Driving Impact in the Warehouse: Value drivers and key levers

Driving Impact in the Warehouse: Value drivers and key levers
Johan Lundin, APM SCM GaTech, Atlanta, GA 09/19/2016

Agenda Warehousing value Lean pharma warehousing Improvement areas
Pharma warehouse layout Case example 1 - Industrial Case example 2 - Industrial

There are three main ways to add value for warehousing; depending on client constraints one or more may be chosen Covered in this document Lever Cost reduction levers Warehouse network strategy Warehouse location optimization, including evaluation of trade-offs between warehouse savings (from consolidation and improved utilization), and total logistics costs (inbound and outbound) Clean-sheet approach for closure, insourcing / outsourcing scenario assessments, and building of business case for recommended future state 1 Operational efficiencies Traditional lean transformation approach exploring productivity improvements and process optimization for existing warehouse locations Structural lean transformation including shift restructuring or elimination of shifts, automation commissioning or decommissioning Performance management for tracking and sustaining progress 2 Warehouse outsourcing Variable cost structure Labor and overhead cost reduction Real estate and equipment cash free-up Depreciation cost avoidance 3

For productivity improvements warehouse operations is broken up into these five key steps
CONCEPTUAL 1 Receiving 2 Put Away Replenishment 3a Full pallet pick 3b Case Pick Staging 4 5 Loading & Shipping

EXAMPLE: Initiatives touch on each step of the warehouse operations to drive end-to-end productivity
Receiving and put away activities Optimize door assignment for inbound trucks to minimize travel time for put-away Optimize slotting configuration based on SKU source, customer destination(s), and turnover Increase use of “drop and hook” trailers to optimize warehouse scheduling/activities Prioritize execution based on: Value expected Ease of implementation Picking and pallet move-ments Increase pick line density to reduce travel time during picking activities Reduce “other pallet movements” through (1) use of higher-quality pallets for local shipments and shuttles, and (2) use pallets appropriate for ultimate shipping destination (e.g., based on customer or method of transportation requirements) Merge bulk storage and pack center storage areas to avoid double-touch Use layer picking for customers ordering in layers Use WMS to support interleaving to boost fork lift “backhaul” Shipping activities Increase cross-docking for full-pallet customers and DC-to-DC transfers Optimize door assignment for outbound trucks to minimize travel time for shipping activities

EXAMPLE: Process to implement productivity improvements
Detailed further WH Visit Analysis Design and pilot Implement Activities Visit and understand existing warehouse layout and zones, space and customer constraints Understand the SKU types (bulk, pallets, cases, etc.) Capture of opportunity levers Send data request to collect required data Implement data cleaning and validation1 Conduct Zoning and racking SKU categorization Slotting Present initial output to client Incorporate client inputs to refine analysis Bottom up analysis and opportunity assessment Iterate and refine the potential opportunity Develop implementation plan for client Pilot slotting and categorization, track and debottleneck initial hurdles Manage daily process changes Track impact and communicate to client Roll out to other plants / DCs a b c Deliverable Key levers applicable to client Broad outline of zones and flows First estimate of opportunity Zones and dimensions Number of racks and configuration SKU categorization and allocation to racks Original and final destinations of SKUs Bottom up opportunity assessment e..g FTEs saved, distance saved per SKU and for total WH Implementation plan Key KPI metrics during pilot phase Refined estimate of achievable savings and time to achieve

IMPORTANT: APM expectations and deliverables
Details Questions to answer What is the productivity improvement potential in APM’s two warehouses in PAR and PBG? What productivity improvement opportunities should APM pursue in their PAR and PBG warehouses? How do APM warehouses compare against peers in terms of productivity and efficiency? Ask for data and you shall receive: Quantitative Qualitative Expecta-tions Be open and transparent – Do not be afraid to ask questions Always drive to impact – Make sure opportunities result in value Share new ideas – Be creative and innovative Have fun while learning – Most impact identified wins Deliver-able Set of productivity improvement opportunities with potential impact per warehouse Total productivity improvement potential per warehouse GOAL: APM wants to increase productivity in PAR and PBG warehouses

Target of Lean Warehousing is to sustainably reduce cost
Lean Warehousing for pharmaceutical companies targets at Significantly reducing warehousing operating cost by increasing productivity, at the same time Improving quality of deliveries by for example avoiding picking errors and broken goods, and Strengthening delivery service levels by shortening lead times and reducing out-of-stock situations Productivity Service level Quality

Lean warehousing addresses the increasing pressure on pharma companies in cost and operational requirements Service level and quality 2 Regionally diverse but generally high service level requirements (esp. multiple deliveries in a day) requiring high flexibility, product availability and short lead times Market environment 1 Lean Warehousing Product portfolio 3 Regionally intensified pressure on margins, e.g. by increasingly high rebate levels and new competitor business models Reduction of cost of warehouse operations simultaneously ensuring high service and quality levels Very high product variety depending on the country and market share also leading to complex order structures with high picking cost Regulation 4 Increasingly strict requirements on operations imposed by Healthcare authorities (e.g., traceability, “Good Distribution Practice”)

