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Integrated Logistics
Introduction to Insight
INSIGHT – Who We Are
> INSIGHT Started 1978> Extensive Supply Chain Design Experience> Professional Staff
• 35 employees• Average tenure – over 17 years experience
> Various Honors and Awards• CLM Distinguished Service Award
> US Offices• Manassas, VA• Bend, OR
> Emphasis on Research and Application
Supply Chain Software
> Supply Chain Design• SAILS
> Tactical Modules• Transportation Planning – SHIPCONS II• International Trade – GSCM
> Components• Labor Scheduling, Master Production Planning,
Supply Planning, Service Resource Scheduling, Dynamic Sourcing
Abbott Laboratories
Allegiance Healthcare
Bristol-Myers Squibb
Exxon Mobil (5 continents)
Exxon Mobil Chemical
Pfizer
Johnson & Johnson
Ross Laboratories
Monsanto (Flexsys NV)
BP Amoco
Cytec
BASF
Pennzoil
PPG Industries
Ipiranga
IMC Agrico
McKesson HBOC
Solutia
Oil/Chemical/Medical
Mars
Pepsi-Cola
Pepsi-Cola Int’l
Pepsi Bottling
Ralston Purina
Avon Products
Nabisco
Clorox
Unilever
Kraft Foods
Dean Foods
Ameriserv, Inc.
CSI
Frito Lay
Frito Lay Int’l
Colgate
Perrier
Dr. Pepper - 7Up
Procter & Gamble
ConAgra
Walker Gillette
Borden Foods
Food & Beverage/CPG
Ferguson Enterprises
Toyota Motor Sales
Toyota Parts
Goodyear Tire & Rubber Co
Case New Holland
Case Parts
Georgia Pacific
Sears
Ingram Books
Purolator
Potlatch
R.R. Donnelly
Toyo Engineering
GE Service Parts
GE Appliances
Manufacturing/Parts Distribution
Consultants/3PL’s
Accenture
KPMG Peat Marwick
Frigoscandia
Norfolk Southern
Pricewaterhouse Coopers
Defense Logistics Agency
APL
CSC
Mark VII
SABRE
Technology
Compaq IBM Global Services Motorola
Integrated Logistics
The Concept
CLM Definition 1995
Logistics is the process of planning, implementing,and controlling the efficient, effective flow and storage of goods, services, and related information from point of origin to point of consumption for the purpose of conforming to customer requirements.
FW1
FW2
FW3
FW4
FW5
P1
P2
P3
Integrated Logistics System Design ModelIntegrated Logistics System Design Model
Raw MaterialsRaw Materials Finished ProductsFinished Products
ReplenishmentReplenishment OutboundOutboundInboundInbound
PW1
PW2
PW3
S1
S2
TransferTransfer
CZ1
CZ5
CZ6
CZ2
CZ3
CZ4
Potential Network SchematicPotential Network Schematic
Evolution of Thought and Practice
• Individual Dispersed Functions
Conflictingobjectiveswithin thelogisticsfunction
TRANSPORTATION
WAREHOUSING INVENTORY
Evolution of Thought and Practice
• Individual Dispersed Functions
• Integration Within Distribution
Conflictingobjectiveswithin thefirm
Logistics
Manufacturing Purchasing
Evolution of Thought and Practice
• Individual Dispersed Functions
• Integration Within Distribution
• Integration Across Corporate Functions
Evolution of Thought and Practice
• Individual Dispersed Functions
• Integration Within Distribution
• Integration Across Corporate Functions
• Integration Across Supply Chain, finding win-wins with Suppliers and Customers
Network Redesign Business Questions> How many distribution centers (D.C.s) should we have? > Where should the D.C.s be located? > Which customers should be served by each D.C.? > How do you best balance inventories against customer service needs
and distribution costs?> Should we contract for warehousing services or operate our own D.C.s?> Should pool points be used and where should they be located? > What do you gain by plant direct shipping? > Should all D.C.s carry all products or should they be specialized by
product line?> Where should my plants be located?> Which product lines should be produced at each plant and how much? > Which suppliers should be used?
Do you need a Network Redesign?
