Faster Response To Foodborne Incidents

More Rapid Responses to
Foodborne Illness Incidents

Bypassing Supply Chain Distribution Sector Complexity using
Brand Distribution Patterns

(C)
Supply Chain Sustainability, LLC
October, 2011
www.supplychainsustainability.com

Using Brand Distribution Patterns to Speed Incident Response

ABOUT THE DECISION SUPPORT TOOL

Risk Mitigation – Food Supply Chain Incidents
Over a three-year period following 9/11, the Partners of Supply
Chain Sustainability, LLC worked under a contract with the
Department of Supply Chain Management at Michigan State
University that was funded by the Department of Homeland
Security through the National Center for Food Protection and
Defense.

(C) Supply Chain Sustainability, LLC - October, 2011

Defense.

Our objective was to build a software decision support prototype
that demonstrated how to more rapidly mitigate the damage of an
intentional or unintentional infection of the U.S. food supply chain.


Defense.

Our objective was to build a software decision support prototype
that demonstrated how to more rapidly mitigate the damage of an
intentional or unintentional infection of the U.S. food supply chain.

The concept underlying the decision support prototype is
deceptively simple… use product brand distribution patterns and
grower-processor business links, rather than traditional product
tracing approaches, to stochastically isolate infection source and
define at-risk consumers.
John E Griggs, Ph.D. - Omar Keith Helferich, Ph.D. - Rosemary Ann Haight


Statement of Objectives

 Demonstrate a decision support tool capable of:

 More Rapidly Identifying
 Potential sources of contamination
 At-risk points of food purchase and consumption

 More Effectively Mitigating
 Loss of life
 Economic loss to supply chain members, communities, and industries


Linking and Data Population

ABOUT THE DATA AND THE
STAKEHOLDERS

About Prototype Data Sources

 Multiple sources of information were used in populating the
Prototype’s database

 Data was purchased (e.g., chains with outlet locations and GPS
locations)

 Acquired under the Freedom of Information Act (e.g., all points of food
sale and consumption in Michigan)

 Downloaded (e.g., U.S. agricultural production of fresh spinach by
county/acres/number of growers)

 Generated (e.g., Environmental Health “agencies” for all U.S. counties )


About Brand Distribution Patterns and Links

Prototype’s database.

 All brand distribution patterns and supply chain member
links by brand and product flow from farm to point of
purchase/consumption were generated
 Even in those cases where familiar names (e.g., Publix, Dole) are used, the
actual brand names sold, distribution patterns, supply chain linkages, and
specific company information (e.g., addresses, telephone numbers, email
addresses) are modified or simply entered in order to add realism to the
Prototype.


About Prototype Infection Simulations


 Stakeholder information, brand distribution patterns and
supply chain linkages were generated.

 The specifics of the simulated source infection of e-coli is for
demonstration purposes only.
 Simulations used do not reflect actual incidents of infection nor are
they meant to reflect, in a negative or positive manner, on any
organization.


About Prototype Data Population - Summary


 Stakeholder information, brand distribution patterns and
supply chain linkages were generated.

 Simulated e-coli infection of a single, hypothetical grower.


Stakeholders: Number of Supply Chain Members

 Spinach Growers: 500
 Location/Size patterned from U.S. agricultural production data

 Processors/Dealers/Brokers: 5,800
 Name/Size patterned from State license data

 Points of Sale: 28,000 outlets
 U.S.-wide Outlets of Major Chains: 14,000
 Michigan Chain and Independent Outlets: 14,000

 Points of Consumption-Michigan Only: 15,000
 Restaurants (casual, family, buffet):9,000
 Educational Sites: 6,000

Stakeholders: Extended Supply Chain Members

 Medical Stakeholders: 6,500
 U.S. Pharmacy Outlets: 6,000
 Michigan Hospitals, Clinics, Physicians, Pharmacies: 500

 Environmental Health: 3,000
 County EH: 3,000

 Stakeholder Access to the Prototype: Input and Analysis
 All Involved Supply Chain Stakeholders
 Investigatory Agencies
 Industry Associations


Simulating Reality… Facilitating Collaboration

KEY PROTOTYPE QUERIES/FEATURES

Key Prototype Queries

 Embedded Queries
 An example of Geographical Analysis
 Query: List the retail outlets of chain organizations within a 100 mile
radius of Okemos, Michigan that sell the New Star brand of spinach



 Geographical Analysis
 An example of Distribution Plan Analysis
 List the Processors/Broker/Dealers and Growers that might be infected
given a set of brands and/or Points of Sale or Consumption that are
believed to be infected.



 Distribution Plan Analysis
 An example of Supply Chain Impact Analysis
 List all retail Points of Sale and/or Consumption that might be offering
infected product given any set of Processors/Broker/Dealers and Growers.



 Distribution Plan Analysis
 Supply Chain Impact Analysis
 Examples of Multi-level Filters over Stakeholder Data Record Queries
 List all Convenience Stores in Ingham County, Michigan offering Aunt Mid’s
products
 List all Growers in California that are farming between 500 and 1,000 acres
of spinach



 Geographical Analysis – Which Stakeholders are where?

