Design and Integration Distribution Center Design and Integration Case Study: Apparel Manufacturer Dean M. Starovasnik Practice Director, Distribution Engineering Design

Overview Peach State Overview Process High Points Case Study This session will provide an overview of an objective design methodology and an example case study where this process was used. Peach State Overview Process High Points Case Study Discussion Though “Discussion” is listed last, questions or comments throughout the session are welcome and encouraged.

Overview Peach State Overview Process High Points Case Study Discussion

Top 25 with Network Totals Peach State Spotlight Peach State Top 25 with Network Totals Founded 1975, Headquartered - Atlanta, GA Regional team members throughout the USA Deep expertise in supply chain network optimization, distribution facility design, operational excellence, labor management, material handling and storage systems engineering and integration, automated systems, robotics, and systems maintenance Over 800 projects completed and over 530 clients served An Associated Company One of the largest Integrated Supply Chain Solutions providers in North America 450+ team members $180+ million annual revenue Member of the Raymond/Toyota Family

Services Consulting Integration Material Handling & Storage Systems Customer Service & Support Global Supply Chain Consulting & Engineering Logistics engineering design – network logistics analysis, modeling & strategy Distribution engineering design – alternative analysis, greenfield & retrofit DC design / facility layout, order fulfillment methodologies & design, business case & metrics development Operational excellence – labor management programs – Six Sigma / Lean continuous improvement Vendor selection – 3PL evaluations, and WMS & WCS requirement definition Project & construction management services Integrated material handling systems – engineering, simulations, procurement, & implementation High-speed sortation, automated order fulfillment, automated palletizing, AS / RS, AGVs & LGVs Rack, shelving and mezzanine systems design, engineering and installation Material handling systems spare parts – sales & inventory management Flexible service & maintenance programs – MHE certified technicians, system tune-ups & maintenance training Equipment sales

Healthcare / CPG / Parts Clients Healthcare / CPG / Parts Food & Beverage Retail / E-commerce

Overview Peach State Overview Process High Points Case Study Discussion

Process Overview To begin, a summary of the overall process will help visualize the destination. This will help in understanding the path to get there. Where do we start? Operational Review Data Collection Data Analysis Profiling Select an Order Fulfillment Methodology (OFM) Based on order, customer and SKU profiles Minimize handling, maximize service level How big? & How fast? Forward pick? Which tools? Numbers of slots, facings, locations Sortation parameters and requirements. Connect the dots Keeping this process in mind while examining each of the individual steps will help keep the forest in view while looking at each tree.

Data-Based Design Process A design methodology based on historical data projected into future design requirements requires a range of data sources. Collect Data Analyze Data Construct Profiles Develop Parameters Model Scenarios Define Requirements Design Parameters: Planning Horizon Growth Rates Inventory Turns Ship Window Hourly Surges Assumptions: SKU Base Handling Unit Type Cartons Shipped Pick Face Days Supply Network Design Requirements: Order Fulfillment Methodology MHE Throughput Rates Pick Zones Storage Media

Profiling – Input to the OFM Decision Identifying the correct OFM’s for each portion of the operation is the first step in developing the facility design. Order Profiles Handling Unit Profiles SKU Profiles Full Case % Broken Case % Full Pallet % Mixed Orders % Special handling Per ship method (parcel vs. truck) Per order distributions Per carton distributions Order completion Single line percentage Per day & hr distributions ABC (Pareto) Distribution Full Case, Broken Case, Full Pallet Volumes Cube movement ORDER FULFILLMENT METHODOLOGIES Primary Manual vs. Automated Considerations: Throughput requirements (hourly volumes) Labor requirements (amount, cost, availability) Service requirements (accuracy, service levels, costs of non-conformance) Broken Case OFMs Full Case OFMs

