Visual Martyn’s Law in Action | From Manual Security Handling to Automated Storage Systems
Manual security handling relies on people, processes, and physical interaction — creating bottlenecks, inconsistencies, and increased risk at scale. As crowd volumes rise, these systems struggle to maintain control, speed, and compliance.
This video shows how automated storage systems transform venue security by removing items from the process before they reach checkpoints. Using smart lockers, attendees store belongings independently, reducing queues, improving throughput, and enabling more consistent, controlled security operations.
By shifting from manual handling to automated infrastructure, venues can reduce human error, lower crowd density, and create a safer, more scalable security model aligned with modern requirements ( See comparison: event lockers vs bag check systems) and Martyn’s Law.
Manual Security Handling vs Automated Storage Systems — Quick Comparison
Manual Security Handling
Human-controlled security model
High staff dependency
Low throughput capacity
Limited scalability
High error risk (human error)
No or limited audit trail
High queue impact at peak times
Automated Storage Systems
System-controlled security model
Minimal staff involvement
High throughput capacity
Modular and scalable
Near-zero error risk
Full digital audit logs
Minimal queue impact
Manual Security Handling vs Automated Storage Systems— Full Comparison
Category
Core Model
Process
Bag / Item Handling
Security Approach
Screening Complexity
Speed (Per Person)
Queue Formation
Ingress Throughput
Peak Demand Handling
Crowd Density (Pre-Entry)
Dwell Time (Before Entry)
Perimeter Risk
Staffing Requirement
Operational Complexity
Consistency
Human Error Risk
Scalability
Security Effectiveness
Audit Trail
Accountability
Visitor Experience
Visitor Independence
Compliance Alignment (Martyn’s Law)
Space Requirement
Cost Model
Cost Predictability
Revenue Potential
Integration Capability
Failure Points
Use Case Fit
Manual Security Handling (Staff-Led Processes)
Staff inspect, manage, and control items manually
Queue → manual check → handling → decision → entry
Manual — handled at checkpoint
Reactive — detect threats at entry
High — variable items and decisions
Slow — dependent on inspection time
High — bottlenecks at entry points
Limited — constrained by staff and checks
Poor — queues grow rapidly under pressure
High — queues increase crowd build-up
High — extended waiting periods
Increased — large crowds form outside security
High — multiple lanes and personnel required
High — coordination, judgement, variability
Variable — depends on staff performance
High — missed items, inconsistent checks
Limited — requires more staff and lanes
Dependent on staff accuracy and conditions
Limited — little or no item-level tracking
Weak — shared responsibility
Friction — delays, intrusive checks
Low — fully controlled by staff
Challenging — queues increase exposure risk
Large — multiple screening lanes and queues
High — ongoing staffing costs
Variable — depends on staffing levels
None
Limited
Staff fatigue, inconsistency, queue escalation
Low-volume or legacy setups
Automated Storage Systems (Smart Lockers / Pre-Entry Infrastructure)
Items are removed and secured via automated systems before entry
Store → secure → proceed bag-free → streamlined entry
Eliminated from checkpoint
Preventative — remove items before entry
Low — fewer variables at checkpoint
Fast — reduced screening requirements
Low — faster throughput reduces queues
High — simplified, faster processing
Strong — system absorbs high volumes
Lower — faster flow reduces crowd density
Low — minimal waiting time
Reduced — faster clearance lowers risk exposure
Lower — fewer staff needed at entry
Low — standardised, automated workflows
High — system-driven consistency
Low — reduced manual intervention
High — scale infrastructure, not labour
Improved — fewer unknowns at entry
Full — digital logs of usage and access
Strong — user-linked interactions
Smooth — faster, less invasive
High — self-service before entry
Strong — reduces external crowd risk
Compact — distributed storage footprint
Lower long-term cost-to-serve
Predictable — infrastructure-based
Possible — paid storage (£5–£10 per use)
Integrates with access control, ticketing, and payments
Minimal — system-driven reliability
High-volume, security-critical environments
Manual Security Handling (Staff-Led Processes)
Core Model
Staff inspect, manage, and control items manually
Process
Queue → manual check → handling → decision → entry
Bag / Item Handling
Manual — handled at checkpoint
Security Approach
Reactive — detect threats at entry
Screening Complexity
High — variable items and decisions
Speed (Per Person)
Slow — dependent on inspection time
Queue Formation
High — bottlenecks at entry points
Ingress Throughput
Limited — constrained by staff and checks
Peak Demand Handling
Poor — queues grow rapidly under pressure
Crowd Density (Pre-Entry)
High — queues increase crowd build-up
Dwell Time (Before Entry)
High — extended waiting periods
Perimeter Risk
Increased — large crowds form outside security
Staffing Requirement
High — multiple lanes and personnel required
Operational Complexity
High — coordination, judgement, variability
Consistency
Variable — depends on staff performance
Human Error Risk
High — missed items, inconsistent checks
Scalability
Limited — requires more staff and lanes
Security Effectiveness
Dependent on staff accuracy and conditions
Audit Trail
Limited — little or no item-level tracking
Accountability
Weak — shared responsibility
Visitor Experience
Friction — delays, intrusive checks
Visitor Independence
Low — fully controlled by staff
Compliance Alignment (Martyn’s Law)
Challenging — queues increase exposure risk
Space Requirement
Large — multiple screening lanes and queues
Cost Model
High — ongoing staffing costs
Cost Predictability
Variable — depends on staffing levels
Revenue Potential
None
Integration Capability
Limited
Failure Points
Staff fatigue, inconsistency, queue escalation
