Supply-Chain Management:
A View of the Future
Leroy B. Schwarz
Krannert School of Management
Purdue University
Supported by e-Enterprise Center at Discovery Park
Outline
• Supply-Chain Management of “Yesterday”
– How Modeled
– How Practiced
• Supply-Chain Management of “Today”
– How Practiced
– How Modeled
Outline (cont.)
• Introduce Paradigm called:
“IDIB Portfolio”
• Describe My Vision of the “Future”of SCM
• Provide an Overview of 2 Projects
• Collaborative Decision-Making and Implementation
• Secure Supply-Chain Collaboration
SCM Models of “Yesterday”
• Took Centralized Perspective
– Assumed Single, Systemwide Objective
Function: F(x1, x2, x3, ...)
– Assumed System Information was:
• Available
• Omnipresent
– Assumed Implementation was “Contractible”
• Typical Results:
– Characteristics of the Optimal Policy for
Special Structures
• Clark & Scarf, ‘60
• Schwarz, ‘73
– Examination of Heuristics for More General
Structures
• Clark & Scarf, ‘62
• Roundy, ‘85
SCM Practice of “Yesterday”
• Single-Owner Chains Took a Centralized
Perspective
– Single Objective Function: F(x1, x2, x3, ...)
– De-Centralized Decision-Making
– Information: Not Available or, at best,
“Asymmetric”
– Implementation: De-Centralized; NOT
Contractible
• Consequently:
– “Supply Chains” Managed as Separate Entities,
regardless of their ownership
Ex.: Local Objective Functions: F1(x1), F2(x2), ...
• Examples
– USAF Logistics Command Consumable
Inventory System
– IBM Service-Parts Inventory System
Consequences of this:
==> Huge Buffers
– Raw, WIP, and Finished-Goods Inventories
– Capacity Buffers (e.g., understated capacity)
– Leadtime Buffers (e.g., overstated leadtime)
“Yesterday’s” Relationship:
“Mismatched”
• Models
– Too Specialized
– Required More Information than Practice Had
• Practice
– Inexperienced with Models & Computers
– Confused by Models
– Suspicious of Models
SCM Practice “Today”
• The Beginnings of “Real” SCM for SingleOwner Chains
– Ex:
Wal-Mart’s Retail Link
Target’s Partners OnLine
• Capabilities
– Broadcast SKU-level Data Across the Chain
– Observe Status ==> Implemetation
“Contractible”
• Results:
– Huge Reductions in Buffers ==> Lower
Operating Costs
– Improved Competitiveness
• Lower Prices
• More Customization
• Higher Availability
• Development of Technologies to Support
Multiple-Owner SCM
• Internet is Providing Experience
• E-Markets
– Providing Buyer-Supplier Linkages
• Data Standardization; e.g. RosettaNet
• Beginnings of SCM for Multiple-Owner
Supply Chains
– VMI, Quick Repsonse
– VICS’ CPFR Campaign
• Huge Challenges for Multi-Owner Chains
– Multiple — often Conflicting — Objective
Functions
– Technical Difficulties in Sharing Information
• SKU Identification
• Time-Frame
– Fear about Information Sharing
• Vertical “Leakage”
• Horizontal “Leakage”
SCM Models of “Today”
• Models with Multi-Ownership, Competing
Objective Functions, and Asymmetric
Information
– Roots in Economics
– 1980’s Work of Monahan, Pasternak
– Contemporary Work
• “Supply-Chain Coordination with Contracts”, G.
Cachon (forthcoming)
• “Information-Sharing and Supply-Chain
Coordination”, F. Chen (forthcoming)
• Models for Assessing the Impact of
Decentralized Decision-Making and/or
Asymmetric Information
– Ex: Lee, et al. “Bullwhip” Paper (MS 43:4)
• Results:
– Assessments of “Agency Loss”
• Non-bathtub Shaped Loss Functions
– Contracting Mechanisms to Improve/Optimize
Performance
Relationship “Today”:
“Out of Step”
• Models beginning to include ownership and
private-information issues, but
– Little Work on How to Share Information or
How to Collaborate on Decision-Making or
Implementation
– Ignoring the Development of More
Sophisticated “Centralized” Models
Relationship “Today”:
“Out of Step”
• Practice ready to “Dance” but No Model
“Partner”
– Using simple models based on “pull down”
menus in ERP systems
– “Swimming” in Data, but uncertain about how to
use it
What About the
Future
of SCM?