OFM Matrix Volume Automation Cube/Order Complexity Two primary factors in determining the appropriate order fulfillment methodologies (OFM) are facility volume and order profile. Product to Order Order to Product SKU Pick & Sort Zone Pick & Sort/Consol Dynamic Zone Pick & Pass Automated Picking Volume Automation Storerooms Garages Cart Batch Pick OP to Pallet Complexity Cube/Order (pallet, carton, tote)

Complexity (Automation & Technology) Broken Case OFMs Complexity (Automation & Technology) Order Picking SKU Picking Discrete (Single) Order Pick Batch (Cluster) Order Pick Pick & Pass SKU Pick & Marry Low lines/order Opportunity to batch many orders High SKU commonality across orders Low volumes Small footprint (travel path) High Lines/order Large Cube/order Limited WMS Low Lines/order Low Cube/order Small footprint (path) Frequent order release WMS capable >1 fit on pick vehicle? Med-high volumes Med Cube/order Limited SKUs complete orders Med-high Lines/order Bulk Pick & Re-Pick Pick To Put Pick & Sort (Tilt-tray) Auto. Pick (A Frame) Pick To Tote Pick To Carton Limited WMS Large number of SKUs needed to complete orders Low number of customer-order sort points per wave High hourly volumes Sturdy/ durable products Very high hourly volumes Sturdy/ durable products Uniform/ standard product shapes & sizes Precise order cube cannot be pre-determined Re-handling/VAS at packing Precise order cube can be pre-determined Order ship ready at point of pick Sequential (Static) Zone Dynamic Zone Enhancements: RF Voice PTL RFID Low order complete % within pick zones High order complete % within pick zones

Full Case Methodologies Full Case OFMs Full Case Methodologies Complexity (Automation & Technology) Order Picking SKU Picking Single Order Pick To Pallet Multi Order Pick To Pallet SKU Pick & Sort Downstream Low volumes Most applicable for large, truck (LTL) orders Small order size Pick vehicle has capacity for >1 order Automation Considerations: Throughput requirements (peak hourly volumes) Labor requirements (amount, cost, availability) –current & projected Service requirements (accuracy, service levels, costs of non-conformance) Dock doors available/required Staging space available/required Pick to Pallet & Sort Zone pick & drop to induct point Pick to Belt Limited WMS Large number of SKUs needed to complete orders Adequate sort & staging space Med-high volume Most applicable for Parcel Small footprint Random storage Very high hourly volumes Small # SKUs represent high % volume

Overview Peach State Overview Process High Points Case Study Discussion

Case Study Project Overview Data Analysis & Requirements Definition Facility Design

Project Overview This client has a very successful, family owned, international business based in South America but had outgrown their current, 20+ year old distribution center. Multi-channel operation DLM (Agents) Retail (owned and department stores) Export Current processes and methods robust Manhattan Associates WMS Engaged, capable IEs on staff Ownership focus on supply chain Combination vertically integrated and outsourced product mix Primarily local manufacturing Basics present continuously “Complimentary” products purchased off-shore Real estate availability limited Urban environment Proximity to production facilities Labor availability

Case Study Project Overview Data Analysis & Requirements Definition Facility Design

Data Validation - Inventory The following exhibit demonstrates the quantity summary of the on-hand inventory composition across a range of parameters. Units Per SKU Inventory Summary Cases Per SKU Inventory Summary

Requirements - Inventory The following exhibit demonstrates anticipated inventory levels in cartons and pallets stored based on a similar turn through the design window.

