2. 13-2
• Planning methodology
• Phase 1: Problem
definition and planning
• Phase 2: Data collection
and analysis
• Phase 3:
Recommendations and
implementation
• Supply chain analysis
methods and techniques
Overview of network and operational
planning
3. 13-3
• Decisions often require complex and data-intensive
analysis
– Complexity is due to
• Large no. of factors impacting total cost
• Range of alternative solutions available
– Data-intensiveness is due to
• Large amount of information required to evaluate each
alternative
– E.g. range of service alternatives, range of cost assumptions, range
of operating technologies
Planning methodologies enable evaluation of
options in response to customer behavior
4. 13-4
Generalized planning methodology
showing major phases of work
• Problem definition and
planning
• Data collection and
analysis
• Recommendations and
implementation
Figure 13.1 Research Process
5. 13-5
Problem definition and planning provides
the foundation for the overall analysis
Feasibility assessment
• Analyze the current situation
• Develop supporting logic
• Estimate the cost-benefit to proceed
Project planning
• State objectives of proposed changes
• State constraints to scope of study
• Establish measurement standards
• Select analysis techniques
• Create a project work plan
6. 13-6
• Requires an
– Internal operational review
– Market assessment
– Technology assessment
• Tables in text illustrate topics of
inquiry for this work
– See Tables 13.1, 13.2 and 13.3
• Situational analysis should
determine existing capabilities
and help define improvement
potential
Feasibility assessment begins with analysis
of the current situation
7. 13-7
• Identify the value proposition to justify
investment in detailed research and
analysis
• Critical fact-based evaluation of
current procedures and practices
– What is working well?
– What areas can we improve?
• Identify potential alternatives
– Define current operations
– Identify likely design alternatives
– Suggest innovative approaches
Develop a supporting logic to integrate the
findings from the current state analysis
• Keep, but prefer 2 data centers. Simplifies operations for same acquisition costs
• NOTE: Modified this alternative to use as contingency if facility acquisition fails
3 Data Centers – Acquire New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
3 Data Centers – Acquire New, DR outsourced
• Cost is too high compared with other alternatives
• Time is too long compared with other alternatives
3 Data Centers – Build New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
3 Data Centers – Build New, DR outsourced
• Keep
2 Data Centers – Acquire New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
2 Data Centers – Build New, DR outsourced
• Cost is too high compared with other alternatives
• Time is too long compared with other alternatives
2 Data Centers – Build New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
2 Data Centers – Acquire New, DR outsourced
• Risk is not mitigated by remaining in existing facilities (common power grid, proximity to terrorist
target)
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
Expand Site and Enhance Existing Facilities –
DR outsourced
• Risk is not mitigated by remaining in existing facilities (common power grid, proximity to terrorist
target)
Expand Site and Enhance Existing Facilities –
DR in house
Rationale Description
Alternative Description
• Keep, but prefer 2 data centers. Simplifies operations for same acquisition costs
• NOTE: Modified this alternative to use as contingency if facility acquisition fails
3 Data Centers – Acquire New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
3 Data Centers – Acquire New, DR outsourced
• Cost is too high compared with other alternatives
• Time is too long compared with other alternatives
3 Data Centers – Build New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
3 Data Centers – Build New, DR outsourced
• Keep
2 Data Centers – Acquire New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
2 Data Centers – Build New, DR outsourced
• Cost is too high compared with other alternatives
• Time is too long compared with other alternatives
2 Data Centers – Build New, DR in house
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
2 Data Centers – Acquire New, DR outsourced
• Risk is not mitigated by remaining in existing facilities (common power grid, proximity to terrorist
target)
• Outsource provider does not guarantee recovery
• Shared recovery over 1,000 miles does not work due to latency sensitive applications
