View
97
Download
2
Tags:
Embed Size (px)
DESCRIPTION
This whitepaper provides a structured approach for making important distribution center design decisions. Content includes: How to develop a throughput design tool that will help you identify your optimal pick strategy and identify ROI- justified automation technology; why the distribution center design process should start with picking; and a checklist of potential solutions to consider
Citation preview
Page 1 of 14
Supply ChainAdvisors LLC
Confidently Committing to a Distribution Center Design When Demand is Unpredictable
Part II Developing a Throughput Design Tool and Determining Pick Strategy
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 2 of 14
Table of Contents
Introduction ...................................................................................................................................................................... 3
Why the Distribution Center World Revolves Around Picking ............................................................................................ 4
Summary of the Throughput Design Process.................................................................................................................... 5
Define Order Types ..................................................................................................................................................................... 5
Determine Return on Investment Parameters ........................................................................................................................... 6
Define Peak Season and Surge Times ...................................................................................................................................... 6
Compile Order Data .................................................................................................................................................................... 6
Create a Labor Profile ................................................................................................................................................................. 6
Create a Throughput Profile Chart ............................................................................................................................................. 7
Calculate Labor Performance ..................................................................................................................................................... 7
Apply Growth Rates .................................................................................................................................................................... 7
Project Future Costs.................................................................................................................................................................... 8
Benchmark Performance ............................................................................................................................................................ 8
Create a “Long List” of Potential Solutions ................................................................................................................................ 8
Determine Pick Strategy ..................................................................................................................................................10
Test Alternate Visions of the Future .................................................................................................................................11
Evaluate Other Factors ...................................................................................................................................................11
Appendix A: Overall DC Design Process .........................................................................................................................12
Start Planning Your Distribution Center Today .................................................................................................................13
Additional Resources: ............................................................................................................................................................... 13
About Commonwealth Supply Chain Advisors ........................................................................................................................ 13
About the Authors ...........................................................................................................................................................14
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 3 of 14
Confidently Committing to a Distribution Center Design
When Demand is Unpredictable - Part II
Developing a Throughput Design Tool and Determining a Pick Strategy
Introduction Part I of this series focused on how companies can develop a storage design tool, a data model to represent the various types of storage
required in a distribution center (DC) with varying levels of growth and SKU proliferation. This is a vital first step in designing a DC –
determining how large the forward pick areas and overstock areas must be, and what storage mediums are required. Armed with this
information, major strategic decisions can be made such as whether to expand a DC, whether a new DC will be large enough to handle
growth, and whether or not to consolidate multiple facilities under one roof. A major goal of DC design can be satisfied by using this
tool: efficient space utilization.
But space is only part of the DC design equation. To have a meaningful impact on the corporate bottom line, the DC must continuously
improve labor efficiency and enable improved customer service. To meet these goals, important decisions must be made as to the
processes which will be used within the operation, and what forms of warehouse automation are required to support those processes.
This installment of the series on DC Design (Part II) will focus on building a Throughput Design Tool with an eye to determining an
overall Pick Strategy and specifying appropriate material handling equipment.
Supply ChainAdvisors LLC
Space Utilization
Customer Service
Labor Efficiency
Part I of the DC Design Series can be accessed by visiting http://www.commonwealth-sca.com/resource-library/
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 4 of 14
Why the Distribution Center World Revolves Around Picking When determining optimal processes within the DC, it is usually advisable to begin with evaluating pick methodology, and then
developing inbound and replenishment processes to support the picking methods. There are several reasons why picking should usually
be “the straw that stirs the drink” in the DC:
Product is generally put-away or replenished in a small number of large transactions, and gets picked in a large number of small
transactions. Thus, outbound labor per unit is higher than inbound labor per unit, and greater returns will be achieved by
optimizing outbound labor than inbound. (Example: 1,000 units of a SKU are put away all at once when a full pallet is deposited
in the forward pick area. Those 1,000 units are picked and shipped in a series of 500 orders, each of which contains two (2)
units each. Pick labor is exponentially higher than put-away labor).
Outbound processes usually have very short cycle time requirements. There is generally a narrow window between the time an
order is received and when it must be picked and shipped. Processes must be designed to facilitate picking which is not just
labor efficient, but also fast.