First.......
The IDIB Portfolio
a.k.a.
The Information, Decision-Making,
Implementation, Buffer Portfolio
“Managing” anything can be
viewed as 4 related activities:
•
•
•
•
Getting Information
Making Decisions
Implementing Decisions
Buffering against Imperfections in
information, decision-making, or
implementation
Every “Management System” is,
in fact, 4 Sub-Systems
• The Information System provides
information
• The Decision-Making System makes
decisions
• The Implementation System implements
decisions
• The Buffer System copes with imperfections
in information, decision-making, or
implementation
Each Sub-System has Cost and
Quality Characteristics
The Information System
– Quality Characteristics
•
•
•
•
•
Accuracy
Leadtime
Aggregation Level
Horizon
Etc.
– Cost: Increasing and Marginally-Increasing
with Quality
Each ... Characteristics (cont.)
The Decision-Making System
– Quality Characteristics
• “Optimality”; i.e., “how good”?
• Leadtime; i.e., “how long to make”?
• Etc.
– Cost: Increasing and Marginally-Increasing
with Quality
Each ... Characteristics (cont.)
The Implementation System
– Quality Characteristics
• Accuracy; i.e., conformance to decision
• Leadtime; i.e., “how long to implement”
• Etc.
– Cost: Increasing and Marginally-Increasing
with Quality
Each ... Characteristics (cont.)
The Buffer System
– Quality Characteristics
• Form
• Robustness
• Etc.
– Cost: Increasing and Marginally-Increasing
with Quality
IDIB “Portfolio”?
• Like a Financial Portfolio, the IDIB System
requires an investment of Dollars
• Like a Financial Porfolio, each Subsystem’s
Characteristics Should Complement the
Characteristics of the Others
– Ex: Robust Buffer System Complements an
Inaccurate Information System
– Ex: Tradeoffs Among Buffer Sub-Systems
Managing the IDIB Portfolio....
.... means changing the nature and quality of
its 4 sub-systems so that total portfolio cost
— which includes the cost of imperfect
buffering — is minimized
This is NOT Rocket Science!
Most Operations-Research
Models Ignore the IDIB Portfolio
• Example: The Newsvendor Model
– Information-System Quality Assumed
– Implementation is Ignored
– Select Decision-Rule to Minimize BufferSystem Cost
IDIB Portfolio View of
Newsvendor “Problem”
• The “Problem” is that acquistion/production
decsion must be made before demand
occurs
• What if:
– Production was instantaneous?
– Production Decision and Implementation
Leadtime ≤ “Horizon” of Known Demand?
What is the Value-Added of the
IDIB Paradigm?
• Vantage Point on the Majority of
Operations-Research Models
• Vantage Point on Past/Present Practice
• Vantage Point on the Future
1st Axiom of the IDIB Portfolio:
Given an existing IDIB Portfolio, increasing
the quality of one of its components
typically facilitates decreasing the quality of
at least one of its other three components
while maintaining the same level of
customer service
“the Tradeoff Axiom”
Examples:
• In a (Q,r) system:
– If all leadtimes are fixed, then the informationsystem, decision-making, and implementation
leadtimes tradeoff one-for-one
– If any of these leadtimes are variable, then
reducing their variance facilitates reducing
safety stock (buffer) inventory
Examples from Practice:
• Schneider National
– Increasing Quality of I, D, and I; Reducing B;
improving service
• Manufacturer Making Transition from a
“Push” (e.g., MRP) to “Pull” (e.g., JIT)
– Reducing Buffer Inventory, increasing Buffer
Capacity
• Domestic Manufacturer Outsourcing to OffShore Supplier
– Reducing Implementation Quality (Leadtime);
Increasing Buffer Inventory
The IDIB Perspective on Stateof-the-Art Practice in SCM
• Involves the sharing of past, present, and
future-oriented information between buyersupplier pair; and/or
• Involves delegation of decision-making or
implementation to the supplier
.....So, then what is the future.......?