Expand Site and Enhance Existing Facilities –
DR outsourced
• Risk is not mitigated by remaining in existing facilities (common power grid, proximity to terrorist
target)
Expand Site and Enhance Existing Facilities –
DR in house
Rationale Description
Alternative Description
8. 13-8
• Benefits should be
estimated for
– Service improvements
– Cost reductions
– Cost prevention
– “Low hanging fruit”
opportunities
Estimate the project’s potential benefits and
risks
Illustration of sample risks defined for each alternative
2 global data
centers in US
RY – Close WHS – Upgrade
(Test/DR)
WP – Close
New site
(Prod/Dev)
RY – Keep
(Dev)
WHS – Upgrade
(Prod/Dev)
WP – Upgrade
(Test/DR)
WHS – Expand
(Prod)
Expand Site and
Enhance Existing
Facilities
3 global data
centers in US
RY – Close WHS – Upgrade
(Test/DR)
WP – Keep
(Dev)
New site
(Prod)
1
1
2
2
3
3
Risks
• Collocated with two hazardous material sites (RY and WP)
• Facility issues with RY (leaking roof)
• RY data center in flight path for Linden/EWR airport
• Limited expansion possibilities
• High operational complexity drives down service quality
• Sub-optimal DR
• Concentrated proximity to Manhattan and Philadelphia
• Same power grid for all sites
Risks
• Collocated with two hazardous material sites (RY and WP)
• Facility issues with RY (leaking roof)
• RY data center in flight path for Linden/EWR airport
• Limited expansion possibilities
• High operational complexity drives down service quality
• Sub-optimal DR
• Concentrated proximity to Manhattan and Philadelphia
• Same power grid for all sites
Risks
• Disruption, transition and change management (some people
issues)
• Network impact (mitigated by deliberate design)
Risks
• Disruption, transition and change management (some people
issues)
• Network impact (mitigated by deliberate design)
Risks
• Collocated with one hazardous material site (WP)
• Disruption, transition and change management (less than
alternative 2)
• Network impact (mitigated by deliberate design)
Risks
• Collocated with one hazardous material site (WP)
• Disruption, transition and change management (less than
alternative 2)
• Network impact (mitigated by deliberate design)
High
Low
Medium
9. 13-9
• State objectives of
proposed changes
• State constraints to scope
of study
• Establish measurement
standards
• Select analysis techniques
• Create a project work plan
Project planning involves these specific
tasks
10. 13-10
• Should define market segment, the time frame for change and
specific performance expectations
• Example objectives
– Provide 100 most profitable customers with perfect order performance
on all orders
– All other customers receive
• 99% inventory availability for category A products
• 95% inventory availability for category B products
• Delivery of 98% of all orders within 48 hours of placement
Statement of objectives should be stated
specifically and in measurable terms
11. 13-11
• Defines the specific organizational elements to be retained
in current system
– Facility, alliance, resource, system, procedural or channel
constraints
• Common examples
– Hold existing manufacturing facilities and product mix constant
– Omit some divisions from a centralized logistics system
• “Why study things we don’t plan to do anything about?”
Statement of constraints should identify
restrictions placed by senior management
12. 13-12
• Standards should
adequately reflect a total
system performance view
– Avoid a suboptimal focus
on logistics functions
• List assumptions that
support standards
• How is each cost
component to be
quantified?
Measurement standards direct the analysis by
listing assumptions about cost and performance
13. 13-13
Develop a project work plan for the
remaining phases of the study
• Schedule of tasks
• Resource requirements
– Personnel
– Data collection and
analysis
– Analysis tools
• Meeting schedules
– Updates to share progress
with executives
Update 2 to ISLT
(12 Aug)
Update 1 to ISLT
Final Case
(29 Aug)
14 Jul 21 Jul 28 Jul 4 Aug 11 Aug 18 Aug 25 Aug
7 Jul
30 Jun
23 Jun
Data Center
Data Center
Facilities
Facilities
Requirements
Requirements
Project
Project
Sep
Final
documents
(9 Sep)
Describe the Need
in Business Terms
Evaluate Alternatives
Communicate Progress and Results
Kickoff
(23 Jun)
Kickoff
(23 Jun)
Workshop
(7 Jul)
Workshop
(7 Jul)
Workshop
(18 Jul)
Workshop
(18 Jul)
Workshop
(21 Jul)
Workshop
(21 Jul)
Workshop
(29 Jul)
Workshop
(29 Jul)
Workshop
(14 Aug)
Workshop
(14 Aug)
Workshop
(27 Aug)
Workshop
(27 Aug)
Preview Case
(25 Aug)
Illustration of sample project work plan with meeting schedule
