What is Activity Profiling?
Warehouse Activity Profiling
is the analysis of historical
sales transaction data for the
purposes of projecting
warehouse activity and
determining storage mode,
physical layout, work flow
processes, and labor and
equipment requirements.
Data
INV.
MASTER
Inventory Snapshots
Average Inventory
Levels
ORDER
MASTER
ITEM
MASTER
Order Header
Order Detail
SKU Number
Description
Item Cube
Pieces Per Case
Cases Per Pallet
Division
Product Group
Item Weight
Item Ordered
Qty
Unit of Measure
2
Developing Profiling Reports & Graphs
STEP #1:
CONSOLIDATE
&
CALCULATE
STEP #2:
ANALYZE (Sort / Rank)
&
PRESENT
Inventory
Master
Order Data
Data
Item
Master
Data
R ank
1
2
3
4
Item
355
138S A
353
S W 95A
N um ber
T otal
O f O rder Q uantity
Lines
O rdered
1895
1820
1734
1669
8971
7238
6630
5266
% Of
T otal
V olum e
0.5742%
0.4633%
0.4244%
0.3371%
C um ulativ # P ick D aily P ick
e V olum e D ays F requency
0.574%
1.038%
1.462%
1.799%
57
57
57
57
33.25
31.93
30.42
29.28
3
Storage Driven
Picking Driven
How Do You Design a
Warehouse?
• Two Ways To Design
a Warehouse
– Storage Driven Approach
via Cube Analysis
– Picking Driven Approach
via Order Analysis
What is the Storage Driven
Approach to Design?
• PART I:
Define Your Storage Zones
• PART II: Design Your Forward
Pick Areas
• PART III: Define How You Will Plan &
Pick Orders
Designing a Warehouse
Part I
Define Your
Storage
Zones
Categorize Items By Cubic Ft of Inventory
Calculate the cubic feet of storage
that each item requires and then
assign it to an “inventory
container” of the appropriate size.
Pallet Rack
Bin Shelving
Multi-Pallet
Drive In
Rack
Drawers
.125
1.5
40.0
320.0
Cubic Feet of Storage Required For An Item
Develop an Inventory Container Graph
Inventory Container Graph
25000
Drawers
# of SKUs
20000
15000
10000
5000
0
0.125
1.5
8
40
320
Cubic Feet of Storage Needed
Now you can begin to think about what storage modes might be
reasonable candidates for the merchandise you are storing…
Develop
a
Pick
Size
Classification
Scheme
Next develop a classification scheme for picks based on the size of the pick.
Usually designers will use pallet”, “case”, and “piece” pick sizes
Piece Pick
Case Pick
Pallet Pick
Assess the Activity In Each Inventory Container
Inventory Container Graph
Assess the activity in the larger
containers to see if there is the possibility
that some of the items should be moved
to a forward pick area. The decision will
be driven by the # of such picks in the
container and the overall size of the
larger container storage area.
25000
15000
10000
5000
0
0.125
1.5
8
40
Cubic Feet of Storage Needed
Move these to
Case Storage
320
Piece Picks Within the Pallet Inventory Area
1200
1000
800
600
400
200
Cummulative # of SKU's
95
85
75
65
55
45
35
25
15
0
5
Piece Pick
Activity
Curve
# of Picks/ Day
# of SKUs
20000
Designing a Warehouse
Reserve Areas
Part II
Define Your
Forward Pick
Areas
Forward Pick Areas
General Process for Forward Pick Design
• Questions that Must Be Answered
About the Forward Pick Area(s):
• How many forward pick areas do you
need?
• Determine how many SKUs should go on
the pick line
• Removing unusual SKUs from the pick line
• Sequence the SKUs on each pick line
You will likely have multiple forward pick areas
For each Pick Size you need to decide if there are a lot of picks
associated with a relatively small subset of the items. If so, you will
likely want to set up a forward pick area for that Pick Size.
O rd e r C o m p le tio n A n a ly s is B y S iz e o f P ic k
80% of Picks
from
20% of Items
100%
90%
80%
70%
F u ll C a se O rd e rs
60%
% O rd e rs
C o m p le te
B ro ke n C a se O rd e rs
50%
O ve ra ll
40%
30%
20%
10%
0%
0%
10%
20%
30%
40%
50%
% Ite m s
These Items should go into
a forward pick area.
60%
70%
80%
90%
100%
Determining How Many Items in Forward Pick
Generally to determine how many items you are going to put in the
forward pick area you look at the tradeoff between adding an item into
the forward pick area and the % of additional orders you are then able
to complete in that area.