1 Pharmaceutical companies are under substantial pressure especially in mature markets EXAMPLE EU Markets are stagnating or even shrinking… … and profits are dropping… Pharmaceutical market size in EU5 at retail prizes USD billion EBIT margin of European-based wholesalers1 Percent CAGR '12-'18, % 179 182 164 -44% 3,3 -5.8 3,1 3,1 2,8 2,9 2,9 -4.2 2,4 2,5 2,4 2,4 2,4 38 38 38 0.2 1,8 1,9 43 43 41 -1.1 -0.8 2000 1 2 3 4 5 6 7 8 9 10 11 2012 2006 2012 2018 … due to a number of reasons Patent expiry and switch to cheaper generics puts pressure on pharmaceutical prices Government austerity leading to cuts on regulated Rx2 reimbursement Changes to business models (e.g. DTP in UK, low cost competitors in Germany) Intense discount competition in major markets (e.g. Germany) 1 Volume weighted, to the extend data available; excluded Alliance Boots due to missing historic segment reporting Rx: Prescription products

2 High service level requirements stress operational flexibility on pharmaceutical companies ILLUSTRATIVE WHOLESALE EXAMPLE Wholesale relevant services Key challenges Delivery cut off times Order lines Picking staff Multiple deliveries per day to each pharmacy1 Pharmacies order frequently and in small quantities, triggered by customer orders and to keep low inventory on hand PharmaCos need to provide substantial flexibility and cope with short cut-off times Pick zone activity Order lines Pick Staff Delivery 45 6000 4500 Over- capacity 30 3000 As part of PharmaCos service model, significant return volume is common Orders placed at multiple wholesalers in parallel Expired, overstocked or ordered in error products Product recalls of PharmaCos 15 1500 Returns 08:00- 08:50 09:00- 09:59 10:00- 10:59 11:00- 11:59 12:00- 12:59 13:00- 13:59 14:00- 14:59 15:00- 15:59 16:00- 16:59 17:00- 17:59 18:00- 18:59 19:00- 19:59 20:00- 20:59 Time Picking peaks can lead to significant overcapacities and require flexible workforce allocation 1 Deliveries per day vary significantly per region. Example Germany: on average 3 deliveries per pharmacy/day (significantly higher frequencies possible); Finland/Sweden: on average 1 deliveries per pharmacy/day

Variety on SKUs and high product complexity leads to complex order structures and high picking cost
3 Major Product categories Challenges for warehouse operations Complex handling requirements for example due to high value, demand patterns, environmental requirements (cold chain products), potential theft (narcotics) or hazardous contents (cytostatics) Price Pharmaceutical warehouses can feature very high product variety (e.g., UK/Ireland 10,000-20,000 SKUs, Germany >100,000 SKUs1) Large product portfolio leads to high order complexity and picking effort (e.g., units per line vary between 1,x in Germany up to 8,x in Scandinavia) Specialty pharma Internal shift from Rx to Gx (generics) - patent expiries imply moving same volumes for less turnover resp. margin in a wholesale business Rx/Gx High product variety in type and shape. In comparison large number of units per order line and strong seasonal impacts (e.g. hay fever and cold season) OTC Volume/Units per order line Products and packaging are frequently changing. Often dead stocks due to expiries and leftovers of last season’s products. Marketing campaigns lead to peaks in demand Health and beauty Specialty, Rx and Gx order volumes strongly influenced by payor tenders 1 Stock Keeping Unit

Regulation imposes specific requirements for pharmaceutical warehouse operations driving cost
4 EXAMPLE EU Increasing regulatory requirements… …raise operations cost for an already low margin business New Good Distribution Practices (GDP) guidelines (2013) Increased requirements for storage and transportation e.g., temperature controlled vehicles and storage Requirement for documentation and a sophisticated quality management system Specific process requirements e.g., for returns handling Requirement for an on-site qualified responsible person Anti-counterfeit drug directive (2011) Requirement for wholesalers to batch track all Rx drugs by 2017 Various additional national regulatory requirements e.g., on cold chain (Nordics) and batch tracking (France) European association of pharmaceutical full-line wholesalers “European pharmaceutical full-line wholesalers express serious concern about sky-rocketing cost entailed by the proposal to revise European Good Distribution Practice Guidelines” – Press release, 4th June 2012

Lean Warehousing at pharmaceutical companies typically achieves up to 20% FTE savings
EXAMPLARY Typical impact Reducing unnecessary walking and searching during picking by improving product placement Avoiding unnecessary replenishment by setting up rules on refill levels and procedures Avoiding double handling of products and bins/boxes by re-designing product flows … Productivity Service level Reducing lead time during picking peaks through better manpower allocation between warehouse areas Reducing missing products in deliveries by ensuring that products are available on picking shelves on time … Quality Reducing picking error rate and number of order deviations Reducing breakage by identifying root causes for damages (e.g. missing A-Frame cushions or tote inlays) … ! Typically, Lean Warehousing initiatives achieve FTE savings impact of 8-20%

