Industrial Data Analysis LLC-Data Study-01

Nuts, Bolts, Fasteners, Etc.

Daily Items Sales Report: • Posting Date • Order Date • Order No. • Invoice No. • SKU/Item No. • Kit Item • Qty Ordered • Qty Invoiced Summary of Data Received: • Date Range: May 1, 2012 to Sept 30, 2012 • Orders Picked: 13,053 • Lines Picked: 14,644 • Qty Picked: 3,412,151 • *SKU’s: 9,762

Data Received / Analyzed

September Sales / Partmaster: • Date Range: Sept. 1, 2012 to Sept 30, 2012 • Item Number • Description • Quantity Sold • Quantity on Hand • Master Carton • Inner Carton • Kit Item • Length • Width • Height • Weight • **SKUs on Hand 18,480

NOTE: *SKU’s represents active SKU’s during time period **SKU’s in inventory Approximately 50% of SKU’s are inactive or obsolete

2

Data: 1st Sigma not Mean (average)

Why use the 1st Sigma, (1st Std Dev beyond the Mean (average)

• The average does not take into consideration the variance of the points on a graph or in the data.

• If one designs a system based upon the average, the system will be undersized and unable to compensate for peak days.

• By using the 1st Sigma (s), the variance of the data is considered, (mean + s) = .50 + .3413 = .8413 or 84.13% of all the points of data.

• On days when activity is above the 84.13% of data points, one can use overtime to compensate for the higher activity

