REDUCING SHIPMENT VARIABILITY THROUGH LEAN LEVELLING Fabian Brenninkmeijer & Melissa Botero May 25, 2017
AGENDA 1. Research Question and Context 2. Methodology 3. Results 1.Variability 2.Transportation Cost 3.Service Level 4.Inventory 4. Conclusion 5. Q&A
1. RESEARCH QUESTION Will a consistent, pre-determined customer shipment profile based on the Lean Levelling principle reduce variability and enable improvements in: Transportation cost Inventory Service levels Before After Number of Shipments Time
1. RESEARCH CONTEXT Consumer goods industry: High shipment variability Large number of SKUs Frequent Promotions Scope: 1 VMI lane of a typical customer Lean Literature Focus of Lean Literature Raw Materials Supplier Plant Retailer DC Thesis Scope Retail Store Consumer
2. METHODOLOGY / APPROACH 1. SKU Segmentation: By # of cases delivered Top 50% SKUs Volume % 100% 80% 60% 40% 20% 0% 0% 3% 7% 10% 13% 17% 20% 23% 27% 30% 33% 37% 40% 43% 47% 50% 54% 57% 60% 64% 67% 70% 74% 77% SKU % Cumulative VMI Sales Top SKUs
2. METHODOLOGY / APPROACH 2. Simulation Various order policies based on fixed % of Top SKU demand Fixed Trucks Follow lean leveling principle Variable Tucks Follow the process logic of VMI system Number of Shipments 15 10 5 - Top SKUs Shipments by Week 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 1 2 3 4 5 6 7 8 Week Actual # Trucks Fixed # Trucks
2. METHODOLOGY / APPROACH 2. Simulation (continued) TOTAL DEMAND 50% TOP SKU DEMAND X% (1-X)% ORDER POLICY Fixed Amount (Average*X%) Weekly Frequency CURRENT ORDER POLICY FIXED SHIPMENTS VARIABLE SHIPMENTS 50% SLOW MOVERS DEMAND CURRENT ORDER POLICY VARIABLE SHIPMENTS 3. Evaluation Performance of different order policies vs actual (variability and 3 KPIs)
3. RESULTS Change % 4% 2% 0% -2% -4% -6% -8% -10% -12% -14% Sensitivity Analysis: KPIs Change (%) Feasible Region 10% 20% 30% 40% 50% 60% 70% 80% 90% Fixed % of Top SKUs Demand Transportation Cost VMI Service Level On Time Service Level Inventory Value Customer DC
3.1 VARIABILITY Top SKUs VARIABILITY (Fixed 75% of Top SKU Demand): Number of Shipments 15 10 5 - Shipments by Week 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 2 4 6 8 Weeks Actual # Trucks 75% 25% 50% DYNAMICS: % Fixed Shipments = Variability IMPROVEMENT (Fixed 75% Top SKU Demand): Coefficient of variation: 31% 16% 50% Reduction
3.2 TRANSPORTATION COST VS. MAIN ASSUMPTION: Contracted rate < Spot Market rate Probability of spot market delivery is reduced by the same % of fixed shipments DYNAMICS: % Fixed Shipments = Number of contracted shipments = CONTRACTED TRANSPORTATION Number of spot market deliveries VS. Average price per load SPOT MARKET POTENTIAL SAVINGS (Fixed 75% of Top SKU Demand): Annual savings of 1% of total transportation costs Ø Potential savings in contracted rates resulting from improved planning capabilities
3.3 SERVICE LEVEL: ON-TIME MAIN ASSUMPTION: Fixed Shipments are more likely to arrive on-time Improved Planning Economies of repetition Probability on- time: Variable Shipments: 94% (current performance) Fixed Shipments: 98% (root cause analysis) DYNAMICS: % Fixed Shipments = On-time Service Level a RESULTING SERVICE LEVEL (Fixed 75% of Top SKU Demand): 96% (vs 94% actual)
3.4 INVENTORY Customer DC DYNAMICS: Shipment Frequency = Inventory VS. Inventory % Fixed Shipments = Inventory Time POTENTIAL SAVINGS (Fixed 75% of Top SKU Demand): 10% ($940K) Inventory value reduction with the optimal policy ØPotential for additional inventory savings for sponsor company due to reduction in Top SKU s volatility