6 overall levers help structuring identified opportunities to ensure a holistic view of the assessed warehouse Levers Main objective 1 People Increase efficiency and flexibility of labour 2 Strategy & processes Reduce handling steps and touches for each product between receiving and shipping How can we increase performance?* 3 Assets & Technologies Align integrated assets and technologies to strategies chosen 4 Layout Optimize layout structure and align with local requirements and restrictions 5 External Influences Adjust supplier and customer requirements to warehouses restrictions 6 Internal organization Reduce span of control incl. overhead and business support functions

People: Training and standardization
3 1 People: Training and standardization Current state Future state Integration of waste due to non standardized processes No standard process description implemented/ designed No trainings done regularly Standardize processes and train all direct (and indirect) FTE Describe all processes in detail, standardize all processes Do not allow process design along exceptions Train all FTE on a monthly base using videos/best practices Make FTE aware of impact during daily hurdles Impact calculations – practice examples Percent Direct labor not aware of waste and does process as good as possible but not as efficient as possible (waste) Dispersion of case examples* Average: 17%* Maximum: 38% (production/ assembly supply)* -5 -10 -15 -20 -25 -30 >30 Improvements Assumption: > 10-15%

2 Strategy and processes: Minimize handling steps during receiving process/put-away Current state Future state Storage area FIFO buffer X X X X Ideally process: Put-away without buffering Receiving docks Received products are buffered somewhere After receiving into system, pallets need to be counted, bar codes are printed and attached to the pallets (no bar code tag of supplier) Storing of pallets is triggered manually Trucks Clear buffer areas with identification (e.g., bar-code sheets) Bar-code attached by supplier to pallets to enable automatic reception of pallets (in combination with ASN) Pallets are directly stored (blocked), only quality pallets are put to quality inspection Improvements Less space requirements in receiving area No searching for pallets, no idle time Process step of printing, receiving, and keying into system not required

4 3 Assets & Technologies: Integrate multi-pick cages (with quantity indicator for each product) Current state Future state Time-consuming multi-pick process as every product has to be confirmed before picking Integrate "pick-by-light" multi-pick cages with visual board for quantities S System S System P Picker 3 P Start Scan label of each product Picker Little display indicating quantity to be picked per product Start Scan label of each product 2 Picking Picking S Face number S Face number P Confirm P Confirm 2 1 S Product numbered System indicates quantities P Confirm last digit S Quantity P Confirm quantities once P Confirm quantity for each product on cage Only once per face Time-consuming pick process Fast picking of products; no confirmation process in between Multiple light cases can be picked at once Repacking can be completely eliminated if supplier delivers in different levels Colleagues in general don't like it and do single product picking (increased walking distance)

Layout: Stretch aisle length
3 4 Layout: Stretch aisle length Current state Future state All pick faces have different volumes and length, even for customer with more than 1 face Stretch aisles include further faces for stores with general high volumes Up to 2 m waste as only few faces have high volumes Balanced pick front as only few customers in average have high volumes 57 m m Congestion due to waiting and picking time Reduced congestion as less side-stepping for picking is needed Congestion due to passing time Less waiting for and passing of colleagues necessary as most pickers have similar pick frequency

External influences: Fix time windows for incoming trucks
5 External influences: Fix time windows for incoming trucks Current state Future state Although delivery time windows are set for suppliers, no truck arrives the warehouse at the right time Strictly managed time windows allow continuous material flows and balanced workloads over the year Actual arrival time Actual arrival time Late arrival Only 12% of arrivals are within 1 hour of their slot time Early arrival Scheduled arrival time Scheduled arrival time High adaptability of FTE required to balance workload Transitional periods included for direct FTE and team leader Increased ability to plan and schedule resources Optimised utilisation of direct FTE and assets (e.g., docks, forklifts, etc.) Elimination of pick processes in expansive shifts

Internal organization: Align span of control
6 Internal organization: Align span of control Current state Future state Fixed (=constant) number of line manager Variable number of line manager integrated Total order per day (‘000) Reduction span of control Transfer of operational tasks to line manager Alignment number of line manager with daily volumes expected +76% Alignment of needs to daily volume Mon Tue Wed Thu Fri Sat Sun Total hours per day Total hours per day 2,652 2,564 2,361 2,652 2,546 2,303 2,141 2,018 2,039 1,891 1,827 1,866 +60% 1,662 1,709 +60% Direct Direct Line manager Var. Line manager Mon Tue Wed Thu Fri Sat Sun Const. Mon Tue Wed Thu Fri Sat Sun No adaptation number of line manager to daily volume changes

Lean Warehousing transformations for pharma companies, various industry specifics need to be accounted for NOT EXHAUSTIVE Key differentiation factors Details on following pages Products Very large amount of SKUs (> 100,000 possible, e.g. in Germany) Value proposition of very high product availability towards pharmacies Products requiring special handling (e.g., narcotics, cytostatics) and/or of substantial value (e.g. cancer medication) Expiring products requiring “First-Expire-First-Out” principle As supplier bonus is key to profitability, product orders often not driven by strict demand model Service delivery Multiple deliveries per day common (e.g., one morning delivery, 2-3 during day) causing picking peaks in daily warehouse operations Short cut-off time needs high workforce flexibility Significant return volume common as part of business model (e.g., expired products, damaged packs, customer recalls, pharmacy stock clearing) Ware- house layout Conveyor system with plastic totes circulating between customers and warehouse Different picking areas reflecting different product order frequency Automated picking systems via “A-frames” Specific infrastructure for products with special handling requirements