79
100
110
120
130
140
150
160
88
92
92
95
98
98
100
68
63
52
44
33
25
22
80
80
60
60
40
40
20
20
0
0
160
84
100%
140
90
100%
120
99
97
95
93
92
90
83
100
33
46
52
67
73
79
81
80
20
30
40
50
60
70
80
Trade Off:
Space Utilization and Efficiency
60
% Days
Picked
40
% Case
Picks
Filled
20
Number of
SKUs
Number of SKUs
% Days Picked
% Case Picks Filled
Determining How Many Items in Forward Pick
R ank
Item
D ays
S hipped
% Of
F requency
(B y D ay)
C ase
P icks
% O f T otal
C um m ulativ e
C ase P icks
C ase P icks
(541,786)
(O ut of 104)
1 S 118R
104
100.0%
20045
3.6998%
3.6998%
2 S 12D C
3 S 23D C
104
104
100.0%
100.0%
10757
4732
1.9855%
0.8734%
5.6853%
6.5587%
4 522X
104
100.0%
3212
0.5929%
7.1515%
104
104
103
103
103
103
103
103
100.0%
100.0%
99.0%
99.0%
99.0%
99.0%
99.0%
99.0%
507
14350
16270
16173
8208
5385
5082
3345
0.0936%
2.6486%
3.0030%
2.9851%
1.5150%
0.9939%
0.9380%
0.6174%
7.2451%
9.8938%
12.8968%
15.8819%
17.3969%
18.3908%
19.3288%
19.9463%
5
6
7
8
9
10
11
12
S P 2I
2091I
3232W
3232I
S P T 8W
S P 8I
S P 8W
P 8I
90
Designing a Warehouse
Part III
Define How
To Plan &
Pick Orders
Wave Planning & Picking Approaches
Daily Order Pool
Orders of this “type” get released to the floor
and picked in the following manner every X
hours
Orders of this “type” get released to the floor
and picked in the following manner every Y
hours
While designers make assumptions at the start of a design about how the
bulk of the orders will be released and picked, the details behind their
thinking are not usually flushed out until the end of the project. They often
also wait until the end to define the planning and picking approaches for the
exceptional orders.
Ways in which you can process orders differently
• Order Selection Criteria & Groups
Forced Upon
You By
The
Business
Efficiency
Opportunity
– Rush vs Regular Orders
– Geography (West Coast vs East Coast)
– Orders Requiring Personalized
Merchandise
– Single vs Multi-Line Orders
– Types of Picks Needed to Complete
Order
– Order Cube (Sm Pkg vs LTL vs TL)
Assess the Significance of Single Unit Orders
Units/Order as a Percentage of Total Orders
.
100%
90%
C u m u lative % o f O rd ers
80%
70%
60%
50%
45% of all Orders are single unit orders.
40%
30%
20%
10%
0%
0
2
4
6
8
10
12
14
16
18
20
U n its P e r O rd e r
One of the greatest opportunities to improve warehouse efficiency is choosing
a different mechanism for picking single unit orders from multi-unit orders.
Assess the significance of grouping by area
Orders Completed By Area
Reserve
(Pallet)
Area
10%
M ix e d
Case
Forward Pick
Area
% P ick L in e s
20%
% O rd e rs
30%
F u ll C a se
O n ly
25%
60%
Piece
Forward Pick
Area
B ro ke n
C a se O n ly
55%
0%
10%
20%
30%
40%
50%
60%
Orders that require merchandise coming from different storage areas within
the warehouse may need to be picked differently.
70%
Deciding on a Picking Approach
Sorting Picks at End of Tour
Order #2
Single Order Picking
Order #1
Multi-Order Picking
Batch Picking
After the different groups of orders have been identified, the designer has to
make a decision about how each group of orders will be picked.
How Will Orders in Forward Pick Be Picked?
Multi LineOrder
Order
Cube
#3
80%
Order #2
75%
Good candidates for
Multi Order Picking
% of Total Orders
70%
60%
50%
40%
30%
20%
10%
10%
5%
5%
3%
1%
8
32
64
Order #1
0%
0.5
1
2
Multi-Order Picking Cart
Order Cube (Cu Ft)
Deciding on a Picking Medium
Label Picking
Radio Frequency (RF)
Barcode Picking
Voice Picking
For each picking approach
you need to decide on a
mechanism for how picks will
be communicated to pickers.
Pick To Light
How Do You Plan & Pick Different Orders
Order Group
Pick Method
Pick Medium
Multi-Order Picking
RF Terminals
Batch Picking
Labels
Small Cube
Multi-Line Orders
Single Line Orders
Summary of Warehouse Design Process
• PART I:
Define Your Storage Zones
• PART II: Design Your Forward
Pick Areas
• PART III: Define How You Will Plan &
Pick Orders
Observations
• Every descriptive tool or technique seems to be
based on a specific “need”
• Profiling/design is less about “describing” an “as
is” warehouse, than about saying how it “should
have been”
• It’s hard to integrate the different descriptive
tools and techniques
• Can we build a comprehensive, computational
“description” from which all the different “needs”
can be met?
Schema
Process
Model
AMPL, AIMS, GAMS, and other
“modeling languages” incorporate
a reference model for the domain
of optimization models, and are
used to create instances of
optimization models.
Can reference models be
developed for the domain of
discrete event logistics systems,
or for subsets of the domain, e.g.,
warehouses, factories, and
supply chains?
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