A measure of how effectively warehouse machinery, tools, or automated systems are used relative to their available capacity. High utilisation indicates efficient use of equipment, while low utilisation may highlight underused resources or process inefficiencies. Monitoring equipment utilisation helps optimise workflows, reduce operational costs, and plan maintenance.

Equipment Utilisation measures how effectively warehouse machinery, tools, or automated systems are used relative to their available capacity. High utilisation indicates efficient equipment use, while low utilisation may highlight underused resources or process inefficiencies. Monitoring equipment utilisation helps optimise workflows, reduce operational costs, and plan maintenance.

It's knowing whether your £200,000 conveyor system is earning its keep or sitting idle.

Why Equipment Utilisation Matters

Capital equipment represents a massive investment. Forklifts cost £20,000-£50,000 each. Automated sortation systems run into the hundreds of thousands. If that equipment is 40% capacity, you're burning money on underutilised assets.

But here's the twist: 100% utilisation isn't the goal either. Running equipment at maximum capacity constantly leaves no buffer for peaks, maintenance, or breakdowns. You need the Goldilocks zone: high enough to justify investment, low enough to maintain flexibility.

Poor utilisation signals deeper problems. Equipment sitting idle whilst in the orders queue indicates workflow bottlenecks. Machinery running constantly beyond rated capacity predicts imminent failure and expensive emergency repairs.

Measuring Equipment Utilisation

The basic formula is straightforward:

Equipment Utilisation = (Actual Operating Time ÷ Available Time) × 100

But "available time" needs defining. Does it include:

• Planned maintenance downtime?

• Shift breaks?

• Weekends?

• Holiday periods?

Operational hours approach: Total hours the facility operates (e.g., 16 hours daily, 6 days weekly).

Calendar hours approach: Total hours (168 hours weekly).

Choose one consistently. Operational hours give higher utilisation figures but more accurately reflect genuine availability.

Example: Conveyor system in operation running 12 hours daily, 5 days weekly:

• Available time: 60 hours weekly

• Actual running time: 42 hours

• Utilisation: (42 ÷ 60) × 100 = 70%

Types of Equipment Utilisation

Physical Utilisation

Time equipment actively operates versus the total available time.

Material handling equipment: Forklifts, pallet jacks, picking carts, automated guided vehicles (AGVs).

Processing equipment: Conveyor systems, sortation equipment, packing stations.

Storage equipment: Automated storage and retrieval systems (AS/RS), vertical lift modules.

Capacity Utilisation

How close does the equipment run to the maximum rated capacity?

Example: Conveyor rated for 5,000 units per hour but processing an average of 3,200 units per hour:

• Capacity utilisation: 64%

This differs from time-based utilisation. Equipment might run 100% of available time but only at 60% capacity, indicating over-specification or growth headroom.

Productivity Utilisation

Measures useful output versus potential output, accounting for efficiency losses.

Formula: (Actual Output ÷ Theoretical Maximum Output) × 100

Example: Automated picking system theoretically achieves 200 picks per hour:

• Actual average: 160 picks per hour

• Productivity utilisation: 80%

The 20% gap represents inefficiencies: equipment stoppages, changeovers, and errors requiring intervention.

Factors Affecting Equipment Utilisation

Demand Variability

Order volume fluctuates daily, weekly, and seasonally. Equipment sized for peak demand runs underutilised during quiet periods.

Example: Retailer experiences 3× normal volume during Black Friday and Christmas. Equipment utilisation:

• Peak periods: 95%

• Normal periods: 35%

• Annual average: 45%

This isn't poor planning; it's reality. The alternative is turning away business during peaks.

Process Bottlenecks

Equipment sits idle waiting for upstream or downstream processes to catch up.

Scenario: High-speed sortation system (10,000 units/hour capacity) receives goods from picking (4,000 units/hour capacity). Sortation utilisation is capped at 40% by picking the bottleneck.

Fix the bottleneck, and utilisation improves across the entire operation.

Maintenance and Downtime

Planned maintenance: Scheduled servicing reduces available time but prevents catastrophic failures.

Unplanned downtime: Breakdowns stop operations entirely. One hour of unplanned downtime often costs more than ten hours at low utilisation.

Best practice: Schedule maintenance during naturally quiet periods (weekends, overnight, seasonal lows).

Shift Patterns

Single-shift operation (8 hours daily) means the equipment sits unused for 16 hours. Add a second shift, and potential utilisation doubles.

Consideration: Labour costs increase with additional shifts. Calculate whether improved equipment utilisation justifies higher staffing costs.

Product Mix

Different products require different handling. Automated systems optimised for uniform cases struggle with mixed SKU sizes, reducing effective utilisation.

Example: AS/RS, designed for standard pallet sizes, operates at 85% utilisation with uniform loads but drops to 55% when handling mixed-dimension freight requiring manual intervention.

