How to Integrate your Production and Logistics Strategy for a CPG - PowerPoint PPT Presentation

How to Integrate your Production and Logistics Strategy for a CPG Company A NEW FORMULATION

Production Planning with Complex Cost Drivers

Agenda Key Messages 1. Overview of Problem 1. Manual planning processes are time consuming and cannot consider all cost drivers . 2. Overview of Model 3. Benchmarking 2. Implementation of lot sizing problems requires 4. Sensitivity Analysis the right formulation that fits the business environment. 5. Key Takeaways 6. Further Research 3. Production lot sizing optimization is not always Areas a trade-off between setups and inventory .

Overview of Problem Is this caused by the lot sizing decision?

Model Overview Selection • Seasonality EOQ? • Deterministic Demand • Capacitated Capacitated Lot • Multiple Lines Sizing Problem • Multiple Items (CLSP) • Plant and 3PL Storage with new extensions

Model Overview New Extensions Ø Double Echelon Setups Costs 1 Gallon Ø Product families with shared setups Bottle Level Bottle Ø Double Echelon Inventory Costs Package Level Ø Plant and 3PL Warehouses 6-Pack 4-Pack Ø 3PL Transport and Handling Cost Customer Y, Customer X, Customer X, Item Level Mineral Spring Water Spring Water Water Ø Beginning and Ending Inventory Positions

Costing Methodology Setups Costs ◦ Opportunity cost of not producing product while the machine is down for setups Holding Costs ◦ Rent, Labor, Tax, Insurance à Annual cost per footprint à Weekly cost per bottle Transfer Cost ◦ Freight Cost ($ per TL) ◦ Handling Cost ($ per pallet) à Handling Cost ($ per TL) ◦ Estimated Transfer Size (TLs per week)

Model Overview Comparison Basic CLSP Setup Costs Inventory Costs Thesis Model Inventory Costs Setup Costs

Basic CLSP vs Model Inventory NA Plant Storage Capacity Transfer Event Binary NA NA Setup Level 1 Binary NA Setup Level 2 Binary NA Machine Capability Binary

Process Flow Inputs: • Weekly Demand Forecast per item Outputs: • Plant Capacities (MSA) • Lot Size Plan • Setup Costs/Times • Inventory • Inventory Costs • Setups • Line Capabilities Model Formulation:

Regional Benchmark Scenario Selection Rationale Strength - Represents network complexity 3,504 • Assets – 3 plants, 12 lines, 1 3PL Warehouse DECISION • Lines have varying capacity and capabilities VARIABLES • Products – 5 bottle sizes, 14 bottle-pack categories • Represents both core and non-core products

Regional Benchmark Demand Burn Period Capacity Demand During this period no pallets should be moved into 3PL warehouse

Regional Benchmark Production 140% MTS 120% % Production Capacity 100% 80% 60% Burn 40% 20% 0% 35 36 37 38 39 40 41 42 Week Number Demand Model Production Capacity Actual Production

Regional Benchmark Inventory 25% Transfer 3PL Inventory to Plant 20% % Plant WH Capacity 15% 10% 5% 0% 34 35 36 37 38 39 40 41 42 Week Number Model Plant Inventory Model 3PL Inventory Actual Plant Inventory Actual 3PL Inventory

Regional Benchmark Weakness : Actual Production Data doesn’t match Demand Data • Actual Production data produces 17% more bottles than forecast data requires • Dynamic Sourcing? • Actual Production data is not a good benchmark for a planning comparison • Need alternative benchmarking data

Manual Plan Benchmark Scenario Selection Rationale Simplified Data set ◦ 1 Plant ◦ 3 Lines ◦ 4 Products : 2 fast movers, 2 slow movers Scenario Features ◦ Build Period – Full Capacity and significant inventory build target

Manual Benchmark Production Weekly Production Quantity 120% % Production Capacity 110% Both plans have 100% similar overall 90% production 80% 70% 60% 14 15 16 17 18 19 20 21 22 Week Number Demand Model Production Manual Production