3


Data Analysis

4

85.3%

92.3%95.4%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0

15,000

30,000

45,000

60,000

75,000

90,000

105,000

120,000

135,000

150,000

1 938 1875 2812 3749 4686 5623 6560 7497 8434

Cu

m %

Qu

anty

Pic

ked

pe

r SK

U

SKU Sequence in order of Activity

SKU Activity-Qty InvoicedMay 2012-Sep 2012

Qty Invoiced Cum % of Activity

10% 20% 30% 40% 50% 60% 70% 80% 90%

Sequence of

Activity

SKU / Item

Number

Name Qty

Invoiced

% of

Activity

Cum % of

Activity

1 10048 CHROME 33mm X 2 3/8" POINTED 140,590 4.4% 4.4%

2 10059B (EACH) CHROME PLASTIC 110,819 3.5% 7.9%

3 10031 CR 33mm STANDARD LUG NUT COVER 100,183 3.1% 11.1%

4 10700 CHROME 33MM NIPPLE LUG NUT 84,181 2.6% 13.7%

5 10007B CR PL 33mm X 4 1/8" 80,100 2.5% 16.2%

6 10005 33mm CR BULLET NUT COVER W/ 79,233 2.5% 18.7%

7 31505 2" FLUSH MOUNT GROMMET ONLY 69,069 2.2% 20.9%

8 10004 CR 1.5" X 2" BULLET NUT COVER 57,460 1.8% 22.7%

9 10117B CHROME PLASTIC 33mm X 3 3/16" 48,921 1.5% 24.2%


10% of SKUs represent 85.3% of Activity

5

Sequence of

Activity

SKU / Item

Number

Name Qty

Invoiced

% of

Activity

Cum % of

Activity

1 10048 CHROME 33mm X 2 3/8" POINTED 140,590 4.4% 4.4%

2 10059B (EACH) CHROME PLASTIC 110,819 3.5% 7.9%

3 10031 CR 33mm STANDARD LUG NUT COVER 100,183 3.1% 11.1%

4 10700 CHROME 33MM NIPPLE LUG NUT 84,181 2.6% 13.7%

5 10007B CR PL 33mm X 4 1/8" 80,100 2.5% 16.2%

6 10005 33mm CR BULLET NUT COVER W/ 79,233 2.5% 18.7%

7 31505 2" FLUSH MOUNT GROMMET ONLY 69,069 2.2% 20.9%

8 10004 CR 1.5" X 2" BULLET NUT COVER 57,460 1.8% 22.7%



6

Average = 1,718

1st Sigma = 2005

0

500

1,000

1,500

2,000

2,500

3,0004

/30

/201

2

5/7

/20

12

5/1

4/2

012

5/2

1/2

012

5/2

8/2

012

6/4

/20

12

6/1

1/2

012

6/1

8/2

012

6/2

5/2

012

7/2

/20

12

7/9

/20

12

7/1

6/2

012

7/2

3/2

012

7/3

0/2

012

8/6

/20

12

8/1

3/2

012

8/2

0/2

012

8/2

7/2

012

9/3

/20

12

9/1

0/2

012

9/1

7/2

012

9/2

4/2

012

Lin

es

Pic

ked

/ D

ayLines Picked / Day

May 2012-Sep 2012

Lines Picked / Day Average 1st Sigma

7

Average = 29,136

1st Sigma = 52,551

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

5/1

/20

12

5/8

/20

12

5/1

5/2

012

5/2

2/2

012

5/2

9/2

012

6/5

/20

12

6/1

2/2

012

6/1

9/2

012

6/2

6/2

012

7/3

/20

12

7/1

0/2

012

7/1

7/2

012

7/2

4/2

012

7/3

1/2

012

8/7

/20

12

8/1

4/2

012

8/2

1/2

012

8/2

8/2

012

9/4

/20

12

9/1

1/2

012

9/1

8/2

012

9/2

5/2

012

Qu

anti

ty In

voic

ed

pe

r D

ayQuantity Invoiced Per Day

May 2012-Sep 2012

Qty Invoiced Average Qty Invoiced 1st Sigma of Qty Invoiced 10 per. Mov. Avg. (Qty Invoiced)

8

Average = 137

1st Sigma = 158

0

50

100

150

200

2505

/1/2

012

5/8

/20

12

5/1

5/2

012

5/2

2/2

012

5/2

9/2

012

6/5

/20

12

6/1

2/2

012

6/1

9/2

012

6/2

6/2

012

7/3

/20

12

7/1

0/2

012

7/1

7/2

012

7/2

4/2

012

7/3

1/2

012

8/7

/20

12

8/1

4/2

012

8/2

1/2

012

8/2

8/2

012

9/4

/20

12

9/1

1/2

012

9/1

8/2

012

9/2

5/2

012

Invo

ice

s P

er

DayInvoices Per Day

May 2012-Sep 2012

Number of Invoices Average Invoices / Day 1st Sigma of Invoices / Day 10 per. Mov. Avg. (Number of Invoices)