Key specifics of pharmaceutical wholesale warehouse layout
Conveyor system Activity areas Goods In Dispatch area Empty tote return Dispatch lanes A Typical warehouse setup Conveyor system with plastic totes or cartons A Special picking (narcotics, flammables) D B Different picking areas, such as bulk picking, static shelves, flow racks B Palette racks with bulk picking and over stocks Tote/ order launch C Automated picking via “A-frames” Cold chain picking Freezers D Products requiring special handling and thus stored separately (e.g., cold chain, narcotics, flammables..) C D Automated picking/ A-frame Flow racks B Static shelves Manual picking area

Key specifics of pharmaceutical warehousing – Conveyor/tote system
Description Reusable plastic totes circulate between pharmacies and warehouses Within the warehouse, order start/launch point regulates flow of totes (up to – totes per hour), potentially splitting orders Totes are transported to A-frames and/or manual picking In manual picking, totes are ejected into picking stations. Often “Poka Yoke” (fool prove) systems in use like RF-picking1 and pick-by-light Before dispatch, totes are equipped with delivery notes, invoices (sometimes at order start) and lids Error station is placed at end of conveyor system to handle issues and perform quality checks (e.g. via check of tote weight) Conveyor/ tote system A Different picking zones B A-Frame C Special handling products D Typical improvement levers Use of totes for put away in goods in or returns process Tote blockages in a station lead to waiting time for pickers 1 RF-Picking stands for Radio Frequency Picking, scanning the tote to receive the order paperless onto handheld device with calculated picking route

Key specifics of pharmaceutical warehousing – Different picking zones
Description Warehouses are split into different picking zones with varying productivity Products are allocated to the different zones according to Picked lines (frequency) Units per picked line (structure) In general in manual picking Fast movers: closest to the conveyor to reduce walking distances Slow movers: furthest from conveyor (e.g. stored in static racks) Automats for high to medium number of picked lines and few units per picked line Flow racks for high number of picked lines and many units per line Static racks are standard solution for low number of picked lines Conveyor/ tote system A Optimum pick technology Pick strategy Automation Manual picking Different picking zones High Static racks Flow racks B Units per line A-Frame C Drawing cabinets A-frame/ automation Low Low High Special handling products Picked lines D Typical improvement levers Correct allocation of products to the different pick areas has a very high effect on overall efficiency

Key specifics of pharmaceutical warehousing – A-frame
Description Medium to large warehouses operate with high degree of automation (40-90% of picked lines) “A-frames” are most common technology Automated ejection of products onto conveyor belt from different channels At end of conveyor, products fall into totes Manual replenishment of channels Different types of A-Frames exist for various pick frequencies Conveyor/ tote system A Different picking zones B A-Frame C Typical improvement levers Regular review and optimization of products in A-frame and other zones to achieve maximum level of automation possible Replenishment of products according to specific rules Aim for maximum replenishment quantity Replenish with pickers in off-peak times Avoid stock outs in A-Frame to prevent rework Special handling products D

Key specifics of pharmaceutical warehousing – Special handling products
Description Warehouse feature a wide variety of special handling products Cold chain Narcotics Bulk Hazardous (flammable and acid) Cold chain products are stored in cold rooms and picked into totes with styrofoam inlays and cooling elements Narcotics are stored in a safe and require significant documentation Bulk products do not fit into totes and thus need to be handled separately Special handling results in lower productivity Conveyor/ tote system A Different picking zones B A-Frame C Special handling products D Typical improvement levers Review if bulk products do not fit into totes Optimize the preparation of cold chain totes

Contents Warehousing value Lean pharma warehousing Improvement areas

CPG case example achieving ~30% cost reduction across transportation, warehousing, and manufacturing
Situation/background What we did Our impact CPG client with large distribution and manufacturing operations Supply chain perfor-mance last 5 years: 5-10% revenue decline per year +15% transport-ation cost increase Flat warehousing cost despite volume decline Transport-ation Evaluated current transport management practices Conducted transportation line-haul RFP: Using transportation clean sheets Set targets for the negotiation process with brokers and carriers Ran multiple rounds of negotiations to reduce transport costs Transportation cost reduction, % 38 Ware-house Diagnosed lean opportunities and should-cost structure within the current setup (‘brownfield’) Evaluated outsource potential using clean-sheet design approach Used best-practice sourcing process, e.g. 3PL evaluation, negotiations and implementation Warehouse cost reduction, % 32 Network Rationalized network considering business constraints (e.g. cut-offs, DC loading): Determined optimal last mile hub locations to cover entire country Improved line haul utilization while maintaining service: Established milk runs across hubs with lower demand and consolidated mail plans Manufacturing cost reduction, % 25

