Battle Testing
Your Distribution Center
DesignPerry Lundberg, VP Supply Chain
Imperial Distributors
Ian Hobkirk, Managing Director
Commonwealth Supply Chain Advisors
Meet the Speakers
Ian Hobkirk:
• Founder and Managing
Director of Commonwealth
Supply Chain Advisors
Perry Lundberg:
• Vice President of Supply
Chain at Imperial
Distributors
About Imperial Distributors
Imperial is recognized as a leader in both distribution and
merchandising of supermarket non-foods. Services range
from:• Labor Saving Services…
Ordering, stocking, and shelf replenishment, spaceman generated planograms, store resets, and store
personnel training.
• Logistics and Distribution Services…
Backhaul, DSD, and crossdock programs. Pre-ticketed or un-ticketed products. Commodity sortation
by category.
• EDI Services…
Advanced shipping notice, electronic funds transfer, electronic invoicing and account specific UPC
downloads.
• Marketing Services…
Category management, assortment planning, promotional development funds, off-shelf product
displays, seasonal programs, and retail price strategies.
About Imperial Distributors
Serving over 3,500 retail locations across 48 states and Puerto Rico
Current Distribution Center
2-level pick
module
Accumulation
buffer
8:1 merge Shipping
sorter
Challenge
Significant, but unpredictable growth: Growth in large chunks rather
than predictable steady growth
Geographic expansion: New customers in new geographic locations
Capacity Challenges
MHE Bottlenecks
Imperial needed to make good decisions about what to do with the
distribution center based on the multiple ways the future could play out.
Factors Contributing to Supply Chain Uncertainty
• SKU proliferation
• Increased levels of e-commerce
• Changing retail compliance
mandates
• Changing regulatory compliance
requirements (traceability, country-of-
origin tracking, etc.)
• Increasing number of non-conveyable
SKUs
• Potential mergers/acquisitions
• Customers placing smaller, more
frequent orders
• Or…large retailers that add regional
DCs and require larger orders
“Prediction is very difficult, especially about the future.”
-Niels Bohr, Nobel prize-winning physicist
Action was Needed!
Imperial needed to make changes in distribution to ensure the
long term viability of the company. They were reluctant to
invest in MHE if the existing building didn’t have enough
space to be a long-term solution for the company.
Options Included…
• Purchase the adjacent parcel of land and build an addition
to the existing building
• Move to another building
• Somehow find a way to better utilize existing building to
support demand
The Impact of the Wrong Decision
Immediate problems
• Inability to ship product
• Inability to pick quickly
• Aisle contention
• Inefficient bin replenishment or
conveyor or carousel systems
Long-term problems
• Design isn’t scalable
• Full-scale rip-and-replace is
required in a short period of
time
• The new facility is outgrown
sooner than expected
The Traditional Method of Decision Making was Insufficient
• Static analysis
• Inflexible
• Difficult to play “what if”
• Hard to link changes to
distribution policy to
financial results
• Multiple long design
cycles to explore each
option
Imperial Found a Better Way…
Phase 1: Data Model & Initial Analysis
• A design was
created that
involved a
building
expansion as well
as additional
forward pick bays
Phase 1: Data Model & Initial Analysis
• A complex data
model was built
which revealed
that this
expansion would
be sufficient to
meet Imperial’s
needs for nearly
any growth
scenario that
would be
experienced over
the next 10 years
Phase 1: Data Model & Initial Analysis
• What methodology was followed to make this
model so useful over the next few years to
Imperial?
Four Sequential Steps…
Determine Space
Requirements
Determine Pick Strategy
Determine Pick
Methodology
Determine Inbound
Processes
Gathering Data
How to develop an analytical tool to
design a DC with infinitely variable
demand forecasts?
• Even if it’s not possible to know
what the forecast is, knowing the
range of potential forecasts is vital
in order to develop a DC design
that is flexible to accommodate all
(or most) of them.
Gathering Data
The goal: develop a
dashboard to allow users
to play “what if,”
experiment with different
designs, and quickly see
the implications of
possible growth trends.
