SUPPLY CHAIN PERFORMANCE MEASURES

1. Y Narahari, Computer Science and Automation, Indian Institute of Science SUPPLY CHAIN PERFORMANCE MEASURES Y. NARAHARI Computer Science and Automation Indian Institute of Science Bangalore - 560 012 hari@csa.iisc.ernet.in http://www.csa.iisc.ernet.in

2. 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

3. 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

4. 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

5. 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 of past decisions • Operational, non-financial measures are excellent indicators of process health

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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 lead times • closed mode operation better than open mode • Strict control of processing times reduces lead times considerably

13. Y Narahari, Computer Science and Automation, Indian Institute of Science FUNDAMENTAL LAWS OF LEAD TIME REDUCTION Third Law: Forrester Effect • Inventories grow in successive echelons of the supply 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

14. Y Narahari, Computer Science and Automation, Indian Institute of Science FUNDAMENTAL LAWS OF LEAD TIME REDUCTION 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)

15. Y Narahari, Computer Science and Automation, Indian Institute of Science FUNDAMENTAL LAWS OF LEAD TIME REDUCTION Fifth Law: Use the Internet • Availability and intelligent use of critical information 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

16. 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 synchronized supply chain network that works like a world class relay racing team • We wish to use best practices in manufacturing, design, and tolerancing domains

17. 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 lead time • 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 of Y given f and the distributions of X1, X2, . . . , Xn. • Synthesis: Find the best nominals and tolerances for X1, X2, . . . , Xn, given nominal and tolerance specifications for Y.

18. Y Narahari, Computer Science and Automation, Indian Institute of Science EXAMPLE: A PLASTICS SUPPLY CHAIN • Procurement • Sheet Fabrication • Transportation • Manufacturing • Assembly • Delivery

19. Y Narahari, Computer Science and Automation, Indian Institute of Science A SIX SIGMA FRAMEWORK • Six Sigma Quality: A process is considered to be of six sigma quality if there are no more than 3.4 non-conformities per million opportunities (3.4 ppm) in the presence of typical sources of variation. • Analysis and Synthesis are based on: • Characterizing product-process quality using process capability indices Cp and Cpk • Use of statistical tolerancing techniques to reduce lead times

20. Y Narahari, Computer Science and Automation, Indian Institute of Science 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

21. Y Narahari, Computer Science and Automation, Indian Institute of Science CONCLUSIONS • There are fundamental laws governing lead time reduction in supply chains • Variability reduction and synchronization among 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