Discovery Summit 2012
Using JMP® to Analyze and
Improve the Lead Time of Direct
Orders in a Global Supply Chain
M. Patricia Nava, Ph.D.
Global Fulfillment & Logistics
AGENDA
• Company Overview
• Supply Chain Challenges
• Descriptive Statistics – Problem overview
• Analysis of Variance – Root cause analysis
• Experimental Design – Proposed solution
• Closing Thoughts
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Global Operations – Fulfillment & Logistics
COMPANY
OVERVIEW
Global Operations – Fulfillment & Logistics
Who Are We?
• FOUNDED IN 1984 by Michael Dell
• A partner to businesses and consumers that delivers
INNOVATIVE TECHNOLOGY and services that
customers can trust
• Pioneered DIRECT MODEL, the revolution at the heart
of our ever-evolving business
• NO. 33 on the Fortune 500
• Deeply committed to SUSTAINABILITY
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Global Operations – Fulfillment & Logistics
A Global Company
EMEA Regional offices:
Austria
Belgium
Czech
Republic
Denmark
Finland
Ireland
Austin
France
Germany
Greece
Hungary
Ireland
Italy
Morocco
Netherlands
Norway
Poland
Russia
Portugal
Scotland
Slovakia
South Africa
Spain
Sweden
Switzerland
United Arab
Emirates
Poland
Bratislava
Shanghai
Nashville
Xiamen
Taipei
India
Panama
Malaysia
Singapore
Americas Regional offices:
Argentina
Brazil
Canada
Chile
Colombia
Mexico
Panama
Puerto Rico
Brazil
APJ Regional offices:
Australia
China
Hong Kong
India
Indonesia
Japan
Korea
Malaysia
New Zealand
Singapore
Taiwan
Thailand
Global Operations – Fulfillment & Logistics
Our Purpose
 Delivering technology solutions that enable
people everywhere to grow and thrive
We make technology that works in service of our customers




We make the complex simple
We make the powerful easy to use
We drive out inefficiency
We deliver superior long-term value
We give customers
the power to do more
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Global Operations – Fulfillment & Logistics
Our Products
Vostro
Desktops &
Notebooks
Latitude
Notebooks
Inspiron
Desktops &
Notebooks
Precision
Mobile
Workstations
7
Alienware
XPS
Notebooks
OptiPlex
Desktops
Precision
Workstations
Storage Solutions
PowerEdge
Servers
Global Operations – Fulfillment & Logistics
Our Customers
We want to help every person at every
age and in every profession achieve their
potential – from the 4-year old starting
school to a data center systems
administrator to the CIO of a global
corporation.
 95% of global Fortune 500
 10 million small businesses
 400,000 classrooms
 Every G20 government
 200,000 physicians
 75,000 channel partners
 60,000 retail locations
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Global Operations – Fulfillment & Logistics
Our Reach
Serving millions of customers
In 180 countries
 More than 103,000 team members
 65% of Dell team dedicated to
servers, storage, networking and
services
 7,000 team members in China
 23,000 team members in India
 12 solutions centers in 2011, 10
more in 2012
 R&D centers in Israel, Silicon Valley
and Austin
 120,000+ Dell systems shipped
each day; more than 1/second
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Global Operations – Fulfillment & Logistics
SUPPLY CHAIN
CHALLENGE
Global Operations – Fulfillment & Logistics
Dell’s Supply Chain By the Numbers
Countries served
Global supply chain nodes
Systems shipped per second
Annual diverse supplier spend
Dell-owned manufacturing sites
Time from China to
US/Europe
Cash conversion cycle
of Sales Inventory
PCs that receive factory customization
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Global Operations – Fulfillment & Logistics
Globalization drives operational efficiencies,
but also creates challenges to meet fast
delivery times
• Suppliers &
Manufacturing
in one part of
the world
• Demand
destinations
located worldwide
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Global Operations – Fulfillment & Logistics
Several fulfillment methods & product builds
drive different lead times to deliver orders
Product
Build
Direct
Indirect
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Build or
configure
to order
Build to
Stock
Fulfillment
Method
Lead Time
Direct to
customer
without
distributors
Longer time
to deliver
Via Retail or
Distributor
Fast delivery
• Each model presents
unique market
opportunities
• Dell supports a range
of both direct and
indirect models to
meet all of its
customers needs
Global Operations – Fulfillment & Logistics
When Dell fulfilled all of its orders under the
Direct Model, velocity was a key challenge
 Customers expect orders to be delivered in a short or
predictable lead time
 The Direct Model & global supply chains create a challenge
for meeting lead times expectations
Objective  Meet our Lead Time goal for Notebooks products
for 95% of the orders.
