The Starting Point
Cordstrap had built a substantial global business over decades selling cargo protection products—composite lashing, woven strapping, dunnage bags, edge protectors—to customers including logistics companies, manufacturers, and shippers worldwide. The core business was healthy but faced familiar pressures: commoditisation, price competition from Asian manufacturers, and customers increasingly viewing protection as a cost to minimise rather than a capability to invest in.
Leadership recognised that continuing to compete solely on product quality and price was a path to margin erosion. With a strong customer base and global presence, they had assets to leverage—but needed to explore whether the company could create new value by transforming how they served customers.
Opportunity Identification
Weeks 3-8The exploration team systematically reviewed the 12 Transformation Shifts, assessing which patterns could apply to Cordstrap's assets, capabilities, and customer relationships.
Shift Pattern Analysis
Three shifts emerged as most promising:
1. Product → Recurring Service: Following Hilti's fleet management model, Cordstrap could shift from selling protection products to managing protection outcomes. Instead of customers buying lashing and dunnage, they would pay for "zero-damage shipments."
2. Low-Tech → High-Tech: IoT sensors could transform protection from passive (products that resist damage) to active (systems that predict and prevent damage). Real-time monitoring of cargo conditions during transit could detect risks before damage occurs.
3. Dedicated → Multi-Usage: If Cordstrap developed proprietary technology for cargo risk prediction, this capability could be licensed to other parties—insurers, carriers, logistics platforms—creating a second revenue stream from the same R&D investment.
Key Partners
- Raw material suppliers (polyester, polypropylene)
- Manufacturing equipment vendors
- Distribution partners
- Testing & certification bodies
Key Activities
- Product manufacturing
- Quality control & testing
- Sales & distribution
- Customer technical support
Key Resources
- Manufacturing facilities
- Product patents & IP
- Technical expertise
- Sales force & distributor network
Value Proposition
- High-quality cargo protection products
- Compliance with international shipping standards
- Technical support & training
- Reliable supply & delivery
Customer Relationships
- Transactional sales
- Account management for large clients
- Technical support hotline
- Training workshops
Channels
- Direct sales team
- Distributor network
- E-commerce (limited)
- Trade shows & exhibitions
Customer Segments
- Manufacturers (automotive, industrial)
- Logistics companies
- Shipping lines
- Freight forwarders
Cost Structure
- Raw materials (40% of COGS)
- Manufacturing labour & overhead
- Sales & distribution costs
- R&D (product development)
Revenue Streams
- Product sales (one-time transactions)
- Training & certification fees (minor)
- Custom engineering projects (minor)
Transformation Concept: "CargoShield Intelligence"
The team developed a transformation concept combining all three shifts, designed to leverage Cordstrap's scale advantages:
Core Offering: Outcome-based cargo protection. Customers pay a monthly fee per shipment lane or container volume. Cordstrap provides all necessary protection products, installs sensors, monitors shipments in real-time, and guarantees damage-free delivery. The existing 1,000+ customer relationships provide a built-in market.
Technology Layer: IoT sensors track shock, tilt, humidity, and temperature during transit. Machine learning algorithms predict damage risk based on route, carrier, cargo type, and conditions. Alerts enable intervention before damage occurs. Cordstrap's global footprint enables 24/7 monitoring across time zones.
Platform Opportunity: The predictive risk intelligence could be licensed to insurers (to price cargo insurance accurately), carriers (to improve handling), and logistics platforms (to offer damage guarantees to their customers). Cordstrap's data advantage compounds with scale.
