CPG Leader Preserves Brand Promise Across Borders with Decisions AI Causing $6M+ in Annual Savings
Introduction
A global CPG leader ships approximately 12,000 loads annually across ambient and cold chain categories in the MEA region including detergents, personal care products, and temperature-sensitive items like ice cream. These shipments span international borders and navigate complex terrain, often involving variable transporter behavior, limited infrastructure, and regulatory scrutiny.
The company’s brand promise of “consistent product quality and on-time delivery” was under threat due to fragmented visibility, manual interventions, and an inefficient quality release process. They turned to Decklar to continue meeting the expectations of their customers and keeping their promise.
The Challenge: Protecting Product, Reputation, and Revenue Without Real-Time Control
To meet service level agreements (SLAs) and protect product integrity. Unilever Gulf needed precise, real-time knowledge of shipment conditions and locations. They faced three main challenges:
- Inefficient Quality Release & Goods Receipt: The goods receipt process was reactive, often lagging actual delivery. This caused inventory imbalances, missed retail campaigns, and productivity loss. Sensitive goods, including ice cream and lotions, required tight environmental control. A single breach in condition or delay in transit could trigger production rescheduling and missed sales windows, further compounding these inefficiencies.
- Theft and Tampering: Hijacking and pilferage led to unauthorized product entry into grey markets.
- Control Tower Overload: Unilever’s CCTV and logistics teams were burdened with constant phone calls, emails, and spreadsheet updates to chase anomalies and validate deliveries especially in the absence of reliable transporter visibility or consistent ETAs.
What They Tried & Why It Didn’t Work
- Carrier Portals & Aggregators provided basic location data but lacked condition monitoring and actionable delay insights. ETAs were transporter-dependent and often inaccurate.
- Manual Escalations to drivers were unreliable and sometimes resulted in misrouted shipments, such as Jeddah deliveries ending up in Dammam.
- ERP/TMS such as Oracle TM supported transport planning but could not unify real‑time condition, transporter performance, and exception data for predictive action.
Enter Decklar’s Real-Time Decisions AI with Visibility
The global CPG leader deployed Decklar’s solution, combining real-time shipment tracking through smart labels and an AI-powered decisions platform. Key capabilities included:
- Every shipment was embedded with a smart label to track both position and environmental exposure (e.g., ambient light).
- AI models flagged when trucks deviated from standard routes or paused unexpectedly such as in a transporter’s yard.
- Decklar integrated with Unilever’s control tower SOP, reducing manual effort and enabling proactive anomaly detection.
- Decisions AI with visibility was used to automatically trigger quality releases and goods receipts, reducing cycle time.
Day 1: Operational Visibility Across Cold Chain
Decklar delivered immediate operational value across all lanes in just five weeks:
- Full transparency into FTL and LTL locations, including when delayed at customs or transporter yards.
- Real-time alerts for unplanned stoppages and door openings (via ambient light detection) to flag possible theft or unauthorized unloading.
- The control tower team finally had a reliable feed of trusted data, eliminating phone follow-ups.
Day 2: Decision AI at Scale
As the system matured, Decklar enabled second-order value:
- Automated Quality Release: Arrival and condition data auto-triggered goods receipt and quality release events, accelerating inventory reconciliation and compliance workflows.
- Security Risk Anticipation: AI detected early signs of tampering or theft risk, enabling the CPG leader’s control tower to act before losses occurred.
- ROI on Promotional Campaigns: Ensured stock availability for planned high-value promotions, protecting revenue lift and brand equity.
Why Decisions AI with Visibility Were Needed Together
Visibility alone showed where shipments were; Decisions AI made that visibility actionable. Without historical and current location and condition insights, AI predictions would lack precision. Without Decisions AI, visibility data becomes a dot on a map or a temperature graph, not actionable intelligence.
Together, they formed a closed loop of awareness and action helping the CPG leader uphold its brand promise with confidence.
ROI Summary
Direct Benefits:
- Quality Release & GRN Automation: $1.8M/year
- Control Tower Productivity Gains: $1M/year
- Inventory Holding Cost Reduction: $1.2M–$1.5M/year
- Avoided Product Loss (Excursion & Theft): $2M+/year
Indirect Benefits:
- Protected Brand Integrity & Consumer Trust
- Improved Insurance Premiums
- On-Shelf Availability During Campaigns
- Reduced Bullwhip Effect on Production & Planning
Total Annual ROI:
$6M+ in direct annual savings, plus significant strategic value within 12 months.
Outcome: From Shipment Tracking to Enterprise-Wide Brand Protection
By deploying Decklar’s Decision AI with Visibility, the CPG leader transitioned from a reactive, fragmented operation to a predictive, brand-protective supply chain. The solution helped prevent brand dilution and reduce regulatory, insurance, and reputational risk by detecting tampering and ensuring every product reached retailers on time, securely, and in full compliance. What started as a shipment monitoring initiative evolved into an enterprise-wide enabler of efficiency, trust, and agility.
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