Product quality Flexibility Produce to Order JIT CAD CAM
ภ%&*1 ภภ, ! , ! ภ& ภ!ภ& Job to Order Low Volume Standardization High Volume Short Life cycle Long Life Cycle Introduction /Growth stage Maturity / Decline stage Customer focus Low cost Long time Delivery Short time Delivery
Strategic Planning Mission & Vision Voice of the Business
Marketing Strategy Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 2/e
Business Strategy
Operations Strategy
Voice of the Customer
Financial Strategy Ch 2 - 11
Organization Of Book Strategy of productive systems Designing productive systems Operating Productive systems
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 33
Strategy Of Productive Systems –1. Operations & competitiveness –2. Operations strategy –3. Quality management 70 60 50 40 30 20 10 0 0
©2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 2/e
1
2
3
4
5
6
7
Ch 1 - 34
Designing Productive Systems `4.ภภ0% !#$ % `5. ภภภภ`6.ภ' ( ภ' . `7. ภ`8. ภภŠ 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 35
Operating Productive Systems 9. ภ10 ภ$ ! 11 $ 12 ภภภ13 ภภ' ภ14 ภ! ภ15 ภ! !0- $" Š2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
Ch 1 - 36
Demand
Industry Life Cycle Model
Development
Growth
Maturity
Decline
Time User / buyer Few Competitive Few Conditions Demand : Supply D?
Growing Saturate Drop Entry Fight to maintain Some Exit Fight for share efficiency/low cost Selective distribution D>S D_>S D<S
Decision Analysis â&#x20AC;˘ i# & "# ภ!- 2 -! j ! *+ ! !#!
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%# ภ(. E , ภภ$ 1. ภ'ภ0F% ( ภ! &% (Alternative acts or Strategies) 2. ภ' ( ?, ( $- ' !ภ0% ( Event or State of Nature) 3. 0 $ ภ( Payoff) 4. ภภ?#$ "!# $ % 5. ' ( ภ' ( ภภภ$ 'ภ0F% # ' Payoff Table Decision 1 2
States Of Nature a b Payoff 1a Payoff 1b Payoff 2a Payoff 2b
• States of nature – events that may occur in the future – decision maker is uncertain which state of nature will occur – decision maker has no control over the states of nature
A payoff is the outcome of the decision
© 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 3
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Decision making Criteria Under Uncertainty • Maximax criterion – choose decision with the maximum of the maximum payoffs
• Maximin criterion – choose decision with the maximum of the minimum payoffs
• Minimax regret criterion – choose decision with the minimum of the maximum regrets for each alternative C2 Supp - 6
Decisionmaking Under Uncertainty Example States Of Nature
Decision Expand *, # " %ภŕ¸
Competitive Conditions $ 800,000 1,300,000 320,000
Competitive Conditions $ 500,000 -150,000 320,000
C2 Supp - 8
Maximax Solution "% % *, # " %ภŕ¸
$800,000 1,300,000 -- Maximum 320,000
Decision: *, #
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 9
Maximin Solution "% % *, # " %ภŕ¸
$500,000 -- Maximum -150,000 320,000
Decision: "% %
Š 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 10
Decision making With Probabilities • Risk involves assigning probabilities to states of nature • Expected value is a weighted average of decision outcomes in which each future state of nature is assigned a probability of occurrence
© 2000by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 14
Expected Value n EV( x) = ∑ p( xi) xi i=1 where xi = outcome i p( xi) = probability of outcome i
© 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 15
Expected Value Example 70% 1 ภ$ '#) , 30% 1 ภ$ '#) , ? EV , = $ 800,000 (0.70) + 500,000 (0.30) = $710,000 EV ? ?
= 1,300,000 (0.70) -150,000 (0.30) = 865,000 -- Maximum
EV , ภŕ¸
= 320,000 (0.70) + 320,000 (0.30) = 320,000
Decision: ? ?
Expected Value Of Perfect Information • The maximum value of perfect information to the decision maker • EVPI = (expected value given perfect information) - (expected value without perfect information)
© 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
C2 Supp - 17
EVPI Example 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 EVPI = $1,060,000 - 865,000 = $195,000
Sequential Decision Trees • A graphical method for analyzing decision situations that require a sequence of decisions over time • Decision tree consists of – Square nodes - indicating decision points – Circles nodes - indicating states of nature – Arcs - connecting nodes
Decision Tree Example 0.60
$2,000,000
Market growth
2 0.40 No market growth
Expand (-$800,000)
1
$225,000 Expand (-$800,000)
Market growth (3 years, $0 payoff)
Purchase Land (-$200,000)
Market $3,000,000 growth 0.80 6 0.20 No market growth
4 Sell land
0.60 3
Market growth
0.40
No market growth (3 years, $0 payoff)
Warehouse (-$600,000) 5 Sell land
$700,000
$2,300,000
0.30 7 $1,000,000 0.70 No market growth $210,000
Evaluations At Nodes Compute EV at nodes 6 & 7 EV(node 6) = 0.80($3,000,000) + 0.20($700,000) = $2,540,000 EV(node 6) = 0.30($2,300,000) + 0.70($1,000,000) = $1,390,000 Expected values written above nodes 6 & 7 Decision at node 4 is between $2,540,000 for Expand and $450,000 for Sell land Choose Expand Repeat expected value calculations and decisions at remaining nodes
Decision Tree Solution $1,290,000
$2,000,000 0.60
Market growth
2 0.40 No market growth
Expand (-$800,000)
$225,000 $2,540,000
$1,740,000 $1,160,000 Market growth (3 years, $0 payoff) Purchase Land 0.60 (-$200,000) 1
3
0.40
$1,360,000 No market growth (3 years, $0 payoff)
Expand (-$800,000)
0.80 6 0.20 No market growth
4 Sell land
$1,390,000 Warehouse $790,000 (-$600,000) 5 Sell land
Market $3,000,000 growth
Market growth
$700,000
$2,300,000
0.30 7 $1,000,000 0.70 No market growth $210,000
Decision Matrix
Decision Trees
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Break-ภb) Sales (Price = $18)
Sales (Price = $12)
Costs and Revenue ($)
900
Sales (Price = $7) Total Cost
700
500
300 Break-Even Points
100 10
30
50
70
Production in Units
90