What the Savings
Can Look Like
Three modeled scenarios across eCommerce, private equity, and third-party logistics. The figures come from our optimization engine running on representative data. They are illustrations, and your own numbers depend on your rates, network and product mix.
Modeled scenarios. The figures below come from our optimization engine running on representative shipping data. They show what the analysis produces. Send us 30 days of your own data and we will show you your number.
Mid-Market eCommerce Brand: 28% Lower Parcel Cost in the Model
The Situation
Picture an eCommerce brand shipping 8,000 parcels per day across 3 carriers with no view of how cost climbs by zone. Rates are negotiated carrier by carrier, without knowing which lanes are competitive and which are losing margin. Cross-country shipments to Zones 7 and 8 cut into profit on the highest-value orders.
How FlexChain Approaches It
In this scenario FlexChain takes 90 days of shipment history and runs zone-skip analysis across 12 origin zip codes. The optimizer finds where volume from several origins can be combined into regional hubs, avoiding the most expensive zone pricing. Rate shopping across all 3 carriers by lane shows that no single carrier is cheapest everywhere, and the best mix shifts by destination zone.
Modeled Results
28%
Modeled parcel cost reduction
$420K
Modeled annual savings
2.1 days
Modeled transit improvement
12
Origin zips in the model
Analysis in about 2 weeks. Rollout across all origins in about 60 days.
PE Portfolio Company: $1.2M in Modeled Freight Savings
The Situation
Picture a private equity portfolio company after a multi-brand acquisition. Each of its 3 consumer goods brands has its own carrier contracts, its own logistics operation, and its own shipping lanes covering the same geographies. Nobody has a combined view of total freight spend or carrier performance across the portfolio.
How FlexChain Approaches It
In this scenario FlexChain brings shipment data from all 3 brands into one analytics environment. Cross-brand lane analysis finds 40+ overlapping routes where pooled volume would earn better rates. The platform models renegotiated contracts on the combined volume and gives portfolio leadership one dashboard for per-brand and total logistics performance.
Modeled Results
$1.2M
Modeled annual freight savings
34%
Modeled cost-per-shipment reduction
3
Brands on one dashboard
40+
Overlapping lanes in the model
About 90 days from kickoff to savings across all 3 brands.
3PL With Multi-Client Pooling: 41% Lower Middle Mile Cost in the Model
The Situation
Picture a regional 3PL running inter-facility transfers for 15+ clients, with trucks 60% empty on middle-mile routes. Each client is billed separately and there is no way to pool volume across accounts. Trucks run underused, per-client costs run high, and margins are too thin to fund growth.
How FlexChain Approaches It
In this scenario FlexChain Command Center models cross-client consolidation across the 3PL's whole network. The optimizer finds shared lanes where shipments from several clients can ride the same truck and still meet delivery windows. Cost is attributed per client throughout, so each client sees only its own share and nothing from other accounts.
Modeled Results
41%
Modeled middle mile cost reduction
15%
Modeled on-time improvement
60%
Empty miles in the baseline
15+
Client accounts pooled
Onboarding in about 3 weeks. Savings expected from the first billing cycle.
See What FlexChain Can Do for You
Whether you ship 500 parcels a day or manage freight for an entire portfolio, we find the savings hiding in your data.
These are modeled scenarios, built on representative data to show how the optimization works. They are illustrations and do not describe specific clients. Actual results vary by operation size, data quality, carrier market conditions, and implementation scope. Timelines are expectations.
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Let's start with a conversation about your supply chain.