Manual Benchmark Inventory Weekly Inventory Position 300% % Plant WH Capacity 250% Model Plan lowers 200% inventory 150% 100% 50% 0% 13 14 15 16 17 18 19 20 21 22 Week Number Model Plant Inv Manual Plant Inv Model 3PL Inv Manual 3PL Inv

Manual Benchmark Inventory Weekly Number of Setups 6 5 Model Plan lowers # of Setups 4 Setups 3 2 1 0 14 15 16 17 18 19 20 21 22 Week Number Model Setups Manual Setups

Performance Benchmark Manual Planning Method Line 1 Setups: 9 Line 3 Setups: 9 • Current method uses average demand every period for fast movers • Planning done one line at a time to reduce complexity Total Setups: 37 Line 2 Setups: 19

Performance Benchmark Model Planning Results Line 3 Setups: 11 Line 1 Setups: 9 • Utilize flexibility to make the right product at the right time and reduce inventory Total Setups: 29 Line 2 Setups: 9

Performance Benchmark Manual Planning Method vs Model Plan Cost Comparison - Manual vs. Model Manual Setup Reduction: 22% Model Inventory Reduction: 9% Costs Transfer Event Reduction: 73% Total Relevant Cost Savings: 29% Line 1 Line 2 Line 3 SubTotal Plant 3PL Transfer SubTotal Holding Holding Costs Setup Costs Inventory Costs Total

Sensitivity Analysis Rationale Regional Benchmark Dataset ◦ Burn period offers best scenario for sensitivity analysis ◦ Spare Production Capacity ◦ Increasing setup costs should increase lot sizes à need spare capacity to see this ◦ Spare Inventory Capacity ◦ Increased lot sizes should add inventory

Sensitivity Analysis Production & Inventory Weekly Production Weekly Inventory High Setups increase % Production Capacity 120% production and inventory % Plant WH Capacity 25% 110% 20% 100% 15% 90% 10% 80% 5% 70% 0% 60% 35 36 37 38 39 40 41 42 35 36 37 38 39 40 41 42 Week Number Week Number Base 4xSetup 4xHolding Demand Base 4xSetup 4xHolding

Sensitivity Analysis Production & Inventory Weekly Production Weekly Inventory % Production Capacity 120% % Plant WH Capacity 25% 110% 20% 100% 15% 90% 10% 80% 5% 70% 0% 60% 35 36 37 38 39 40 41 42 35 36 37 38 39 40 41 42 Week Number Week Number Base 4xSetup 4xHolding Demand Base 4xSetup 4xHolding High holding costs increases make to order and reduces inventory

Sensitivity Analysis Setups Weekly Number of Setups 12 10 # of Setups 8 6 4 Increased Holding Costs increases 2 setups in only 3 instances by 1 setup 0 35 36 37 38 39 40 41 42 Week Number Base 4xSetup 4xHolding

Sensitivity Analysis Conclusions Change in Setups ◦ +/- 6% change in setups for +/-4x change in relative setup to holding cost value shows robustness Change in Inventory ◦ Plant warehouse utilization only increased to 9.4% with a 4x increase in setup cost

Key Takeaways Improve Plant Warehouse Utilization Reduce Transfer Events to the 3PL Plan on Multi-Dimensions Utilize Flexibility of all Lines

Further Research Areas • Three Echelon Formulation for Bottle-Packsize-Label • Backordering and Safety Stock features • Transportation Cost • Uncertain Demand/Capacity

Thank You

Performance Benchmark How Do you Reduce Setups and Inventory? • Manual Plan uses average carries extra inventory throughout • when you have inventory build target • Model Plan uses inventory early and builds to inventory target later Uses extra capacity to build slow • mover inventory to reduce setups Slow mover inventory build is less • than inventory reduction on fast movers