•
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Note: This study was conducted when Dell fulfilled all of its products under the Direct Model
Global Operations – Fulfillment & Logistics
DESCRIPTIVE
STATISTICS
-Problem
Overview
Global Operations – Fulfillment & Logistics
For this study, the lead time was measured from
the time the order is entered until it is shipped
Steps in the supply chain process
Order
Entry (OE)
Prod. Plan
(IP)
Manufacturing
(TP)
Air
Shuttle
(Shuttle)
Fulfillment
Centers (FC)
Shipped to
Customer
(SC)
Delivered to
Customer
(POD)
Meet our Lead Time Goal for 95% of Cases
Note: Time to deliver to customer (POD) was out of the scope of this analysis
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Global Operations – Fulfillment & Logistics
Analysis followed a top-down approach using
products hierarchy & steps in the supply chain
Notebooks Product Hierarchy:
• Line-of-Business (LOB)  Designed for different customer needs
200+ Notebook
– Product Families
 Type of processor, form factor, other
offerings at any
given time
›
Configurations  Selection of memory, hard drive, other
 Analysis was conducted at LOB & product family levels for the overall lead
time across the entire supply chain, then at individual steps in the process.
Note: For full information about Dell products go to www.dell.com.
LOBs illustrated in this analysis will be referred as LOB-A or LOB-B
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Global Operations – Fulfillment & Logistics
Data included order transactions with the major
attributes defining the orders (monthly periods)
• LOB
• Product family
• Systems quantity
• Level of configuration
• Fulfillment center
• Destination country or state
• Time-stamps at the beginning & end of each step in the supply
chain
Note: JMP was able to process large amounts of data without performance issues (files sizes from
~70MB up to ~300MB)
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Global Operations – Fulfillment & Logistics
JMP® distribution & percentiles charts depicted
overall process capabilities and variability
• Distribution charts were used to measure mean & variation of the
lead-times
– By LOB
– By Product Family
– By each stage in the process and by aggregated stages
• Percentile charts were used to measure the degree of predictability
in each case
Overall Lead Time
(OE-SC)
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Percentiles
12
98%
10
Calendar
Days
Goal
90%
8
75%
6
50%
could ship within
the goal
 Variability
4
2
2.4
0
LOB-A
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 50% of orders
LOB-B
prevents
predictability
Global Operations – Fulfillment & Logistics
Charts at stage level provided additional clues
for how to address the next part of the analysis
LOB-A Cycle Time per Stage
7
6
Percentiles
5
Calendar
Days
4
98%
90%
3
75%
2
50%
1
0
OE - IP
IP - TP
TP Shuttle
Shuttle FC
FC - SC
LOB-A Lead Time by Aggregated Stages
12
Calendar
Days
10
Percentiles
90%
75%
50%
4
2
0
OE-SC
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 Manufacturing & Fulfillment
stages are the ones with the
shortest cycle time (TP & FC)
 Process from TP-SC can
achieve our lead time goal at
95th percentile.
98%
8
6
Goal
 Variability in early stages of
the process needs to be
further investigated
IP-SC
 OE and IP contribute to
substantial increase of lead
time
TP-SC
Global Operations – Fulfillment & Logistics
ANALYSIS OF
VARIANCE
- Root Cause
Analysis
Global Operations – Fulfillment & Logistics
Analysis of Variance was used to understand
the factors driving variation at each stage
• Tested significance on several factors using JMP Analysis of Variance
– The analysis was done at LOB level for one and several factors at a time
OE-IP
Day of OE
Product Fam.
High Config.
IP-TP
Day of OE
Product Fam.
High Config.
TP-Shuttle
Shuttle-FC
Day of OE
Product Fam.
High Config.
Day of TP
Day of Shuttle
Facility
FC-SC
Order size
Facility
Day of FC
International
Factors Examined at Each Stage
Note: Financial hold and orders with staggered delivery requested by the customers
were known factors driving variation at OE-IP, thus, we did not include them in this
analysis
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Global Operations – Fulfillment & Logistics
Degree of impact for each factor was determined
by comparing the Means across factors levels
Analysis of Variance
Source
FAMILY_DESC
Error
C. Total
DF
8
315330
315338
Sum of Squares
45244.14
520511.47
565755.62
Mean Square
5655.52
1.65
F Ratio
3426.158
Prob > F
0.0000
Means for Oneway Anova
Level
Prod Fam-1
Prod Fam-2
Prod Fam-3
Prod Fam-4
Prod Fam-5
Prod Fam-6
Prod Fam-7
Prod Fam-8
Prod Fam-9
OE - IP
Factor
Product Type
Prod-Typ + OE-Day
High-config.
Day of OE
Number
19316
34934
917
140694
67821
125
4979
3236
43317
LOB-A
Impact
High
Med
No
No
Mean
2.32419
1.06997
2.30219
0.93412
0.77275
0.75548
2.03927
1.17875
1.14538
Std Error
0.00924
0.00687
0.04243
0.00343
0.00493
0.11492
0.01821
0.02259
0.00617
Lower 95%
2.3061
1.0565
2.2190
0.9274
0.7631
0.5303
2.0036
1.1345
1.1333
Upper 95%
2.3423
1.0834
2.3853
0.9408
0.7824
0.9807
2.0750
1.2230
1.1575
Comments
Average for some families > 2X
Unexpected higher Avg. for high-vol fam. when OE = Wed & Thurs (LOB-A)
Not relevant for LOB-A
Not relevant for LOB-A
High
Med
Low
No
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Global Operations – Fulfillment & Logistics
Impact for all factors & interactions tested at
each stage were classified for each LOB
Impact of Factors for LOB-A
OE-IP
Factor
Product Family
Prod-Fam + OE-Day
High-config.
