acme case study description jan 2016
TRANSCRIPT
Confidential Information. Do not disclose. © Fortna 1 © Fortna> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN
SYSTEMS> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN SYSTEMS> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN SYSTEMS
Case Study InformationPrepared for CICMHE Material Handling Student Design Competition
ACME Footwear Operations Design
January 18, 2016
Confidential Information. Do not disclose. © Fortna 2 © Fortna
Sections of this Deck
• Project Overview (from Our Company)• Current Process• Data Analysis• Labor Model• Future State Requirements• Expected Deliverables
Confidential Information. Do not disclose. © Fortna 3 © Fortna
Project Overview (from Our Company)
Confidential Information. Do not disclose. © Fortna 4 © Fortna
• ACME is a wholesale footwear distributor that services varying sizes of customers for athletic footwear.
• ACME’s current distribution center (DC) in Outwest, AZ, is at capacity for both storage and throughput, thus limiting ACME’s ability to grow.
• The current location is landlocked, thus restricting growth in-place.• The current Outwest lease expires in July 2017. ACME wants to move operations from the
facility no later than the end of 2016 to allow time for de-commissioning.• Current operations are very manual with little to no automation.• ACME has been experiencing 10+% annual unit growth; ACME believes they can plan on
7% unit growth into the future. • ACME is seeking a solution for a new facility that will accommodate growth through 2021.• ACME wants to explore alternative solutions that are cost justified and will make the
operation more efficient, more flexible, and less complex• The current operation is to be considered “baseline” for analysis purposes.• ACME wants to implement a new DC with minimal, ideally zero, risk and with with no
negative impact on their customers.• ACME has established a hurdle rate of 12% for any alternatives considered; ACME’s current
cost of capital is 8%.• ACME desires to stay in or near Outwest, AZ, and will be securing land in the area
Project Overview
In Summary, ACME requires a new, cost-justified DC to support business projections through 2021
Confidential Information. Do not disclose. © Fortna 5 © Fortna
Burning Platform
The existing DC is at capacity with no room to expand and an expiring lease
ACME has been experiencing high anual unit growth and expects ~7% until at least the Design year 2021
ACME is seeking new, justified alternative operational processes as they seek a right-sized facility to support future business
requirements
Project Overview – Burning Platform
Confidential Information. Do not disclose. © Fortna 6 © Fortna
Project Overview – Background
• In 2009, our company completed the design and then built the current Outwest, AZ, distribution center (DC) for ACME to service their wholesale footwear business.
• In 2014, ACME found they were operating very inefficiently and had no room to expand. They called our company and requested that we conduct an Operations Assessment to help extend the life in their current facility as long as possible. Only some of our recommendations were followed.
• We were recently engaged to design the new DC. We have good stock keeping unit (SKU) and order data for 2014-2015. They want a DC that will handle business for five years after move out in 2016, using 7% annual unit growth.
Our Company’s history to date with ACME is as follows:
Confidential Information. Do not disclose. © Fortna 7 © Fortna
Key Assumptions – Project
• To try to accommodate variation, design rates for the current facility were set to be approximately 2x the projected average rates based on an examination of the variation between the average and the daily maximums (measured at approximately 3x during the design stage).
• These design rate assumptions will need to be revisited in light of the new data and the availability of daily outbound levels.
• ACME would like to run an extended shift at most once per month. • Design changes from their current process (documented later in the PPT) must
be justified using the financial performance threshold specified previously.o No change for the sake of change. All changes are to be based on a well-articulated
business case.• Alternative analysis will be limited to fulfillment options around footwear and
storage media options (no new distribution channels or business segments).• The Outwest lease expires in July 2017, but the goal is to transition to the new
DC by January 2017 to allow for material handling equipment tear out and cleanup efforts in the current DC.
Confidential Information. Do not disclose. © Fortna 8 © Fortna
The Business Case Approach
Business Case Approach & Assumptions
• Scenarios to be evaluatedo Baseline scenario – current operations
projected forwardo Recommended design – recommended
operations design projected forward• Benefits Considered
o Describe main benefits that recommended solution provides compared to the current operations
• Costs Consideredo Describe all the investments and impact as a
consequence of implementing the solution (for the analysis, assume none of the current equipment can be salvaged)
• Financial Considerationso List the quantitative financial aspects that
will be taken into account in the business case
Benefits Costs
Revenue Increase
Cost reduction
Better Asset Utilization
Operating Expenses
Capital Expenditures
* Cost of Goods Sold represents the cost for ACME to acquire or produce the products (shoes). This cost ranges from $8 - $135 with most between $15 and $40.