It is for these reasons that it usually makes sense to begin the design process with an evaluation of picking requirements, since this is
the biggest opportunity to reduce labor and improve customer service. This “bias” towards pick processes over inbound and
replenishment will be manifested in the following ways:
A short replenishment interval for the forward pick area is advisable in order to increase SKU density and reduce walking, even
if this means that additional labor must be added to replenish pick bins. Generally speaking, pick labor savings will still offset
additional replenishment labor.
The bins in the forward pick area will be slotted in the optimal pick sequence, rather than the optimal replenishment sequence.
Exception to the Rule:
Multi-Step Replenishment
There are times when optimizing bins in forward pick can add excess labor to the replenishment process, and a more complex
replenishment methodology may be worth considering. For example, the overstock area may contain very large pallet level quantities of
a SKU, and be slotted in very random order. Since travel distances are so great as product is picked from overstock, it usually makes
sense to group these picks in overstock bin sequence. However, if the replenishment consists of full cases picked to a pallet, when that
mixed-SKU pallet is brought to the forward pick area to be put-away, it may be impossible to follow a logical travel path as the cases
required can be buried at the bottom of the pallet. While the pick sequence was optimized, the put sequence is not. Given the greater
travel distances in the overstock area, this may be an acceptable trade off. However, there are two other processes companies have
employed in an effort to make the trade-off more equitable:
1. Pick to a sub-divided movable unit: Special fixtures can be designed which essentially allow a multi-shelf cart to be affixed to the
fork of a multi-level order-picker. Product is picked and placed in a designated shelf on the picking unit. When it is time to put
product away, few if any, cases are buried under others, and the put-away can be done in bin sequence. There may be some
trade -offs, however, in that less product can usually be picked to a sub-divided fixture than to a pallet alone.
2. Multi-step replenishment: This process is used when there is a very frequent replenishment interval to forward pick (such as
multiple times in a day or week). It involves setting up a “ready reserve” or staging area between overstock and forward pick.
The ready-reserve area is slotted in the same sequence as the forward pick area, but contains a somewhat larger supply of each
SKU than forward pick. The idea is that the time consuming move from random, palletized overstock is made into this ready
reserve area. The time-sensitive replenishment to forward pick is made from this ready reserve area – picked and put in the
same sequence. While the overall amount of labor required for replenishment may actually increase, the timing of the critical
forward-pick area re-stock is shortened. In certain operations, this trade-off can be worthwhile.
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 5 of 14
Summary of the Throughput Design Process The following sections outline a recommended methodology for designing a throughout design tool. A general summary of the steps
involved is shown below.
Define Order Types When modelling outbound product flow, it is first important to define the various types of orders which can be picked. Create a few
distinct order profiles based upon how an order must be picked.
Sometimes it is easiest to do this by sales channel, as each channel sometimes has a distinct profile. For instance, e-commerce orders
may consist of one or two lines, and be drawn from a large SKU set. Wholesale or retail orders may have dozens of lines but may be
drawn from a smaller SKU set.
Key order attributes to look for when defining order types are:
Lines per order
Pieces per line
Define order types
Determine ROI parameters
Define peak season and surge times
Compile order data
Create a labor profile
Create a throughput profile chart
Calculate labor performance
Apply growth rates
Project future costs
Benchmark performance
Create a “long list” of potential solutions
Determine pick strategy
Test alternate visions of the future
Evaluate other factors
Determine pick methodology (next installment)
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 6 of 14
SKU set (number of potential SKUs which the order can be drawn from)
Multi-delivery orders (i.e. ship the same SKUs to multiple stores)
Pick type: piece pick, case pick, pallet pick
Determine Return on Investment Parameters There are usually numerous varieties of material handling solutions that might improve the operation of a given DC. However, only a
fraction of these often prove to be cost-justifiable.
One of the goals of a throughput analysis is to quickly eliminate solutions which will not provide an attractive return-on-investment
(ROI) to the company, and focus energy around solutions that will. In order to do this, a thorough understanding of the operational goals
and ROI parameters is vital. This will usually involve executive-level participation.