Key Partners
- IoT sensor manufacturers
- Cloud infrastructure providers
- Carriers & logistics platforms
- Insurance companies
- Data analytics partners
Key Activities
- Service delivery & installation
- Real-time monitoring operations
- Data analytics & ML model training
- Customer success management
- Platform development & licensing
Key Resources
- IoT sensor network
- Predictive analytics platform
- Shipment data & ML models
- Customer success teams
- Protection product inventory
Value Proposition
- Guaranteed damage-free delivery
- Real-time shipment visibility
- Predictive risk intelligence
- Reduced total protection cost
- Data-driven supply chain insights
Customer Relationships
- Ongoing partnership (not transaction)
- Dedicated success managers
- Quarterly business reviews
- Shared KPIs & outcomes
Channels
- Direct enterprise sales
- Digital platform (dashboard)
- API integrations (TMS/WMS)
- Partner channel (insurers, platforms)
Customer Segments
- High-value cargo shippers (primary)
- Automotive & industrial OEMs
- Cargo insurers (platform)
- Logistics platforms (platform)
Cost Structure
- Service operations & delivery
- Technology platform (cloud, sensors)
- Customer success teams
- Data infrastructure & analytics
- Protection product costs (variable)
Revenue Streams
- Monthly service subscriptions
- Per-shipment fees (usage-based)
- Platform licensing (insurers)
- Data & analytics services
Before: Product Sales
After: Outcome-Based Service
Riskiest Assumptions Identified
Before proceeding, the team identified the critical assumptions that could kill the concept:
Desirability: Will customers actually pay for outcomes instead of products? Will they trust Cordstrap with service delivery?
Feasibility: Can we achieve accurate enough damage prediction with IoT sensors? Can we deliver service at scale?
Viability: Can we price the service profitably while delivering value vs. product-only purchasing?
Adaptability: What happens if sensor technology commoditises? Can we defend the model?
Decision Point
The team presented the CargoShield Intelligence concept to the executive committee. Given the significant canvas changes (all 9 blocks affected) and the scale of the opportunity, leadership approved proceeding to hypothesis testing with a focus on Desirability first—if customers didn't want this, nothing else mattered. Budget: $400K for a 12-week testing sprint.
Hypothesis Design & Testing
Weeks 9-20The team designed experiments to test each critical assumption, starting with desirability and moving through feasibility and viability. They set success thresholds before running any tests.
Hypothesis Testing Results
Desirability
"Logistics managers at automotive parts shippers will sign LOIs for outcome-based protection because damage currently costs them 2-3% of shipment value."
Desirability
"Customers will value real-time visibility as much as the damage guarantee because they currently lack shipment condition data."
Feasibility
"We can predict cargo damage risk with 90%+ accuracy using shock, tilt, humidity, and route data from IoT sensors."
Feasibility
"We can deploy and retrieve sensors efficiently using our existing field service network and logistics partners."
Viability
"We can deliver CargoShield at $85/container with 45% gross margin, competitive with product-only costs."
Viability
"Customer acquisition cost will be under $8,000 because we're selling to existing relationships."
Adaptability
"Our predictive model creates defensible advantage because accuracy improves with proprietary shipment data."
Adaptability
"The service model survives a 30% volume drop because 60%+ of costs are variable."
Key Evidence Gathered
| Experiment | Method | Sample | Result |
|---|---|---|---|
| Customer demand validation | LOI requests | 30 prospects (top accounts) | 18 LOIs signed |
| Value driver research | Customer interviews | 25 logistics managers | Visibility + guarantee top priorities |
| Sensor accuracy pilot | Instrumented shipments | 500 containers | 84% prediction accuracy |
| Sensor retrieval operations | Logistics pilot | 150 shipments | 96% retrieval rate |
| Unit economics validation | Cost tracking | 75 service deliveries | $95/container, 40% margin |
| Insurance partner interest | Concept presentation | 6 major insurers | 4 expressed pilot interest |
"We've been trying to reduce damage for years with training and procedures. The idea that a supplier could actually guarantee outcomes—and show us the data in real-time across our entire global network—that fundamentally changes the conversation from cost management to value creation."
Decision Point
Evidence showed strong desirability (18 LOIs from major accounts), workable feasibility (with continued iteration on prediction accuracy), and viable economics (with adjusted pricing). Leadership approved proceeding to a full pilot with 15 customers across three regions, allocating $3M for 9-month pilot operations including technology build-out.
Pilot & Validate
Months 6-12Cordstrap launched CargoShield Intelligence with 15 pilot customers across EMEA, North America, and Asia-Pacific, delivering full service operations including product installation, sensor deployment, real-time monitoring, and damage guarantee. The goal: prove the model works across regions and refine operations for global scale.