Confidential Information. Do not disclose. © Fortna 9 © Fortna
Current Process
Confidential Information. Do not disclose. © Fortna 10 © Fortna
A very traditional, manual operation
Current Process Description
• The shoes are received in cartons via trailers or shipping containers, floor loaded.• Cartons are palletized for put-away to reserve (or directly to the forward area);
approximately 71% of the units are put away to reserve.• ACME has the capability to crossdock received goods, but doesn’t currently utilize
this process.• Most of the SKUs are only held in reserve; either full-height pallet locations, half-
height pallet locations or wire deck locations (that are approximately one quarter the height of a pallet location);
• Picking from the reserve area occurs via an order-picker truck with up to 6 orders at a time positioned on one pallet (this occasionally requires double handling the cartons).
• A small subset of the SKUs (mostly taken from A and B SKUs) are allocated a forward location, which is the bottom level of the pallet rack (locations are assigned randomly); picking from this area occurs via a pallet truck with up to 4 orders at a time.
• All picked units are transported and staged at the appropriate dock based on order-to-dock assignments and floor-loaded onto trailers (even full-pallet orders),
• Outbound cases contain, on average, 9.6 pairs of shoes (cases are not always full).
Confidential Information. Do not disclose. © Fortna 11 © Fortna
Current Process and Current Productivity Rates
Confidential Information. Do not disclose. © Fortna 12 © Fortna
Current Process - Abbreviations
• CPH – cases per hour or cartons per hour; the terms cases and cartons are used interchangeably in this problem description.
• LPN – license plate number (a unique identifier)• ASN – advance shipment notice (electronic) before arrival• BOL – bill-of-lading (contents of trailer)• OP – order picker• OB – outbound• UPH – units per hour• Q/A – quality assurance
• Note: As indicated by the flow chart, mixed-SKU pallets may be prepared in receiving, but this is just for transporting to storage. They are not stored as mixed-SKU pallets.
Confidential Information. Do not disclose. © Fortna 13 © Fortna
Data Analysis
Confidential Information. Do not disclose. © Fortna 14 © Fortna
For the Data Analysis, the following assumptions were considered:
Data Analysis – Assumptions
• The baseline period for orders was from 7/1/2014 to 6/30/2015, 249 workdays
• All the item master SKUs without dimensions were assigned a default dimension
• No outliers were removed• SKU Classifications (general description):o A = Very Fast Movero B = Fast Movero C = Medium Movero D = Slow Movero E = SKU with no activity
• Additional information on the SKUs are provided in the following file:o ACME Case Study SKUProfile Aug 23.xlsx
• The spreadsheet contains two sheets:o SKUProfile – detailed information on the SKUso Info – description of the main fields in SKUProfile
Confidential Information. Do not disclose. © Fortna 15 © Fortna
Additional Information 481 “E” SKUs are not included
above.
