Boost Picking Operations With AI Scheduling

Optimal picking for all of your order pickers to increase productivity and cut travel time by up to 43%

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The new way of picking in the “never normal” era

Manual

• Determining the daily workload per warehouse area is difficult.
• Batches aren't put together most efficiently.
• There are no optimized picking lists

Automated

• Lower labor costs by forecasting workloads.
• Intelligent batch picking increases productivity.
• Picking path optimization cuts travel time nearly in half.

Common Picking Problems

“Our pickers are transferred from area to area in response to new order waves, as we have no visibility into the upcoming hours’ workload.”
“While pickers are provided with picklists, they should have their own paths to take.”
“Sorting operations necessitate a small batch size, whereas picking efficiency necessitates a large batch size. What is the cost-benefit analysis?”

AI Scheduling enables planners
to understand the optimal picking sequences.

AI Scheduling on top of your WMS

AI

AI-powered Warehouse Workforce Demand Planning

To avoid over- or under-staffing, adjust labor allocation throughout a shift to ensure that work is completed on time. Pickers can be reassigned to other areas based on shifts in projected workloads per warehouse area throughout the day.
Route

Real-Time Batching & Waving

Have optimized batches of pick lines that are assigned to pickers. Creating optimal waves based on customer order batching across multiple areas, order drop time, and maximum wave sizes.
Map

Picking Path Optimization

Determine the best path for the worker to take through the warehouse to complete their work. Picklist optimization within a wave or batch based on warehouse area layout and pick dimensions.
AI Scheduling

Key results, powered by Solvice

Customer details

40+

Warehouses

50-500

Workers per warehouse

€18 Mld

Revenue

Results

50%

Decrease in actual overtime

11%

More accurate workload prediction
Customer details

150k

Orders per day

3.000

Batches

90.000

Sqm.

32

Warehouse areas
Results

15-20%

Increase in order efficiency

39%

Decrease in travel time
Customer details

1.000+

Workers

€120 Mln

Revenue

Results

10%

Less congestion

20%

Shorter travel times

Aim high, start small, and iterate quickly

How AI-powered labor demand planning and picking optimization can be used to automate and optimize fulfilment operations.
The role of data in labor planning and picking scheduling.
How to integrate AI-powered capabilities to your current WMS.
Sales person
In your demo, Solvice expert Michaël Saintobyn will show you how warehouses use automated, AI-driven scheduling to optimize picking operations.

To learn more, request your demo

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