 Distribution Plan Analysis – Which supply chain Stakeholders are at-
risk of being points of infection?

 Supply Chain Impact Analysis – Where might Consumers come in
contact with infected product?

 Multi-level Filters over Stakeholder Data Record Queries – Which
Stakeholders match a specific set of criteria?


Key Prototype Features

 Embedded Data Filtering Options
 E-mail, Data Export, Mapping
 Documents Management and Sharing
 Web-site Linkages to and between Stakeholders and
Resources
 Expandability to other Food Commodities (e.g., expanded
brand-specific distribution patterns and links) while
retaining basic Stakeholders information (e.g., chain
structures, and all prototype functionality


By-Passing Supply Chain Distribution Complexity
For speed of mitigation Brand

BRAND-LINKAGE: PROCESSOR TO POS
Brand

A Linear View of the Food Supply Chain…

Source

Commodity Movement from Source to Sale


Source Processing



Source Processing Distribution



Source Processing Distribution Sale


A Brand-Centric View of the Food Supply Chain…

Source Processing Sale

Bypass the Problem of Distribution Complexity


A Brand-Centric View of the Food Supply Chain…


Source Processing Distribution Sale


Brand Links, not Shipment-level Links, from
Processors to Points of Sale or Consumption
using Brand Distribution Patterns.


Prototype View of the Spinach Food Supply Chain

Sale/Purchase Agreements

Growers &
Processors
Importers


A High-Level Prototype View of Stakeholders
and Linkages.



Branding/Purchase Agreements


Points of Sale
Growers & &
Processors Distribution
Importers
Consumption



and Linkages





Points of Sale
Growers & & Consumers
Processors
Importers
Consumption




and Linkages


How it Works

UP AND DOWN THE SUPPLY CHAIN
TO IDENTIFY AT-RISK SUPPLY CHAIN
MEMBERS

Simulation: Identifying At-Risk Stakeholders

 1. For any set of provided brands and/or points of purchase
and/or consumption, the Prototype assumes that any other
brand carried by any of the provided points of purchase and
consumption could also be infected and thus are added to
Prototype’s search routine.



 1. All brands carried at all identified points of purchase and
consumption are considered to be at-risk of infection.

 2. The multiple supply chain linkages for all at-risk brands
are traced up the supply chain and all involved
processors/brokers/dealers and all growers are identified
and are considered to be at-risk.



 1. All brands carried at all identified points of purchase and
consumption are considered to be at-risk of infection.

 2. All linked processors/brokers/dealers and growers linked
to all identified brands are identified and are considered to
be at-risk.

 3. The links for all identified at-risk
processors/brokers/dealers and growers are tracked down
the supply chain and all points of at-risk points of sale or
preparation for on-site consumption are identified and
considered to be at-risk.


Simulation: The Steps

Brand A in Outlet X is considered to be at-risk and entered into
the Prototype.

The Prototype Model:
 1. Adds other at-risk brands, if any.
 Brands B and C are carried at Outlet X and those brands are added to
the search criteria.
 2. All at-risk downstream processors, brokers, dealers and
growers linked in any way to Brands A, B and C are identified.
 3. All at-risk upstream downstream points of sale linked in
any way to the identified processors, brokers, dealers and
growers are identified.

(C)
Supply Chain Sd0 ustainability, LLC - October,
2011

Prototype: Cycle of Use

 Query the Prototype
 Input a set of brands, points of purchase, or points of consumption,
that according to reports and investigation, may be at risk.



 Receive the Results
 Up the supply chain: All processors, brokers, dealers and growers that
could be infection sources.
 Down the Supply Chain: Given the identified processors, brokers,
dealers and growers, identify all consumer points of purchase or
consumption that could have offered, are currently offering, or might
soon offer infected product.



 Use the Information
 Analyze and share information
 Conduct alternative queries
 Focus inspection efforts
 Inform consumers of possible at-risk points and in terms meaningful
to and understandable by the consumer (e.g., brands, chains, locals).



 Use the Information
 Re-query the Prototype using:
 Consumer reports
 Reports from pharmacies and hospitals and environmental health
agencies
 Investigation and sampling results
 Supply chain member data and suggestions
 Expert opinions


Stating the Obvious

 The more complete and accurate the inputs… the more
specific and accurate the listing of possible infection source
and points of consumer risk.


Stating the Obvious

 The more accurate the listing of possible infection source and
points of consumer risk, the more accurate the information
provided to consumers and the more accurate the
identification of potential sources of infection.


Stating the Obvious

 The more accurate the listing of possible infection source and
points of consumer risk, the more accurate the information to
consumers and the more probable the potential of sources of
infection.
 The faster the resolution of the problem, the lower the risk of
loss of life, the higher the level of consumer confidence, the
faster the economic recovery for growers, processors,
brokers, dealers, retailers, restaurants and other
Stakeholders.