> You would like answers to some of the 11 “business questions”
> You have never redesigned your network(s) or it has been many years since the last redesign was completed
> Multiple divisions exist within the parent company and you are not leveraging Warehousing and/or Transportation.
> You are acquiring a company
Integrated Logistics
Process to Redesign Supply Chains
Introduction
> Redesigning a Supply Chain is a PROCESS
> The SAILS software is a TOOL used in this process
> When you’re redesigning a Supply Chain, a good process is beneficial.
> This is the process that I’ve used many times, with good results, to redesign Supply Chains.
The Process
> Establish Project Management
> Define Objectives and Scope
> Design Model
> Data Collection
> Model Validation
> Optimization
> “What If” and Sensitivity Analysis
> Recommendation
> Implementation
> Post-Implementation Review
Project Management
> Establish Project Sponsor
• Best experiences with CFO or CEO
> Why has the project been initiated?
• What is the “compelling event”?
• What needs improving?
- Too much Inventory
- Customer Service lead times need tightened
- Logistics Costs too high
Project Management
> Executive ("Steering") Committee required?
• Establish cross-functional team (MIS, Logistics, Sales, Manufacturing, Customer Service, Purchasing, R&D, Finance, etc.), usually VP or Director level:
- Break down organization "silos"
- Create a better solution
- Improve the probability that the solution will be accepted by the entire organization
• Meet every 6 - 8 weeks
Project Management
> Establish full-time Project Manager > Establish Working Committee
• Establish team, usually Manager level, with "hands on" responsibility to spend 25 to 50 percent working on this project
• Meet "formally" every 2 - 3 weeks> Utilize Steering Committee to create “Task Forces”:
• Customer Service• Product Compatibility and R&D Requirements
(temperature, etc.)• Inventory Carrying Cost Methodology• Accounting Issues, such as Fixed vs. Variable
Warehousing Costs
Objectives and Scope
> Objectives (and Goals)• Why has the project been initiated? (What needs
improving)?• What business question(s) do you need answered?• Define as many "What If" and Sensitivity Analysis questions
to be answered, as possible • STAY STRATEGIC
> Scope• Which Business Units included?• Due to product incompatibilities, do multiple Supply Chains
need to be designed? How many?• Outbound (and Inbound(?))?• U.S. (and Canada(?) and Mexico(?))?• Include/exclude import/export (port)?
Model Design
> To design the model correctly, the objectives, the scope, and as many "What If" and Sensitivity Analysis questions, as possible, should be defined. Failure to do this, will increase the risk that the model will not be designed correctly, requiring extensive efforts to redesign the model later in the project.
> First step, sketch the current flows of the existing supply chain(s), defining all the “links”. Discuss what future flows should be allowed
> How many supply chains need to be designed? Sketch them.
Model Design
> For each supply chain (model):• How many echelons? • Current and candidate D.C.s, cross-docks, etc.• How do you ship products (Small Package, LTL, TL,
Pool, Pick-up, Rail, etc.)• D.C., cross-dock, etc. missions• Customer Service guidelines, current, proposed
and “what if”• Etc., etc.
> Roles and responsibilities of each member of the Working Committee. Assign tasks and due dates.
Data Collection> Collect:
• Network Description- Locations (Customers, D.C.s, Plants, Suppliers)
• Transportation Costs- Inbound, Replenishment, Transfer, Outbound
• Demand Data- Every Line Item from Every Order for a year
• Facility Data (Suppliers, Plant and D.C.)- Fixed & Variable Costs- Capacities
• Eligibility- D.C.s- Product Master with Production Source(s) Identified - Suppliers
> VERIFY all data to ensure that it is valid
Model Validation
> First, replicate flows (volumes)
• MY GOAL --- 99.75+% accurate
> Second, replicate costs. (This is an iterative process, until the variance between actual and the model reach an acceptable level).
• MY GOAL:
- Nationally, within 1 to 2 percent of “unexplained” variance.
- By facility, within 5 percent of “unexplained” variance.
Model Validation
> (If the “unexplained” variance is at the 5 - 10 percent range, no confidence exists when an optimization run shows a 10 percent cost reduction. It is not until the “unexplained” variance is in the 1 to 2 percent range that an optimization run showing a 10 percent cost reduction can be believed).