Data Analysis Summary
SKUs
32,702LINES
8,504,3227.5 L/O
Orders
1,134,974UNITS
26,986,21024 U/O – 3 U/L
Baseline for Period 7/1/2014 to 6/30/2015 (249 days)
Orders Lines UnitsAverage 4,558 34,154 108,378
1 Std Dev 6,373 50,354 163,2332 Std Dev 8,188 66,555 218,0873 Std Dev 10,003 82,755 272,941
Max 12,944 109,822 372,068
Daily Volumes
Confidential Information. Do not disclose. © Fortna 16 © Fortna
Velocity Analysis – SKUs, Lines and Units
A
B
C
D
8 or more lines per day on average
2 or more lines per day and less than 8 lines per day on average1 or more lines per 2 days and less than 2 lines per day on averageless than 1 line per 2 days on average
The above tables were utilized to set a “Velocity Category” for each SKU based on lines per day
A’s represent 2.8% of the SKUs and they move 51.6% of the lines and 44.7% of the units
A&B’s account for 9.6% of the SKUs and they move 77.5% of the lines and 70.3% of the units
This table excludes “E” SKUs
Breakdown Average Cumulative Cumulative Cumulative CumulativeDescription Daily Lines SKUs SKUs SKU % Line % Unit %
20 Lines / Day 20 265 265 0.8% 28.7% 25.0%8 Lines / Day 8 640 905 2.8% 51.6% 44.7%5 Lines / Day 5 578 1,483 4.5% 62.2% 54.2%2 Lines / Day 2 1,647 3,130 9.6% 77.5% 70.3%1 Line / Day 1 2,129 5,259 16.1% 86.3% 80.8%1 Line / 2 Days 0.5 2,908 8,167 25.0% 92.4% 88.2%1 Line / 5 Days 0.2 4,672 12,839 39.3% 96.8% 93.9%1 Line / 10 Days 0.1 4,078 16,917 51.7% 98.5% 96.2%1 Line / 20 Days 0.05 3,725 20,642 63.1% 99.3% 97.8%1 Line / 50 Days 0.02 4,770 25,412 77.7% 99.8% 99.3%1 Line / 100 Days 0.01 2,307 27,719 84.8% 99.9% 99.7%1 Line / Year 0.004 4,983 32,702 100.0% 100.0% 100.0%
SKU CountCumulative
SKU %Cumulative
Line %Cumulative
Unit %163 0.5% 21.5% 18.2%327 1% 32.1% 27.7%654 2% 44.9% 39.0%
1,635 5% 64.4% 56.1%3,270 10% 78.3% 71.1%4,905 15% 85.2% 79.2%6,540 20% 89.5% 84.9%8,175 25% 92.4% 88.2%9,810 30% 94.4% 90.8%
11,445 35% 95.9% 92.7%13,080 40% 96.9% 94.1%14,715 45% 97.7% 95.1%16,351 50% 98.3% 95.9%17,986 55% 98.8% 96.6%19,621 60% 99.1% 97.4%21,256 65% 99.4% 98.0%22,891 70% 99.6% 98.6%24,526 75% 99.7% 98.9%26,161 80% 99.8% 99.6%27,796 85% 99.9% 99.7%29,431 90% 99.9% 99.8%31,066 95% 100.0% 99.8%32,702 100% 100.0% 100.0%
Confidential Information. Do not disclose. © Fortna 17 © Fortna
Velocity Analysis – SKUs, Lines and Units~16.5% of SKUs have 1 day or less of activity all year
(when including E parts)
Velocity
SKU Count
%
A 905 2.7%B 2,225 6.7%C 5,037 15.2%D 24,535 73.9%E 481 1.4%
Total 33,183
Velocity
Line Count %
A 4,388,356 51.6%B 2,204,844 25.9%C 1,266,082 14.9%D 645,040 7.6%E 0 0%
Total 8,504,322
Velocity
Quantity %
A 12,070,354 44.7%B 6,909,546 25.6%C 4,830,332 17.9%D 3,175,978 11.8%E 0 0%
Total 26,986,210
A B C D8 Lines per Day 2 Lines per Day
1 Line per 2 Days Less than 1 Line per 2 Days
E No Activity
905 2,2255,037
24,535
4810
5,00010,00015,00020,00025,00030,000
A B C D E
SKU
Coun
t
Velocity Category