4. CONCLUSION Lean leveling reduces shipment variability Finding the right ratio of fixed vs variable shipments is crucial Evaluation criteria should be balanced to benefit both buyer and seller Optimal solution Transportation Cost Inventory Customer DC 75% fixed Top SKU shipments 1% Reduction - $6,500 per year 10% Reduction - $940 K Service Level 2% Improvement - 96% Potential additional savings: freight rate and sponsor company inventory
Q&A
APPENDIX
Variability Total Shipments 25 Total Shipments by Week Number of Shipments 20 15 10 5-11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 2 4 6 8 Weeks Actual # Trucks New Policy # Trucks
Inventory Levels 6,000,000 Top SKU Inventory Value Inv Value 4,000,000 2,000,000-11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 2 4 6 8 Week Top SKUs Real Top SKUs Fixed Top SKUS Hybrid Inv Value 20,000,000 15,000,000 10,000,000 5,000,000 - Total Inventory Value 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 2 4 6 8 Weeks Total Inv Real Total Fixed Total Hybrid
Scenario Evaluation KPI Actual Shipments Fixed Hybrid Fixed Model Hybrid Model Fixed vs Hybrid 100% Average 75% Average Vs Actual Vs Actual Number of Shipments Shipments/Year 684 702 684 18-18 Percentage of fixed shipments/year 0% 57% 43% 57% 43% 14% COV of weekly shipments 31% 15% 16% -15% -14% -1% Transportation Costs Total Transportation Cost/Year 896,216 910,841 889,676 $ 14,625 $ (6,541) $ 21,165 Average Transportation Cost/Shipm 1,310 1,297 1,301 $ (12.8) $ (9.6) $ (3.2) Service Level On-Time Service Level 93.9% 96.5% 95.9% 2.6% 1.9% 0.6% VMI Service Level 98.1% 98.6% 98.5% 0.6% 0.5% 0.1% Inventory at Customer DC - Average (cases/week) 202,619 207,428 179,281 4,809 (23,338) 28,147 COV of inventory level (cases) 12% 8% 9% -3% -3% 0% Total Number of Top SKU cases deliv 1,433,457 1,534,358 1,372,753 100,901 (60,704) 161,605 Min (USD/week) 10,237,380 10,347,589 10,276,272 $ 110,209 $ 38,892 $ 71,317 Average (USD/week) 12,782,906 13,367,597 12,259,533 $ 584,691 $ (523,373) $ 1,108,064 Max (USD/week) 15,829,899 15,569,052 14,669,825 $ (260,847) $ (1,160,074) $ 899,226
Sensitivity Analysis Sensitivity AnalysisNew Order Policy % Fixed Average: 10% 20% 30% 40% 50% 60% 70% 80% 90% 75% Shipments Percentage of fixed shipments /Year COV of weekly shipments (Difference: Hybrid - Actual) Transportation Average Transportation Costs Cost/Shipment (Difference: Hybrid - Actual) Service Level 1.4% 8.7% 15.3% 22.3% 28.7% 34.8% 39.9% 45.6% 51.0% 42.8% -9.8% -10.0% -11.2% -11.9% -12.7% -13.1% -13.6% -14.4% -15.2% -14.1% $ (0.3) $ (1.9) $ (3.4) $ (5.0) $ (6.4) $ (7.8) $ (8.9) $ (10.2) $ (11.4) $ (9.6) On-Time Service Level 94.0% 94.3% 94.6% 95.0% 95.2% 95.5% 95.8% 96.0% 96.3% 95.9% VMI Service Level 92.2% 93.5% 94.7% 95.9% 96.8% 97.6% 98.3% 98.9% 99.4% 98.5% Inventory at Customer DC Average cases/week (Difference: Hybrid - Actual) COV of inventory leve in cases (Difference: Hybrid - Actual) Average Change USD/week (Difference: Hybrid - Actual) (56,598) (52,985) (49,398) (45,523) (40,956) (36,418) (28,162) (16,804) 2,810 (23,338) -2.0% -2.3% -2.2% -2.3% -2.3% -2.5% -2.7% -3.4% -3.4% -3.1% (1,543,143) (1,439,280) (1,330,705) (1,216,336) (1,089,559) (938,712) (683,955) (291,235) 348,971 (523,373)
Top SKU Top SKU s Shipments Cases 2000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 Weeks Actual VMI Fixed 75% Inventory USD 60,000 10,000 (40,000) Top SKU Inventory Value 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 Weeks Actual Inventory Inventory 75%