14. 13-14
Data collection and analysis activities
Assumptions and data collection
• Define analysis approach and select
techniques
• Define and review assumptions
• Identify data sources
• Collect data
• Validate data
Analysis
• Develop questions for analysis
• Validate the baseline analysis
• Analyze each alternative
• Complete sensitivity analysis
15. 13-15
• Spreadsheet and statistical
software availability have
increased use of these
techniques
• Examples
– Determine the inventory/service
trade-offs using safety stock and
fill rate formulae
– Determine the order cycle time
that required to deliver 95% of
customer orders
– Determine the transportation
dollar benefits for consolidating
LTL orders into TL orders
Analytical approach uses numerical tools to
evaluate each alternative
16. 13-16
• Conduct experiments using a
physical or numerical model of
the real system
– Understand overall system
behavior over time
– Use to evaluate operations under
different strategies
• Appropriate when
– Limited number of variables are
evaluated
– Need a more realistic
representation of the process
– Need customer order or SKU
level of detail
Simulation is widely used, particularly when
significant uncertainty is involved
17. 13-17
• Appropriate for
– Problems where objectives and
constraints can be expressed in
mathematical terms
– Alternatives involving sweeping
changes to the logistics systems
• Limitations include
– Demand on computing resources
– Models are smaller in scope than
simulations
• Example
– Determine the best location for
distribution facilities subject to
meeting supply, demand, and
delivery time constraints
Optimization uses linear programming to
evaluate and select best alternative
18. 13-18
• Business
– E.g. relevant market, consumer
and product trends, resource
availability, and competitive
actions
• Management
– E.g. alternative warehouse
locations, transport modes,
ownership arrangements,
logistics processes, fixed and
variable costs
• Analysis
– Define constraints and limitations
to fit the problem to the technique
selected
Define and review assumptions
20. 13-20
• What are the sources for
– Sales and customer
orders?
– Specific customer data that
includes a spatial
dimension?
– Manufacturing and
purchasing costs?
– Transportation data?
– Benchmarking data on
competitive capabilities and
flow?
Identify data sources to fit the analytical
technique
21. 13-21
• First, develop questions
about alternatives and the
range of acceptable
uncertainty
• Second, validate the
technique and model using
validation data
• Third, repeat the analysis for
each alternative to be
evaluated
• Finally, the best-performing
alternatives can be
evaluated for sensitivity to
other factors or scenarios
Analysis involves use of technique and data
to evaluate logistics alternatives
22. 13-22
Recommendations and implementation
Development of recommendations
• Identify best alternative
• Estimate costs and benefits
• Develop risk appraisal
• Develop presentation
Implementation
• Define implementation plan
• Schedule implementation
• Define acceptance criteria
• Implement
23. 13-23
• Identify best alternative
• Estimate costs and
benefits
• Develop risk appraisal
• Develop presentation
Recommendations to management are developed
through critical review of the analysis results
Fit to
Principles
Slow Fast
High
Low
Speed to Execute
$95MM
Expand & Enhance
Existing - Build
$95MM
Expand & Enhance
Existing - Build
$76MM
Expand & Enhance Existing –
Build & Outsource DR
$76MM
Expand & Enhance Existing –
Build & Outsource DR
2 Data Centers – Co-locate &
Outsource DR
2 Data Centers – Co-locate &
Outsource DR
3 Data Centers -
Build
$115MM
3 Data Centers -
Build
$115MM
3 Data Centers – Build &
Outsource DR
$91MM
3 Data Centers – Build &
Outsource DR
$91MM
2 Data Centers - Build
$133MM
2 Data Centers - Build
$133MM
2 Data Centers – Build
& Outsource DR
$114MM
2 Data Centers – Build
& Outsource DR
$114MM
3 Data Centers -
Acquire
$49MM
3 Data Centers -
Acquire
$49MM
$49MM
2 Data Centers -
Acquire
$49MM
2 Data Centers -
Acquire
Preferred Alternatives
3 Data Centers – Co-locate &
Outsource DR
3 Data Centers – Co-locate &
Outsource DR
Sample presentation visual showing best alternative
24. 13-24
• Define implementation plan
– Events, activities and decisions
with dependent relationships
• Schedule implementation
– Timeline of plan details
– E.g. acquire facilities, negotiate
agreements, mobilize teams,
and conduct training
• Define acceptance criteria
– How will we measure success?
