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

Transcription

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

2 Production Planning with Complex Cost Drivers

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

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

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

6 Model Overview New Extensions ØDouble Echelon Setups Costs ØProduct families with shared setups Bottle Level 1 Gallon Bottle ØDouble Echelon Inventory Costs ØPlant and 3PL Warehouses Package Level 6-Pack 4-Pack Ø3PL Transport and Handling Cost Item Level Customer X, Spring Water Customer Y, Mineral Water Customer X, Spring Water Ø Beginning and Ending Inventory Positions

7 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)

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

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

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

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

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

13 Regional Benchmark Production % Production Capacity 140% 120% 100% 80% 60% 40% 20% 0% MTS Burn Week Number Demand Model Production Capacity Actual Production

14 Regional Benchmark Inventory 25% Transfer 3PL Inventory to Plant % Plant WH Capacity 20% 15% 10% 5% 0% Week Number Model Plant Inventory Model 3PL Inventory Actual Plant Inventory Actual 3PL Inventory

15 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

16 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

17 Manual Benchmark Production Weekly Production Quantity % Production Capacity 120% 110% 100% 90% 80% 70% 60% Week Number Demand Model Production Manual Production Both plans have similar overall production

18 Manual Benchmark Inventory Weekly Inventory Position 300% % Plant WH Capacity 250% 200% 150% 100% 50% 0% Week Number Model Plant Inv Manual Plant Inv Model 3PL Inv Manual 3PL Inv Model Plan lowers inventory

19 Manual Benchmark Inventory 6 Weekly Number of Setups # of Setups Model Plan lowers Setups Week Number Model Setups Manual Setups

20 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 Line 2 Setups: 19 Total Setups: 37

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

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

23 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

24 % Production Capacity 120% 110% 100% 90% 80% 70% 60% Sensitivity Analysis Production & Inventory Weekly Production High Setups increase production and inventory Week Number % Plant WH Capacity 25% 20% 15% 10% 5% 0% Weekly Inventory Week Number Demand Base 4xSetup 4xHolding Base 4xSetup 4xHolding

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

26 Sensitivity Analysis Setups 12 Weekly Number of Setups # of Setups Increased Holding Costs increases setups in only 3 instances by 1 setup Week Number Base 4xSetup 4xHolding

27 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

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

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

30 Thank You

31 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