2nd Axiom of the IDIB Portfolio:
Investment to improve the quality of any
single component of the IDIB Portfolio will,
over some range, decrease total cost of the
Portfolio; but, beyond some quality level,
increase total cost of the Portfolio
“Do-Nothing-in-Excess Axiom”
The Future of Supply-Chain
Management Involves
Collaborative Decision-Making
and/or Implementation
Why?
• For Supply Chains that already share
information, the returns from additional
information sharing are diminishing
• For Supply Chains that are already
delegating some decision-making, the
returns from additional delegation are
marginally diminishing
Two Personal Projects
• Models for Collaborative Decision-Making
– How to Improve Decision-Making and
Implementation Based on Shared Information
• Protocols for Secure Supply-Chain
Management
– How to Improve Decision-Making and
Implementation without Sharing Information
Models for Collaborative SupplyChain Decision-Making
with
Vinayak Deshpande
&
Jennifer Ryan
Starting Point is “Collaborative
Planning, Forecasting, and
Replenishment” (CPFR)
What is CPFR?
• A process model, shared by the buyer and
supplier, through which inventory status-,
forecast-, and promotion-oriented
information are shared and replenishment
decisions generated
The 9 Process Steps:
Step 1:
Develop Front-End Agreement: Roles,
Measurement, Readiness
Step 2:
Create Joint Business Plan: Strategies and
Tactics
Step 3:
Create Sales Forecast: Buyer or Supplier
Step 4: Identify Exceptions for Sales Forecast
The 9 Process Steps:
Step 5:
Resolve/Collaborate on Exception
Items
Step 6: Create Order Forecast
Step 7: Identify Exceptions for Order
Forecast
Step 8: Resolve/Collaborate on
Exception Items
Step 9: Order Generation
CPFR: Who’s Behind it?
Federated
Department Stores
CORNING
FIELDCREST CANNON
Mead
Consumer Products
Schnuck
Markets
School & Office
Benchmarking
Partners
Staples
JCPenney
QRS
CPFR History:
• ‘95/96: Wal-Mart Warner-Lambert “CFAR”
Pilot
• ‘97: VICS Develops CPFR Initiative
• ‘98: VICS CPFR Guidelines Published
• ‘99: Pilots Between
– Kimberly-Clark & K-Mart,
– P&G & Meier, Target, Wal-Mart
– Nabisco & Wegman’s, etc.
• ‘00:1st Production Rollout: K-Mart
CPFR’s Future:
• “n-Tier” Collaboration
– Extension to Include Master-Scheduling
Decisions
– Include Transportation
Research Topics in CPFR:
• Process Model: How and Where does the
CPFR model (e.g., forecast collaboration)
fit into the supply-chain process?
• Front-End Agreements: How Should
agreements be structured, performance
measured, and benefits shared?
• Data Sharing: How should data be shared
(aggregation/disaggregation issues)?
• Exception Processing: What constitutes an
exception?
Secure Supply-Chain
Collaboration
with
Mikhail Atallah
&
Vinayak Deshpande
The Starting Point....
“Information Asymmetry” is one of the
major sources of inefficiency in Managing
Supply Chains
==> Wrong Investment in Capacity
==> Misallocation of Resources
==> Distorted Prices
==> Reduced Customer Service
==> Unnecessary Additional Costs
.... there are Very Good Reasons
for Keeping Private Information
Private
• Fear that Supply-Chain Partner will Take
Advantage of Private Information
• Fear that Private Information will Leak to a
Competitor
So, then, the Obvious Question...
Is it possible to enjoy the benefits
of Information-Sharing without
Disclosing Private Information?
It Depends
If the Value of Private
Information is the Information
Itself, then..