Delivers rapid impact across 6 supply chain areas
Targeted debottlenecking of constrained assets to rapidly release revenue Inventory optimization to rapidly release cash Leverage planning for volume consolidation and capacity/ inventory allocation across sites and markets Inventory Implement best-practice transportation levers to reduce costs Transport Production Warehouse Planning Network Optimize distribution network to reduce warehousing and transportation costs Implement best-practice lean warehousing levers to reduce costs

WAREHOUSE: Implement best-practice lean warehousing and service procurement process to rapidly reduce costs Value driver Reduce warehousing cost by taking out labor costs and facility/equipment lease costs Approach Implement best-practice lean warehousing levers and/or service procurement process Typical Impact Warehouse impact % cost reduction 10-30

WAREHOUSE: Key lean levers and service procurement process for reducing warehousing costs
Key levers Description Vendor/manufact-uring collaboration 1 Work together with vendors to optimize logistics flow (e.g. load carriers, packaging, planning) Reduce receiving and put-away workload 2 Improve the layout and workplace organization as well as reduce process waste Streamline replenish-ment process Create a “hot line” for high volume SKUs with larger slots to reduce replenishments 3 Profiling in storage and picking Profile items by velocity and optimize utilization of easily accessible locations to minimize walking in and out of aisles 4 Streamline picking process Implement pick-path optimization and improve tools as well as technology 5 Minimize outbound workload Optimize layout of shipping buffer to avoid resorting and leverage equipment for loading 6 Labor/work scheduling Implement best-practice labor scheduling approach and tool 7 Warehouse outsourcing Engaging sourcing group to launch a best-practice procurement process with many service providers 8 Reduce overhead and expenses Delayer organization, simplify admin tasks, and evaluate leasing costs for facility/equipment 9

WAREHOUSE: Client example showing how rapid improvement levers can drive 30% cost reduction in a warehouse Starting point Approach Impact achieved Client overview Specialty chemicals warehouse Situation Poor performance and high operating costs Objective Rapidly drive productivity to reduce cost and improve service level Benchmarking and clean-sheet modeling Used a clean-sheet approach to calculate the optimal cost to operate the warehouse and benchmark all processes Interviews to understand maturity and need to improve processes and structure Placing a man on the ground to run warehouse for 4 weeks Walk-through of warehouse to identify opportunities Layout inefficiencies (storage to picking distance, picking layout) Processes inefficiencies, e.g., time- consuming labeling, counting, checking, movement in singe item pick zone No labor scheduling resulting in poor workload balancing Performance management not existing 30 Warehouse cost reduction, Percent Implemented changes (selection) Remove duplicative counts or use barcode upstream Reduce scanner time to improve picking speed Move labor-intensive processes (e.g., labeling) upstream Change layout to remove 4th/5th unergonomic levels

WAREHOUSE: Warehousing can be improved through a series of key levers (1/3)
Exemplary improvement suggestions Suggested analyses/tools 1 Vendor/manu-facturing collaboration Coordination with manufacturing/vendor to get aisle- friendly pallets Pallet/package architecture to reduce handling time Inventory management-related solutions (minimum order quantities, receiving in case quantities) Define time windows for inbound trucks EDI connection with suppliers to ease receiving process Feedback form for how pallets are built or inbound delays Process analyses Shop-floor observations 2 Reduce receiving and put-away workload Clean dock philosophy on a daily basis Standardize process by type (FTL, LTL, mixed pallets, parcel) Active performance management and role of supervisor Improve the layout and workplace organization Process analyses Shop-floor observations 3 Streamline replenishment process Ensure accurate minimum/maximum levels Standardize slot sizes (i.e., picking slots have one week of demand) Create a “hot line” for high volume SKUs with larger slots to reduce replenishments Coordinate replenishment with put away Build aisle-friendly replenishments Potentially segregate replenishment stock and mirror picking slots Process analyses Shop-floor observations

Exemplary improvement suggestions Suggested analyses/tools 4 Profiling in storage and picking Follow best practices around profiling: Condense area to reduce pick path Profile items by velocity and optimize utilization of easily accessible locations to minimize walking in and out of aisles Segment by customer or commonly picked together Increase/standardize pallet size Reduce/differentiate rack height Current state profiling “heat” chart Compare space utilization ratios Process analyses Shop-floor observations 5 Streamline picking process Arrange warehouse to optimize picking Minimize congestion Put in place processes around startup and end of pick path Standardize pick quantity (i.e., 30 minutes) Improve pick tool, cart, information Standardize quality check Leverage technology, e.g. pick-by-voice, pick-by-light Analyze picking productivity/quality Quantitative pick-path assessment Process analyses Shop-floor observations 6 Minimize outbound workload Optimize layout of shipping buffer to avoid resorting Use trailer yard to enable direct loading Leverage equipment, e.g., flexible roll conveyor for parcel loading Use time windows to level outbound area Balance operator allocation to avoid waiting times Process analyses Shop-floor observations

