1. Strategy for Direct to Store Delivery
Authors: Amit Panditrao and Kishore Adiraju
Advisor: Dr. Chris Caplice
Sponsor: Niagara Bottling, LLC

2. Agenda Introduction Methodology Data analysis Transportation model
Safety stock model
Recommendations
Future research
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3. Where do these products come from?
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4. DC Delivery Pitfalls Bulky and fast selling products Warehousing costs
Getting products to the store is an age old question for the retailer
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5. Direct To Store (DTS) delivery
Benefits
Sales growth
Competitive advantage
Better in-stock levels
Reduction in total supply chain cost
Getting products to the store is an age old question for the retailer
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6. Thesis focus Research question Sponsor company
What is the impact of DTS on supply chain costs?
What is the best supply chain strategy to rollout DTS?
Sponsor company
Largest private label bottled water manufacturer
in the US
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7. Methodology
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8. Methodology – Overview
Data collection
Sample selection
Data analysis
Models
Transportation
Inventory
Sensitivity analyses
Results
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9. Methodology – DTS scenarios
100% DC
Partial DC and DTS
Multi-retailer 100% DTS
Single-retailer 100% DTS
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10. Data Analysis
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11. Data analysis – Network and stores
AZ, CA, NV
473 stores
4 DCs
1 Plant
Plant
DCs
Geographical dispersion of stores of Customer A
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12. Data analysis – Demand POS data of two product families
Mean: 630 cases
Median: 560 cases
Range: 0 – 5,124 cases
Standard Dev: 370 cases
DTS demand: Lognormal (6.31, 0.54)
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13. Transportation model
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14. Transportation model Monte Carlo Simulation
Annual cost and capacity estimates
Basic period – one week
Assumptions
Rate per mile
Stop-off charge
Truck speeds
Loading/Unloading times
Order size / Stop distribution
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15. Transportation cost estimation
3 Components: Line haul, local tour, stop-off
Stop-off
Line haul
Local tour
Stop-off
Plant
Stop-off
Store cluster
13 store clusters in AZ, NV and CA
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16. Transportation cost
42% increase
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17. Multi-customer delivery
Transportation cost reduces by 4%
Local trip cost
Stores more closely spaced
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18. Sensitivity – Order size
Stop-off contributes the maximum
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19. Transportation vs Safety stock
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20. Safety stock model
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21. Niagara’s safety stock model
Inputs
Demand per store
Customer response time (CRT) – Time window in which the manufacturer must deliver product to the store
Manufacturing lead time distribution (MLT)
Customer response time
Probability (MLT > CRT)
Manufacturing lead time
Manufacturing lead time
Order receipt
On-time shipment
Delivery date
Back order
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22. Retailer’s safety stock model
LTDC
SLDC
LTStore
SLStore
LTDTS
Safety Stock1Store
Retailer’s
Safety Stock
SLStore
Safety StockDC
Safety Stock2Store
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23. Niagara’s safety stock
Inputs
DC CRT = 5 days
DTS CRT = 3 days
Service level = 98.5%
76% increase
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24. Retailer’s safety stock
Inputs
DC to store = 1 day
Niagara to DC =5 days
Niagara to Store =3 days
DC service level = 75%
Store service level = 99%
65% increase
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25. Recommendations
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26. Recommendations Large order sizes Multi-customer delivery
Less complexity in scheduling store delivery
Transportation cost savings vs. inventory cost increase
Multi-customer delivery
Confidentiality issues
Additional truck loading/unloading time
Lead time reduction
Lesser safety stock in the system
Trade-off with transportation cost
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27. Recommendations Faster and flexible production
Fulfill smaller and frequent DTS orders
Manufacture within customer response time
Collaborative partnership
Forecasting, Promotion planning, Store ordering
Share benefits
Change Management
Internally – Sales, Logistics, Inventory planning,
Demand planning, IT
Externally – Retailer (Merchandising, Stores,
Supply chain), Carrier management
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28. Future research For a manufacturer For a retailer
Re-design network - Should the warehouse be located closer to metro areas?
Own transportation fleet – With increased truck utilization, is owning a fleet worthwhile?
Develop production flexibility – How much flexibility is needed for frequent and smaller DTS orders?
For a retailer
Evaluation methods for DTS proposal
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29. Q&A
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