> Develop spreadsheet, starting with the model (validation) costs, adjusting for known (“explained”) variances, and comparing to actual costs
Model Validation
> “Explained” Variances (examples):• Transportation Costs
- Returns/Product Recall- Damaged- Accessorial (Fuel, Delay, Lumpers, etc.)- Expedited Transportation- Accounting Anomalies
• Warehousing Costs- Different Inventory Turns- Overflow Warehousing- Accessorial (Special Services, extra shifts, overtime,
etc).- Accounting Anomalies
• Plant Costs
Optimization
> Optimize the Supply Chain, meeting the customer service Requirements.
(This should occur very quickly, a
majority of the analysis should be "What If" and Sensitivity analysis).
“What If” and Sensitivity Analysis
> Most common Analysis:
• Sensitivity Analysis:
- Distribution cost vs. number of D.C.s- Distribution cost vs. Customer Service
– Cost for improved service
– As service is improved, are current D.C.s still being utilized
“What If” and Sensitivity Analysis
> Most Common Analysis (continued)• “What If” Analysis:
- Impact of inflation (D.C. vs transportation costs)- Growth Analysis (can handle forecasted growth)- Impact of plant capacity expansion (new plants)- Impact of new product introduction
– Which plant– 1 vs. 2 plants
- D.C. capacity expansion- Alternative echelon networks
– Plant direct– Cross-Docks / UPS Zone Skipping
- Implementation priority analysis
Recommendation
> A recommendation should be made, including:
• Supply Chain ("flow" and costs), AS IS
• Supply Chain ("flow" and costs), TO BE
• Expected benefits
• What was analyzed but didn't produce benefits
• Implementation plan, including
- Priorities- Technology
• Organizational impact
Implementation
> Additional time should be planned for further "What If" and Sensitivity Analysis to assist the implementation team.
(For example, the model recommends a D.C. in Omaha. The implementation team can not find the space in Omaha at a reasonable price. What is the additional transportation cost if the D.C. were in Kansas City or Des Moines)?
> Now is the time to support the implementation with tactical analysis.
Post-Implementation Review
> I’m a strong believer that 6 to 12 months after the implementation, the project should be evaluated and the actual benefits quantified.
> Most of my recommendations have reduced the number of D.C.s, so more volume was going through fewer locations. Due to increased leverage (transportation and warehousing), the actual benefits usually exceed what the software predicted.
• All projects 5 to 15 percent Logistics savings• Majority in 8 to 12 percent range
Integrated Logistics
The Optimizer
Too often users don’t ask enough questions about what the solver does and how. They seem to assume that if a program can make pretty pictures, it must also be able to get good answers.
In short, THEY BUY THE PICTURES, NOT THE SOLUTIONS!
CZ1
CZ2
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DC1DC1
DC2DC2
PLANT 1PLANT 1
PLANT 2PLANT 2
00
55
44
22
33
33
44
22
00
11
50,00050,000
100,000100,000
50,00050,000
SAMPLE PROBLEM
Capacity: 60,000Capacity: 60,000
Capacity: Capacity:
CZ1
CZ2
CZ3
DC1DC1
DC2DC2
PLANT 1PLANT 1
PLANT 2PLANT 2
00
55
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00
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50,00050,000
100,000100,000
50,00050,000
HEURISTIC SOLUTION 1HEURISTIC SOLUTION 1
““LEAST OUTBOUND COST”LEAST OUTBOUND COST”
140,000140,000
60,00060,000
Inbound costInbound cost $820,000$820,000
Outbound costOutbound cost $150,000$150,000
TotalTotal $970,000$970,000
CZ1
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DC1DC1
DC2DC2
PLANT 1PLANT 1
PLANT 2PLANT 2
00
55
4422
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00
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50,00050,000
100,000100,000
50,00050,000
HEURISTIC SOLUTION 2HEURISTIC SOLUTION 2
““LEAST TOTAL FLOW COST”LEAST TOTAL FLOW COST”
50,00050,000
60,00060,000
Inbound costInbound cost $570,000$570,000
Outbound costOutbound cost $200,000$200,000
TotalTotal $770,000$770,000
90,00090,000
The key to good analysis is the range and quality of alternatives generated for evaluation.
