cscmp 2014: battle-testing your distribution center design

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


• 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


• 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


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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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)


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



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



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


• 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


• 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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