SKUs by Velocity Category4,388,356
2,204,844
1,266,082645,040
0 0K
1.0M
2.0M
3.0M
4.0M
5.0M
A B C D ELi
nes
Velocity Category
Lines by Velocity Category12,070,354
6,909,5464,830,332
3,175,978
0 0K
2.0M 4.0M 6.0M 8.0M
10.0M 12.0M 14.0M
A B C D E
Quan
tity
Velocity Category
Quantity Sold by Velocity Category
Confidential Information. Do not disclose. © Fortna 18 © Fortna
Velocity Analysis – SKUs, Lines and Units
Not all of the 33,183 SKUs are on hand 17,973 on-hand SKUs account for more than 7 million units
on hand
7,210,958 Units on Hand
2,398,528
1,783,8681,520,972
1,191,970
315,620
0K 500K 1.0M 1.5M 2.0M 2.5M 3.0M
A B C D E
Qty
On H
and
Velocity Category
Qty on Hand by Velocity Category
Velocity SKU Count %
A 905 2.7%B 2,225 6.7%C 5,037 15.2%D 24,535 73.9%E 481 1.4%
Total 33,183
Velocity Line Count %
A 4,388,356 51.6%B 2,204,844 25.9%C 1,266,082 14.9%D 645,040 7.6%E 0 0%
Total 8,504,322
905 2,2255,037
24,535
4810
5,00010,00015,00020,00025,00030,000
A B C D E
SKU
Coun
t
Velocity Category
SKUs by Velocity Category4,388,356
2,204,844
1,266,082645,040
0 0K
1.0M
2.0M
3.0M
4.0M
5.0M
A B C D E
Line
s
Velocity Category
Lines by Velocity Category
A
B
C
D
8 or more lines per day on average
2 or more lines per day and less than 8 lines per day on average1 or more lines per 2 days and less than 2 lines per day on averageless than 1 line per 2 days on average
Confidential Information. Do not disclose. © Fortna 19 © Fortna
Days Sold
Less than 1% of the SKUs are sold more than 200 days per year 16.8% of the SKUs are sold 1 time per year.
Days Sold SKU Count CummulativeSKU % Lines Cummulative
Lines % Units CummulativeUnits %
>225 39 0.1% 491,584 5.8% 1,404,376 5.2%>200 232 0.7% 1,846,056 21.7% 4,780,080 17.7%>150 776 2.4% 3,082,080 36.2% 8,385,626 31.1%>125 1,226 3.7% 3,775,800 44.4% 10,542,102 39.1%>100 1,988 6.1% 4,809,512 56.6% 13,677,328 50.7%>75 3,294 10.1% 5,833,276 68.6% 17,046,956 63.2%>50 5,464 16.7% 6,767,086 79.6% 20,137,098 74.6%>30 8,367 25.6% 7,444,782 87.5% 22,597,376 83.7%>20 10,984 33.6% 7,829,804 92.1% 23,956,146 88.8%>10 15,829 48.4% 8,202,846 96.5% 25,383,814 94.1%>5 20,356 62.2% 8,357,078 98.3% 26,152,738 96.9%>3 22,853 69.9% 8,415,918 99.0% 26,383,306 97.8%>1 27,207 83.2% 8,487,500 99.8% 26,774,996 99.2%>0 32,702 100.0% 8,504,322 100.0% 26,986,210 100.0%
Confidential Information. Do not disclose. © Fortna 20 © Fortna
Outbound Behavior – Orders
Daily orders ramp up before Christmas and then through spring and early summer
1,134,974 Total Orders
Total Avg Daily Orders 4,5581 Standard Deviation 6,3732 Standard Deviation 8,1883 Standard Deviation 10,003
Maximum Daily Orders 12,944
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
7/1/
2014
7/15
/201
47/
29/2
014
8/12
/201
48/
26/2
014
9/9/
2014
9/23
/201
410
/7/2
014
10/2
1/20
1411
/4/2
014
11/1
8/20
1412
/2/2
014
12/1
6/20
1412
/30/
2014
1/13
/201
51/
27/2
015
2/10
/201
52/
24/2