At the outset of the analysis, it is important to answer questions like:
What about the operation are we trying to improve?
How do the possible operational improvements translate to value?
Are we trying to reduce labor costs?
Are we trying to reduce order fulfillment cycle times?
What is the longest acceptable period of time for the solution to pay for itself? (the ROI period)
Define Peak Season and Surge Times It is important to arrive at both an average throughput model as well as to calculate the worst-case scenario in terms of throughput. For
many companies, this means looking at two key factors:
Seasonal peaks
Daily surges
Many companies see significantly increased volumes of business during certain times of the year (for example the 4th quarter retail
holiday season). Calculating seasonal peaks generally involves comparing outbound order data from a normal period with that of the
peak season to establish a peak factor (ex.: 22%).
Companies often have daily surges in volume as well. For example, many customers may wait and place orders right before the
distributor’s published order cutoff time, causing a surge of orders during this period. This daily surge (the busiest hour of the day)
should also be calculated.
When determining a worst-case scenario for throughput, both of these factors must be combined (i.e. one must look at the busiest hour
of the day during the busiest season of the year).
Compile Order Data The data required to analyze throughput is generally a detailed history of sales orders for a period of time, ideally 12 months.
This data set should include line-level detail for each sales order. Key fields can include:
Sales order #
Sales order type (see above section)
Line #
SKU #
Quantity to be picked
Cartonization data
Date Processed
Create a Labor Profile In order to rapidly evaluate the ROI for various forms of material handling equipment, it’s important to understand the makeup and costs
of the current workforce in place within the warehouse. It must be defined, at as granular a level as possible. At a minimum, functions
like picking, packing, and shipping must be broken-out as categories, but it can also be immensely helpful if the labor force can be
further categorized by what order types the worker is picking, packing, or shipping. This is not always an easy task, especially if workers
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 7 of 14
are cross-trained and play multiple roles on any given day. In these instances, it may be necessary to examine an hourly breakdown of
labor by worker, if this is known.
The output of this exercise is a table which lists each role, and the number of full-time equivalents (FTEs) or Labor Hours spent
performing that role on both an average and peak period.
At this stage of the analysis, it’s important to remember that the information does not have to be perfect. The goal is to create a general
ROI model to begin narrowing down the list of potential processes and technology that can improve the operation.
Once the number of FTEs performing each task has been established, the cost of each FTE must be factored in. It is usually advisable
to look at “fully loaded” rates which include salary, payroll taxes, and benefits. Calculate the total annual payroll by job function.
Create a Throughput Profile Chart Once these parameters have been established, then a Throughput Profile Chart can be created. This chart looks at several characteristics
of each of the order types:
Total orders per day
Total lines per day
Total pieces per day
Total outbound cartons per day
These factors must be calculated for all order types, and for both average and peak/surge periods.
When the total volumes are calculated, then averages can be compiled including:
Average lines per order
Average pieces per line
Average cartons per order
It is generally useful to further break these numbers down to the hourly level, and in some cases to the minute. Labor standards are often
based on hourly work levels, and material handling capacities are often based on volumes at the minute level. Additionally, it is often
useful to perform some basic statistical analysis on the calculated averages to ensure they are representative of “typical” values (i.e. one
extremely large order skewing the average lines per order).
Calculate Labor Performance The volume of outbound product flowing from the DC has now been established. It is next necessary to merge this information with the
labor profile which was compiled earlier. The goal of this step is to turn the throughput information into a set of standardized key
performance indicators (KPIs) which can be used to benchmark the performance of the DC.
The most important KPI to calculate when analyzing a piece-pick distribution operation is usually hourly lines picked per worker. As
long as the individual items picked are relatively small, then the unit count picked is generally not as important as lines picked. For
example, the difference in time between picking three pencils and ten pencils is negligible, making the line count a more meaningful
measure in this instance. Also, many inventory systems track piece counts of bundled units, making handled pieces impossible to track.
However, for case-pick operations, or other picking where items are bulky, the unit count can make a more significant difference in
evaluating pick rates.
