Faster response times,
lower delivery costs,
and increasing e-commerce orders represent a few of the new dynamic
customer expectations putting pressure on existing supply chain networks.
Businesses who build optimized manufacturing
and distribution networks will be able to not only exceed
service level expectations, but also reduce operational costs.
Common challenges such as inadequate product-to-factory allocations
and manufacturing footprint, non-optimal distribution center locations,
avoidable inventory holding costs, long transportation lead times,
and low truck utilization rates make this a complex task –
requiring mathematical programing and optimization models,
deep business domain knowledge,
and machines with high computational power.
SNOW AI, built by BCG, combines advanced mathematical modeling,
an intuitive interface and a customizable SaaS model to remove this complexity
and unlock 5-10% customer service level improvement.
20-30% network complexity reduction.
10-25% conversion and logistics costs reduction and up to 30%
less CO2 emissions and higher product supply resilience.
In a few clicks, SNOW AI helps clients identify optimal factory and distribution
center locations, fine tune the overall network through efficient
assignments, transportation and inventory allocation,
and build a resilient and sustainable distribution and manufacturing supply chain network.
It deploys fast, requires no technical training,
and offers sophisticated, out-of-the-box visualizations.
SNOW AI’s battle-tested approach has enabled clients
to uncover millions of dollars in savings by identifying avoidable
capital expenditures, ensuring continuous operational efficiencies
and a more sustainable and resilient setup.
Build your future-ready supply chain today using
SNOW AI.