Distribution Center Design and Integration Case Study – Health & Beauty Aid Manufacturer

2. Distribution Center Design and Integration Case Study – Health & Beauty Aid Manufacturer Presented to: Warehouse & Distribution Science ISyE 6202 Georgia Institute of Technology By: Dean M. Starovasnik Practice Director, Distribution Engineering Design Peach State Integrated Technology

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

4. Peach State Overview

5. Corporate Credentials • Headquarters in Atlanta, GA. • Regional offices throughout North America. • Over 34 years of experience engineering and integrating supply chain logistics, distribution, and material handling solutions on a national and global scale. • Results Oriented, Performance Driven, Team Based Culture. • Deep expertise in Supply Chain Strategy, Distribution/Manufacturing Design and Engineering, Site Operational Optimization and Labor Standards, Material Handling Systems Integration, and Customer Support.

6. Industry – Thought Leadership • Council of Supply Chain Management Professionals (CSCMP) Track Chair 2004 and 2006 • Conference Presentations • ProMat • Retail Leaders Industry Association (RILA) • National Conference on Operations & Fulfillment (NCOF) • HK Systems Annual Material Handling and Logistics Conference • Peach State Speakers’ Bureau • Numerous White Paper Publications • Material Handling Equipment Distributors Association (MHEDA) – Member, Past Board Member, President 2003 • The National Logistics & Distribution Conference (NLDC) Founder and Producer • Georgia Tech Supply Chain and Logistics Institute – Lecture Presenter since 2000 • DC Velocity – Editorial Board Member • Frequent contributor to major trade journal articles

7. Core Services Focused on Results – “From Strategy to Reality” Global Consulting & Engineering Facility Design & Engineering Material Handling Solutions Customer Service and Support • Logistics network strategy and design • Strategic distribution master planning • Rationalizing for outsourcing/3PL • Labor Management and Operational Excellence • Facility Designer Toolsettm determines the appropriate mix of people, space, equipment, and systems. • Solution development focused on delivering a rapid ROI. • Detailed engineering, bid management, procurement, and implementation of integrated material handling systems • High-speed sortation, automated order fulfillment, AS/RS, AGV/LGVs, and palletization. • Material handling systems spare parts to keep your facility running. • Service and maintenance programs that are tailored to ensure maximum ‘uptime’ and performance.

8. Major Clients Serving the ‘Best of the Best’… Manufacturing Parts Distribution Healthcare & Pharmaceuticals Consumer Products/Retail Food & Beverage

9. Facility Design Process

10. 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. Keeping this process in view while examining each of the individual steps will help keep the forest in view while looking at each tree. • 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

11. Data Analysis Methodology Our analysis methodology transformed historical data into future design requirements: 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

12. Facility Design Profiles Profiles of different data elements help to address the variety of questions that must be answered in the facility design effort. Actual development of most profiles involves generating each “day’s” activity, statistically analyzing them then developing the distributions.

13. 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 • Per ship method (parcel vs. truck) • Per order distributions • Per carton distributions • Order completion • Single line percentage • Per day & hr distributions • Full Case Pct • Broken Case Pct • Full Pallet Pct • Mixed Orders Pct • Special handling • Lot control • Hazmat • Refrig/Freezer • 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

14. OFM Matrix 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 Pick to AutoPak Dynamic Zone Pick & Pass Automated Picking Volume Automation Storerooms Garages Cart Batch Pick OP to Pallet Line/Order Cube/Order (media)

15. Broken Case Methodologies Complexity (Automation & Technology) Order Picking SKU Picking Pick & Pass Discrete (Single) Order Pick Batch (Cluster) Order Pick Pick & Pass SKU Pick & Marry • Low lines/order • Opportunity to batch & release 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 travel path • Frequent order release • WMS capable • Can fit >1 order 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 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 Sequential (Static) Zone • Enhancements: • RF Voice • PTL RFID • Low order complete % within pick zones • High order completion pct within pick zones

16. Full Case Methodologies Complexity (Automation & Technology) Order Picking SKU Picking Single Order Pick To Pallet Multi Order Pick To Pallet SKU Pick & Sort Downstream SKU Pick & Sort Downstream • Low volumes • Most applicable for large, truck (LTL) orders • Small order size • Pick vehicle has capacity for >1 order Pick to Belt Pick to Pallet & Sort Zone pick & drop to induct point Pick to Belt • 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 • 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

17. Case Study

18. Project Overview The design project we are reviewing proceeded through implementation. The client is philosophy, a high end skin care cream manufacturer. They were moving very fast, with aggressive growth projections and desired a rapid evidence of return on investment. • Growing through the recession (20%) • Recently purchased by a private equity firm • High profile, luxury product identity • Persistent demand from existing customers • New customers gained through Internet and QVC • Originally in two fulfillment facilities • Both space constrained • Retail & QVC fulfilled in one facility • Internet fulfilled (from same SKU base) at HQ • Spec building selected prior to design • Size and door count validated immediately • Sufficient for 2015 and beyond • Some expansion capability available

19. Data Analysis Results

20. Outbound Profiles – Daily Activity The below statistics help to illustrate the activity levels of the combined business, Retail DSDC and Internet channels. • Combined • Retail DSDC • Internet

21. Outbound Profiles – Order Statistics The below statistics help to illustrate the nature of the orders across the combined business, Retail DSDC and Internet channels. • Combined • Retail DSDC • Internet

22. Outbound Profiles - Throughput The daily throughput profile reveals considerable seasonality, peaking in October & November.

