Simplifying Landed Cost Modeling Series Part 1: Creation

Simplifying Landed Cost Modeling Series Part 1: Creation

Modeling delivered cost within a supply chain is a hot item for businesses. This is due to the fact that it is difficult to pull out some accounting statements, point to a few numbers, and say, “yep. Here’s your Total Landed Cost.” However, the true power of creating such models lies not only in capturing hidden costs, but in their ability to play out “what if” scenarios. The problem is that these types of models are complex and require high effort. The inputs can range from a few to several hundred.

There are several layers of complexity that can be introduced into the model. These complexities include creation, validation, usage, outputs, and upkeep. In this post, I will focus on the complexities found in the creation of the model. Complexities in creation involves:

Purpose For The Model

Take time to capture the voice of your customer, and try to understand what they need from the model. Is it for analysis? Understanding the relationships in their supply chain/business? Validation of business decisions? Capturing accurate costs? Making operational decisions? Each one of these (or whatever the voice of the customer says) will have its own unique characteristics and require different ‘depths’ of modeling. We do not want to overproduce or waste time capturing depth and complexities if the customer is not asking for it.


The number of required inputs is dictated by the purpose of the model. A model trying to capture the true costs will typically require more inputs than a model to validate a decision. Try to understand the ‘driver inputs’ - inputs which have the greatest impact on the results. You will typically find that input impacts can be stratified into A, B, and C’s (much like inventory). It’s the critical few that should be the main focus throughout the creation of the model.

Relationships Between Inputs And Variables

The vast majority of the time and effort should be spent creating mathematical relationships between the ‘driver inputs’ and any vital variables created within the model. The world is complex. Trying to capture triggers and impacts between variables can quickly lead to complex mathematics. The model may or may not require this type of mathematical depth. With some thought and effort we can usually simplify the relationship equations while still capturing 95% of the needed results. We should strive to keep the relationships in a model as transparent and approachable as possible.

Simplifying the processes and inputs in creating our models will allow us to fulfill the purpose of the model, while reducing unnecessary complexities that will plague the rest of the steps in completing the finished technology. Use the voice of the customer to scope the model’s needs. This ‘vision’ should be used to minimize the number of inputs and mathematical relationships that are required to fulfill the customer’s needs.

Written by Chris McLaughlin, Lean Deployment Specialist at LeanCor

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Posted by LeanCor Supply Chain Group

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LeanCor Supply Chain Group is a trusted supply chain partner that specializes in lean principles to deliver operational improvement. LeanCor’s three integrated divisions – LeanCor Training and Education, LeanCor Consulting, and LeanCor Logistics – help organizations eliminate waste, drive down costs, and build a culture of continuous improvement.

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