Pilot Operations
Customers: Six automotive/industrial manufacturers, four chemical and pharmaceutical shippers, three wind/renewable energy component manufacturers, and two high-tech electronics companies. Combined volume: ~1,400 containers/month across Asia-Europe, transpacific, and intra-regional routes.
Service Delivery: Cordstrap teams installed protection and sensors at origin facilities. Three regional monitoring centres (Rotterdam, Singapore, Chicago) tracked shipments 24/7. When sensors detected risk conditions, field teams or local partners were dispatched for intervention. Products and sensors were retrieved at destination through an expanded partner network.
Technology Performance: Prediction accuracy improved from 84% to 91% over the pilot period as the model ingested more diverse route and cargo data. False positive rate dropped from 6% to 2.5%, significantly reducing unnecessary interventions and building customer confidence.
Economics: Actual delivery cost averaged $88/container at scale. With tiered pricing averaging $110/container, gross margin reached 20% in the pilot—approaching target and improving monthly as operations scaled and the model reduced intervention costs.
Pilot Learnings & Iterations
What Worked: Damage reduction exceeded expectations across all cargo types and routes. Customers valued visibility more than anticipated—11 of 15 pilot customers requested API access to integrate data into their own TMS/WMS systems. The damage guarantee created strong customer lock-in; no pilot customer wanted to return to products-only. Cross-selling of additional protection products increased 23% among pilot accounts.
What Needed Adjustment: Sensor retrieval in some Asian ports proved challenging; the team developed partnerships with local logistics providers in 12 additional countries. Initial monitoring centre staffing underestimated volume; added 30% headcount for full 24/7 coverage. Pricing model evolved from simple per-container to tiered volume pricing with route complexity factors.
Surprise Discovery: Four major cargo insurers approached Cordstrap during the pilot, interested in accessing shipment data to improve their risk pricing. Two global logistics platforms inquired about white-labelling the service. This validated the platform licensing opportunity earlier and larger than expected.
"In nine months, our damage claims dropped by 80% across 3,000 shipments. The ROI case is overwhelming—we're converting from pilot to a three-year enterprise agreement and expanding to all our Asia-Pacific routes. This is now a strategic supplier relationship, not a commodity purchase."
Decision Point
All 15 pilot customers converted to multi-year contracts. Eight expanded scope to additional routes or facilities. Net Promoter Score among pilot customers was 74. Unit economics were on track to target margins at scale. The board approved full commercialisation with $12M investment over 18 months for global sales expansion, operations infrastructure, and technology platform development.
Scale
Months 12-24With the model validated, Cordstrap scaled CargoShield Intelligence commercially while managing integration with the core product business. The platform licensing opportunity was advanced in parallel.
Commercial Scaling
Sales Expansion: Dedicated sales team of 24 people across three regions focused exclusively on CargoShield, supported by solution engineers and customer success managers. Target: existing Cordstrap customers with high damage rates and complex supply chains—the top 300 accounts represented the initial focus. Sales cycle shortened from 6 months (pilot) to 3.5 months (commercial) as case studies, references, and proof points accumulated.
Operations Build-out: Regional monitoring centres expanded in Rotterdam (EMEA hub), Singapore (APAC hub), and Chicago (Americas hub), with follow-the-sun 24/7 coverage. Field service partnerships expanded to 65+ countries through a combination of Cordstrap's existing service network and new logistics partners. Sensor inventory scaled to 200,000 active units.
Technology Investment: Platform enhanced with enterprise-grade customer dashboard, real-time APIs for TMS/WMS integration, mobile apps for field teams, and advanced analytics for supply chain insights. Prediction model retrained monthly with an ever-expanding dataset of 50,000+ monitored shipments.
Platform Licensing Launch
The cargo risk intelligence platform was productised as "CargoShield Insights" for external licensing:
Insurer Product: Cargo insurers access anonymised risk predictions and route analytics to price policies more accurately and identify loss prevention opportunities. Five insurers signed licensing agreements generating $3.2M in annual platform revenue, with per-query fees scaling with usage.
