10 Best Practices to Improve Order Picking Efficiency in Your Multi-channel Distribution Centers or Warehouses

Picking is one of the most important functions that is performed in the warehouse for the reasons below,
1. Often picking process is the most time-consuming process, hence could become a bottle neck, if not done fast enough.
2. The more orders are picked, the more orders can be shipped, that means more orders can be invoiced, hence picking directly increases the revenue for the Distribution Center.
3. Picking also directly impacts the throughput metric, hence improving the productivity and speed of the picking process, directly improves the throughput of the distribution center. Throughput is the measure of inventory that is received into the inbound dock doors and shipped through the outbound dock doors by fulfilling orders.

Listed below are some of the best practices that can be followed while performing the picking process in any Distribution Center

Follow Location Sequence for the Pick Path
When pickers pick travelling in a location sequence, the picking process becomes efficient for the reasons below.
1. Users don’t have to go to the same locations twice.
2. Users are not going in a zig zag manner, but instead following a streamlined path, hence there is no confusion in where the picker went and where he did not go.
3. While picking in location sequence it is easy to skip picks if the inventory has not been replenished in the unit pick locations and then after all the picks are picked complete, it is easy to go back to the skipped locations to ensure fulfilling orders after the replenishment is complete
4. Sophisticated Warehouse Management Systems have the ability to configure the pick location sequence in multiple ways allowing different warehouse layouts to be easily accommodated.

Establishing Multiple Zones, where a group of locations become a Zone
Dividing the pick locations into Zones and assigning pickers to specific zones contributes to even better picking process for the reasons below
1. Pickers travel time is reduced, meaning pickers are confined within one zone, hence they spend more time picking instead of spending any time walking.
2. When pickers are confined within zones, then spend more time within their zone, so they become experts within their zones, they are specialized in their zones, so they are finding items at a faster pace within their zones.

SKU Velocity Classification A, B, C – Track SKU Velocity
1. SKU classification into A, B & C SKUs based on SKU velocity enables correct slotting of SKUs, meaning the SKUs that are fast moving or high velocity SKUs, which are often called the A SKUs are slotted close to the shipping area, hence can be picked faster spending less time on travel.
2. Whereas SKUs that are moderately moving or moderate velocity SKUs are often called B SKUs and are slotted moderately close and not very far from the shipping area, hence can be picked relatively faster, spending less time on travel to pick them.
3. SKUs that are slow moving or low velocity SKUs are often called as C SKUs and are slotted far away from the shipping area, hence can be picked faster, spending less time on travel to pick them.
4. Sophisticated Warehouse Management Systems have the ability to automatically mark the SKUs as A, B or C SKUs, depending on sales volume, hence users don’t have to do anything extra to classify SKUs.
5. Sophisticated Warehouse Management Systems also have the ability to automatically create move tasks and assign them to the users, so these SKUs can be moved automatically from the Fast moving bins to slow moving bins depending on SKU.

Non Conveyables
Non Conveyable’s are the SKUs that don’t ride the conveyors for the following reasons.
1. Too big.
2. Too small.
3. Oblong shape/size.
4. Anything that is not within the specifications that the conveyor can convey.
It is a good idea to assign a separate zone or determine a way to isolate those picks and group only the non conveyable picks, so that those SKUs can be picked separately and shipped separately.
This isolates the picking process for the non conveyables, so that this picking process does not interfere with the picking process for the conveyable SKUs adding more bottle necks along the way.

Non Sortables
Non Sortables are the SKUs that don’t ride the Sorters for the following reasons
1. Too big.
2. Too small.
3. Oblong shape/size.
4. Anything that is not within the specifications that the Sorter to Sort.
It is a good idea to assign a separate zone or determine a way to isolate those picks and group only the non sortable picks, so that those SKUs can be picked separately and shipped separately
This isolates the picking process for the non sortables, so that this picking process does not interfere with the picking process for the sortable SKUs adding more bottle necks along the way.

Task Based Picking
1. Slicing and Dicing the picking work into tasks based on zones, after sequencing the picks by location, based on capacity of the carts, creating such batch picking tasks and then assigning those tasks to pickers enables picking process to be completed in a faster, accurate and efficient manner.
2. Further confining tasks within specific zones to reduce picker’s travel time makes completion of picking tasks even more efficient.
3. Also tracking such tasks for different pickers and providing real time feedback to the pickers on their performance in terms of picks per hour, while simultaneously providing a color indication as to Red, Green or Yellow helps the picker to meet the daily departmental goals.

Engineering Labor Standards with Ergonomics
1. What gets measured gets managed. There is a big difference in the behavior of operators, when everyone realizes that they are being measured and incentivized based on the amount of work they get done.
2. Operators just don’t stand around anymore when they run out of work, instead they are not only much more pro-active in seeking work but also more engaged as a team and get a lot more work done.
3. When the motions that pickers undergo are measured, optimized for ergonomics and appropriate engineering labor standards are established, then targets can be assigned to pickers on how many picks they need to complete taking into account the nature of the product they are picking, the amount of travel they are doing and also based on the handling attribute at the SKU level.
4. This also includes sharing the performance KPIs on a daily basis in some form of displays in a notice board or in a wide screen TV hence not only the process is transparent but also encourages certain competitiveness.