A New Method
Real-time calculation of
storage requirements as the
forecast is changed
Growth variables can be
manipulated to experiment with
potential views of the future
Compile Source Data
Data requirements generally include:
Item master
Location master
Historical sales orders
Inventory snapshots
Historical purchase orders
Good Data Gathering Practices are Vital to Success:
• Identify future scenarios
• Identify the “Results” metrics
• Identify variables which will
Impact growth
• Determine the data
• Determine the baseline data
range
• Create a formal data request
• Create replicable reports
• Export the data
• Validate the data…
Validate the Data
• Confirm fields:
• Check formatting:
• Check consistency
• Check pack sizes
• Summarize data and review
ranges
• Perform some basic “sanity
checks” V1.0
• Manage outliers
• Sanity checks V2.0 – step
outside of the data…
Sanity Checks V2.0: Step Outside of the Data
• Take the data summary and walk through the
distribution center
• Confirm actual storage positions with a physical site
survey
• Confirm actual throughput
• Run the results by the people who are closest to the
action: managers and floor level workers
What to do when Cube Data Doesn’t Exist:
•Un-tested cube data can be worse than
no data at all
•Bin surveys can be valuable
•They are much more accurate in the
short term
•But…it is harder to extrapolate results
into the future
Imperial Phase 2: Exploring a Facility Expansion
• Now that Imperial had a data-
validated design, they could
pursue their ideal solution:
expanding the DC
• Unfortunately, the adjacent
parcel of land was found to
have some environmental
issues which made it
unsuitable for Imperial’s
needs
Imperial Phase 2: Exploring a Facility Expansion
• Once the expansion was
proven to be impractical,
Imperial decided to buy some
more time by adding pick-
faces
• The original data model was
used to determine the type of
storage mediums required
and quantity
• The model was also used to
slot product in the new pick-
faces
Creating the Storage Design Tool
Basic structure of the tool should consist of three (3) worksheets:
Dashboard
Concepts to Incorporate…
• Conservative inventory
policy
• Target supply
• Re-order points
• Minimum purchase quantity
• Rounding to pack sizes
• Bin break points
• Bin utilization factors
• Pickable pallet locations
vs. non pickable
• Carton flow
• Shelving
• Conveyability fields
• Longest dimensions
• Weights
• “Top-off logic”
• The 95% rule
• Target weeks of supply
• Overstock rules
• Seasonality
• Longest dimensions
Concept: Cube vs. Longest Dimension
• Pure “liquid cube” numbers can be misleading
• It is important to use actual length, width and height
data if possible
vs.
Concept: Seasonality
• Take demand snapshots from multiple seasons at the
SKU level
• Important to distinguish between seasonal surges of
high-cube vs. regular cube items
• Design a facility that can accommodate a reasonable
range of seasonality
vs.
Concept: Conveyability
• Cubic dimensions and weight may not
paint a complete picture of conveyability
or of suitability for storage in mediums
like carton flow
• “Pack type” field is ideal to have for each
SKU
• Product categories can provide clues to
conveyability
• Current bin location can also be a
determinant for future bin locations
Example SKU to Illustrate Several Key Design Concepts:
• What is the optimal forward pick bin for
this SKU?
• How many bins are required?
Boston Red Sox
Snow Globe
Concept: Determining Storage Medium
• 2 week supply = 2 units
• 2 units take up about 15% of one (1) shelf
• But…
2-week demand: 2 units
Units stored in forward pick: 2 units
Concept: Packsizes
• This SKU comes in packs of four (4)
• It is unlikely that we will replenish forward pick in less than case
quantities
• A case of (4) takes up about 1/3 of a shelf
2-week demand: 2 units
Units stored in forward pick: 4 units, 1 case
Shelf is divided into three discrete bins
Concept: Overlapping Replenishment
When we replenish this SKU, we will probably not wait until the
entire supply in forward pick is exhausted.