23. Outbound Profiles - Internet The daily throughput profile reveals considerable seasonality, peaking in November.

24. Outbound Profiles – Retail DSDC The daily throughput profile reveals some seasonality, peaking in September & October.

25. Outbound Profiles – Lines Per Order Lines per order profiles were developed for Retail DSDC and Internet orders.

26. Outbound Profiles – Units Per Order Unit per order profiles were developed for Retail DSDC and Internet orders.

27. Outbound Profiles – Cube Per Order Cube per order profiles were developed for Retail DSDC and Internet orders.

28. Outbound Profiles – Cartons Per Order Cartons per order profiles were developed for Retail DSDC and Internet orders.

29. SKU Data Review

30. Pareto Profile - Lines A Pareto profile helps illustrate the concentration (or lack thereof) of activity within a particular range of products. The below shows the variation in line activity across the SKU base for Retail, Internet and Combined orders.

31. Pareto Profile - Units The below shows the variation in unit activity across the SKU base for Retail, Internet and Combined orders.

32. Pareto Profile - Cube The below shows the variation in cubic velocity across the SKU base for Retail, Internet and Combined orders.

33. Total Active SKUs by Month The total SKUs active in a month at peak is over 800 SKUs. This compares to a baseline of ~1,370 total SKUs with activity across the timeframe analyzed.

34. OFM - Zone Pick & Consolidate 34

35. Outbound Profiles – Full Case vs. Broken Case To determine how orders “are” fulfilled, full case and broken case volumes were calculated for both Retail DSDC and Internet orders, first in lines.

36. Outbound Profiles – Full Case vs. Broken Case To determine how orders “are” fulfilled, full case and broken case volumes were calculated for both Retail DSDC and Internet orders, next in units.

37. OFM Rationale & Criteria The benefit of zone pick & consolidate OFM is a reduction in non-value added labor and an improvement in quality & cycle time. • Multi-channel order fulfillment in common areas provides considerable benefits: • Improved utilization of labor throughout year • Increased opportunity to use shipping sortation automation • Common shipping area increases flexibility due to variations in channel seasonality • Handling full case separate from piece pick allows for proper slotting of the SKU by cubic velocity in that UOM while reducing the walk time. • Performing all piece picks in a common module consolidates repack operations in one location for enhanced process control and efficiency. • Consolidation can be error prone and also increase non-value added handling. A shipping sorter assist with palletization of LTL and fluid load of parcel carriers will address both issues. • Repack replenishment can also be supported by “picking” the required replenishment cases, and then delivering to the repack module, either via conveyor or, after palletizing by SKU, by vehicle.

38. Full Case OFM – Pick to Label 39

39. Full Case Pick to Label Rationale The benefit of a pick to label OFM is the elimination of non-value added repack activity while improving quality with verification of cases at the shipping sorter. • Retail orders require a large portion of their volume in full case quantities (80%). • Creating a full case pick zone using a pick to label approach will eliminate the non-value added handling of repacking all case quantities into repack containers. • Pick to label addresses the issue with small cases while retaining efficient picking. Cases 3” tall or less will be handled as piece picks. • Repack replenishment can also be supported by “picking” the required replenishment cases, palletizing by SKU and then delivering to the repack module. 40

40. Pick To Belt – MHE Capital The Pick to Belt concept is quite simple and economical. The below budgetary estimate illustrates the expected capital needed to implement this capability. 41

41. Broken Case OFM – Zone Pick & Pass 43

42. ZPP – Rationale The expected benefit of a pick and pass order fulfillment methodology is the elimination/reduction of non-value added labor. • Cartons requiring units from multiple zones must be manually moved from zone to zone increasing walk time by pickers. • Pickers remaining in their zones while conveyor moves the cartons from zone to zone will eliminate the non-value walk time. • By separating full case volumes from broken case, the pick faces in the ZPP can be reduced to minimize pick travel paths. • Appropriate configuration of powered and gravity conveyors can assist with the passing required to complete cartons. 44

43. Broken Case Pick Module A broken case pick module with pallet & carton flow and static shelving provides flexibility and efficient order fulfillment across both Retail and Internet channels. 45

44. Design Requirements 47

45. Growth Projections The different fulfillment channels contribute varying amounts to the overall corporate growth of Client. 48

46. Storage Requirements Storage requirements were based on increases in shipping volumes for all three channels. Baseline storage for 2012 was calculated from inventory data for retail and internet volumes and historical requirements for Primary Location storage. Note that the driving factor is kitting storage. The growth associated with this area does not overcome the improvement in turns until 2012. 49

47. Pick Module Sizing Each SKU was assessed for its broken case volume, Internet and Retail. These volumes were then assigned to pick media. Replenishment was assumed to be every four days on average for a slot classification. A “slice” is one bay wide, includes both sides and all levels of the module. The number of slices determines the overall length of the module. 50

48. Conceptual Design 51

49. Facility Overview While the overall concept has remained unchanged, some elements were modified to meet requirements and improve design. 52

50. Full Case Pick Lines The below two lanes with shelving in 3 bays at the downstream end support over 99.2% of the full case units, 73% of those in the pallet flow bays. 53