Use Case Fit
Low-volume or legacy setups
Automated Storage Systems (Smart Lockers / Pre-Entry Infrastructure)
Core Model
Items are removed and secured via automated systems before entry
Process
Store → secure → proceed bag-free → streamlined entry
Bag / Item Handling
Eliminated from checkpoint
Security Approach
Preventative — remove items before entry
Screening Complexity
Low — fewer variables at checkpoint
Speed (Per Person)
Fast — reduced screening requirements
Queue Formation
Low — faster throughput reduces queues
Ingress Throughput
High — simplified, faster processing
Peak Demand Handling
Strong — system absorbs high volumes
Crowd Density (Pre-Entry)
Lower — faster flow reduces crowd density
Dwell Time (Before Entry)
Low — minimal waiting time
Perimeter Risk
Reduced — faster clearance lowers risk exposure
Staffing Requirement
Lower — fewer staff needed at entry
Operational Complexity
Low — standardised, automated workflows
Consistency
High — system-driven consistency
Human Error Risk
Low — reduced manual intervention
Scalability
High — scale infrastructure, not labour
Security Effectiveness
Improved — fewer unknowns at entry
Audit Trail
Full — digital logs of usage and access
Accountability
Strong — user-linked interactions
Visitor Experience
Smooth — faster, less invasive
Visitor Independence
High — self-service before entry
Compliance Alignment (Martyn’s Law)
Strong — reduces external crowd risk
Space Requirement
Compact — distributed storage footprint
Cost Model
Lower long-term cost-to-serve
Cost Predictability
Predictable — infrastructure-based
Revenue Potential
Possible — paid storage (£5–£10 per use)
Integration Capability
Integrates with access control, ticketing, and payments
Failure Points
Minimal — system-driven reliability
Use Case Fit
High-volume, security-critical environments
What Is Manual Security Handling?
Manual security handling refers to staff-led processes where personnel:
- Physically inspect bags
- Handle and move items
- Store belongings in shared areas
- Manage access and retrieval
Common examples:
- Bag searches
- Cloakrooms
- Back-of-house storage rooms
- Concierge-style handling – See also: manual storage vs lockers →
What Are Automated Storage Systems?
Automated storage systems (e.g. smart lockers) are self-service, technology-driven solutions where users:
- Store items independently
- Access via QR code, PIN, or app
- Retrieve belongings without staff involvement
Core features:
- Individual secure compartments
- Digital access control
- Real-time usage tracking
- Contactless operation
The Core Problem with Manual Handling
Manual processes are inherently linear and labour-intensive.
Every item requires:
- Staff interaction
- Time to inspect or move
- Decision-making under pressure – A limitation highlighted in bag searches vs pre-entry locker storage →
Result:
- Slower processing
- Increased queues
- Inconsistent security outcomes
Why Manual Systems Fail at Scale
At high volumes:
- Staff fatigue reduces effectiveness
- Processing times increase
- Bottlenecks form at entry points
- Risk exposure increases due to crowd build-up
Key issue:
Manual systems cannot scale without adding more people — and even then, performance degrades – Common in cloakroom vs lockers comparisons →
How Automated Storage Systems Solve This
Instead of:
One staff member handling one item at a time
You get:
Hundreds of users storing items simultaneously – See approach in bag searches vs pre-entry locker storage →
Security Advantages
Reduced Risk & Controlled Storage
- No misplacement of items
- No inconsistent decision-making
- Each item stored in an individual compartment
- No shared risk environments- Compared with event lockers vs bag check systems →
Full Tracking & Accountability
- Time-stamped digital logs
- User-linked access records
- Clear accountability for every item stored and accessed
Operational Efficiency Gains
Manual Handling:
- Labour-heavy
- Difficult to scale
- Requires constant supervision – Also seen in manual storage vs lockers →
Automated Systems:
- Low operational overhead
- Predictable performance
- Minimal supervision required
Throughput Comparison
Manual Model:
- Sequential processing
- Throughput capped by staff capacity – Demonstrated in event lockers vs cloakrooms →
Automated Model:
- Parallel processing
- Throughput scales with number of lockers
Impact on Event Ingress
Manual Handling:
- Slows entry
- Creates queues outside venues
- Increases congestion risk – Related: cloakrooms vs lockers for event security →
Automated Storage:
- Removes items before entry
- Speeds up security lanes
- Improves crowd flow
Alignment with Martyn’s Law
Martyn’s Law emphasises:
- Risk reduction
- Preparedness
- Proportionate security measures – See application in bag searches vs pre-entry locker storage →
Automated systems support this by:
- Reducing items entering venues
- Improving traceability
- Minimising queue-related vulnerabilities
Cost & ROI Comparison
Manual Handling:
- High staffing costs
- Ongoing operational expense
- No direct revenue – Compare with free storage vs paid locker systems →
Automated Systems:
- Reduced labour costs
- Pay-per-use revenue model
- Long-term operational savings – Learn more: capex vs opex locker model →
User Experience
Manual:
- Waiting in queues
- Handing over personal items
- Delays during collection – Compared with self-service lockers vs staffed storage →
Automated:
- Instant storage
- Full user control
- Faster, frictionless experience
When to Transition to Automation
Automated storage becomes critical when:
High visitor volumes
Peak-time congestion
Security compliance pressure
Limited staffing resources
Demand for premium experience
The Bottom Line
Manual security handling was built for lower-risk, lower-volume environments.
Modern venues require systems that:
- Scale instantly
- Reduce reliance on human processes
- Improve both security and efficiency
Automated storage systems transform security from a bottleneck into a controlled, scalable process
See full comparison: cloakrooms vs lockers for event security →