Optimal Utilisation Targets

Industry benchmarks vary by equipment type and operation:

Material Handling Equipment

Forklifts: 60-75% utilisation is considered optimal. Higher suggests too few units (congestion, waiting). Lower suggests over-investment.

Pallet jacks: 40-60% typical. Lower investment cost makes lower utilisation acceptable.

AGVs: 70-85% target. High capital cost requires strong utilisation to justify ROI.

Automated Systems

Conveyor systems: 65-80% optimal. Need a capacity buffer for surge demand and maintenance windows.

Sortation equipment: 70-85% target range. An expensive investment requires high utilisation.

AS/RS: 75-90% ideal when operating. Downtime for maintenance is still necessary.

Support Equipment

Printers and scanners: 40-70% typical. Lower utilisation is acceptable given the modest cost.

Packing stations: 80-90% during operating hours. Relatively low cost means adding capacity is inexpensive insurance.

Improving Equipment Utilisation

Workload Balancing

Distribute work evenly across available equipment rather than overloading some whilst others sit idle.

Warehouse management systems automate this through intelligent task allocation, ensuring balanced utilisation.

Example: Warehouse with four packing stations. Without WMS, orders queue at two busy stations whilst two others are underutilised. With WMS, orders automatically route to available stations. Result: 35% improvement in overall station utilisation.

Shift Optimisation

Match equipment availability to demand patterns.

Analysis: Track order arrival times and fulfilment urgency. If 70% of orders arrive before 2pm, requiring same-day dispatch, concentrate equipment and staff in the morning/early afternoon.

Extended hours: If utilisation is low because equipment runs only 8 hours but orders span 12 hours, consider extended shift patterns.

Preventive Maintenance

Counter-intuitive: Scheduling planned downtime actually improves utilisation by preventing longer unplanned outages.

Data:

• Planned maintenance: 2 hours monthly (2% downtime)

• Avoided unplanned failures: 8 hours monthly average (8% downtime)

• Net gain: 6% improved utilisation

Process Improvements

Eliminate bottlenecks constraining equipment throughput.

Scenario: Conveyor utilisation capped at 60% because manual packing can't keep pace. Options:

• Add packing capacity (more stations, more staff)

• Automate packing (expensive but removes the bottleneck)

• Accept current utilisation (if still profitable)

Right-Sizing Equipment

Sometimes low utilisation signals over-investment. Better to sell or redeploy excess equipment than pay for unused capacity.

Example: 3PL purchased five forklifts for expected growth that didn't materialise. Running at 40% utilisation. Better to sell two units, operate three at 65% utilisation, reduce depreciation and maintenance costs.

Flexible Deployment

Cross-train staff and configure equipment for multiple purposes.

Example: Picking carts double as replenishment trolleys. When demand is low, the same equipment supports stock replenishment. Improved overall utilisation without additional investment.

Technology and Tracking

Modern systems provide granular utilisation data:

Warehouse management systems: Track equipment task allocation, idle time, and throughput rates.

IoT sensors: Monitor actual equipment operation; running time, cycles completed, and idle periods.

Maintenance management systems: Log downtime reasons (planned maintenance vs breakdowns), identify patterns.

Analytics dashboards: Visualise utilisation trends, compare across equipment types, and identify improvement opportunities.

Example: A fashion retailer implements IoT tracking on all material handling equipment. It discovers that forklifts average 52% utilisation but with massive variation; three units consistently above 75%, two barely reach 30%. Investigation reveals poor spatial allocation. Reorganisation balances utilisation across the fleet and eliminates the need for planned forklift purchases.

Common Utilisation Mistakes

Focusing Only on Peak Utilisation

Running at 95% utilisation during Black Friday doesn't offset the 30% average the rest of the year. The annual average matters more for investment justification.

Ignoring Quality and Safety

Pushing utilisation too high reduces time for proper maintenance, increases error rates, and compromises safety. It is better to run at a sustainable 75% than an unsustainable 95%.

Not Segmenting Data

"Average utilisation" across dissimilar equipment is meaningless. Track by equipment type, shift, season, and operational area.

Chasing 100% Utilisation

No buffer for peaks, maintenance, or problems. Recipe for operational chaos and equipment failure.

Getting Started

1. Identify critical equipment – Focus on high-value or bottleneck assets first.

2. Establish tracking – Manual logs initially, automated systems as you scale.

3. Calculate baseline utilisation – Measure 2-4 weeks for reliable data.

4. Set realistic targets – Based on equipment type and operational patterns.

5. Identify low-hanging fruit – Simple improvements yielding quick wins.

6. Implement changes – Address obvious inefficiencies systematically.

7. Monitor continuously – Utilisation changes as business evolves.

Equipment utilisation isn't about squeezing maximum output from machinery at all costs. It's about finding the sweet spot where investment delivers value without sacrificing flexibility, sustainability, or quality.

Get it right, and you'll justify capital expenditure, optimise operational costs, and build resilient operations that scale efficiently.