Supply chain planning visibility and shipment cost reduction
S U P P L Y C H A I N
P L A N N I N G &
S H I P M E N T
C O S T
R E D U C T I O N
T E C H N O L O G Y
ETL – Ideata
Data warehouse – Amazon
Reporting – Ideata
Data Analytics, Advanced
O V E R V I E W
World’s leading international Yarn manufacturer has business across different
continents the customer ships over 3,000 shipments to its customers yearly.
Without a central view into its domestic and international networks, distributor
channels and shipping capacity across locations, offices were shipping supplies to
out-of-network distribution centers from 5x distances when much closer facilities
These cross-country deliveries resulted in an accumulation of unnecessary costs
and complications like price hikes and service issues to carriers, receivers, and end
customers. There were opportunities to improve its supply chain network and
decision making process and needed an in-depth network analysis. Client hoped to
reduce the overall cost, shorten time to market, on-time delivery improve
efficiencies in logistics and a harmonized inventory planning process.
A P P R O A C H
Implemented an integrated logistic planning and optimization solution that enabled
customer to reduce logistics costs and deliver improved speed to market.
– Integrate Siloed Systems
Ideata helped deliver a central data hub enabling the customer to analyze data
points from their front, middle and back office systems. They were able to build
associations between once siloed data sources including ERP, scheduling, supply
chain and distributor management systems and enhance collaboration to improve
delivery efficiency with reduced cost.
– Data Standardization And Preparation
Handled different operation systems and diverse market requirements to prepare a
central view of their global logistics operations.
– Data analytics and Reporting
Identifying which shipments went beyond recommended mileage limits or were
more costly than target metrics. We were able to integrate distributor supplies
from all possible warehouse locations and configure it to determine the lowest
possible costs for shipment delivery with optimal delivery time.
– Advanced Analytics
We were able to build advanced machine learning driven data models that helped
the customer with an advanced transportation network optimization which utilized
location density, inbound and outbound rates, truck/shipment availability, existing
warehouse relationships, and future business projections while building
O U T C O M E
We were able to achieve greater supply chain planning visibility, reduced shipment
cost, improved data and process governance, enhanced collaborative reporting and
higher customer satisfaction levels.