Exemplary improvement suggestions Suggested analyses/tools 7 Labor/work scheduling Level load volumes and concentrate the work window Redistribute shifts and breaks to match demand Schedule resources day by day according to demand forecasts based on weekly/monthly patterns Clearly layout a process to shift labor throughout the entire operations based on workload shifts by hour/day/season Cross-train staff throughout key areas to allow for labor migration between area Workload balancing chart Visual board showing allocation of tasks between teams Process analyses Shop-floor observations 8 Warehouse outsourcing Engaging sourcing group to launch a formal RFI & RFP process with many service providers Adopting a clean-sheet approach Business case and savings based on best-in-class operations (e.g. leverage wage rates) Respondents asked for design and proposal to deliver desired performance based on our business and system requirements Warehouse clean-sheet analysis 9 Reduce overhead and expenses Reduce overhead, automate admin tasks, increase process stability to reduce need for quality control Evaluate alternative sites to reduce facility lease cost Limit use of public warehousing to slow movers Change equipment supplier and maintenance program Analyze spans of control Benchmark overhead and support functions Compare facility lease rates Equipment lease and maintenance cost comparison

WAREHOUSE: Key lever example – Slotting SKUs by velocity minimizes travel time, which increases overall picking productivity Data analytics Site visit Approach and impact achieved SKUs profiled based on number of picks 5% of SKUs represent-ing 47% if picks SKUs slotted based on rack availability No consideration to travel distance Re-slotted high velocity SKUs to prime picking locations (shortest distance to entry/exit) Average travel time reduced with 50% and overall picking time with 33% 30% labor reduction achieved through higher productivity Pick distribution, % Warehouse layout Top 20 1 min 8 min 100 54% 47% SKU distribution % Average pick time Minutes Average pick time Minutes Labor reduction Percent Top 20 ~ 6 ~ 30 Handle ~ 1 ~ 1 ~ 4 Search Handle ~ 1 95% Search ~ 1 Travel ~ 4 Travel ~ 2 5% SOURCE: Sanitized client example

WAREHOUSE: Key lever example – Workload balancing between shifts and functions reduces tool staffing requirement FTEs with reduction potential Current state Future state Weekdays Weekend days Weekdays Weekend days Mor-ning Mor-ning # of Shifts Total # FTE Mor-ning Mor-ning # of Shifts Total # FTE FTE Delta Night Late Night Late Day Night Night Late Comments Inbound 3 2 2 3 2 2 21 14 1 2 2 1 2 2 21 10 Focus work on morning/ day shift ~4 FTE Day 1 5 1 Day 1 5 1 Shuttle 1 1 1 1 1 1 1 21 6 No Change 9 Leverage shuttle driver to pick in bulk area on lower volume hours Shuttle 2 1 1 1 15 3 Picking 5 4 4 2 2 2 21 19 2 3 3 1 1 1 21 11 ~8 FTE Focus work on morning/ day shift Balance workload with packaging Repack-aging 1-4 5 ~2 No Change 5 ~2 Re-packaging labor will be used to balance workload Foreman 1 1 1 1 1 1 21 6 1 1 1 15 3 Weekend: Incoming good FTE is foreman ~3 FTE Total 51 36 SOURCE: Sanitized client example

WAREHOUSE: Key lever example – Rapidly improving client’s approach to warehouse operations outsourcing Previous warehouse outsourcing process Implemented warehouse outsourcing process Best-practice sourcing process not followed No RFI to gather market information Uncompetitive RFP process, since only incumbent provider for deconsolidation center (APL) was asked to quote Engaging sourcing group to launch a formal RFI & RFP process with many service providers 8-12 week sourcing process with rigorous evaluation and selection criteria Adopting a clean-sheet approach to warehouse design Business case and savings based on best-in-class operations Respondents asked for design and proposal to deliver desired performance based on our business and system requirements Rigid requirements (e.g., design of operations, labor, automation) demanded from potential providers Outlined the pricing model Shared baseline costs minimizing possibility for a clean-sheet response from the provider RFI was sent to ~15 renowned warehousing service providers, RFP sent to about 10 of them Warehousing is not the core competency of the only provider asked to quote (APL) Very conservative timelines for implementation Aggressive timelines put in place for sourcing and implementation; focus to get full-year impact in 2015

Contents Warehousing value Lean pharma warehousing Improvement areas

10-13% total opportunity identified through productivity initiatives
DISGUISED CLIENT EXAMPLE 10-13% total opportunity identified through productivity initiatives a Category-2 Pack Center Under Const Category-1 Category-3 Category-4 Category-5 Catego--ry-1 Catego--ry-2 Pack Center Zone segmentation Broad zones in warehouse according to SKU characteristics b Rack Sizing Appropriate sizing of racks e.g. 5 high to 6 high for certain areas c Slotting logic Fast moving SKUs closer to doors and at bottom of racks d Door assignment In-and-out on both sides of warehouse minimizes travel within warehouse e Segmentation at Plants Enables trailers to dock at appropriate doors of the warehouse f Layer picking Use layer picking where order is >= 1 layer g Create KPIs to manage productivity Identify productivity KPIs to track, manage, and improve performance across warehouse