9

Average = 47.4

1st Sigma = 60.3

0

10

20

30

40

50

60

70

80

90

1004

/30

/201

2

5/7

/20

12

5/1

4/2

012

5/2

1/2

012

5/2

8/2

012

6/4

/20

12

6/1

1/2

012

6/1

8/2

012

6/2

5/2

012

7/2

/20

12

7/9

/20

12

7/1

6/2

012

7/2

3/2

012

7/3

0/2

012

8/6

/20

12

8/1

3/2

012

8/2

0/2

012

8/2

7/2

012

9/3

/20

12

9/1

0/2

012

9/1

7/2

012

9/2

4/2

012

1-L

ine

Ord

ers

/ D

ay1-Line Orders / Day

May 2012-Sep 2012

Number of 1 Line Orders Average 1 Line Orders 1st Sigma of 1 Line Orders

11

Average = 19.0

1st Sigma = 25.4

0

10

20

30

40

50

60

70

80

90

1004

/30

/201

2

5/7

/20

12

5/1

4/2

012

5/2

1/2

012

5/2

8/2

012

6/4

/20

12

6/1

1/2

012

6/1

8/2

012

6/2

5/2

012

7/2

/20

12

7/9

/20

12

7/1

6/2

012

7/2

3/2

012

7/3

0/2

012

8/6

/20

12

8/1

3/2

012

8/2

0/2

012

8/2

7/2

012

9/3

/20

12

9/1

0/2

012

9/1

7/2

012

9/2

4/2

012

2-L

ine

Ord

ers

/ D


May 2012-Sep 2012


12

Average = 10.01st Sigma = 13.7

0

10

20

30

40

50

60

70

80

90

1004

/30

/201

2

5/7

/20

12

5/1

4/2

012

5/2

1/2

012

5/2

8/2

012

6/4

/20

12

6/1

1/2

012

6/1

8/2

012

6/2

5/2

012

7/2

/20

12

7/9

/20

12

7/1

6/2

012

7/2

3/2

012

7/3

0/2

012

8/6

/20

12

8/1

3/2

012

8/2

0/2

012

8/2

7/2

012

9/3

/20

12

9/1

0/2

012

9/1

7/2

012

9/2

4/2

012

3-L

ine

Ord

ers

/ D


May 2012-Sep 2012


13

Average = 89.3

1st Sigma = 102.7

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

1504

/30

/201

2

5/7

/20

12

5/1

4/2

012

5/2

1/2

012

5/2

8/2

012

6/4

/20

12

6/1

1/2

012

6/1

8/2

012

6/2

5/2

012

7/2

/20

12

7/9

/20

12

7/1

6/2

012

7/2

3/2

012

7/3

0/2

012

8/6

/20

12

8/1

3/2

012

8/2

0/2

012

8/2

7/2

012

9/3

/20

12

9/1

0/2

012

9/1

7/2

012

9/2

4/2

012

>3-L

ine

Ord

ers

/ D

ay>3-Line Orders / Day

May 2012-Sep 2012

Number of > 3 Line Orders Average >3 Line Orders 1st Sigma of >3 Line Orders

14

5,020

2,016

1,055

0

1,000

2,000

3,000

4,000

5,000

6,0001

10

19

28

37

46

55

64

73

82

91

10

0

10

9

11

8

12

7

13

6

14

5

15

4

16

3

17

2

18

1

19

0

19

9

20

8

21

7

22

6

23

5

24

4

25

3

26

2

27

1

28

0

28

9

29

8

30

7

31

6

32

5

33

4

34

3

35

2

36

1

37

0

37

9

38

8

39

7

40

6

41

5

42

4

43

3

44

2

45

1

46

0

46

9

47

8

48

7

49

6

Ord

ers

Pro

cess

edLines Per Order

Standard Scale

Lines per Order

15

Lines Per

Order

Number of

Orders

1 5,020

2 2,016

3 1,055

4 671

5 491

6 364

7 317

8 297

9 261

10 235

5,020

2,016

1,055

1

10

100

1,000

10,000

1

12

23

34

45

56

67

78

89

10

0

11

1

12

2

13

3

14

4

15

5

16

6

17

7

18

8

19

9

21

0

22

1

23

2

24

3

25

4

26

5

27

6

28

7

29

8

30

9

32

0

33

1

34

2

35

3

36

4

37

5

38

6

39

7

40

8

41

9

43

0

44

1

45

2

46

3

47

4

48

5

49

6

Ord

ers

Pro

cess

ed

Lines Per OrderLogrithimic Scale

Lines per Order

16

Lines Per

Order

Number of

Orders

1 5,020

2 2,016

3 1,055

4 671

5 491

6 364

7 317

8 297

9 261

10 235

Average = 563

Average = 5,428

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,0005

/1/2

012

5/8

/20

12

5/1

5/2

012

5/2

2/2

012

5/2

9/2

012

6/5

/20

12

6/1

2/2

012

6/1

9/2

012

6/2

6/2

012

7/3

/20

12

7/1

0/2

012

7/1

7/2

012

7/2

4/2

012

7/3

1/2

012

8/7

/20

12

8/1

4/2

012

8/2

1/2

012

8/2

8/2

012

9/4

/20

12

9/1

1/2

012

9/1

8/2

012

9/2

5/2

012

Mas

ter

& I

nn

er

Car

ton

s /

Day

Master & Inner Cartons /DayMay 2012-Sep 2012

Master Cartons Sold Average Master Cartons Sold Inner Cartons Sold Average Inner Cartons Sold

17


Data Summary

18

The data listed both Order Date and Posted Date. Only 10% of the orders were posted the same day. The date used for the Data Analysis is the Posted Date. Time Frame:

• Date Range: May 2012 – Sep 2012 • Number of Weeks: 22 weeks • Number of Days: 106 days (does not include Sat or Sun)

Data:

• Total Quantity Invoiced: 3,08,379 items • SKUs Invoiced: 182,097 • Total Invoices: 14,449 • Total Orders: 12,937 • Invoices/Order: 1.121 • SKU/Invoice: 12.56 • SKUs/Order: 14.08 • Active SKUs: 9,368 • Average Picks / SKU: 19 • Std Dev Picks / SKU: 37 • 1st Sigma Picks / SKU: 56 • SKUs on Hand 18,480

Data Summary

19

Orders: • Total: 12,937 • Average Orders/ Day: 122 • 1st Sigma: 147

Invoices:

• Total: 14,499 • Average Invoices/ Day: 136.8 • 1st Sigma: 158

Qty Invoiced / Day:

