acme case study description jan 2016

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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


Project Overview (from Our Company)


• 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


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


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:


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.


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.


Current Process


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).


Current Process and Current Productivity Rates


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.


Data Analysis


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


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


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%


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


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


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%


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


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


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


Aver

age

Line

s pe

r Day

Day of Week

Average Lines by Day of Week


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


122,

738

91,6

11

102,

032

104,

270

120,

399

0K

20K

40K

60K

80K

100K

120K

140K


Aver

age

Units

per

Day

Day of Week

Average Units by Day of Week


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


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


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


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


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


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


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


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


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


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


Seasonality 'C' Velocity SKUs

0

1,000

2,000

3,000

4,000

5,000

6,000


# 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


Seasonality 'D' Velocity SKUs

0

5,000

10,000

15,000

20,000

25,000

30,000


# o

f "D"

SKU

s

Month

Seasonality 'D' SKU Velocity Dynamics

EDCBA


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


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!


Labor Model


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


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



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.



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



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



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


Future State Requirements SummaryCurrent state summary for ACME Footwear and future state projection needs

8,204.666,941.6

218,924.4


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.


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

acme case study description jan 2016

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