1. 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
2. Outline
• Supply-Chain Management of “Yesterday”
– How Modeled
– How Practiced
• Supply-Chain Management of “Today”
– How Practiced
– How Modeled
3. 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
4. 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”
5. • 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
6. 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
7. • 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
9. “Yesterday’s” Relationship:
“Mismatched”
• Models
– Too Specialized
– Required More Information than Practice Had
• Practice
– Inexperienced with Models & Computers
– Confused by Models
– Suspicious of Models
10. SCM Practice “Today”
• The Beginnings of “Real” SCM for Single-
Owner Chains
– Ex: Wal-Mart’s Retail Link
Target’s Partners OnLine
• Capabilities
– Broadcast SKU-level Data Across the Chain
– Observe Status ==> Implemetation
“Contractible”
12. • 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
13. • 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”
14. 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)
15. • 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
16. 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
17. 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
20. The IDIB Portfolio
a.k.a.
The Information, Decision-Making,
Implementation, Buffer Portfolio
21. “Managing” anything can be
viewed as 4 related activities:
• Getting Information
• Making Decisions
• Implementing Decisions
• Buffering against Imperfections in
information, decision-making, or
implementation
22. 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
23. 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
24. 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
25. 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
26. Each ... Characteristics (cont.)
The Buffer System
– Quality Characteristics
• Form
• Robustness
• Etc.
– Cost: Increasing and Marginally-Increasing
with Quality
27. 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
28. 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!
29. Most Operations-Research
Models Ignore the IDIB Portfolio
• Example: The Newsvendor Model
– Information-System Quality Assumed
– Implementation is Ignored
– Select Decision-Rule to Minimize Buffer-
System Cost
30. 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?
31. 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
32. 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”
33. Examples:
• In a (Q,r) system:
– If all leadtimes are fixed, then the information-
system, 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
34. 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 Off-
Shore Supplier
– Reducing Implementation Quality (Leadtime);
Increasing Buffer Inventory
35. The IDIB Perspective on State-
of-the-Art Practice in SCM
• Involves the sharing of past, present, and
future-oriented information between buyer-
supplier pair; and/or
• Involves delegation of decision-making or
implementation to the supplier
.....So, then what is the future.......?
36. 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”
37. The Future of Supply-Chain
Management Involves
Collaborative Decision-Making
and/or Implementation
38. 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
39. 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
41. Starting Point is “Collaborative
Planning, Forecasting, and
Replenishment” (CPFR)
42. 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
43. 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
44. 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
46. 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
47. CPFR’s Future:
• “n-Tier” Collaboration
– Extension to Include Master-Scheduling
Decisions
– Include Transportation
48. 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?
50. 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
51. .... 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
57. 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
58. 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
59. We are Developing Secure
Multi-Party Protocols for Supply-
Chain Management:
“Secure Supply-Chain Collaboration”
60. More Specifically...
...we are developing protocols to
enable Supply-Chain Partners to
Make Decisions that
Cooperatively Achieve Desired
System Goals without Revealing
Private Information
61. 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
63. 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, θi,
about its market that influences its order to
the supplier; Supplier has prior Pr(θ)
• If ΣOrdersi > K, Supplier Uses Pre-
announced Allocation Mechanism
64. 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) = θi - 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.
65. 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’ θi’s
66. Allocation Mechanisms
• Supplier has Capacity K
• Retailers place orders: q1, q2, q3,..qN
• Assume Σqi > K
• Linear Allocation: qi’ = qi - (Σqi- K)/N’
• Proportional Allocation: qi’ = qi • (K/ Σqi )
67. Proportional Allocation Protocol
1.Retailers choose a random R;
2.Every retailer sends its R•qi to Supplier
3.System computes:
D = (R•Σqi/K)
and sends it to all the retailers
4.Every retailer computes its allocation:
qi’ = R•qi/D
and sends to supplier
68. Notes:
• We are assuming that retailers will tell the
truth; i.e., reveal the quantity they truly
want; (one that is consisent with their θi)
• Supply Chain Profit will be reduced if
they don’t
• Contracting Mechanisms will be
Required
69. Notes:
• The Supplier Learns each Retailer’s qi, but
not θi
• Supplier Might be able to Infer θi
• Shipping Proxies
70. 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)