Day of OE
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IP-TP
TP-Shuttle
Impact
Factor
Impact
Factor
Impact
High
Med
No
No
Day of OE
Product Family
High-config.
Med
High
No
Order size
Product Family
High-config.
Day of TP
Med
High
No
Med
Shuttle-FC
Factor
Day of Shuttle
Facility
FC-SC
Impact
Factor
Impact
Med
Med
Order size
Facility
Day of FC
High-config.
International
High
Med
Med
No
High
Global Operations – Fulfillment & Logistics
Findings of Analysis of Variance highlighted
a potential solution to the problem
• Attributes of
the orders
drive different
lead-times
•
Factors such as Product family,
Configurability, and International drive
legitimate lead time impact due to
differences in their work content
•
Impact of some factors could be mitigated
by process changes
•
Products with a standard platform and low
level of customization were the ones having
the shortest cycle time
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• We need to
have different
lead time
goals per type
of order
Global Operations – Fulfillment & Logistics
EXPERIMENTAL
DESIGN
- Proposed
Solution
Global Operations – Fulfillment & Logistics
Experimental Design was proposed to
measure and predict orders’ lead-time
• Experimental design can be set up by varying the
attributes associated to the orders (factors’ levels)
• Estimated lead-times (responses) should be monitored
and maintained regularly due to ongoing changes of
processes & products offerings
Example of Experimental Design
Factor
Level
1
2
3
4
:
:
71
72
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Prod Fam
Std New
1
1
1
1
:
:
1
1
Day of OE
High Config.
Ord Size
International
Response
M-T
F
S-S
N
Y
Sm Med Large N
Y LeadTim e (OE-SC)
1
1
1
1
LT-1
1
1
1
1
LT-2
1
1
1
1
LT-3
1
1
1
1
LT-4
:
:
:
:
:
:
:
:
1
1
1
1
LT-71
1
1
1
1
LT-72
Global Operations – Fulfillment & Logistics
We can match customer needs with process
capabilities to estimate lead times
For some customers needs, defined by the attributes of their orders,
we should be able to provide the right lead time expectation
Type 1 (sweet spot):
Need systems very fast
on standard platform
Monitor & Control Lead Times
Deliver
Customers Expectations
Type 2:
Customer
Needs
Need systems with special
services & customization and
are willing to wait more time
Type 3:
Need staggered delivery or the
latest technology (new
products) and are comfortable
with long lead times
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Global Operations – Fulfillment & Logistics
We tested proposed solution to get desired
lead time with 95% predictability
• We tested the lead-time on several
products with standard
configurations and conditions
established by Type-1 customers
(sweet spot)
• Results still showed variation
preventing us achieve the desired
lead-time on the 95% of the orders
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JMP graphical tracing
feature was very
helpful to uncover the
hidden cause of delays
across the supply
chain
Global Operations – Fulfillment & Logistics
Orders that could move fast through the supply
chain showed higher lead times than our goal
Distributions
OE_IP
TP_Shuttle
IP-TP
1 16 2
0 1 2 3 4 5 6 7 8 9 10 11 12 130 14 15
Shuttle-FC
3
4
5
6 0
1
• By selecting the first class in
the first histogram (OE-IP),
we could trace the orders
on the data files of the
other histograms
2
3
4
5
6
7
OE-SC
FC-SC
Variation
prevented us
achieve the
95%
predictability
2
3
4
5
0 61
2
3
4
5
6
7
8 19 2103 11
4 5 6 7 8 9 10
12 14 16 18 20
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• After several iterations
narrowing the search, we
could find the root cause of
the unexpected delays
FINDING:
The affected orders were
not being processed on a
first-in, first-out sequencing
Goal
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Global Operations – Fulfillment & Logistics
CLOSING
THOUGHTS
Global Operations – Fulfillment & Logistics
Reinforcing First-in, First-out (FIFO) sequencing
is key to achieving 95% predictability
• JMP graphical & tracing capabilities helped us uncover the hidden
issue: Some orders were not being processed with FIFO sequencing
• Issue was communicated to associated teams for a prompt
resolution
• A second simulation was run assigning corrected lead time to
affected orders, as if they were processed FIFO
• After the fix, we found that we could achieve the desired lead time
on the targeted product with 95% coverage
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Global Operations – Fulfillment & Logistics
Summary & Conclusions
• Global supply chains create a challenge to meet predictable lead
times for orders under the direct model
• Lead time of orders can be predicted based on the attributes of the
order
• Statistical analysis was essential for this study to highlight areas of
improvement and to propose a solution
• JMP's graphical tools were crucial as we uncovered the previously
hidden failure to use FIFO sequencing consistently when moving
orders across the supply chain
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Global Operations – Fulfillment & Logistics
Thank You!