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Faster response times, 

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lower delivery costs,

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and increasing e-commerce orders
represent a few of the new dynamic

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customer expectations putting pressure
on existing supply chain networks.

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Businesses who build 
optimized manufacturing

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and distribution networks 
will be able to not only exceed

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service level expectations,
but also reduce operational costs.

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Common challenges such as inadequate
product-to-factory allocations

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and manufacturing footprint,
non-optimal distribution center locations,

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avoidable inventory holding
costs, long transportation lead times,

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and low truck utilization rates
make this a complex task –

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requiring mathematical programing
and optimization models, 

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deep business domain knowledge, 

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and machines
with high computational power.

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SNOW AI, built by BCG,
combines advanced mathematical modeling,

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an intuitive interface and a customizable
SaaS model to remove this complexity

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and unlock 
5-10% customer service level improvement.

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20-30% network complexity reduction.

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10-25% conversion and logistics costs
reduction and up to 30%

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less CO2 emissions and higher product
supply resilience.

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In a few clicks, SNOW AI helps clients
identify optimal factory and distribution

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center locations, fine tune
the overall network through efficient

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assignments, transportation
and inventory allocation, 

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and build a resilient and sustainable distribution
and manufacturing supply chain network.

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It deploys fast, requires
no technical training, 

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and offers sophisticated,
out-of-the-box visualizations.

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SNOW AI’s
battle-tested approach has enabled clients

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to uncover millions of dollars in savings
by identifying avoidable

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capital expenditures, ensuring continuous
operational efficiencies

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and a more sustainable 
and resilient setup.

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Build your future-ready 
supply chain today using

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SNOW AI.