Apply Growth Rates Once the current throughput of the facility is calculated, then growth rates can be applied. Just as with defining the ROI parameters,
executive participation at this step can be very useful. Some of the questions to be answered include:
What annual rate of volume growth is expected in the operation?
Do growth rates vary based on the type of order being shipped?
What is the time horizon for which the analysis will be performed?
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 8 of 14
A cautionary note: sales forecasts are often based on a dollar value of growth which is predicted. This does not often translate one-to-
one into DC volume growth. Growth may be expected to be greater for certain high-dollar-value products which can skew the results
somewhat. It is important to get a forecast for outbound distribution volume.
As has been noted previously, determining a growth forecast can often be a challenging task when the future is uncertain. Just as when
the Storage Design Tool was created, the Throughput Design Tool must be architected to allow key variables like growth rate to be
manipulated, with the overall results displayed in real-time.
When growth rates are applied, a separate table should be created listing the projected future throughput of the building in pieces, lines,
and cartons, for both average and peak periods.
Project Future Costs Once the growth of throughout has been projected, it is next necessary to calculate the increased annual labor cost required to process
this throughput. The baseline assumption which should be made is that the rates at which orders are picked, packed, and shipped by
workers will not change.
Project what the annual labor cost increase will be if the volume growth projections are realized but there is no change to distribution
processes or technology.
Benchmark Performance Once KPIs have been established, it is now possible to benchmark the performance of the DC and to begin to narrow down the list of
potential solutions.
Published benchmark data on DC performance rates can be found from numerous sources. It is wise to take a realistic view of this data.
Since handling characteristics can vary so widely from one operation to another, only a few benchmarks are really of broad value. These
include pick rates (broken out by piece picking and case picking), pick accuracy, and order turn-around times. There are many other
published benchmarks which Commonwealth has found to be of questionable value. For instance, “lines received per hour” can vary
tremendously due to a number of factors. The receipt could be a small parcel that contains six lines and can be processed very quickly.
Another receipt could also contain six lines, but could consist of an entire container of product with thousands of cases to count and
label. A broad KPI in this area is of little value.
Commonwealth Supply Chain Advisors maintains a detailed table of dozens of different types of pick methodologies and generally
accepted rates at which the picking can take place. Even with this detailed data, it is vital to have a seasoned expert review the specific
requirements of the operation to determine what pick rates might be attainable with process changes. There are a number of very
subjective factors which influence pick rates which cannot be listed in a matrix, including: relative size of the product, type of data
confirmation which occurs, method of inserting product into an order container such as a box or envelope, etc. An experienced set of
eyes can often weigh some of these subjective factors and help set realistic expectations for pick levels.
Create a “Long List” of Potential Solutions To ensure that all viable processes and technologies are considered, it is important to start with a complete list of available solutions.
Commonwealth uses a list similar to the one in the box below as a starting point for evaluation. The list is divided first into Pick
Strategies and Pick Methodologies.
Pick Strategies consist of three basic ways to pick product (vehicle-based, conveyor-based, and goods-to-picker), along with some
variations of each. Pick Methodologies refer to the process used to pick; the same methodology can often be used for all three pick
strategies (example: zone picking). See the checklist of potential solutions to consider below:
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 9 of 14
Packing
Pick-to-shipper
Wave management
“Wave-less” picking
Re-sequencing
Buffering
Sorting
Pre-sort
Recirculation sequencing
Vehicle-based picking
Low level
o Cart-based
o Pallet truck-based
Multi-level
o Multi-level order pickers
Conveyor-based picking
Pure conveyor system
Carts with conveyor
Powered vehicles with conveyor
Goods-to-picker systems
Carousels
AS/RS
o Mini-load
o Shuttle
o Other
Robotic
Cluster picking
Types:
o Conveyor-based cluster picking
o Cart-based cluster picking
o Pallet-truck-based cluster picking
o Order-picker-based cluster picking
Features:
o Early out
o Dynamic re-batching
Zone picking
Sequential zone pick (pick and pass)
Simultaneous zone pick (pick and consolidate)
