A Fundamentally Different Piece Picking Solution that Delivers Global Benefits

A Fundamentally Different Piece Picking Solution that Delivers Global Benefits

NextShift’s unique autonomous mobile robotics system is the key to winning the piece-picking efficiency battle.

NextShift autonomous robots reduce travel time, optimize picker movements, and increase order speed to boost piece picking performance by at least 2x and dramatically cut operating costs. NextShift software is the key. Our innovative, field-proven system manages


  • Where the pickers pick and in what sequence,
  • The pickers’ travel paths,
  • How many pickers are required for the order volume,
  • How orders are grouped and sequenced,
  • How many totes are required to support the process,
  • Where the totes are placed and picked up and when,
  • The tote travel path through the warehouse,
  • The robots’ travel path through the warehouse,
  • How many robots are required to support the time reduction and work speed goals

Optimization Produces Balanced Value

NextShift software uses the physical layout of the facility (pick face distances, pack/ship distances, and SKU locations) and data that describes the pick process (orders to be picked, typically from a Warehouse Management System) to create optimization across orders, pickers, totes, and of course, robots.

Order optimization looks at the order volume and mix.  This process runs dynamically as orders or batches of orders are received.  It determines how many orders need to be picked, how many of those are single line orders and how many are multi-line orders.  The ratio of single-line orders to multi-line orders and the size of the multi-line orders will determine how to pick them most efficiently. In many cases, combining two single-line orders in one tote is the most efficient way to pick them, but each situation can be different. Multi-line orders can be automatically split into multiple totes for efficiency, based on size and weight of each SKU. The NextShift system re-sequence orders to create the most efficient grouping of picks that produces the highest utilization and least travel time for both pickers and robots.

Order optimization drives picker optimization. Picker walking time is greatly reduced and pickers no longer load and unload carts. With the NextShift system pickers only pick to totes, while the robots do all the order moves. The system also reduces the time between picks through clustering. All of this substantially cuts the amount of labor required to pick orders.

For tote optimization the NextShift system runs a ‘binning’ calculation to determine what orders fit into totes (by volume and weight) and how many totes will be required. This calculation reduces the number of totes without adding much secondary sortation to the process. This minimizes the number of totes and speeds the process by requiring fewer tote moves.

Robot optimization calculates the number of robotic moves required to pick the orders, given the number of totes, pick sequences and order moves required. This reduces robot travel time while minimizing robot idle time.

This four-part automation harmony supports a powerful and highly flexible piece picking workflow. In our next blog we’ll look at how it works in action.