The replenishment supply (1) case will overlap the existing supply
(1) case
Additional space must be allocated for these situations
(Overlap allowance is not always 100%)
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2-week demand: 2 units
Units stored in forward pick: 4 or 8 units, 1 – 2 cases
Concept: Bin Break Points
As growth is experienced, target supply may increase to 9 units
A “bin break point” must be defined where the item will be stored
in the next larger storage medium (example: 3 shelf bins, 1 full
shelf)
2-week demand: 9 units
Units stored in forward pick: 12 units/3 cases
Concept: Top-off Logic
As demand increases further, the unit is promoted to
carton flow rack
2-week demand: 13 units
Units stored in forward pick: 16 units/4 cases
Concept: Top-off Logic
• Since it is bad practice to mix SKUs in a lane of carton
flow, then no space will be lost by filling up or “topping-off”
the lane
• This will reduce replenishment interval and reduce
overstock space requirements
2-week demand: 13 units
Units stored in forward pick: 20 units/5 cases
Concept: The 95% Rule
• Sometimes the “perfect” quantity in forward pick results in orphaned
product in overstock
• An orphan factor can be setup (ex: 95%) which states that if 95% of
the quantity on hand in the building will fit in forward pick, then the
entire quantity will be slotted here
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Pallet flow rack
(forward pick)
Static Rack
(overstock)
Concept: Pickable vs. Non-Pickable Pallets
• Utilization factor can be very high for pallets that are
purely used as overstock
• Pallets which will be picked from, or depleted in piecemeal
fashion for replenishment must have a lower utilization
factor
Concept: Flex Bays for Forward Pick
• Modular bay design for pick modules - the same 108"
wide bay can be converted to:
Images: Easyrack, Frazier Industrial Company, 1stoprackservices
Static Shelving Carton Flow Pallet Flow
How it Works:
• Live Demo of a Tool
The Functional Life of the Facility or Material Handling System can be Predicted with a Good Degree of Accuracy…
Imperial Phase 3: Exploring a New Building
• Imperial’s strong growth
continued, and the company still
needed a longer term
distribution solution
• The company began exploring
the option of leasing a larger
building to relocate the
distribution center to
• It was extremely important to
Imperial’s ownership to keep
jobs in the local community,
which limited the choices of
available buildings to some
extent
Imperial Phase 3: Exploring a New Building
• A potential building was
identified
• The building had some
challenging characteristics
which needed to be evaluated
• The same data model was used
to evaluate the new building and
determine the best layout
• After extensive study, it was
determined that the building
characteristics and the financial
aspects of the lease would not
be a suitable long term solution
for Imperial
Using the Results to Create Flexible Designs…
Column Spacing Matters
• Columns should be spaced in increments that will allow
them to fall in the flue spaces of rack rows with a variety of
different aisle spacing
Flex Bays vs. Long-Aisle Shelving Layouts
• If there is a significant amount of static shelving in the
layout, then longer shelving aisles may be more
space effective than flex-bays
“Every Other Aisle” Concept
Or…
Single aisles with room to expand
Lift Truck Style #1: Battery Powered, Counter-Balanced Sit-Down Truck, 4-Wheel
Strengths:• No emissions issues• Versatile• Trailer loading/unloading• Dock-to-stock operation• Attachments (roll clamps, etc.)
Weaknesses:• Requires a large stacking aisle
(141”)• Frequent on/off operator
movements are inefficient
Lift Truck Style #2: Battery Powered, Counter-Balanced Sit-Down Truck, 3-Wheel
Strengths:• More maneuverable than 4-
wheel trucks• Trailer loading/unloading• Dock to stock operation• Attachments (roll clamps, etc.)