• Average: 29,136 • 1st Sigma: 56,551

Picks Invoiced / Day: • Average: 1,718 • 1st Sigma: 2,005

Data Summary (continued)

20

Orders / Day: • Average Orders /Day: 165.7 • 1st Sigma: 202.0

1-Line Orders / Day: • Average 1-Line Orders /Day: 47.4 • 1st Sigma: 60.3



>3-Line Orders / Day: • Average >3-Line Orders /Day: 89.3 • 1st Sigma: 102.7

Master Cartons: • Total: 59,721 • Average Cartons/ Day: 563 • 1st Sigma: 728

Inner Cartons: • Total: 575,336 • Average Cartons/ Day: 5,428 • 1st Sigma: 7,700

Data Summary (continued)

21

Storage Medium for Quantity Picked

PALLET FLOW: This storage medium is for very high active products, allowing the picker to pick complete cases and partial case picks. For this analysis it is used for items where 2 or more cases are picked per day.

CASE FLOW: This storage medium allows the picker to pick individual items or full cases if required. This medium can pick items very quickly. For this analysis, any item that is picked at least once every 2 day should be placed in this medium.

SHELF PICK: This storage medium is for slow to “dead” items. In this analysis, any item that is picked less that 1 pick every 2 days is located in this medium.

22


AUTOMATED STORAGE & RETREIVAL SYSTEMS (AS/RS): This storage medium is for slow items. AS/RS systems are used when floor space is at a premium or the foot print of the building is very small, and going vertical makes sense. In this analysis, any item that is picked less that 1 pick every 2 days is located in this medium.

23

85.3%

92.3%95.4%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0

15,000

30,000

45,000

60,000

75,000

90,000

105,000

120,000

135,000

150,000

1 938 1875 2812 3749 4686 5623 6560 7497 8434

Cu

m %

Qu

anty

Pic

ked

pe

r SK

U

SKU Sequence in order of Activity

SKU Activity-Qty InvoicedMay 2012-Sep 2012

Qty Invoiced Cum % of Activity

10% 20% 30% 40% 50% 60% 70% 80% 90%

19% of Quantity Picked 3,865 SKUs

Storage Medium Shelf Pick or ASRS

68% of Quantity Picked 800 SKUs

Storage Medium Case Flow

10% of Quantity Picked 38 SKUs

Storage Medium Pallet Flow

3% of Quantity Picked 4,665 SKUs

Shelf pick or Static Pallet Rack


24

Estimated Manpower Required for Picking

25

Case Pick from

Pallet Flow

Item Pick from

Flow Rack

Item Pick from

Shelf Pick

Item Pick

from ASRS

Raw

Manpower

Work

Efficiency

Manpower

Total Picks 3,335 89,316 89,446 89,446

Days Picking 106 106 106 106

Available Hours / Day 7.5 7.5 7.5 7.5

Picks / Hour 4.19 112.35 112.51 112.51

Estimated Picks/Associate 90 240 15 120

Manpower / Storage Medium 0.05 0.47 7.50 0.94

Manpower w/o ASRS 0.05 0.47 7.50 8.02 0.80 10

Manpower /w ASRS 0.05 0.47 0.94 1.45 0.80 2

• The pick activity that is illustrated on each chart denotes the average and the 1st Sigma of each analysis. The 1st Sigma of activity is used to compensate for peaks in the data instead of using the average.

• The data that assigns the storage medium that each SKU is assigned, is on a spreadsheet. The spreadsheet is available to identify what storage/pick medium is to be used for each SKU. This allocation is based upon the activity of each SKU.

• It is my recommendation to build a system that can handle the following: • 2,005 lines per day (add anticipated growth) • 158 invoices per day (add anticipated growth) • 147 orders per day (add anticipated growth) • Replenishment of 728 carton /cases per day (add anticipated growth) • Locations in Storage/Pick Medium

• 40 locations for pick from pallet • 800 location for pick from flow rack • 8,500 locations for slow items to be picked from shelf pick • 9,200 locations for items on hand that have had no activity during the

period analyzed. • These locations need to be dynamic, to accommodate the change in

the activity of the SKUs over time. • With the large number of SKUs that have had no activity, there is no

need to add any additional locations to the shelving. The number of SKUs on hand should change very little over the next 5 years.

Summary

26

Industrial Data Analysis LLC-Data Study-01

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Transcript of Industrial Data Analysis LLC-Data Study-01