Steel Works Inc. Faces Severe Crisis Despite Decades of Successful Growth

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Steel Works, Inc. is a company in crisis. Founded in 1980 by a group of material scientists from MIT, the company has grown to over $400 million in sales in thirteen short years. It now operates in 5 separate locations and has more than 2500 employees. The company operates two different and independent divisions. The Custom Products division has incurred rapid growth and accounts for one third of the company’s sales at $133 million. Their market trades on their ability to provide innovative technical solutions.

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They tend to develop custom solutions for individual customers. The Specialty Products division carries two-thirds of the company’s sales at $267 million. They commercialize products developed by Custom Products and provide them to a broader customer base. As a result of having fewer large customers, they experience a higher volatility in demand.

According to the company’s Chief Financial Officer, Jean Du Blanc, the company’s service level is the worst in the industry. CEO, Kirk Callow, estimates that sales are down approximately 30% and expenses are ticking upward an additional 25%.

Inventory levels are high and are not scientifically structured to meet the demand at an acceptable service level. The company has brought in a consultant to help provide a solution, but the recommendations don’t necessarily fit with the company’s business strategy. With a plethora of complex supply chain issues, the company needs a quick solution to help them start digging out of the hole they’re currently buried in.

What did the CONSULTANT say?
Before delving in and creating new solutions to the current crisis, it is a worthwhile exercise to examine the recommendations of the consultant, Fred Chow.

His first suggestion was to dump the ‘highly volatile’ products. This includes low margin products and those with low annual sales. His recommendation here is to focus on high volume, high margin products that generate large revenue. While there was some push back from the company on this idea, it may still have some merit. Yes, customers that buy large volumes of one SKU may also purchase small volumes of another and it isn’t always wise to poke a stick at this particular bear, but there are products such as DuraFlex R15 and DuraFlex R23 that literally go months without any sales. The Unit Margin for these items, however, ranks in the top three for all products (see Table 1) making this a very tough decision.

Another recommendation was to use statistical forecasting to anticipate demand. This is a solid recommendation for products that are sold to a single customer. It becomes harder when multiple customers buy the same product and have their own individual demand volatility. The aggregate can be hard to model. Instead of putting together complicated models to try to anticipate demand, it might be easier to get the information directly from the customer. Often times what we see as volatility the customer sees as cyclic and predictable. Finally, Mr. Chow recommended consolidating warehouses. This is another generic recommendation that is more complex in execution than it is on its surface. There’s not enough information in the case study to determine the feasibility of this recommendation.

Analyzing the Data
If we examine the coefficient of variation to measure the dispersion between SKU’s, it becomes clear that the high volume products such as BuraBlend R12 and DuraBlend R15 have a much lower CV value at 0.20 and 0.25 respectively (see Table 1). Demand volatility moves upwards pretty quickly for the remaining five SKU’s. When we weigh average demand against unit margin we see that DB R12 and DB R15 generate the lion’s share of the revenue for Steel Works (Table 1). In an ABC model, these two products would definitely be the ‘A’ products.

In order to examine the inventory expectations for the company, it is necessary to make a few assumptions. We start with the formula for average inventory level (Simchi-Levi, Kaminsky, & Simchi-Levi, 2008, p. 45):

By using this formula and making a few educated assumptions for ‘r’, ‘L’, and ‘z’, we can determine what our inventory levels should be for Steel Works products. The monthly cycle leads us to believe that ‘r’ is on the order of 1 month defined here as four weeks. ‘L’ will be less than ‘r’ and probably between one and two weeks. While it is a speculative assumption, we will assume a one week lead time which we will take as 0.25 months. Now, when examining the service level, we want customers to be happy, and yet, we need to balance holding costs of inventory. I would expect the service level to be between 95% and 100% and will use 97% or a ‘z’ of 1.88 (Simchi-Levi, Kaminsky, & Simchi-Levi, 2008, p. 43). We can find the Safety Stock using the equation (Liu, 2014):

The inventory picture we derive from these equations paints a very telling picture of customer service issues with Steel Works. The data shows that there are several SKU’s where inventory levels are below the amount needed to maintain the service level at 97%. Conversely, many of the SKU’s have inventory levels way about what is needed to maintain the desired service level. This leads to additional and unnecessary costs (see Table 1).

Putting it All Together
DuraBlend R12 and DuraBlend R15 show safety stock well below (25-30%) the minimum stock levels. This is likely the cause of the unacceptable service level that Kirk Callow spoke of. The balance of the SKUs each have an inventory level higher than needed to maintain the service level required. This is representative of the costs and excess inventory levels that Jean Du Blanc spoke of. By adjusting the inventory levels to the calculated levels, it will be possible to both lower costs of your ‘B’ and ‘C’ inventories, and increase service levels on your ‘A’ inventory. Fred Chow didn’t miss the mark entirely in regards to obsolescing low moving SKUs. A better option, however, might be to combine SKUs where possible. In many cases, customers are able to use similar products and would be willing to entertain the idea if it means a lower cost. Passing on the cost saving in this case gives the customer a carrot and would help flatten demand. This is a potential win/win for both Steel Works and their customers. This might also lead to longer production runs and combined warehousing.

Both will drive costs down. Steel Works, Inc. needs to look towards integrating the separate divisions. The synergies in manufacturing and managing the supply chain will drive down costs of doing business. Custom Products can act as the Product Development wing of the company. It often deregulates products to sell to the non-core customers already. Specialty would be the work horse for the company. It already has 2/3rd of the sales. If it had access to Custom Product’s line of goods it could enhance its already substantial line up. The overall take for this case study is that Steel Works, Inc. is a company entrenched against itself. While there are numerous examples of how to streamline the individual supply chains enclosed, the real win would be integrating both divisions and their supply chains into a single supplier with a common customer base. Table 1

References
Liu, T. (2014, January). Inventory Management PPT. Retrieved February 8, 2014, from https://oc.okstate.edu/d2l/le/content/989236/viewContent/3732087/View Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2008). Designing and managing the supply chain: Concepts, strategies, and case studies. Boston: McGraw-Hill/Irwin.