Abstract
Purpose
The purpose of this research is to describe how total cost concept with logistical based costing (LBC) is developed in detail and then used to build logistical models on the Microsoft Excel™ platform that are integrated from the customer's factory to the supplier's door.
Design/methodology/approach
The models developed in this project are deterministic, event‐based algorithms to compare logistical conduits for bulk and containerized commodities. The demand chain approach is used to derive the pathways in reverse order from the customer to the supplier. The methodology is necessary to find all possible conduits from origin to destination, including points where product may cross over between various logistics systems. The approach is applied to the bulk and container system with disconnects (elevators, ports) serving as the demarcation points. The pathways from supplier to end‐user must be identified prior to application of classification and costing techniques. A goal of this research was to compare the per unit cost of two different logistical systems – bulk versus container – in two case studies. The first case study was for a miller in Northern China and the second was for a mill in Helsinki, Finland.
Findings
The spreadsheet models produced results that were within 3 percent of real world costs. Each demand chain was shown to be unique and required customized cost functions to properly configure algorithms.
Research limitations/implications
The paper suggests that, while a core algorithm may exist for all supply/demand chains, no one particular algorithm configuration suffices. Each supply/demand chain is unique, in terms of both costs and performance. The use of modular cost functions provides the customization necessary to address this issue.
Practical implications
This project verifies that successful implementation of a model is dependent on following a set of procedures that begins with a clear statement of what the model is to measure, along with what is to be included and what are the constraints imposed on the algorithm. Mapping the flow of the goods through logistical systems provides visibility as to where costs are incurred and how they are to be assigned to the supplier or customer. An improperly assigned variable in the early stages of a supply/demand chain reduces accuracy of subsequent calculations. LBC increases the precision of models by properly establishing the configuration of cost drivers for each stage of the supply/demand chain by avoiding the use of the cost averaging used in statistical analysis.
Originality/value
This paper provides a standardized approach for mapping, costing and building global supply/demand chain models. The ultimate customer, once thought of as the “end of the line”, now dictates the cost and performance requirements of logistical conduits. While this paper encapsulates methods for building total cost models from the customer's perspective, other configurations can be readily constructed to examine physical and performance characteristics.