Carrier Integration: Shipping lines and freight forwarders access the platform via API to offer damage guarantees to their own customers, powered by Cordstrap's underlying risk intelligence and intervention network. Two major carriers and one global freight forwarder piloting integration, with revenue-share economics.
Data Services: Aggregated, anonymised supply chain analytics offered to shippers and consultants for route optimisation and carrier benchmarking—an emerging revenue stream with significant potential as the data moat deepens.
Business Integration
Relationship with Core Business: CargoShield operates as a separate business unit with its own P&L and leadership, but leverages core Cordstrap resources: manufacturing (protection products), global brand reputation, and existing customer relationships. Critically, product sales to CargoShield customers increased 28% as the service expanded—the model drove significant incremental product revenue rather than cannibalisation. Service customers simply used more protection, more consistently.
Organizational Model: A dedicated 85-person CargoShield team includes sales, customer success, operations, technology, and data science. The unit reports directly to the CEO with board-level visibility. Transfer pricing ensures both units benefit from internal product sales.
Ongoing Exploration: With the exploration capability now proven, the team continued identifying new opportunities. Three additional concepts entered the exploration phase: predictive maintenance for reusable packaging assets, a cargo compliance and documentation platform, and sustainability tracking for supply chain emissions—each leveraging the data and customer relationships built through CargoShield.
Transformation Outcomes — Year 3
Key Partners
- Raw material suppliers (core)
- IoT sensor manufacturers (new)
- Cloud infrastructure (new)
- Local logistics partners (new)
- Cargo insurers (new)
Key Activities
- Product manufacturing (core)
- Service delivery operations (new)
- 24/7 monitoring centre (new)
- Data analytics & ML (new)
- Platform development (new)
Key Resources
- Manufacturing facilities (core)
- IoT sensor network (new)
- Predictive analytics platform (new)
- Shipment data (new moat)
- Customer success teams (new)
Value Proposition
- Quality protection products (core)
- Guaranteed damage-free delivery (new)
- Real-time visibility (new)
- Predictive risk intelligence (new)
- Data-driven insights (new)
Customer Relationships
- Transactional sales (core)
- Outcome-based partnerships (new)
- Customer success management (new)
- Quarterly business reviews (new)
Channels
- Direct sales (core)
- Distributor network (core)
- Digital platform/dashboard (new)
- API integrations (new)
- Partner channels (new)
Customer Segments
- All cargo shippers (core products)
- High-value cargo shippers (service)
- Cargo insurers (platform)
- Carriers & platforms (platform)
Cost Structure
- Manufacturing (core: 40% COGS)
- Service operations (new: variable)
- Technology platform (new: fixed)
- Customer success (new: semi-fixed)
Revenue Streams
- Product sales (core: 76%)
- Service subscriptions (new: 19%)
- Platform licensing (new: 5%)
Key Lessons from the Transformation
Start with Desirability—Even at Scale
Despite pressure to build technology first given available resources, the team validated customer demand with LOIs before major investment. Eighteen signed LOIs from top accounts de-risked an $12M commercialisation decision.
Leverage the Customer Base
With 1,000+ existing relationships, Cordstrap had a built-in test market and sales pipeline. Acquisition costs were 65% lower selling to existing customers than acquiring new ones. Trust was already established.
Iterate Economics Relentlessly
Initial pricing and margin assumptions proved optimistic. The team ran three pricing model iterations during the pilot before finding the right structure. Flexibility preserved the opportunity.
Service Amplifies Products
Fears of cannibalisation proved unfounded. Service customers consumed 28% more protection products as relationships deepened and usage expanded to new routes and facilities. The flywheel worked.
Data Compounds Into Moat
The predictive model improved with each shipment. After 50,000+ monitored containers, accuracy reached 91%—a level that would take competitors years to replicate without equivalent data history.
Platform Opportunities Emerge
The $4.8M licensing revenue wasn't in the original plan—it emerged from insurer and carrier interest during the pilot. Staying alert to unexpected value creation paths turned a bonus into a meaningful revenue stream.