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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

[email protected]

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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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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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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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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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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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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OPERATIONAL,

NON-FINANCIAL MEASURES

Quality

Reliability Dependability/Performability Flexibility

volume product mix routing delivery time

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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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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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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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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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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


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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


REDUCTION


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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)


REDUCTION


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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


REDUCTION


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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


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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


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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

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