o VNA pick for slow movers
o AS/RS pick for slow movers
o Diverse size items
Conveyor-based vs. cart-based
2. Pick Methodology (Covered in Part III)
Batch picking
Primary pick
o One SKU to one MU
o Multiple SKUs to one MU
Secondary pick/put
o Single line orders
o Single unit-single line orders
o Multi-line orders from
homogenous MUs
o Multi-line orders from mixed MUs
o Varieties
Pick-to-tote
Pick-to-pallet
Pick-to-tow-vehicle
o Sort methods
Manual sortation
Unit sortation
Single-sort
Multi-sort
3. Post-Pick Strategy (Covered in Part III)
1. Pick Strategy
Checklist of Potential Solutions
Pick Methodology (Continued)
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 10 of 14
Determine Pick Strategy The next step is narrowing the list down from the universe of potential solutions to a
“medium list” for closer consideration. The easiest way to make this “first cut” is usually to
perform a general cost-based ROI analysis of the three major pick strategies:
Vehicle-based picking
Conveyor-based picking
Goods-to-picker systems
Some of the solutions on the list may be able to be crossed off quickly and intuitively,
without extensive analysis or benchmarking. For instance, if a company employs ten workers
in the DC, and is seeking a two year ROI for their solution, it is possible to immediately
eliminate solutions like goods-to-picker systems, since the known cost of these solutions is
generally hundreds of thousands or even millions of dollars. Even if two-thirds of the labor
costs could be reduced with this technology, two-year savings would be about $400,000, not
nearly enough to pay for an Automated Storage and Retrieval System (AS/RS) (note: such
a system may still be warranted if space savings are a key component to ROI). So, a range
of solutions may be able to be eliminated intuitively before the analysis even begins. Even
if the proposed solution is a “simple” process change, a certain base cost for IT
modifications, testing, and roll-out should be assumed.
Once some solutions have been intuitively crossed off of the list, a benchmark-based analysis
can further refine the range of options and establish the general pick strategy.
The first step in this process is to go back to the Throughput Profile Chart and revisit the
potential labor costs which will be seen if throughout increases but pick rates remain the
same. This is the baseline future state cost. Next, utilize some “generous” benchmarks of
potential pick rates with various forms of technology and test to see if an attractive ROI can
be obtained.
For example, some horizontal carousel implementations have produced pick rates in excess
of 400 lines per hour per worker. While these rates depend heavily on a number of subjective
factors, they can be a good starting point for this medium-level ROI test. If an attractive ROI
cannot be established at a rate of 400 lines per hour, then it will certainly not be seen at a
more realistic rate of 200 – 300 lines. It may be possible to cross some solutions off the list
using this method. Apply the potential pick rate of 400 lines per hour to the projected
throughput rate in the DC and establish the number of FTEs required if this automation were
employed. Calculate the labor cost savings over the two-year ROI period in our example.
Then, create a very general estimate of what the cost of a properly-sized carousel system
might be, and determine if it can be paid for within the two-year ROI period based on the
projected labor savings.
Obviously this exercise will involve some working knowledge of the costs associated with
the various forms of technology which are available in the DC. For the purposes of this step,
a general order of magnitude cost estimate will often be sufficient. It is usually not cost-
efficient this early in the process to begin working with equipment vendors to engineer and
price solutions at a detailed level. Again, published benchmark costs have been produced
which can be of use, but as always, it is helpful to have an experienced eye review the
potential concepts as well. One key tool which can assist in this process is the Storage Design
Tool which was discussed in a previous installment of this series. For technology such as
carousels, AS/RS, and conveyor-based pick modules, the equipment cost scales based upon
the amount of storage which is required, so having a good figure for this using the Storage
Design Tool is vital. Often this data coupled with some benchmarks on cost per unit of
storage can help work up a good high-level cost estimate for the equipment.
Vehicle-Based Picking Examples
Pick Cart (Image Source: Creform Corporation)
Pallet truck (Image Source: The Raymond
Corporation)
Goods-to Picker System Examples
Carousel (Image Source: Abel Womack)
AS/RS (Image Source: Abel Womack)
Conveyor-Based Picking Example
Conveyor-Based Pick Module
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 11 of 14
Following these steps can be an effective way to determine the general strategies which are, at least, feasible in the context of the specific
project at hand.
