|
Who the client was
They were a $4 billion distribution operation, with 250,000 skis and over a dozen warehouses who had recently made it through an industry downturn and wanted to preserve operating efficiency, even as they grew.
|
|
|
|
|
|
Why they looked to us for help
They had questions about their distribution system design and efficiency. One issue that pre-occupied them was that their main competitor used a different mix of dedicated and outsourced capabilities. They wanted to know which approach was better. They wondered how their system would perform if they experienced significant changes in demand and mix. |
|
|
|
|
What we did for them
We began by building a simulation model and using it to predict how their system efficiency would vary under different assumptions. They had a wealth of data available, including process costs and volumes, so our model was able to answer some specific questions. We discovered that: |
|
|
|
|
|
![PALADIN](images/img-13.jpg) |
On average, they were more efficient than the competitor |
|
![PALADIN](images/img-13.jpg) |
Their cost structure was more fixed, so the competitor enjoyed less down-cycle risk |
|
![PALADIN](images/img-13.jpg) |
Exacerbating the fixed-cost-problem was a system which was geographically designed for more volume levels in the north-east and was not ready for demographic growth in the mountain and sunbelt states, and |
|
![PALADIN](images/img-13.jpg) |
Supplier concentrations had shifted since the system’s initial design, leading to the evolution of sub-optimal workarounds. |
|
|
|
|
The model also highlighted opportunities for greater efficiencies that could be obtained at the cost of lower customer service levels. |
|
|
|
|