calculating cost to serve
Companies struggle to gather and transform their data into a useful, trusted calculation of Cost-to-Serve. Competitive Insights uses End-To-End transactional data from multiple, disparate sources to capture the specific cost elements you need.
This data goes through a 3 Stage data validation process, using Machine Learning (ML), and is then transformed to provide the most accurate and specific cost insights. These insights support multiple initiatives or discover opportunities for significant cost reduction not visible through standard cost accounting or allocation methods.
+ Customer service overhead
+ Customer value learn costs
+ Order management overhead
+ Business unit and factory planning overhead
+ Materials and capital acquisition planning overhead
+ COGS materials
+ Materials purchase price variance
+ Factory capital acquisition and indirect materials
+ Sourcing, procurement and accounts payable overhead
+ Raw materials carrying and obsolescence costs
+ COGS internal conversion costs or outsourced manufacturing costs
+ Standard cost variances
+ Finished goods and WIP inventory carrying and obsolescence costs
+ Internal warehouse costs (space, equipment, people)
+ 3PL/4PL costs
+ Tax, licensing and customs
+ Inbound and outbound carrier costs
+ Logistics security costs
+ Special services (boxing, labeling, etc.)
+ Product returns costs
+ Repair costs
+ Supply chain management overhead (admin and center of excellence)
+ Supply chain IT overhead
+ Supply chain Finance overhead
+ Supply chain HR overhead
+ Costs of continuous improvement and poor quality mitigation
Competitive Insights’ Net Landed Cost to Serve uses transactional data captured across the end-to-end supply chain for an actionable cost to serve measurement for every SKU sold to every end delivery location.
Competitive Insights incorporates data from procurement to delivery. It can even include post-sale service. End-to-end, top to bottom, Net Landed Cost to Serve is the most accurate measure.