015
3/10
/201
53/
24/2
015
4/7/
2015
4/21
/201
55/
5/20
155/
19/2
015
6/2/
2015
6/16
/201
56/
30/2
015
Orde
rs
Order Date
Daily Orders
Average 1 Std Dev 2 Std Dev 3 Std Dev
4,35
2
4,08
0
4,60
4
4,40
9
5,32
3
0
1,000
2,000
3,000
4,000
5,000
6,000
Monday Tuesday Wednesday Thursday Friday
Aver
age
Orde
rs p
er D
ay
Day of Week
Average Orders by Day of Week
Confidential Information. Do not disclose. © Fortna 21 © Fortna
Outbound Behavior – Lines
Daily lines shift up before Christmas and stay high until early summer
8,504,322 Total Lines
Total Avg Daily Lines 34,1541 Standard Deviation 50,3542 Standard Deviation 66,5553 Standard Deviation 82,755Maximum Daily Lines 109,822
0
20,000
40,000
60,000
80,000
100,000
120,000
7/1/
2014
7/15
/201
47/
29/2
014
8/12
/201
48/
26/2
014
9/9/
2014
9/23
/201
410
/7/2
014
10/2
1/20
1411
/4/2
014
11/1
8/20
1412
/2/2
014
12/1
6/20
1412
/30/
2014
1/13
/201
51/
27/2
015
2/10
/201
52/
24/2
015
3/10
/201
53/
24/2
015
4/7/
2015
4/21
/201
55/
5/20
155/
19/2
015
6/2/
2015
6/16
/201
56/
30/2
015
Line
s
Order Date
Daily Lines
Average 1 Std Dev 2 Std Dev 3 Std Dev
34,7
26
28,4
14
34,3
78
32,6
54 40,3
12
05,000
10,00015,00020,00025,00030,00035,00040,00045,000
Monday Tuesday Wednesday Thursday Friday
Aver
age
Line
s pe
r Day
Day of Week
Average Lines by Day of Week
Confidential Information. Do not disclose. © Fortna 22 © Fortna
Outbound Behavior – Units
Daily units align with orders and lines
26,986,210 Total Units
Total Avg Daily Units 108,3781 Standard Deviation 163,2332 Standard Deviation 218,0873 Standard Deviation 272,941Maximum Daily Units 372,068
0K 50K
100K
150K 200K 250K 300K 350K 400K
7/1/
2014
7/15
/201
47/
29/2
014
8/12
/201
48/
26/2
014
9/9/
2014
9/23
/201
410
/7/2
014
10/2
1/20
1411
/4/2
014
11/1
8/20
1412
/2/2
014
12/1
6/20
1412
/30/
2014
1/13
/201
51/
27/2
015
2/10
/201
52/
24/2
015
3/10
/201
53/
24/2
015
4/7/
2015
4/21
/201
55/
5/20
155/
19/2
015
6/2/
2015
6/16
/201
56/
30/2
015
Units
Order Date
Daily Units
Average 1 Std Dev 2 Std Dev 3 Std Dev
122,
738
91,6
11
102,
032
104,
270
120,
399
0K
20K
40K
60K
80K
100K
120K
140K
Monday Tuesday Wednesday Thursday Friday
Aver
age
Units
per
Day
Day of Week
Average Units by Day of Week
Confidential Information. Do not disclose. © Fortna 23 © Fortna
Order Composition by SKU Velocity
A relatively large fraction (66.9%) of orders can be completed with only A and/or B SKUs
1,134,974 Total Orders
37.5
%
16.0
%
4.7
%
1.8
%
0.4
%
1.3
%
0.2
%
0.3
%
13.4
%
4.2
%
1.4
%
0.3
%
9.2
%
2.3
% 6.8
%
0 %5 %
10 %15 %20 %25 %30 %35 %40 %
Perc
enta
ge o
f Tot
al O
rder
s
Velocity Combinations
Velocity AnalysisPercentange of Orders by Velocity Combinations
Confidential Information. Do not disclose. © Fortna 24 © Fortna
Order Composition by Distinct SKUs
On average there are approximately 3,400 distinct SKUs shipped per day. On a monthly basis, there are approximately 13,000 distinct SKUs shipped.