Gamification for Picking
Gamification tackles the challenge of making work resemble a game, so instead of doing the work with drudgery, boredom, and a sense of pressure or like a zombie, workers get interested and do better. Gamification, done right, pushes people to new levels of engagement and makes work more enjoyable. Further, this approach transforms what is normally an extrinsic reward (business success or a bonus) into an intrinsic reward (meeting and exceeding clear goals, create a shared sense of community, and building a sense of enthusiasm). Of course, extrinsic rewards work well in conjunction with gaming, especially if employees see an increase in pay for their efforts.

Multiple shifts with well-planned replenishments
Understanding thoroughly, the dynamics of different processes and the dependencies of one process over another helps clearly assign priorities and ensure the processes that other processes are dependent on get completed on a timely basis. One such example is replenishments, replenishments need to be completed on time, in order ensure the pickers are not standing around and waiting for the product to make it to the bin locations to complete fulfilling their orders and/or cartons. Hence it is paramount to ensure the bin locations are full, before the pickers start picking. It helps a lot to have a 2nd shift or 3rd shift exclusively just to complete replenishments hence no time is lost in completing picking. Also staying on top of these Replens during the day helps complete picking on time as well. Typically there are 3 types of Replenishments, they are called Priority 40, Priority 50 and Priority 60, based on priorities under which they need to be completed. Typically it takes a while for the operations team to get a handle on ensuring these Replens get done on time after the new WMS has gone live. Pro-actively paying attention to the Replens and the picking dynamics help avoid any gotchas.

Inventory accuracy through daily cycle counts
One of the most important factor that makes a huge difference in the operations is the inventory accuracy within the whole facility. Maintaining a 99% accuracy rate within the building not only helps with improving operations, but also instills a rigor and discipline, we all know how life is so much easier and better when we find things in our home, where we always look. No yelling among the family members, no last minute searching and frustration not finding the things in their places. Same thing applies to the DC as well, when the product is in the right bin location and in the right reserve location, the pickers are not chasing ghosts any more, instead they focus all their time on picking. Deploying a dedicated cycle count team as part of the 2nd or 3rd shift to count pick locations to make sure the inventory count is 100% accurate in the bin locations helps a lot to avoid chasing ghosts, especially during the picking process.

ABOUT THE AUTHOR

Puga Sankara is the co-founder of Smart Gladiator LLC. Smart Gladiator designs, builds, and delivers market-leading wearable technology for retailers, distributors, and 3PL service providers. So far, Smart Gladiator Wearables have been used to ship, receive, and scan more than 100 million units and/or boxes. Users love them for the lightweight, easy-to-use soft overlay keyboard and video chatting ability, data collection ability etc. Puga is a supply chain technology professional with more than 17 years of experience in deploying capabilities in the logistics and supply chain domain. His prior roles involved managing complicated mission-critical programs driving revenue numbers, rolling out a multitude of capabilities involving more than a dozen systems, and managing a team of 30 to 50 personnel across multiple disciplines and departments in large corporations such as Hewlett Packard. He has deployed WMS for more than 30 distribution centers in his role as a senior manager with Manhattan Associates. He has also performed process analysis walk-throughs for more than 50 distribution centers for WMS process design and performance analysis review, optimizing processes for better productivity and visibility through the supply chain. Size of these DCs varied from 150,000 to 1.2 million SQFT. Puga Sankara has an MBA from Georgia Tech. He can be reached at puga@smartgladiator.com or visit the company at www.smartgladiator.com. Also follow him at www.pugasankara.com.

Author:
Puga Sankara
About:
Puga Sankara is the co-founder of Smart Gladiator LLC. Smart Gladiator designs, builds, and delivers market-leading mobile technology for retailers, distributors, and 3PL service providers. So far, Smart Gladiator Wearables have been used to ship, receive, and scan more than 50 million boxes. Users love them for the lightweight, easy-to-use soft overlay keyboard and video chatting ability, data collection ability etc. Puga is a supply chain technology professional with more than 17 years of experience in deploying capabilities in the logistics and supply chain domain. His prior roles involved managing complicated mission-critical programs driving revenue numbers, rolling out a multitude of capabilities involving more than a dozen systems, and managing a team of 30 to 50 personnel across multiple disciplines and departments in large corporations such as Hewlett Packard. He has deployed WMS for more than 30 distribution centers in his role as a senior manager with Manhattan Associates. He has also performed process analysis walk-throughs for more than 50 distribution centers for WMS process design and performance analysis review, optimizing processes for better productivity and visibility through the supply chain. Size of these DCs varied from 150,000 to 1.2 million SQFT. Puga Sankara has an MBA from Georgia Tech. He can be reached at puga@smartgladiator.com or visit the company at www.smartgladiator.com. Also follow him at www.pugasankara.com.
More articles by: Puga Sankara

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