Minimizing Less Than Full Pallets and Maximizing Pick Efficiency - Case Study

Industry:

  • Grocery Retail & Wholesale

Markets:

  • USA
  • Europe
  • Southeast Asia

Distribution Network:

  • 25+ Self-managed DCs & 7,500+ stores

Applications in Scope:

Project Location:

  • USA

About the Customer:

A multinational Dutch-Belgian grocery retail and wholesale corporation with multiple distribution centers (DCs) in the United States. Client’s Operations and IT teams partnered with ITOrizon where we recommended and spearheaded a 90 Day systems and operations study.

Objective:

Client’s primary objective is to improve picking efficiency across all the picking zones and minimizing less than full pallets to increase pallet and truck utilization and minimize transportation cost.

In addition to that, operations wanted to improve work readiness before peak hours, ensuring sufficient inventory availability in pick slots to reduce wait times for pickers during outbound operations.

Operational Challenges:

  • Too many less than Full pallets
  • Too many partial pallet pick tasks across zones
  • Too many pick shorts
  • Less optimized travel path

IT Challenges:

  • Inability to analyze the issues in production across all the business, Manhattan Active Warehouse Management and automation functions without disrupting operations.
  • Need to come up with enhanced design and configurations without disrupting the current operational flow.
  • Need to cross regression test between parallel base deployments and the customer side enhancements.

Solution:

As part of the 90-day study, the ITOrizon SCM Architect, and Engineers captured the data for the current engineering design, MAWM configurations and Waving outputs, Voice Automation design, Order details, Slotting design, Inventory levels in Reserve and Active, Replenishment outputs, People habits, and Voice System behaviors.

In addition to the Data analysis, ITOrizon analyzed existing warehouse processes and end-to-end business processes across all SCM-integrated systems to get a comprehensive understanding before proposing new configurations in Manhattan Active.

Based on the findings, ITOrizon recommended comprehensive process changes and configuration changes across all areas with respect to Locations, Pallet / Carton Cubing, Replenishment, Task Creation, and Voice Picking.

Results:

Maximizing Full Pallets: The team focused on maximizing full pallets, aiming for 70 cubes in each pallet. With cube and pallet volumes of 1728 and 120,000, respectively, a cubing logic was implemented to create separate pallets for specific sets of zone groups based on the data analysis.

Maximizing Pick Efficiency: The number of pallet picking tasks was reduced by aggregating tasks by zone-sets. This orchestration ensured maximum business operation benefits.

Top-Up Replenishment: The implementation included a smart replenishment system. Post-picking, if inventory fell below a predefined threshold, the application intelligently refills locations to their maximum capacity. This reduces waiting times for inventory fill-up, leading to a significant improvement in picking efficiency.

Data Analytics: The detailed data and process analysis gave the insights required to optimize the warehouse.

ITOrizon Inc., a global end-to-end IT supply chain ecosystem service leader based in Atlanta, with offshore locations in India and Dubai, has been helping clients ensure success for more than 10 years. We maximize the value of existing ecosystem investments while outpacing the competition with a human-first service delivery client experience. Industry analysts such as Gartner, ISG, and ARC Advisory have recognized us for our high-performance services team, built to scale and delivering strategic advisory, implementation/integration, digital transformation, and managed support services.

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