Zoning is the first lever for carrying out productivity improvements and is a two-step process
Activities Warehouse visit One-day expert walkthrough of each DC to identify productivity pain points and develop solution hypotheses: Common logistic characteristics across products (e.g., SKUs built on a specific pallet type, SKUs that can be cross-docked) Products having to travel long distances Dock door utilization (e.g., allocations for inbound vs. outbound) Product flow SKU Categori-zation Gather pallet and case shipping data from both peak and regular-season volumes Understand DC constraints (e.g., equipment such as packaging machines that are too expensive to move) Align with client on improved flow and design zoning plan (tip: stay focused on flow, do not be over concerned on space) Build implementation plan

Flows and inventory are analyzed and balanced to create an efficient zone layout
DISGUISED CLIENT EXAMPLE Inbound Outbound Internal moves Category of SKUs Inbound pallets '000 Plant-1 Plant-2 Plant-3 DC-2 OTHER Category-1 (shipped in bulk to customer) 8.4 7.5 2.9 1.5 4.8 Category-2 (contract manufacturing) 13.0 7.8 N/A N/A N/A Category-3 (specific type of pallets) 3.2 16.3 0.8 3.2 7.6 Category-4 (standard pallets) 10.0 9.3 8.0 8.9 8.4 Category-5 (shipped to other DC) 0.4 N/A N/A N/A N/A Category-5 to DC-2 Cateory-5 Cateory-4 Cateory-4 Cateory-1 5 categories identified during the walkthrough Categories :1-5 based on unique characteristics of SKUs Category-5 was flow to another internal facility Category -1 was a distinct package type inbound to support packing Cateory-5 Cateory-4 case pick Category-4 pallet pick BUFFER Cateory-2 & 3 case pick Cateory-1 case pick Cateory-3 Full pallet pick Cateory-2 Cateory-1 Cateory-2 Category-1 Cateory-4 Cateory-4 Cateory-3 Category-2

Warehouse dimensions for each zone are derived from maximum inventory levels and pallet sizes
DISGUISED CLIENT EXAMPLE Rack storage Floor storage 300ft 5 80ft Category-5 Category-1 packaging center 2b Cateory-4 case pick Buffer 2a 1b Cateory-1 pallet pick Cateory-4 pallet pick 380ft1 4a 4b Category-3 pallet pick Category-3 case pick 1a 3 2a Cateory-1 case pick Category-2 Case pick Cateory-2 pallet pick 190ft 230ft 200ft 520ft 230ft 70ft 100ft 75ft 155ft 350ft 20ft 1 Note that length of warehouse is not to scale relative to the width

Within zones, racking size is designed and implemented, per warehouse constraints
b Optimum rack heights are designed based on current configuration and ceiling space Allow for pallet height and clearance Zoning analysis provides number of inventory positions (sourced from product master data) Total capacity (number of cases/pallets) is calculated based on new rack heights To sustain optimal pallet height one or more of the below options may be followed: Update WMS1 master data to direct pallet storage into the right-sized slots (i.e., “Directed put away”) Size inbound pallets per the slotting dimensions, often by adding a layer of product (tip: be aware of any customer implications) Adjust racking size to fit pallets New racking installation is expensive, but adding a set of beams is relatively cheap and can improve storage density by 20% 1 Warehouse management system

b Optimizing rack heights to allowed XX% of warehouse racking to increase from 5-high to 6-high DISGUISED CLIENT EXAMPLE Analysis of pallet heights and inventory confirmed that half of the SKUs could fit into a smaller rack height, allowing 6 pallet high storage rather than 5 With a small investment in beams and labor the existing racking was reconfigured, creating an additional XX% storage capacity

c Slotting begins with segmentation of SKUs by velocity, developing velocity subzones within zones Cumulative Percent % of all picks C Remaining SKUs C B SKUs with 80% of the Picks A B SKUs with 60% of the Picks A Staging Area No of SKUs Segment A: Segment B: Segment C: SKUs with highest picks. Closest to the Staging area SKUs with medium picks. Midway from the Staging area SKUs with Lowest picks. Farthest from the Staging area

Faster moving SKUs are slotted close to inbound and outbound doors, and closer to the ground, minimizing travel within subzones c Top view of warehouse width Slow movers Medium movers Fast movers Staging Area/Dock Doors A SKUs with 60% of the Picks B Instead of using one side for inbound and one for outbound, both inbound and outbound movements were carried out on both sides to allow fast moving SKUs stored closer to staging area / doors SKUs with 80% of the Picks Outbound From plant C Remaining SKUs C From packing Standard case pick Standard pallet pick Remaining SKUs Replenish Case pick B SKUs with 80% of the Picks A From plant SKUs with 60% of the Picks Outbound Staging Area/Dock Doors

Slotting tool heat maps based on SKU velocity & visualization were used for reconfiguration, and routine management of slotting locations c Warehouse: Before Slotting Warehouse: After Slotting Each cell corresponds to a particular location, with the color coding based on SKU velocity (i.e., darker cells indicate higher velocity) Non-optimal slotting will show variation of velocity throughout aisles and rows Optimal slotting is indicative of like-velocity SKUs grouped together in a warehouse After slotting redesign, darker cells are concentrated nearest the staging area(s)

