How a Global Pharma Distributor Transformed Its Security & Cold Chain Trust with Decisions AI: $23M+ in Cost Efficiencies and Risk Prevention Unlocked

Introduction

A world-leading global U.S. pharma distributor responsible for moving nearly half of all medicines in the country operates over 81,000 full truck loads (FTLs) from a national distribution hub and 27 Forward Distribution Centers (FDCs). It plays a critical role in ensuring temperature-sensitive and high-value medicines reach pharmacies, hospitals, and retail stores nationwide. It faced mounting pressure to improve delivery performance, reduce working capital tied up in in-transit inventory, and resolve customer disputes faster. 

This scale brought serious logistics challenges: maintaining cold chain integrity, preventing theft and tampering, and streamlining delivery operations, all while fulfilling SLAs contextual to shipment criticality. The provider turned to Decklar to gain proactive risk management, smarter prioritization, and operational assurance using Decisions AI with real-time visibility. 

The Challenge: High Risk, Low Precision in Security and Cold Chain Management   

The company faced three major issues that impacted costs, safety, and performance: 

• Security and Theft Risk: High-value pharmaceutical cargo is exposed to theft. A single truckload theft could cost up to $15M in pharmaceutical losses. 

• Cold Chain Vulnerability: Weekend or late-night shipments were especially vulnerable to non-compliance as reefer trailers were frequently switched off during delays or layovers. 

• Inefficient SLA Execution: Uniform SLAs meant cotton balls and life-saving drugs were treated the same. This led to misprioritization, delayed delivery of critical goods, and no linkage between shipment condition and business impact. 

What They Tried & Why It Didn’t Work

1. ERP/TMS Systems (such as SAP): Operated on batch updates, lacking real-time data or condition-aware decisioning. This required manual auditing to investigate delays, compliance issues, or manually reported security breaches.
2. Carrier Aggregated Visibility Providers: With shipment transit times oscillating between 1 to 5 days, aggregated visibility & ETA were often delayed or updated once the shipment reached the destination. Condition data was not available.  ETA updates often lagged by days and lacked cold chain context.
3. Security Control Tower Companies: These companies offered control tower service but didn’t have an actionable control tower platform for efficient & proactive risk mitigation – including response They offered staffing but lacked a proactive or predictive technology stack.
4. Macro Risk Visibility Platforms: The platforms were effective in alerting about macro disruptions like port congestion, wildfires, tsunamis, etc. However, they were unable to forecast its precise impact on the FTLs in motion.
5. Generic Track & Trace Solutions: Only provided location and condition data which could not account for detection of chain-of-custody lapses or early warning contextual to the stage of the shipment. It lacked the ability to link conditions with root causes or prescribe actions.  

Without a unified view or prescriptive intelligence, the company struggled to move from tracking to proactive risk mitigation and management. 

Enter Decklar’s Real-Time Decisions AI with Visibility 

Decklar deployed sensors at scale on truckload and integrated with the company’s existing ERP system. What followed was a transformation in decision-making: 

• Live Monitoring of High-Value & Cold Chain Loads 

• Tamper & Theft Alerts Using Light Detection (Door Opening) 

• Electronic Proof of Delivery with Geotagging 

• Contextual Dashboards for Field Ops, Dispatch, and Corporate HQ 

• Real-Time Exception Warnings Triggered by Risk Tiers & SLA Violations 

Day 1: Operational Intelligence & Risk Containment with Visibility 

In just six weeks: 

• The team could pinpoint where and when reefer trailers were powered down in real time. 

• Field teams received auto-alerts for tampering and temperature breaches. 

• Delivery confirmation was automated with location-verified geotags. 

• Manual reconciliation and post-facto investigations were reduced significantly. 

Day 2: Decisions AI Improved SLA Precision and Compliance

By month three, Decklar’s Decision AI engine began powering: 

• Risk Tiering by Product Type: Allowed for differential handling of urgent or high-value vs. non-urgent or low-value goods. 

• Predictive Breach Detection: Triggered actions pre-emptively when temperature excursions or route deviations signaled future SLA non-compliance. 

• Tamper Chain of Custody: Traced the origin & root cause of breaches at scale. 

• Automated Quality Release: Condition data automatically cleared ambient shipments freeing ops teams & dock door personnel from manual QA. 

• Security ROI Realization: Enabled security investment to be justified as insurance even one averted $15M theft would recover ROI for years. 

Why Decisions AI with Visibility Were Needed Together 

Visibility Alone gave real-time status updates & condition data but couldn’t translate incidents into prioritized actions or financial impact. Decisions AI Alone lacked the real-world telemetry. It needed live data to intervene when shipments were in transit or predict future shipment risk based on lane, nodal, and points of interest (POI) intelligence gathered across the lanes. Together, they enabled this global pharma distributor to move from static oversight to dynamic control delivering precision, speed, and resilience. 

ROI Summary  

Direct Benefits: 

• Security Loss Prevention: Risk-adjusted value of prevented thefts, with a single prevented theft worth $15M. 

• Cold Chain SLA Compliance: ~$4.9M/year in avoided spoilage and write-offs by identifying risky handoffs and enabling proactive intervention. 

• Manual Labor Savings through Automated Goods Receipt & Quality Release: $3.5K/year from exception automation and auto-release processes. 

Indirect ROI Opportunities: 

• In-Transit Revenue Forecasting: Linking shipment progress to downstream sell-through timelines. 

Total Realized & Potential Impact: 

• $23.4M + strategic resilience across revenue, compliance, and security 

Outcome: From Risk Exposure to Predictive Command 

By embedding real-time decisions AI with visibility into its healthcare logistics network, this global pharma distributor replaced reactive tracking with predictive decision-making. Decklar helped them go beyond compliance by safeguarding brand equity, optimizing cold chain delivery, and future-proofing operations in one of the most sensitive supply chains globally. Decisions AI with visibility didn’t just cut costs, it elevated trust, speed, and control. 

It even turned reactive logistics into an intelligent, compliant, and secure operation. The distributor now delivers life-saving medicines faster, safer, and more predictably across 81,000+ FTLs annually. 

The result: Trust, precision, and control delivered at scale. 

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