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Y Narahari, Computer Science and Automation, Indian Institute of Science
SUPPLY CHAINPERFORMANCE MEASURES
Y. NARAHARI
Computer Science and Automation
Indian Institute of Science
Bangalore - 560 012
http://www.csa.iisc.ernet.in
mailto:[email protected]://www.csa.iisc.ernet.in/http://www.csa.iisc.ernet.in/mailto:[email protected] -
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Y Narahari, Computer Science and Automation, Indian Institute of Science
OBJECTIVE OF TALK To identify and understand different
indices of supply chain performance
To understand the "science" of lead time
reduction in supply chains
To appreciate the role of Internet
technologies in improving the delivery
time performance of supply chains
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Y Narahari, Computer Science and Automation, Indian Institute of Science
OUTLINE OF TALK Taxonomy of Supply Chain Performance
Measures
Quick Response Supply Chains
Fundamental Laws of Lead Time
Reduction
Synchronized Supply Chains
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Y Narahari, Computer Science and Automation, Indian Institute of Science
FUNCTIONAL VS PROCESS
PERFORMANCE MEASURES Functional measures provide only a
partial picture Functional excellence does not imply
process excellence Function-based optimization can be
disastrous Our attention will be on supply chain
process performance measures
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Y Narahari, Computer Science and Automation, Indian Institute of Science
FINANCIAL MEASURES OF
SUPPLY CHAIN PERFORMANCE Financial Measures
Market share
Stock Valuation Profits ROI Inventory Turns
Financial measures are lagging metrics, a result ofpast decisions
Operational, non-financial measures are excellentindicators of process health
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Y Narahari, Computer Science and Automation, Indian Institute of Science
OPERATIONAL,
NON-FINANCIAL MEASURES Cycle time Customer service level
order fill rate stockout rate backorder level probability of ontime delivery
Inventory levels Resource utilization Capacity/Throughput
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Y Narahari, Computer Science and Automation, Indian Institute of Science
OPERATIONAL,
NON-FINANCIAL MEASURES
Quality
Reliability Dependability/Performability Flexibility
volume product mix routing delivery time
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Y Narahari, Computer Science and Automation, Indian Institute of Science
QUICK RESPONSE
SUPPLY CHAINS
Minimal cycle times supply chain end-to-end lead time
order-to-delivery lead time
Minimal spread in cycle times
Synchronization among various stages
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Y Narahari, Computer Science and Automation, Indian Institute of Science
LEAD TIME REDUCTION Cycle time is an all-encompassing
measure
Provides competitive edge
Leads to increased customer
satisfaction Leads to reduced inventory, reduced
onsolescence and increased quality
Y N h i C t S i d A t ti I di I tit t f S i
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Y Narahari, Computer Science and Automation, Indian Institute of Science
COMPONENTS OF
SUPPLY CHAIN LEAD TIME Procurement lead time
Manufacturing lead time
Distribution lead time
Logistics lead time
Setup times
Waiting times
Decision-making times
Synchronization times
Y N h i C t S i d A t ti I di I tit t f S i
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Y Narahari, Computer Science and Automation, Indian Institute of Science
FUNDAMENTAL LAWS OF
LEAD TIME REDUCTION
First Law: Little's Law Average Inventory is the product of average
waiting time and throughput rate Inventory reduction and optimal utilization of
resources is the key to lead time reduction Throughput and lead time are negatively
correlated (classical queueing theory) Load balancing and optimal resource allocation
will help
Y Narahari Computer Science and Automation Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
FUNDAMENTAL LAWS OF LEAD TIME
REDUCTION
Second Law: Pollaczek-Khintchine Formula Waiting times are positively correlated to variance
of arrival and processing times Input control Process control Fluctuation smoothing
Controlled arrivals can significantly reduce leadtimes closed mode operation better than open mode
Strict control of processing times reduces lead
times considerably
Y Narahari Computer Science and Automation Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
Third Law: Forrester Effect
Inventories grow in successive echelons of thesupply chain as demands get amplified in the
upstream direction
Inventory expansion leads to rising levels of lead
time Accurate forecasting and intelligent use of
information are is key to reducing the effects of
this
FUNDAMENTAL LAWS OF LEAD TIME
REDUCTION
Y Narahari Computer Science and Automation Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
Fourth Law: Taguchi's Loss Taguchi's loss function is decided by variability
and also bias (deviation from optimal nominal)
Do not always try to eliminate variation, but
minimize the effects of variability Find robust operating points (nominals)
FUNDAMENTAL LAWS OF LEAD TIME
REDUCTION
Y Narahari Computer Science and Automation Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
Fifth Law: Use the Internet
Availability and intelligent use of criticalinformation is a key requirement
Use of Internet and Ecommerce
Technologies can help dramatically in this Synchronization between the front-end
and back-end is critical
FUNDAMENTAL LAWS OF LEAD TIME
REDUCTION
Y Narahari, Computer Science and Automation, Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
SYNCHRONIZED SUPPLY
CHAINS Variability is the main enemy in achieving lead time
reduction,as evidenced by:
Forrester Effect Pollaczek-Khintchine Formula Taguchi's Loss Function
Our objective is to design a highly synchronizedsupply chain network that works like a world classrelay racing team
We wish to use best practices in manufacturing,design, and tolerancing domains
Y Narahari, Computer Science and Automation, Indian Institute of Science
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Y Narahari, Computer Science and Automation, Indian Institute of Science
DESIGN OF SYNCHRONIZED
SUPPLY CHAINS Y = f (X1, X2, . . . , Xn)
Y represents supply chain lead time or order-to-delivery leadtime
f is a deterministic function X1, X2, . . . , Xn are lead times of individual business processes,
continuous random variables
Y is a continuous random variable
Analysis: Compute the probability distribution ofY given f and the distributions ofX1, X2, . . . , Xn.
Synthesis: Find the best nominals and tolerancesforX1, X2, . . . , Xn, given nominal and tolerance
specifications for Y.
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, p ,
EXAMPLE:
A PLASTICS SUPPLY CHAIN
Procurement
Sheet Fabrication
Transportation
Manufacturing
Assembly
Delivery
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p
A SIX SIGMA FRAMEWORK Six Sigma Quality: A process is considered
to be of six sigma quality if there are no morethan 3.4 non-conformities per millionopportunities (3.4 ppm) in the presence oftypical sources of variation.
Analysis and Synthesis are based on:
Characterizing product-process quality usingprocess capability indices Cp and Cpk Use of statistical tolerancing techniques to reduce
lead times
Y Narahari, Computer Science and Automation, Indian Institute of Science
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WHERE CAN WE APPLY
THIS? Due Date Setting
Selection of Supply Chain Resources
Make-to-stock versus make-to-order
versus build-to-order
Resource Allocation
Selecting logistics providers
Select Robust Operating Points
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CONCLUSIONS There are fundamental laws governing lead
time reduction in supply chains
Variability reduction and synchronizationamong internal business processes of a
supply chain is a key to achieving a high level
of delivery performance
Use of Internet and Ecommerce technologies
could be a key for achieving outstanding
delivery performance