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Steel Works, Inc. OM 783 Supply Chain Strategy and Analysis. Background of Steel Works, Inc. . Annual sales of $400 Million ? Can this be possible given information in case? Conflicting data? What do we do about it? 5 Locations Custom division Develop products for single customer
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Steel Works, Inc. OM 783 Supply Chain Strategy and Analysis
Background of Steel Works, Inc. • Annual sales of $400 Million? • Can this be possible given information in case? • Conflicting data? What do we do about it? • 5 Locations • Custom division • Develop products for single customer • Specialty division • Sell custom products to other companies at higher price
What is the objective? • Stay in business! • Grow business? • Improve customer satisfaction? How? • Minimize inventory cost • What are components of cost? • How measured? • Provide high level of customer service • How high? • How measured?
Consultant Recommendations • Discontinue products that have low sales. • Use statistical forecasting to predict demand. • Reduce number of warehouses. Staff Reaction: Won’t work! Why?
What do data in case tell us? • Exhibit 2: 80% of products have high volatility? • Maybe, but … • What about Exhibit 1? • 5 large customers (> $25 mill) • 107 small customers (< $1 mill) • Is this a potential problem?
What is proper model for this scenario? • Are we in a continuous review or a periodic review inventory setting? • Why? How do we know? • What are proper parameters for model? • Why? • How measure in reality? • Can we validate our choice of model and assumptions? • How? • Look at production batch sizes given in case
How to analyze case? • Model suggestions? Assume we use Periodic Review with r = 1 month and L = 1 week Calculate expected inventory and compare to Steel Works, Inc. actual inventory. • What do we find?
Recommendations? • Why do divisions operate separately? • Any economies to be gained by combining? • How can Steel Works better manage their customer relationship process? • How can Steel Works make sure that they are continuing to use right model, right parameters, etc.? • Should we adjust production parameters by product? How?
Questionable Assumptions? • How confident are you that demand is normally distributed? • How can you test? • Are data accurate? • How can you test?