This document summarizes a project to reduce travel time in a warehouse in order to improve on-time shipping performance. The project team analyzed data on travel distances, order volumes, and late order reasons. They redesigned warehouse layout and item locations to reduce average travel by 56%, cutting late deliveries attributed to travel from 28% to 15%. The changes are expected to save over $87,000 over five years. Ongoing monitoring of top products will help maintain the benefits from the new layout.

1. Travel Reduction
Jared D.Amato | Green Belt Reporting

2. Executive Summary
Our goal is to ship every order complete within 2 work days. We have
found that travel time in the warehouse accounts for 28% of all failures.

3. ProjectTeam Roles and Responsibilities
Jared Amato
Operations
Manager
Anni XXXXX
Data Collection
Clinton XXXX
Simulation
Victor XXXXX
Process
Operator
Jose XXXXX
Process
Operator

4. Problem Statement
 The Ideal State
 Ship all orders complete within 2 days of confirmation from customer, utilizing no more that 8
man hours a day per every 2 FTE
 The State Before the Project
 February 2015 –April 2015 | 5726 orders | 64 working days | 89 orders per day.
 Average DistanceTraveled 285 feet per order.
 4.8 miles a day.
 The consequence if we had done nothing
 Continuing to have 15% of shipments late
 No time to QC orders
 Not giving the staff adequate time to do inbound QC
 Not having proper time to cycle count

5. Project Proposal
 Customer Requirements
 2 day order ship complete
 100% Accuracy
 Scope of Project
 Reducing order fulfillment travel distance
 Warehouse item classification
 Objectives
 Improve our order turn time to meet customer requirements of shipping complete within 2 days.
 Improve our accuracy
 Efficiency Improvement
 CriticalY – Order CycleTime
 CriticalY -Accuracy

6. Project Proposal
 CriticalY – Order CycleTime
 85% of orders ship on time (4867 orders)
 15% were late (859)
78 82
107
165
189
238
0
50
100
150
200
250
1
Late orders by reason
Credit Shipping Order Processing QC Build Time Pulling

7. Project Proposal
 CriticalY – Order CycleTime
3
3.5
4
4.5
5
5.5
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6.5
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364
Xi Chart Distance in miles per day
Distance UCL LCL CL
40
90
140
190
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364
Xi Chart orders per day
Orders UCL LCL CL

8. Project Proposal
 CriticalY – Order CycleTime

9. Project Proposal
CriticalY – Order CycleTime

10. Project Proposal
 CriticalY – Accuracy

11. Proposed State

12. Project Proposal
 CriticalY – ParetoTop Items
 Move the 43 items closer to the
shipping dock
$13,515,974.20
$2,520,775.02
$848,382.61
$-
$2,000,000.00
$4,000,000.00
$6,000,000.00
$8,000,000.00
$10,000,000.00
$12,000,000.00
$14,000,000.00
$16,000,000.00
$18,000,000.00
Dollar Value
InventoryAnalysis
80% = 43 items 15% = 79 items 5% = 370 items

13. Protocol and tools

14. Findings
 Summary of raw data –

15. Findings
 Summary of raw data -
1
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7
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 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Xi Chart Distance in miles per day
Distance UCL LCL CL
40
90
140
190
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 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Xi Chart orders per day
Orders UCL LCL CL

16. Findings
 Summary of raw data –

17. Findings
 Summary of raw data –
78 82
107
165
189
238
0
50
100
150
200
250
1
Late orders by reason
Credit Shipping Order Processing QC Build Time Pulling
21 23
33
51
55
28
0
10
20
30
40
50
60
1
Late orders by reason
Credit Shipping Order Processing QC Build Time Pulling
Before After

18. Success Factors
 ReducedTravelTime by 56%
 Reduced restocking / put away time (Non validated)
 Completed within budget
 Excluding light retrofit (Energy Trust Rebate not applied)
 Delivered on time (7 days early)
 Reduced warehouse foot print by 40%
Average Miles Before 4.82
Average Miles After 2.71
Mile Reduction 2.10
Percent Reduction 56%
Hourly Wages 17.82$ Savings
Weekly Income 712.80$ 401.54$ Weekly Income
Monthly 3,086.42$ 1,738.66$ Monthly
Yearly 37,037.09$ 20,863.87$ Yearly

19. Control
 Part of our new SOP for end of month reporting is running the top products list which
outlines product sales and quantity.This will show us if something moves up or down
in the ranking of top products. This will flag us to evaluate moving items around so we
don’t loose the momentum of the savings.

20. Benefits
 Financial – Cash flow Analysis
 Project five year savings - $87,365
 Payback Period – End of year one
 IRR – 154%
 NPV - $32,330
 Invoices Paid Sooner

21. Benefits
 Non-financial
 Customer Satisfaction
 Employee Morale
 Marketing

22. Recommendations
 Conclusions to date – Since I only have data for the one month it is hard to speculate
but I think the success will still be realized in the coming months.
 Learning to date – the big take away are the next two things to tackle (QC and Build
Time) Before the project the top 3 accounted for 695 of late deliveries.

23. Define
 Project Prioritization –We have quite a few projects that we need to address. Delivery
Performance was the one we all could agree goes to the root of our mission.

24. Define
 Kano Model –We debated the three phases a lot. Everyone had their own thought of
what was basic, performance and excitement. At a point in our history we were the
only company with a two day turn time. Now it is expected.
Training No System
Too Much Walking
Procedures Spread Out
No Expert
No accountability
Locations to small
No accountability Not having all the tools Not having all the product in one place
Fast moving in the back of the warehouse
Delivery
Failures
(Y)
Management Man Method
Measurement Machine Material
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause CauseCause
Cause
Cause
Cause

25. Measure
78 82
107
165
189
238
0
50
100
150
200
250
1
Late orders by reason
Credit Shipping Order Processing QC Build Time Pulling

26. Analyze
3
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4.5
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5.5
6
6.5
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 53 55 57 59 61 63
Xi Chart Distance in miles per day
Distance UCL LCL CL

27. Improve
Cashflow Cumulative Savings
Investment (10,000.00)$ (10,000.00)$
Savings year 1 13,909.28$ 3,909.28$ Earnings year 1
Net Savings year 2 20,863.87$ 24,773.15$ Earnings year 2
Net Savings year 3 20,863.87$ 45,637.02$ Earnings year 3
Processstep Potential failure mode Potential failure effects
S
E
V
Potential causes
O
C
C
Current processcontrols
D
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T
R
P
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Actionsrecommended
Responsibility (target
date)
Actionstaken
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w
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w
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Pulling Orders
Fail to meet 2 day
delivery
performance
Lowcustomer
satisfation
7 Travel Distance 8 Additional People 8 448 ABC Analysis Jared
Warehouse
Layout
3 5 4 60

28. Control
 SOP’s identifying when to runTop Products.Validated monthly

29. Conclusions
 The next phase in this would be a software upgrade where the order is packed, QC’d
and shipped the moment it is picked.