Average Distinct SKUs per Day 3,4281 Standard Deviation 4,354
01,0002,0003,0004,0005,0006,0007,0008,0009,000
10,000
7/1/
2014
7/15
/201
47/
29/2
014
8/12
/201
48/
26/2
014
9/9/
2014
9/23
/201
410
/7/2
014
10/2
1/20
1411
/4/2
014
11/1
8/20
1412
/2/2
014
12/1
6/20
1412
/30/
2014
1/13
/201
51/
27/2
015
2/10
/201
52/
24/2
015
3/10
/201
53/
24/2
015
4/7/
2015
4/21
/201
55/
5/20
155/
19/2
015
6/2/
2015
6/16
/201
56/
30/2
015
# o
f Dis
tinct
SKU
s
Order Date
Count of Distinct SKUs per Day
Average 1 Std Dev
02,0004,0006,0008,000
10,00012,00014,00016,000
7/1/
2014
7/22
/201
48/
12/2
014
9/2/
2014
9/23
/201
410
/14/
2014
11/4
/201
411
/25/
2014
12/1
6/20
141/
6/20
151/
27/2
015
2/17
/201
53/
10/2
015
3/31
/201
54/
21/2
015
5/12
/201
56/
2/20
15
# o
f Dis
tinct
SKU
s
Order Date
Count of Distinct SKUs per Week
02,0004,0006,0008,000
10,00012,00014,00016,000
# o
f Dis
tinct
SKU
s
Order Date
Count of Distinct SKUs per Month
Confidential Information. Do not disclose. © Fortna 25 © Fortna
Order Profiles – SKUs
On average there are approximately 10 lines per SKU per day. On average, there are approximately 32 units per SKU per day
VelocityTotal SKUs
A 905 519 661 17,623 28,471 48,475 77,446B 2,225 864 1,036 8,854 13,563 27,749 42,716C 5,037 1,085 1,398 5,084 7,767 19,398 32,730D 24,535 959 1,521 2,590 4,181 12,754 24,020
Daily Outbound Volumes by Velocity Category
Daily Outbound VolumeSKUs
Avg 1 Std DevLines
Avg 1 Std DevUnits
Avg 1 Std Dev
Confidential Information. Do not disclose. © Fortna 26 © Fortna
Outbound Order Profile – Lines per Order
Total Average Lines per Order 7.51 Standard Deviation 9.3
02468
10121416
7/1/
2014
7/22
/201
48/
12/2
014
9/2/
2014
9/23
/201
410
/14/
2014
11/4
/201
411
/25/
2014
12/1
6/20
141/
6/20
151/
27/2
015
2/17
/201
53/
10/2
015
3/31
/201
54/
21/2
015
5/12
/201
56/
2/20
156/
23/2
015
Aver
age
Line
s pe
r Ord
er
Order Date
Average Lines Per Order
Average 1 Std Dev
31%
10%
18%
24%
11%
4%2%
0.00.51.01.52.02.53.03.54.04.5
0%
5%
10%
15%
20%
25%
30%
35%
1 2 3-5 6-10 11-20 21-50 > 50
Average Qty per Line % o
f Tot
al O
rder
s
Lines per Order
Lines Per Order
Average qty per line
Confidential Information. Do not disclose. © Fortna 27 © Fortna
Outbound Order Profile – Units per Line
Total Average Units per Line 3.21 Standard Deviation 4.5
0123456789
10
7/1/
2014
7/22
/201
48/
12/2
014
9/2/
2014
9/23
/201
410
/14/
2014
11/4
/201
411
/25/
2014
12/1
6/20
141/
6/20
151/
27/2
015
2/17
/201
53/
10/2
015
3/31
/201
54/
21/2
015
5/12
/201
56/
2/20
156/
23/2
015
Aver
age
Units
per
Lin
e
Order Date
Average Units Per Line
Average 1 Std Dev
60.7%
22.7%
10.1%2.7% 1.8% 1.3% 0.7%
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3-5 6-10 11-20 21-50 > 50
% o
f Lin
es
Units per Line
Units Per Line
Confidential Information. Do not disclose. © Fortna 28 © Fortna
Outbound Order Profile – Units per Order
Total Average Units per Order 241 Standard Deviation 34
01020304050607080
7/1/
2014
7/22
/201
48/
12/2
014
9/2/
2014
9/23
/201
410
/14/
2014
11/4
/201
411
/25/
2014
12/1
6/20
141/
6/20
151/
27/2
015
2/17
/201
53/
10/2
015
3/31
/201
54/
21/2
015
5/12
/201
56/
2/20
156/
23/2
015
Aver
age
Units
per
Ord
er
Order Date
Average Units Per Order
Average 1 Std Dev
27.9%25.6%
13.6%
17.8%
9.2%
2.6% 1.8% 1.5%0%
5%
10%
15%
20%
25%
30%
1 2-5 6-10 11-20 21-50 51-100 101-250 > 250
% o
f Ord
ers
Units per Order
Units Per Order
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Outbound Order Profile – One Line Orders
30.5% of the orders are one line orders, with 91.3% of those having only 1 unit
Total Avg. Daily One Line Orders 1,391Percent of Total Orders 31%