Segmented shipping and door assignment are critical for slotting and zoning to work
DISGUISED CLIENT EXAMPLE Segmentation at plants Enables trailers to dock at appropriate doors of the warehouse Plant segmentation: Description In order for zoning and slotting to work plants need to ship in full truckloads of product categories Rationale: Shipping full truck loads allows trucks to dock at the doors close the category zone in the warehouse allowing minimum internal movements Changes at shipping location (plant) : Product zones indicated on shuttle drivers’ paperwork Number of fully segmented vs. un-segmented shipments were captured and used to assess pilot effectiveness Changes at receiving location (DC): Trailers directed to appropriate dock doors based on product zone notations Key safeguards: Production flow needs to be remain unchanged “Emergency brake” (e.g., un-segmented shipping) is activated if production is in danger of stopping and/or staging area is full 75%1 loads segmented in week one of pilot has resulted in 31% increase in put-away rate ( pallets/hour) Results: 1 Average segmentation for pilot from 8/24 to 8/28 (% loads segmented = 100,100,100,55,25,0)

Scenario analysis and simulation was carried out to ensure minimal adverse effect on staging area or production flow d e DISGUISED CLIENT EXAMPLE Scenario Recommended solution 1 Base case Unchanged production 3 drivers 5 dock doors No segmentation Based on scenario analysis, clients approved a pilot of complete segmen-tation at 1 plant Week 1 of pilot saw a 31% improvement in DC put away times, with no impact on production Segmented shipping processes were rolled out to all plants and DCs after 1 month of piloting 2 Complete segmentation (4 groups) Unchanged production 3 drivers 5 dock doors Each zone segmented into its own truck 3 Partial segmentation (3 groups) Unchanged production 3 drivers 5 dock doors Partial segmentation groupings: PECO & Co man, standard, bulk

Layer picking was introduced for high volume case pick with a 4x improvement in efficiency
Equipment and layout Customized fork truck attachment that grabs complete layers of cases Runs between dedicated guides bolted to floor Typically supports 120 SKUs in the usual 300’ DC block layout Minor IT changes required Total implementation cost approx $150k Pick rate impact Manual case pick rates per person per hour being achieved Case pick increased to 600 cases per person per hour Considerations Analyze case pick orders to ensure high utilization of equipment and justify investment

g Two types of KPIs need to be tracked regularly to ensure savings capture from productivity improvements Description How to use effectively Performance KPIs Metrics with best-in-class targets1 Provide snapshot of overall warehouse performance Compare actual performance to targets in order to facilitate productivity management Use metrics to drive continuous improvement Create dashboard to facilitate regular reporting (daily, monthly) Use stop light system (e.g., red, yellow green) to visually communicate performance against targets Use regular calls to celebrate high performing KPIs and discuss underperforming KPIs Communicate select productivity KPIs to employees through visual dashboards in the warehouse to be transparent about metrics and goals Cost driver KPIs Metrics often without targets Not directly controlled by DC Support performance KPIs Provide insights into DC cost/ performance variation Create dashboard to facilitate regular reporting (daily, monthly) Supplement performance KPIs to understand driver behind cost and operational performance Discuss daily by exception only 1 Best-in-class targets vary across industry; current targets provided from a cross-sectional view of industries

Productivity and cost KPIs enable root cause problem solving and to hold key stakeholders accountable g Internal transportation dashboards Performance review routines Daily KPI tracking Daily review of previous day’s metrics1 Brainstorming and issue resolution Discussion on causes/issues to be escalated Weekly root cause identification Weekly review of productivity and cost metrics Formal root cause problem solving on productivity issues (e.g., $/case, $/lb, cases / man hour) Discussion on causes/issues to be escalated and/or cross-functional teams needed to resolve (e.g., plants) Conduct meetings with warehouse managers to develop corrective and preventive actions for external issues Track ongoing improvement initiatives and dollar impact Internal External 1 e.g. man hours per shift, on time delivery, shipment accuracy

Holding KPI-based performance dialogues with vendors is the key to sustaining savings
Description Monthly KPI meeting Quarterly business review Team Discussion points Duration and forum Review performance metrics based on monthly scorecard Ask for corrective and preventive measures to address issues Agree upon timelines for addressing issues Review prior corrective action plans Ask for feedback on how client can improve working relationship Improvement initiatives status review and impact tracking Warehouse managers, Client lead Scorecard sent first week of every month, for prior month; with discussion in the following week 60 minute in-person meeting Review carrier performance trends Review progress on action plans from monthly calls Escalate unresolved issues with carrier management Celebrate success for high-performance Joint brainstorming on improvement ideas Warehouse managers, client lead, VP Logistics, COO 60 min in person meeting for each warehouse

Driving Impact in the Warehouse: Value drivers and key levers

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Driving Impact in the Warehouse: Value drivers and key levers

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