Solver Technology: Heuristics
Characteristics• common sense consideration of limited alternatives• not guaranteed to find best solution• solution dependent upon quality of decision rules• run-to-run comparisons unreliable
Applications
– crew scheduling– vehicle routing– shipment planning
Solver Technology: Simulation
Characteristics• imitates sequence of events/conditions over time• no attempt to find best solution• limited to process evaluation• difficult to validate• expensive to develop, maintain, and run• run-to-run comparisons very difficult
ApplicationsApplications
– queuing problemsqueuing problems– inventory controlinventory control– plant/DC operationsplant/DC operations
OPTIMIZATION generates and considers all alternatives in a given scenario --
with heuristics and expert systems alone, many alternatives are never envisioned, much less evaluated!
Solver Technology: Optimization
Characteristics• evaluates all possible alternatives• guaranteed to find best solution• run-to-run comparisons reliable• not widely available
ApplicationsApplications– network designnetwork design– production planningproduction planning– cash flow planningcash flow planning
SOLVER TECHNOLOGY
USING MIXED INTEGER LINEAR PROGRAMMING
*SAILS is TRUE OPTIMIZATION
(*RESEARCH PUBLISHED IN REFEREED ACADEMIC JOURNALS)
CZ1
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DC1DC1
DC2DC2
PLANT 1PLANT 1
PLANT 2PLANT 2
00
55
4422
33
33
44
22
00
11
50,00050,000
100,000100,000
50,00050,000
OPTIMAL SOLUTION
“TRUE LEAST COST”
140,000140,000
60,00060,000
Inbound costInbound cost $120,000$120,000
Outbound costOutbound cost $470,000$470,000
TotalTotal $590,000$590,000
40,00040,000
60,00060,000
Good models are like bright lights
focused on dark corners.
Conventional wisdom is frequently wrong -- Management Science has shown this time and time again.
Integrated Logistics
SAILS Model
Multiple Stages of Manufacture
STAGE 1STAGE 1 STAGE 2STAGE 2
RawRaw
materials materials
inin
FinishedFinished
productsproducts
outout
Line 1Line 1 Line 1Line 1
Line 2Line 2
Line 3Line 3
Line 2Line 2
Line 3Line 3
RawRaw
materialsmaterials
IntermediateIntermediate
productsproducts
FinishedFinished
productsproducts
Important Model Features
Multiple stages of manufacture (conversions)Multiple stages of manufacture (conversions) Multiple processing lines per stageMultiple processing lines per stage N-echelons of distribution centersN-echelons of distribution centers Multiple cost functions per facilityMultiple cost functions per facility Sole source optionSole source option Facility status: fix/float optionsFacility status: fix/float options Multi-Time PeriodsMulti-Time Periods
PRODUCT AGGREGATION
Stock CodesStock Codes Product GroupsProduct Groups
TR 968-14TR 968-14
TR 472-10TR 472-10
TR 784-16TR 784-16
TR 968-14TR 968-14
TR 472-10TR 472-10
TR 784-16TR 784-16
EL 497-23EL 497-23
TR 968-14TR 968-14
TR 472-10TR 472-10
TR 784-16TR 784-16
CQ 491-79CQ 491-79
1. Tires1. Tires
3. Mechanical3. Mechanical
2. Electronics 2. Electronics
Product Groups1 2 3 4 5 . . . . . . . ICustomer
zones 1
2
3
4
5...
L
XX
Annual demand
DEMAND DATA: TARGET
Destinations1 2 3 4 5 . . . . . . . N
Origins11
22
33
44
55......
MM
XX
Average cost/cwtAverage cost/cwt
TRANSPORTATION DATA: TARGET
998888 6666
55
77 332222
1100
4444
GEOGRAPHIC AGGREGATION
1-DIGIT ZIP ZONE
UNITUNITVARIABLEVARIABLE
COSTCOST
VOLUMEVOLUME
TRADITIONAL CAPACITY LIMITSTRADITIONAL CAPACITY LIMITS
CapacityCapacityLimitLimit
UNITUNITVARIABLEVARIABLE
COSTCOST
VOLUMEVOLUME
“ELASTIC” CAPACITY LIMITS
CapacityCapacityLimitLimit
}
PenaltyPenalty
Integrated Logistics
Case Study
ADF, Inc.