...obviously, information
must be disclosed for value
to be created
But, if the Value of Private
Information is a Decision .......
...then it is possible to create
value without Disclosing Private
Information
Example
In CPFR:
Determine agreed-upon planned
orders without sharing forecasts, etc.
Secure Multi-Party Computation
• SMC is Decades Old
• Elegant Theory
• General Results w.r.t. Existence,
Complexity, etc.
• Recently, Practical Protocols for Specific
Problems
Ex.
Electronic Voting
Information Retrieval
SMC Paradigm
• Alice has Private Information: XA
• Bob has Private Information: XB
• Want to Determine f(XA, XB)
• f(XA, XB) is well defined
• No Trusted Third Party
• Provide f(XA, XB) to Alice, Bob, both, or
Neither
We are Developing Secure MultiParty Protocols for Supply-Chain
Management:
“Secure Supply-Chain Collaboration”
More Specifically...
...we are developing protocols to
enable Supply-Chain Partners to
Make Decisions that
Cooperatively Achieve Desired
System Goals without Revealing
Private Information
Our Goals:
• Develop and Apply SSCC Protocols to
Some Well-Known SCM Problems
• Simple e-Auction Scenarios
• Simple Capacity-Allocation Scenarios
• Bullwhip Scenarios
• Compare Effectiveness of Protocols vs.
non-cooperative decision-making
Our Goals (cont.):
• Develop Proof-of-Concept Software
• Examine Security versus Cost Tradeoffs
Ex: Capacity Allocation
• Single Supplier; N Retailers; Single Sales
Period
• Supplier has constant marginal production
cost, but fixed capacity, K
• Retailers operate in non-competing markets;
each retailer i has private information, qi,
about its market that influences its order to
the supplier; Supplier has prior Pr(q)
• If SOrdersi > K, Supplier Uses Preannounced Allocation Mechanism
Cachon and Lariviere (MS, ‘99)
• Examine this scenario from perspective of
the retailers in non-cooperative setting
• Linear Demand: Market-Clearing Price, r(q)
r(q) = qi - q
• Several Very Interesting Results
– Retailers will over-order even if Pareto
allocation mechanism is used
– Supplier and Supply-Chain Profit can increase
if a truth-telling mechanism is replaced by
manipulable one.
Deshpande & Schwarz (‘02)
• Examine this scenario — and a newsvendor
scenario — from perspective of maximizing
Supply-Chain Profit assuming truth-telling
• Derive conditions under which two
commonly-used allocation mechanisms
maximize supply-chain profit
• Our SSCC Protocols use these mechanisms
without revealing the retailers’ qi’s
Allocation Mechanisms
• Supplier has Capacity K
• Retailers place orders: q1, q2, q3,..qN
• Assume Sqi > K
• Linear Allocation: qi’ = qi - (Sqi- K)/N’
• Proportional Allocation: qi’ = qi • (K/ Sqi )
Proportional Allocation Protocol
1.Retailers choose a random R;
2.Every retailer sends its R•qi to Supplier
3.System computes:
D = (R•Sqi/K)
and sends it to all the retailers
4.Every retailer computes its allocation:
qi’ = R•qi/D
and sends to supplier
Notes:
• We are assuming that retailers will tell the
truth; i.e., reveal the quantity they truly
want; (one that is consisent with their qi)
• Supply Chain Profit will be reduced if
they don’t
• Contracting Mechanisms will be
Required
Notes:
• The Supplier Learns each Retailer’s qi, but
not qi
• Supplier Might be able to Infer qi
• Shipping Proxies
We Have Only Just Begun...
• Tough Issues to Deal with:
– SMC Complexities; e.g.,
• How to Deal with Collusion
• Computational Complexity (e.g., simultaneity)
– Supply-Chain Modeling Complexities; e.g.
• Contracting/Incentive Issues
– SSCC Complexities; e.g.,
• Inverse Optimization
• Bob’s Objective is fB(xA, xB); Alice’s is fA((xA, xB)
Discussion....