The Scoop on G2P Pick Rates

It’s a familiar scenario: You buy a cutting-edge new toy and want to step on the gas to see how fast it goes.

Whether you’re test driving a luxury sports car or rolling out a Ferrari-red robot in your warehouse, performance isn’t just about raw speed.

Let's examine why your operation may not be reaching the "advertised" throughput rate, what factors actually determine pick rate, and tips to maximize your goods-to-person (G2P) automation ROI.

Why “Rate” is Not Always THE Rate 

One of the biggest disconnects in fulfillment automation is the difference between the mechanical rate (the number of bins the system is capable of presenting under ideal conditions) and the operational pick rate (what happens in the real world). It’s the same as buying a car that’s rated for 200 mph on the track but realizing traffic and stoplights mean you’ll rarely break 50.

Mechanical rate is not the real rate that you can expect your G2P to run in an everyday production environment. The real rate is a whole-system calculation that blends equipment, orders, people, and design.

Examples of real-world impacts:

• An initial ramp-up period is expected between when a system is installed and when the system reaches maximum operational rate.
• Pre-cartonization limits flexibility because orders must be sequenced by box size. Post-cartonization allows better flow.
• A system rated at 120 picks/hour may average closer to 100 once operator variability is accounted for.
• Peak fatigue periods may drag pick rate below baseline, especially if workstations aren’t designed for ease and recovery.

To better understand the language of G2P performance and ROI calculations through the lens of operations, we will discuss:

1. Factors That Affect Pick Rate
   
   • Mechanical 
     
   • Order Management and Batching
   • Humans
   • Storage Design & Inventory
2. Performance Framework
   
3. ROI
4. Key Takeaways

• Partner Spotlight - TGW

Factors That Affect Pick Rate  

Mechanical Considerations 

Mechanical design directly impacts achievable pick rate and should be the first factor considered when evaluating performance. Equipment capabilities and potential delays must be built into the equation.

Station configuration also plays a role: one-to-one and one-to-many setups each bring tradeoffs, while order width (single tote versus multiple totes) directly affects efficiency. These mechanical factors establish the baseline before moving on to actual pick-rate calculations.

Order Management and Batching 

• Order pool size matters: If you can gather all orders for tomorrow and sequence them ahead, that’s ideal. In reality, orders often arrive throughout the day, so there isn't always the opportunity to pick and choose. 

• Batch size and order commonality: Order commonality (e.g., a factor of 4) means each line item or tote may satisfy multiple orders. The effectiveness of batching depends on the size of your order pool and how many orders are active at one time.
  Over time, the “batch factor” runs out. You cherry-pick the easy, high-commonality orders first, leaving behind orders with little or no commonality. OR you may only see three orders at a time.  In that window, SKU commonality drops to zero.
• Constraints from SL A s: Service level agreements (SL A) may force you to group orders by delivery time rather than commonality. If orders must be processed quickly, batching flexibility decreases.
• Cycle time and service level: The time it takes to complete an order directly impacts your ability to meet SL A s. Faster cycle times allow more flexibility to bring orders forward and still meet deadlines.
• System design tradeoffs: Tight SL A s may force you to prioritize speed over batch optimization. Systems like cube-based ASRS shine when orders are given in advance, and they can pre-arrange bins. If they can’t, cycle times increase, and you pay for it in throughput.

Human Factors

A system may be designed to do “X” presentations per hour, but human factors play into the actual pick rate. The gap is often due to operator performance and process conditions. Every operation has high- and low-performing operators. Realistic pick rates may be 15–20% lower than the mechanical spec.

Fatigue and natural productivity cycles (morning peak, midday dip, afternoon decline) affect consistency. Ergonomics and workstation design also determine how sustainable performance is across a shift.

Pick rate calculations must reflect real-world operator capability rather than ideal design rates. A vendor might claim a system can achieve 500 lines per hour. Validating that requires breaking down what the operator actually has to do:

• Walk between stations
• Reach and grab items
• Wait for bins or totes
• Handle exceptions and delays

When you add human motion and fatigue into the equation, the true operational rate is usually lower than the glossy spec sheet.

Storage Design and Inventory 

Fill Levels and Retrieval Time

One of the first things to consider in an ASRS is how full the system is. Fill levels directly affect retrieval speed. The more densely packed the system, the longer it can take to fetch a bin. That delay adds up quickly when throughput targets are tight.

Storage Planning Questions

Every storage strategy begins with a few simple but critical questions:

• What unit of measure are you receiving - pallet, case, or each?
• What is the smallest unit of measure you will be picking?
• What exactly will you be storing in each tote?

The answers drive how efficiently your automation performs day-to-day.

Replenishment vs. Picking Tradeoff

There’s always a give-and-take between replenishment and picking. Dropping a full case into a tote speeds up replenishment, but if your operation picks at the “each” level, workers now need to open cases and handle smaller units, which slows down throughput.

Tote Design Considerations

The number of locations or compartments inside each tote also matters. Tote design should be matched to product size, SKU velocity, and the overall storage strategy to keep the balance between replenishment and picking efficient.

SKU Velocity Considerations

Not every SKU is suited for ASRS storage. Very fast-moving SKUs can bog the system down since their totes are constantly being retrieved and it’s often faster to pick them manually. On the other hand, medium movers typically hit the “sweet spot” for G2P performance. Slow movers, or “dogs,” are also good candidates for ASRS, since automating their retrieval reduces operator walking and improves efficiency on the floor.