Velocity Category # of SKUs SKU % 1 Line Orders Order %A 898 6.1% 121,740 35.1%B 2,041 13.8% 82,792 23.9%C 4,003 27.1% 77,528 22.4%D 7,813 53.0% 64,290 18.6%
14,755 100.0% 346,350 100.0%
Velocity Category Units Unit % 1 Unit Orders 1 Unit Order %A 148,472 36.4% 104,470 33.0%B 100,258 24.6% 76,494 24.2%C 89,890 22.0% 73,384 23.2%D 69,332 17.0% 61,866 19.6%
407,952 100.0% 316,214 100.0%
One Line Orders Analysis
0
500
1,000
1,500
2,000
2,500
3,000
7/1/
2014
7/22
/201
48/
12/2
014
9/2/
2014
9/23
/201
410
/14/
2014
11/4
/201
411
/25/
2014
12/1
6/20
141/
6/20
151/
27/2
015
2/17
/201
53/
10/2
015
3/31
/201
54/
21/2
015
5/12
/201
56/
2/20
156/
23/2
015
Aver
age
One
Line
Ord
ers
Order Date
Average One Line Orders
Average
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Seasonality – A’s and B’s SKUs
The charts capture the number of months that “A” and “B” SKUs behave as an average “A” or “B” SKU A very small number of SKUs (less than 30) behave as an “A” SKU for all 12 months Approximately 350 of the “B” SKUs never behaved like a “B” SKU in a single month
Total A SKUs: 905 Total B SKUs: 2,225
020406080
100120140160180
2 3 4 5 6 7 8 9 10 11 12
# o
f SKU
s
Number of MonthsCount of SKUs where its monthly velocity equaled its overall velocity
Seasonality 'A' Velocity SKUs
0100200300400500600700800900
1,000
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
# o
f "A"
SKU
s
Month
Seasonality 'A' SKU Velocity Dynamics
EDCBA
050
100150200250300350400
0 1 2 3 4 5 6 7 8 9 10 11 12
# o
f SKU
s
Number of MonthsCount of SKUs where its monthly velocity equaled its overall velocity
Seasonality 'B' Velocity SKUs
0
500
1,000
1,500
2,000
2,500
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN#
of "
B" S
KUs
Month
Seasonality 'B' SKU Velocity Dynamics
EDCBA
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Seasonality – C’s and D’s SKUs
Most “C” and “D” SKUs are active over a low number of months
Total C SKUs: 5,037 Total D SKUs: 24,535
0100200300400500600700800900
0 1 2 3 4 5 6 7 8 9 10 11 12
# o
f SKU
s
Number of MonthsCount of SKUs where its monthly velocity equaled its overall velocity
Seasonality 'C' Velocity SKUs
0
1,000
2,000
3,000
4,000
5,000
6,000
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
# o
f "C"
SKU
s
Month
Seasonality 'C' SKU Velocity Dynamics
EDCBA
01,0002,0003,0004,0005,0006,0007,0008,000
0 1 2 3 4 5 6 7 8 9 10 11 12
# o
f SKU
s
Number of MonthsCount of SKUs where its monthly velocity equaled its overall velocity
Seasonality 'D' Velocity SKUs
0
5,000
10,000
15,000
20,000
25,000
30,000
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
# o
f "D"
SKU
s
Month
Seasonality 'D' SKU Velocity Dynamics
EDCBA
Confidential Information. Do not disclose. © Fortna 32 © Fortna
Subline Analysis – Analyzing the Type of Picks
Although approximately half of the units sold are sold as an each, the each unit of measure has a disproportionate percentage of the orders and lines (due to 12 units per case and 16 cases per pallet)
E - Eaches C- Cartons P - Pallets
units sold in cartons
units sold in pallets
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Average Days On-Hand Inventory by Velocity
“A” SKUs have approximately 2.8 months on average of on-hand inventory “D” SKUs have approximately 48 months on average of on-hand inventory!
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Labor Model
Confidential Information. Do not disclose. © Fortna 35 © Fortna
Labor Model Assumptions
Premises
35CONFIDENTIAL – Information contained in this document is confidential and thus protected from disclosure.