Test Alternate Visions of the Future In keeping with our theme of designing a DC when the future is uncertain, the next step is to use the Throughput Design Tool to
experiment with the range of potential visions for the future which could play out.
By manipulating variables such as volume growth in various order types, variations in labor costs, and other factors, it is possible to
establish the various break points at which certain picking strategies make financial sense. Experiment with both conservative and
aggressive growth projections, and over various time periods. Weigh the value of keeping the current technology against the efficiency
gains of new technology. A properly architected Throughput Design Tool will allow the user to make statements like:
“If we continue our current rate of growth, we’ll be able to cost justify a goods-to-picker system by year six.”
Evaluate Other Factors Labor savings, while a key factor in the choice of a Pick Strategy, should not be the only criteria to consider. Additional areas which
influence the decision should be:
Space Savings
Flexibility
Scalability
Complexity
For example, a vertical lift module system may not be cost justifiable based on labor savings, but the space savings it offers may be
enough to make the technology worth considering. The Storage Design Tool discussed in the first installment of this series can be an
excellent way to evaluate space savings.
In another example, a mini-load AS/RS may offer significant labor savings, but the business requirements over time may be so uncertain
that an AS/RS would be too inflexible of a choice.
All of these factors should be carefully weighed when choosing a pick strategy.
In Our Next Installment (Part III): Determine Pick Methodology Once a Pick Strategy has been selected, additional order analysis is required to determine the optimal Pick Methodology. Our next
installment in the series will focus on this step.
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 12 of 14
Appendix A: Overall DC Design Process The steps contained in this guide are part of a larger process which has been developed by Commonwealth Supply Chain Advisors to
design DCs when demand is uncertain. The overall steps in this process are:
Determine Space Requirements
(Covered in Part I of the series)
Determine Pick Strategy
(Covered in this installent of the series - Part II)
Determine Pick Methodology
(To be covered in Part III of the series)
Determine Inbound Processes
(To be covered in Part IV of the series)
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 13 of 14
Start Planning Your Distribution Center Today
Additional Resources:
Paper: Confidently Committing to a Distribution Center Design When Demand is Unpredictable, Part I – Creating a Storage Design
Tool
Ebook: 6 Ways to Postpone Distribution Center Expansion
Paper: E-Commerce in the Distribution Center – Making a Graceful Transition
Presentation: Improving Warehouse Productivity Without Tier 1 Technology
About Commonwealth Supply Chain Advisors Commonwealth is a leading supply chain consulting firm that helps companies of all sizes structure their supply chain networks, design
distribution centers, and select and implement warehouse management systems (WMS). Commonwealth is based in Boston and works
with clients across the globe. For more information, visit www.commonwealth-sca.com or contact Jennifer Thomas at (617) 948-2153.
Commonwealth Supply Chain Advisors • 20 Park Plaza, Suite 400 | Boston, Massachusetts 02116 (O) 617.948.2153 | (F) 617.507.6112 | www.commonwealth-sca.com
Page 14 of 14
About the Authors
Ian Hobkirk
Mr. Hobkirk is the founder and Managing Director of Commonwealth Supply Chain Advisors.
Over his 20-year career, he has helped hundreds of companies reduce their distribution labor
costs, improve space utilization, and meet their customer service objectives. He has formed
supply chain consulting organizations for two different systems integration firms, and managed
the supply chain execution practice at The AberdeenGroup, a leading technology analyst firm.
His career has provided him with a broad perspective on how to solve supply chain problems
without automatically resorting to expensive technology. Mr. Hobkirk has authored dozens of
white papers on supply chain topics, and his opinions have been featured in publications such as
DC Velocity, Modern Materials Handling, and The Journal of Commerce.
John Diebold
Mr. Diebold is Director of Consulting for Commonwealth Supply Chain Advisors. Over his
career, he has designed over 100 distribution centers and led dozens of pure distribution center
optimization initiatives. He has worked for many of the top companies in distribution
automation: FKI Logistex, White Systems, Kardex Remstar, and Sapient Automation which
gives him a truly unique perspective on when and how to apply technology in the distribution
center. Mr. Diebold holds a Master of Industrial Engineering with focus on Systems Engineering
from New Jersey Institute of Technology.