Steel works
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School
Rutgers University, Newark *
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Course
890
Subject
Industrial Engineering
Date
Feb 20, 2024
Type
docx
Pages
2
Uploaded by CountRose21200
Steel Works, Inc.
Business Situation
- Steel Works, Inc. was formed in 1980 by three brilliant MIT material
scientists. It produces customs and specialty division steel and had annual sales of $400
million in 1993. With 2500 employees spread across five locations, the company is currently
facing significant internal issues like a high inventory level, subpar customer service that is
costing them market share as customers switch to rivals, a 30% decline in sales, and a 25%
increase in expenses. The CEO wants a week to fix all these concerns.
Analysis and Insights
– The custom division maintains three manufacturing sites and six
product lines, all of which are close to their R&D centers and warehouses. They mostly rely
on logistic networks to distribute their products, resulting in significant inventories. They
reduce production costs by manufacturing product families at the same factory. Around 90
percent of the products are sold to one customer. The specialty division accounts for around
67% of overall sales, with one customer accounting for up to 10% of total revenue. The
custom division generally creates goods under contract for a single customer until that
product becomes a part of the company's system. Their lead times are relatively high,
especially the supplier lead time. This will lead to delay in production and affect customer
satisfaction.
Recommendations
- Steel Works, Inc. should focus customer service while also shortening
production lead times and improving forecasting accuracy. Using ABC analysis, the items
should be classified based on their importance in terms of sales and volume. Its primary focus
should be on high-value, high-demand products, while crucial items should be kept in stock.
To manage products in the highly variable category, customer forecasts should be followed
up on in the specialty division. An enhanced inventory management system with data-driven
computations should be deployed to attain optimal stock levels. OTD and fill rates should be
monitored to monitor supply chain performance, and the data gathered should be used to
enhance the process.
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