Improving Warehouse Productivity via SAP and Smart Digital Applications

Author: Scott Barrett

Whether it comes in the form of a scathing articles from the NY Post, or more lengthy exposé from HBO's John Oliver, Amazon has found itself in the news recently for how challenging and exhausting it can be as a picker in their warehouse. Some employees say they can easily walk 15-18 miles a day through the cavernous warehouse moving from aisle to aisle picking the little things we buy everyday out of their bins and getting them onto the pack stations. We all know Amazon is a leader in the logistics game so it’s no surprise that we are seeing this as a fairly common problem and we are excited to share that we recently implemented an algorithm and digital solution at one of our high-tech clients to help improve and hopefully avoid a similar situation.

For this case, the client was seeing their delivery count rise rapidly with their overall company growth but the quantity for each delivery falling. The picking teams were spending more time and walking longer distances while getting fewer items for more deliveries. This race through the aisles was inefficient with physical paper pick lists, and first-come-first-serve manual assignments of the picking tasks. The model was quickly showing non-scalable signs as the business continued to grow.

In close partnership with the client’s Warehouse, Supply Chain, and IT teams, we looked at how to leverage their existing SAP system and all its standard data to optimize the process from Delivery Note (DN) creation through the picking process. We tackled the problem in three ways:

  • Elimination of the paper pick lists at DN creation. Instead, upon creation, the DNs are sent to a virtual queue, intelligently grouped by ship-to, carrier cutoff times, consolidation opportunities, etc., and ready for the floor clerk to release them for picking
  • As DNs are released for picking, a custom “Best Path” algorithm calculates all necessary paths through the warehouse and its aisles, and delivers the digital picklist onto the iOS mobile devices within seconds, sorted in a way that would require the minimum number of steps to retrieve all assigned items
  • The Picking team leverages a digital app and swapped the physical paper picklists for iOS devices, paired with a wearable scanner – lighter, cheaper, and easier to use/maintain than the larger typical warehouse scanners

While the implementation of the digital mobile app and the development of the real-time links to SAP WM / eWM were very interesting, it is the behind the scenes algorithm that really addressed the problem called out in those Amazon criticisms. We added advanced logic, defining the ranking of the bins in relation to the packing stations so when the deliveries are released for picking, the routing calculation follows these steps:

  • Walk out to the farthest spot from the pack stations thus making the longest walk burdened by the lightest load
  • Map all possible paths back towards the packing station, picking up the remaining items on the way. Restrictions like high bin picking certification, double-back vs. snake routing options, etc. are all captured in the calculation so it would never return an infeasible path
  • Select the path that has the minimum steps
  • Deliver the sorted list of bins in seconds to the iOS device and away they go.

Here is a simple example of four path options across three aisles:

Pick Algo

While it is very exciting to develop and implement innovations like this that meaningfully move supply chain metrics on day one, minimizing the path a picker takes has real human value as well. It will not transform that job into an easy one, but if a project like this can shed a few miles a day off the warehouse employee’s workload, the success can be measured in more than just delivery metrics.

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