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Cold Chain · Chicago, IL

Chicago Cold Chain: 91% → 99.3% On-Time Delivery in 90 Days

How a temperature-sensitive freight operator transformed service reliability and secured a critical contract renewal.

99.3%
On-Time Delivery
90 days
Time to Results
91→99%
Service Level Jump
3 mo
Payback Period

Company Background

Chicago Cold Chain Logistics handles temperature-controlled freight for food manufacturers, pharmaceutical distributors, and grocery chains across the Midwest. With a 28-vehicle refrigerated fleet and $1.9M in annual operating costs, they compete on service reliability in a market where a single failure can mean product loss and contract termination.

The Challenge

At 91% on-time delivery, they were 8 percentage points below the 99%+ threshold required by their largest client — a regional grocery chain that had flagged the performance gap in a formal QBR. They had 6 months to improve or face a contract review.

The root cause was complex: a mix of manual dispatch decisions, no real-time visibility into vehicle temperature or location, and reactive exception management that caught problems too late to correct them.

The Solution

Predictive Delay Detection

ML model trained on 18 months of delivery history to flag at-risk deliveries 4+ hours before the delivery window closes — giving dispatchers time to intervene.

Real-Time Route Monitoring

Live GPS + traffic integration with automated re-routing when delays are detected. Average recovery time from a traffic exception dropped from 47 minutes to 8 minutes.

Driver Performance Scoring

Behavioural scoring across speed, idling, routing compliance, and on-time rate. Bottom-quartile drivers moved up 23 percentage points after targeted coaching.

Preventive Maintenance Alerts

IoT temperature and vehicle health monitoring with automated maintenance scheduling. Unplanned breakdowns fell 78% in the first quarter.

The Outcome

On-time delivery hit 99.3% by week 10 — comfortably above the 99% threshold and ahead of the 6-month deadline. The grocery chain client not only renewed the contract but expanded its volume by 40%.

The predictive delay model now prevents an average of 4.2 late deliveries per week that would previously have occurred. Each prevented late delivery saves approximately $1,200 in compensation and re-delivery costs.

"We went from 91% on-time delivery to 99.3% within 90 days. Our biggest retail client renewed their contract specifically because of that improvement. Jandojegs didn't just fix a number — they saved the relationship."

CEO

Chicago Cold Chain Logistics

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