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 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 FUNDAMENTAL LAWS OF LEAD TIME REDUCTION

14. 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

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

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