• Implement the recommendation
– Establish controls to monitor
plan and acceptance criteria
Implementation is necessary to realize any
business benefits from the recommendations
25. 13-25
• Design decisions
• Design logic
• Inventory decisions
• Transportation decisions
• Freight lane analysis
• Inventory analysis
Methods and techniques of analysis for
supply chain decisions
26. 13-26
Design decisions focus on selecting number and
location of plants, warehouses and other nodes
• Determine total costs and trade-offs
for alternative channel strategies,
activity outsourcing or offshoring
decisions
• Typical questions include
– Where should plants and distribution
centers be located?
– Which market areas should be served
by each distribution center?
– Which product line should be stocked
at each warehouse?
– What marketing channels should be
used to serve international markets?
– Which service providers should be
used for long-term contracts?
27. 13-27
• Optimization models consider a range of complex data to evaluate
alternatives
– Aggregate customer demand
– Aggregate supply availability
– Product and information flows at each stage
– Transportation alternatives and costs
– Other variable costs
• Major problems with linear programming
– Need explicit functional relationships for full range of design options
– Only as valid as the design problem definition
– Often limited by number of stages in the supply chain and problem size
Design logic defines the method used to select
from a number of available options
29. 13-29
• Markets defined by geographic
segments
• Products defined by the number of
stock keeping units required
• Network defines channel members
and locations including current and
proposed
• Customer demand as shipment
volume by market geography
• Transportation rates for inbound and
outbound volume
– For each shipment size
– For each potential transportation link
• Variable and fixed costs
• Tax incentives
Data requirements for supply chain analysis
include the following key elements
30. 13-30
Illustration of how the US might be
segmented in market areas
Figure 13.3 Supply Chain Network
31. 13-31
Illustration of a network definition for
channel of industrial and retail customers
Figure 13.4 Channel Network Example
32. 13-32
• Baseline analysis is done
first to validate cost and
establish credibility of the
analysis
• Other alternatives are
modeled and analyzed
• Results can be compared
to baseline to identify
performance
improvements
Evaluation of alternatives
Baseline Model
Alternative Models
35. 13-35
• Treatment of inventory carrying
cost
• Assumptions of shipment sizes
over range of alternatives
– Constant or varies with change in
number of warehouses
• Focus of analyses
– Expanding boundaries of supply
chain members
– Minimize total cost vs. maximize
profit
– Periodic vs. ongoing
Concerns of supply chain design tools
36. 13-36
Illustration of the analytic inventory
concept to make inventory decisions
Figure 13.7 Analytic Inventory Overview
Results of analysis
37. 13-37
Illustration of the simulation approach
to inventory analysis
Figure 13.8 Inventory Simulation Overview
Results of analysis
38. 13-38
• Strategic routing decisions
– Identify long-term fixed transport
modes
• Monthly or yearly routes
• Tactical routing decisions
– Allocate resources for the short-
term
• Daily or weekly routes
• Objective is to minimize the
combination of vehicles, hours
and miles required to deliver
product
Transportation decisions range from
strategic to tactical in scope
40. 13-40
Transportation analysis techniques
• Heuristic approaches
– Use rule-of-thumb techniques to
sequentially add and delete stops
• Exact approaches
– Use linear programming to
identify best routes
• Interactive approaches
– Use simulation, cost calculator or
graphics capability to support
interactive decision process
• Combination approaches
– Blend of the three approaches is
very effective
• Criteria for evaluating
approaches
– How general is the
approach?
• E.g. special situations,
multiple depots, time
windows, vehicle capacities
– How accurate is the
approach?
• Is it a close approximation of
performance characteristics?
41. 13-41
• Network defines all possible
routes
• Demand data defines periodic
customer pickup and delivery
requirements
• Operating characteristics
define
– Number of vehicles
– Vehicle limitations
– Driver constraints
– Operating costs
Data requirements for transportation
analysis
42. 13-42
Freight lane analysis seeks to balance volume
between origin and destination points
Figure 13.10 Example of Triangular Freight Lane
Table 13.6 Freight Lane Analysis of Monthly Movements
Results of analysis
• Develop additional volume between
Cincinnati and Chicago
– Move product sources to Chicago
– Alliance with shipper with no back-
haul
43. 13-43
Illustration of inventory analysis showing
key results for management review
Table 13.7 Typical Inventory Analysis Report