Performance Framework

Performance is always a balancing act. Capacity, utilization, throughput, productivity, and operational rates work in sync to deliver ROI.

1. Capacity is your ceiling, what the system could do if everything were perfect. It’s based on equipment specs, layout, and theoretical limits.
2. Rate tells you how a piece of equipment in the system is designed to mechanically operate (e.g., tote presentation every 3 seconds). It’s a design benchmark, not a performance guarantee.
3. Operational Rate is the realistic speed at which tasks are completed, factoring in fatigue, layout, item complexity, and other real-world conditions. It reflects how efficiently people and systems work.
4. Throughput is the actual output, determined by multiplying operational rate by the number of active workers and stations. It’s what you actually get done.
5. Utilization compares throughput to capacity, showing how much of the system’s potential is being used. High utilization means you're nearing your system’s limits; low utilization may indicate underuse or inefficiencies.
6. Productivity measures how efficiently inputs (like labor, time, and energy) are converted into outputs. It influences operational rate and throughput. High productivity means more output per unit of input whether that’s picks per labor hour, totes per shift, or orders per dollar spent.

How Productivity Interacts with Others

• Productivity drives operational rate: The more efficient your workforce or automation is, the faster tasks get done.
• Operational rate drives throughput: Faster, more consistent execution leads to higher output.
• Throughput compared to capacity gives utilization: This shows how much of your system’s potential is being realized.
• Rate and capacity set the boundaries, but productivity determines how close you get to them.

Enter in Order Cycle Time and Storage Capacity 

On time and in full orders is the goal. Going fast might feel good, but without completing orders it may not matter much.

Order Cycle times, how things are stored and retrieved, and how the inventory is presented will impact the overall system performance framework and what is possible.

Order Cycle Time is the total time it takes to process an order, from receipt to shipment. It’s influenced by throughput, operational rate, and productivity. Lower cycle times often indicate higher productivity and throughput.

Storage Utilization measures how effectively storage space is used. It reflects the percentage of total storage capacity actively occupied by inventory and is shaped by:

• SKU density and velocity
• Tote/bin dimensions and product profiles
• Replenishment frequency and days-on-hand
• System design (e.g., mini-load vs. shuttle vs. cASRS)

Poor utilization can lead to poor inventory availability, requiring more time to get things where they need to be.

ROI

CapEx, OpEx & Time to Value

Return on investment (ROI) for a goods-to-person system goes far beyond the initial equipment price tag. It starts with capital expenses. These include the G2P technology itself, operator workstations, and supporting infrastructure such as conveyors that connect the point solution to the rest of the warehouse.

Once the system is live, operational expenses become the focus. Efficiency in picking, packing, replenishment, and exception handling all impact long-term performance and ROI.

Facilities costs add another dimension to the calculation. Key considerations include how effectively the system utilizes space and the overall cost per cubic foot.

Finally, ROI depends on how quickly the system delivers measurable results. Time to Value captures the length of time it takes for your investment to realize its full operational impact.

Key Takeaways for Operations Leaders 

1. Involve operations teams during solution design.
2. Calculate your operational rate, not just the mechanical one.
3. Define a realistic standard operator performance rate.
4. Maintain a steady operating cadence to avoid peaks and troughs.
5. Simplify operator work methods and prioritize ergonomics.
6. Don’t design on averages or incomplete assumptions, model real conditions.
7. Avoid linear processes or siloed subsystems that create bottlenecks.
8. Ensure adequate queueing at workstations to keep people productive.
9. Provide enough system capacity to minimize replenishment drag.
10. Plan for “rainy day” scenarios and operational forgiveness.
11. Build an operating plan to sustain balanced material flow across shifts.
12. Base design on actual order profiles, SKU velocities, and slotting rather than estimates.

Calculating G2P pick rate is about understanding the interplay between throughput, capacity, human factors, and order management. By focusing on operational realities, you’ll set your warehouse up for better performance, higher utilization, and stronger ROI.

FINDING THE RIGHT SOLUTION

TGW Stingray Shuttle

The Stingray ASRS Shuttle is a high-throughput, high-density storage and retrieval system designed to handle large, diverse SKU populations. It’s ideal for high-volume ecommerce and retail fulfillment and operates effectively across a wide range of temperatures.

 High-density, high-throughput solution idea for high-volume ecommerce and retail fulfillment

TGW PICKCENTER ONE

The PickCenter One is a high-performance, manual goods-to-person workstation that supports efficient single-order processing, helping operators work with precision while reducing physical strain.

TGW PICKCENTER MULTI

Built for multi-order processing, the PickCenter Many is an advanced manual workstation that brings efficiency and flexibility to high-volume fulfillment. This configuration empowers operators to manage multiple orders simultaneously with speed and accuracy. Perfect for operations handling diverse SKUs and dynamic order profiles.

TREW AND TGW SOLUTIONS

HOW TO GET STARTED

Are you ready to start your automation journey and wonder how to get started and what might fit your operation?

Reach out to a qualified automation provider that can assess your operation, evaluate your current mechanization, and deliver performance improvement with data driven solutions that produce results.