Data Analysis - Outbound Outbound data has been analyzed across a number of different characteristics. The following data represents the different daily outbound volumes from the line data provided. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis - Outbound This outbound data was looked at in terms of daily volumes of units, lines and orders as well as in handling units of outbound cartons. Outbound Daily Characteristics Average daily “orders (shipments) are at 6,585 orders per day Unique shipment ID = OrderNumber+LoadNumber+ShipVia Average daily lines are at 71,487 lines per day Average daily units are at 122,078 units per day The daily outbound graph shows little seasonality and the peak-to-average ratio for lines is 1.25 Data includes Saturday & Sunday activity Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis - Outbound In the perspective of Campaign, the following exhibit demonstrates the outbound volumes by each Campaign from 7/23/13 to 7/22/2014. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound Also provided was the business projections from the Client team members. This data was used to forecast the resulting annual volumes through the design period. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound The annual outbound unit volumes are demonstrated below by channel. Annual outbound units Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound From the annual numbers we determine the average and peak day unit volumes. Average day – expected units Peak day – expected units Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound From the annual numbers we determine the average and peak day line volumes. Average day – expected lines Peak day – expected lines Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound From the annual numbers we determine the average and peak day order volumes. Average day – expected orders Peak day – expected orders Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Requirements - Outbound The annual outbound carton volumes are demonstrated below by channel. Annual outbound cartons Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis - SKU The ratio of outbound lines to SKU suggests high commonality, ranging from 1 to 22 lines per SKU; average roughly 12 lines per SKU. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis - SKU The following exhibit demonstrates the product distribution across product status and the line volume associated to each grouping. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis – SKU The following exhibit demonstrates the ABC analysis across a number of different variables. A items represent top 80% of lines shipped, B items next 15%, C items next 4% and D items bottom 1%; N items had a current quantity on-hand but no outbound history.

Data Analysis - SKU We also took a look at the SKU breakdown across the Campaigns. The following demonstrates the make-up of the Campaigns across the ABC analysis. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Data Analysis - SKU Approached by Campaign, the following exhibits demonstrate the ABC SKU movement by Campaign. The average per campaign is roughly 3,100 SKUs. Unique shipment ID = OrderNumber+LoadNumber+ShipVia

Case Study Project Overview Data Analysis & Requirements Definition Facility Design

Process Definition The process combinations that will be analyzed includes the following areas for comparison. Pick-n-Pass (non-automated) picking with in-line label & seal and destination sortation – This serves as the baseline of the current design and subsequent comparison Pick-n-Pass (automated) picking with in-line label & seal and destination sortation Cart batch picking with in-line label & seal and destination sortation Further comparison will include either a manual sort or an automated sort outbound. These areas will be scaled by the anticipate volumes and the capital cost, labor and space impacts will be compared to find the best applications for the outbound process.

Process Definition Similar Concepts

Process Definition First the layouts for the associated methods are created. The first exhibit below is the floor level of the manual Pick-N-Pass option.

Process Definition This exhibit represents the second level of the manual Pick-N-Pass option.

Process Definition This exhibit represents the floor level of the automated Pick-N-Pass option.

Process Definition This exhibit represents the second level of the automated Pick-N-Pass option.

Process Definition This exhibit represents the floor level of the cart batch option.

Process Definition This exhibit represents the second level of the cart batch option.

Process Definition New Concepts

Process Definition The cost estimates below represent the equipment costs of the baseline design including manual pick-n-pass picking.

Process Definition The resulting labor impacts of the three picking process options and the two outbound processing options are calculated in the exhibit below.

Recommendations To determine the most cost effective solution we look at the cost differences among the options. The following exhibits show picking cost impacts.

Recommendations Converting the previous page into a cash-flow comparisons, we find the following results. This shows that option 1 is not only competitive with option 3 for least combined initial cost, but is also the long term least cost option.

Final Design The below provides a look at the final facility design. Export Reserve Storage Shipping Receiving Pick Module Packing VAS Reserve Storage Reserve Storage

Final Design

Recommendations The features of the recommended layout are the following This design meets all volumetric requirements through the year 2021 Adding the third level of picking will add capacity beyond the 2024 design window Labor reductions are targeted to already congested areas of receiving, put-away and replenishment Fluid loading will help keep dock space clearer during daily processing

Overview Peach State Overview Process High Points Case Study Discussion 52

Questions? M.I.T 53

E-mail: dstar@peachstate.com Contact Information E-mail: dstar@peachstate.com Web: www.peachstate.com Phone: 678-327-2013 54