> Manufacturer of consumer goods > Founded in 1927> Sales in 1980: $460mil> 12 major categories of product > 2 production technologies> 11,000 customers> 100,000 orders per year> 98% fill rate with 7 day order cycle> 5 plants and 17 distribution centers
Historical Situation - 1930
PlantDistribution centerMarket area
$
ADF DISTRIBUTIONCOST RELATIONSHIPS
1930 (est.)Transportationto Customers
InventoryCarrying Costs
Warehousing
Transportationto Warehouse
HISTORICAL SITUATION - 1940
PlantDistribution centerMarket area
P1P1
HISTORICAL SITUATION - 1950
PlantDistribution centerMarket area
P1P1, P2 P2
HISTORICAL SITUATION - 1960
PlantDistribution centerMarket areaLocal overflow warehouse
P1P1, P2 P2
HISTORICAL SITUATION - 1970
PlantDistribution centerMarket area
P1P1, P2 P2
P1P2
AT TIME OF STUDY
PlantDistribution centerMarket area
P1, P2 P2
P1
P2
P1
$
CURRENT ADF DISTRIBUTION COSTS
Transportationto Customers
InventoryCarrying Costs
Warehousing
Transportationto Warehouse
study1960 1970
PD/Percentof COGS
_
_
_
_
_2
10
8
6
4
6.5%
Actual8.2%
11.4%
DISTRIBUTION COSTS GROWINGFASTER THAN MANUFACTURING COSTS
_ _
DISTRIBUTION COSTSGROWING FASTER THAN SALES
Sales
Distribution
19701970 studystudy
P.D. CostsPercent of Sales
1970 - 5.8%study - 8.0%
$8 MM
$138 MM
$37 MM
$463 MM
INVENTORY TURNOVER DECLINING
Cost of Goods Sold
Finished Goods Inventory
1970 study
Inventory Turns1970 - 7.5study - 6.0
$13 MM
$97 MM
$54 MM
$324 MM
MANAGEMENT’S RESPONSES HAVE BEENINCREMENTAL AND SUBOPTIMAL
Impact on functional area
Arbitraryinventory cuts
Additionalwarehouses
Mode mix changes
Plant warehousespace usurped
Manufacturingcosts
Transportationcosts
Warehousingcosts
Inventorycosts
Customerservice/sales
MANAGEMENT OBJECTIVE
Fundamental question askedby management . . .
What production-distribution networkwill yield greatest return on assets,given all trade-offs in the system?
Specific Issues
> What are the appropriate customer service goals to pursue?
> How should inventory be stratified and positioned in the various levels of the production - distribution system?
> How many distribution centers should there be, where should they be, and what service areas should be assigned to each?
> Should new plant locations be opened and should the production mix among plants be changed?
> Which plants should provide which products to each warehouse and what mix of transportation modes should be used?
RECONFIGURED SYSTEM
PlantDist. center
P1, P2 P2
P1P2
P1
P1, P2
Change in:
Distribution Centers 17 9
Distribution Center Replenishment Flows 22 6
Plants 5 6
Financial Results
> Actual• Reduction in Distribution Costs of 20%
- Fewer DCs- Less Plant to DC freight- Less inventory
• Increase in ROA of 8% over an already favorable 12.5%
> Expected• Improvement in customer service/satisfaction• More streamlined network• Improved inventory deployment
If
• TL increases disproportionately vs. LTL
• LTL increases disproportionately vs. TL
• Service level (order cycle time) relaxed
• Unit production cost estimates at new plant low by >10%
• Cost of money under 10%
Outcome of Specific Contingency Analyses
Then
• West Coast plant more advantageous
• 3 more warehouses feasible
• 1 less warehouse feasible
• Logistics benefits of new plant negated
• 4 additional warehouses feasible
Network Evaluation Process
Plan & Launch Project
Generate Baseline
Optimizationof existingnetwork
Alternatescenario
definition
Alternatescenario
optimization
ManagementAnalysis
Financialgoals
Raw materialavailability
Manufacturingtechnology
Corporatepolicies/
strategiesServicegoals
Marketinggoals
analysis
Futuretransportation
costs
Integrated Logistics
Summary
