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Chithra Govindan Improving Inventory Performance for Slow Moving SKUs Student: Chithra Govindan, PSCM 2018
Advisor: Dr. Javad Feizabadi A global lubricants manufacturing and marketing company servicing 100 markets across the globe To critically analyze supply chain risk pooling solutions in improving slow moving SKUs inventory performance
Cost savings via reduction in inventory holding cost of slow moving inventory Methodology Motivation / Background Key Question / Hypothesis Relevant Literature Initial Results Expected Contribution January 2020 Poster Session External benchmarking:
Inventory turnover lower than industry: 5 vs. 12 Year on year increase in inventory levels not commensurate with sales volumes Company financial trending:
Steep reduction in Can we identify potential solutions to improve inventory performance within a lubricants manufacturing firm, without compromising expected service levels? SKU Demand Analysis Silver, Pyke & Peterson, 1998. “Inventory Management and Production Planning and Scheduling. John Wiley & Sons Lee, 1996. “Effective Inventory and Service Management Through Product and Process Redesign”. Operations Research 44(1): 151-159. 1 4 5 470 2000+ plant warehouses distributors SKUs customers SKU Demand Analysis Conduct As-Is versus Expected Analysis on Inventory Levels Explore supply chain risk pooling alternatives Recommendation on risk pooling solutions Robust analysis & data generation on alternative opportunities 01 02 05 04 03 SCOPE Fast moving SKUs : Focused improvement on demand forecast accuracy (on-going) Slow moving SKUs : To explore supply chain risk pooling solutions Slow moving SKUs: ~17% of inventory value 50% of SKUs have high volatility, ~25% of inventory value Forecast accuracy averaging ~60% Obsolete SKUs: ~10% of inventory value Product Portfolio Optimization Location / Lead Time Pooling<br>