Weaknesses:• Requires a medium-sized
stacking aisle (130”)• Frequent on/off operator
movements are inefficient
Image source: Toyota
Lift Truck Style #3: Battery Powered, Counter-Balanced Stand-Up Truck
Strengths:• Highly maneuverable• Requires the smallest stacking aisle of
any truck that can also load trailers (102”)• Easy on/off movements for operators• Trailer loading/unloading• Dock to stock operation
Weaknesses:• Not as well-suited to attachment
handling (rolls, clamps, etc.)• Narrower stacking aisles are possible
with other equipment• 4-stage mast may be required to lift to high
elevations and to load low-height trailers
Lift Truck Style #4: Battery Powered, Reach Truck
Strengths:
• Requires the smallest
stacking aisle of any truck
without a guidance
system (110”)
• Easy on/off movements
for operators
Weaknesses:
• Cannot load trailers
• Cannot handle
attachments (rolls,
clamps, etc.)Image source: Toyota
Lift Truck Style #5: Very Narrow Aisle (VNA) Turret Truck
Strengths:
• Can operate in aisles as narrow as 66”
• Wire guidance system allows for high
speed travel
• Enables pallet handing and case
picking
Weaknesses:
• Cannot load trailers
• Slow operation outside of stacking
aisles
• High cost
• Aisle contention can occur – two
vehicles cannot be in the same aisle at
the same time
Image source: Raymond Corporation
Plan Ahead
• Plan ahead for conveyor-
based picking…
• Plan ahead for a second
level…
Pick Methodology: 26 Ways to Pick
Cluster picking
1. Types:
a) Conveyor-based cluster picking
b) Cart-based cluster picking
c) Pallet-truck-based cluster picking
d) Order-picker-based cluster picking
2. Features:
a) Early out
b) Dynamic re-batching
Batch picking
6. Primary pick
a) One SKU to one MU
b) Multiple SKUs to one MU
7. Secondary pick/put
a) Single line orders
b) Single unit-single line orders
c) Multi-line orders from homogenous
MUs
d) Multi-line orders from mixed MUs
e) Varieties
i. Pick to tote
ii. Pick to pallet
iii. Pick to tow-vehicle
f) Sort methods
i. Manual sortation
ii. Unit sortation
A. Single sort
B. Multi-sort
Zone picking
3. Sequential zone pick (pick and pass)
4. Simultaneous zone pick (pick and
consolidate)
a) VNA pick for slow movers
b) AS/RS pick for slow movers
c) Conveyor based
d) Cart based
• Some are flexible, some are less flexible!
Which Technologies Are the Most Flexible Over Time?
• Very flexible technologies
• Cart-based picking
• Scalable
• Inexpensive
• Plan ahead to allow sufficient
aisle width for future conveyor
• Voice-directed warehousing
• Can be implemented with minimal
impact on underlying systems
• Selected processed can be
automated
Which Technologies Are the Most Flexible Over Time?
• Moderately flexible technologies
• Conveyor-based picking
• Plan ahead for additional
levels
• Plan ahead for linear
expansion
• Modular bay design
• WMS
• Not bolted down
• Flexibility depends on architecture
Which Technologies Are the Most Flexible Over Time?
• Less Flexible Technologies:
• Pick-to-light systems
• VLMs
• AS/RS
• Carousels
Automated Packing and Shipping –Tips:
• Plan ahead for automated packing
• Allow buffering capacity for sortation – phased
approach
• Plan ahead for additional sorter diverts
Imperial Phase 4: Upgrading the Current Equipment
• For the immediate term, Imperial
has decided to make some
strategic upgrades to their
current material handling
equipment
• These upgrades involve
replacing crucial componentry
while not disrupting the
operation
• Imperial has chosen to take their
data modeling to the next level
by using simulation software to
validate the proposed changes
Imperial Phase 4: Upgrading the Current Equipment
• Proposed changes include:
• Upgrading the 8:1 merge to
increase throughput
• Upgrading the shipping sorter
• Exploring ways to add a recirc
loop to the sorter
• Exploring ways to rework the
accumulation buffer to make
picking more efficient
• Goals of the simulation include:
• Ensure there are no bottlenecks
• Ensure proper flow and
throughput
• Ensure that problems are
SOLVED, not just pushed
downstream
Imperial Distributors: Wise Investments in Design
• Imperial chose to build a flexible data
model two years ago when it first
began evaluating future options
• The model was architected in a way
that would allow the company to
easily play “what if” and examine
potential future scenarios
• The model was an effective tool which
allowed the company to examine
several options which presented
themselves in the light of solid data
and facts
• Imperial is confident that the
proposed new changes will be a key
enabler of growth for years to come
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