-
Longer shifts and weekends will continue to be used to handle above-average, “peak” demand
(in addition to 242.7)
Hours
Effective Hours per Shift at Average
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Future State Requirements
Confidential Information. Do not disclose. © Fortna 37 © Fortna
Future State Requirements
Premises• SKUs will grow at an average annualized rate of
2% for 2016 and the 5-year planning horizon• SKU growth will remain the same across all SKUs
handled by operation
SKU growth impacts sizing of the forward pick area from a pick facings perspective
SKU Growth
Confidential Information. Do not disclose. © Fortna 38 © Fortna
Future State Requirements
Premises• Orders will grow at an average annualized rate of 7% for 2016 and the 5-year
planning horizon• Orders growth will remain the same across all SKUs handled• Ratio of 8-Hour Design day to Average day = 1.8 (i.e., Design day is 1.8x
Average day)• Ratio of Max day to Average day = 3.2 (i.e., Max day is 3.2x Average day)
Orders growth impacts sizing and output requirements for packing and shipping
Order Growth
Note: An average day represents an average level of performance, whereas a design day represents the performance level for which the new facility will be designed.
Confidential Information. Do not disclose. © Fortna 39 © Fortna
Future State Requirements
Premises• Lines will grow at an average annualized rate of
7% for 2016 and the 5-year planning horizon• Lines growth will remain the same across all
customer orders• Average lines per order ~7.5• Ratio of 8-Hour Design day to Average day =
1.96• Ratio of Max day to Average day = 2.9Lines growth impacts picking throughput and equipment machine rates
Lines Growth
Confidential Information. Do not disclose. © Fortna 40 © Fortna
Future State Requirements
Units Growth
Premises• Units will grow at an average annualized rate of
7% for 2016 and the 5-year planning horizon• Units growth will remain the same across all
customer orders• Ratio of 8-Hour Design day to Average day = 2.02• Ratio of Max day to Average day = 3.4
Unit growth impacts forward and reserve media sizing and equipment selection
Confidential Information. Do not disclose. © Fortna 41 © Fortna
Future State Requirements
Inventory Growth
Premises• Inventory will grow at an average annualized
rate of 7% for 2016 and the 5-year planning horizon
• Impact on on-hand inventory will remain the same across all SKUs
• Current average inventory turns of 3.7, inclusive of all SKUs, will remain the same throughout the planning horizon
Inventory growth impacts reserve media sizing and equipment selection
Confidential Information. Do not disclose. © Fortna 42 © Fortna
Future State Requirements SummaryCurrent state summary for ACME Footwear and future state projection needs
8,204.666,941.6
218,924.4
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Expected Deliverables
• Evaluation of Scenarios:o Baseline scenario – current operations projected forwardo Recommended design – recommended operations design
projected forward• Describe main benefits that the proposed solution provides
compared to the current operations.• Describe the investments and impacts of implementing the
solution.o For the analysis, assume none of the current equipment can
be salvaged.o Include estimated staffing required to support the distribution
functions.• Include the quantitative financial aspects that are considered in
the business case.
Confidential Information. Do not disclose. © Fortna 44 © Fortna
Expected Deliverables• When preparing the deliverables, please refer to the following documents:
2015-2016_Judging_sheet.pdf2015-2016_Rules_Procedures.pdf
• In addition, the following resource may be helpful for cost analyses:o http://www.werc.org/assets/1/Publications/TranSystems Rules of Thumb
2010 v2.pdf• Ensure the following items are addressed: o Fundamental design philosophy, assumptions, and calculations behind
the proposed design,o Product flow description along with design layout drawing that
illustrates the proposed general layout of the building and equipment,o Equipment selection and space utilization,o Operational plan,o Implementation plan,o Economic justification, ando Integration plan.
Confidential Information. Do not disclose. © Fortna 45 © Fortna> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN
SYSTEMS> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN SYSTEMS> SUPPLY CHAIN STRATEGY > DISTRIBUTION CENTER OPERATIONS > ORGANIZATIONAL EXCELLENCE > MATERIAL HANDLING > SUPPLY CHAIN SYSTEMS
Case Study Information
ACME Footwear Operations Design
August 23, 2015