A Simulation Scenario

EXERCISING THE PROTOTYPE

Setting Up the Scenario

 A single Grower was set as the source of supply chain
contamination.
 Baja Farm 02 (Mexico)
 That Grower was linked to
 North Bay Produce, Inc. (Michigan)
 Nova Produce (Michigan)
 The Processor and Brokers were liked in such a manner that
the possible combination of at-risk points of purchase or
consumption:
 Organizations: 7 retail chains (US-wide, Michigan-only) and one
Michigan Casual Dining chain.
 Geography: 3,771 total outlets located in 45 States


Query 1: Inputs

5 Brands were identified as possible/known sources of
consumer infection.

Aunt Mid’s 4 Outlets were identified as possible/known
points of consumer infection.
Dole
14 possible sources of infection
Earthbound
Kroger
were identified
Farms
Meijer

Grateful Growers
Harvest Casual Dining 1 Processors/Broker/Dealers
8 6
North Bay Casual Dining 2
Spinach


Query 1: Output

If the 6 GOWERS identified were contamination sources...

Baja Farm 02 And, if the 8 Processors/Brokers/Dealers
identified were contamination sources...
Quebec Farm 01

Sonora Farm 3
The at-risk points of consumer
Albert's & Aunt
Mid’s purchase and consumption would
Sonora Farm
112
Fresh Express &
Natural
be…
Selections
Spinach Farm
27
New Star & North 7,425 Outlets controlled by 18 Across 49
Bay
Organizations States
Spinach Farm River Ranch and
Mid-Michigan
120


Query 1: Summary Information

 RTR provided the following “at-risk” information:
 In addition to the 5 brands inputted, 2 additional Brands that might be
contaminated
 There were 8 Processors, Dealers, Brokers that sold the 7 brands
 6 Growers sold product to the 8 Processors, Dealers, Brokers
 7,424 points of purchase or consumption were identified as possible
contamination points: Located in 49 States; Top 3 (39%) were Florida,
California, Michigan
 In addition to the 4 retail organizations inputted, 7 additional retail
organizations might be providing contaminated product… 5 of the 11
organizations controlled 87% of the 7,424 points of purchase or
consumption


Query 1: The Distribution of the 7,425 Outlets


Query 2: Inputs

consumer infection.

Dole 5 Outlets were identified as possible/known
Earthbound
Farms
Meijer were identified
MI Supermarket
Chain 3
Fresh Express Supermarket
Chain 3 Processors/Brokers/Dealers Growers
Casual Dining 3 9 7
North Bay
Spinach Publix


Query 2: Output


Baja Farm 02 And, if the 9 Processors-Brokers identified were
contamination sources...
Quebec Farm 01

Sonora Farm 3
Albert's & Aunt The at-risk points of consumer
Mid’s
Fresh Express & purchase and consumption
Sonora Farm
112
Natural
Selections
would be…
New Star & North
Spinach Farm Bay
120 Nova & Mid- 8,620 Outlets controlled by 22 Across 40
Michigan Organizations States
Spinach Farm Dole
375



contaminated
North Carolina, Michigan
consumption


Query 3: Inputs

consumer infection.

3 Outlets were identified as possible/known
Aunt Mid’s
MI Supermarket
Chain 3 were identified
Florida Fresh

Publix
Processors/Brokers/Dealers Growers
North Bay 6 5
Food Lion
Spinach


Query 3: Output


Baja Farm 02 And, if the 6 Processors-Brokers identified were
contamination sources...
Quebec Farm 01

Aunt Mid’s
The at-risk points of consumer
Sonora Farm 3 Fresh Express purchase and consumption
New Star
would be…
Spinach Farm
North Bay
27 4,484 Outlets controlled by 11 Across 45
Nova Organizations States
Spinach Farm
375 Mid-Michigan



contaminated
North Carolina, Michigan
consumption


Query 4: Input – Grower & Processor

1 Grower was identified as the most probable source of
consumer infection.

1 Processor/Broker/Dealer was identified as
potential source of consumer infection.
The Prototype identified 1 other
Baja Farm 02 processor/broker dealer
(Mexico)
North Bay
Produce, Inc.
Nova Products


Query 4: Input – Brands

If the Grower is Baja Farm 02.

And if the Processor/Broker/Dealer are North
Bay and Nova.
The Prototype identified 3
Baja Farm 02 North Bay Brands
(Mexico) Produce, Inc.

Florida Fresh North Bay
Southern Best
Nova Products Spinach Spinach


Query 4: Output

Combining the inputs…

Baja Farm 02

North Bay The results would be…
Produce

Nova Produce

Florida Fresh
Spinach
3,761 At-Risk Outlets 7 Organizations 45 States
North Bay • 98% in Top 5 • 57 % in Fla., NC. Va.
Spinach Organizations

Southern Best


Query 4: The Distribution of the 3,761Outlets


Query 4: End of Simulation

 In this query sequence, the inputs provided started upstream with a
single grower then, moving downstream to two
processors/brokers/dealers.
North Carolina, and Virginia.
 7 retail organizations might be providing contaminated product… 5 of
the 7 organizations controlled 98% of the 3,761 points of purchase or
consumption.


OUR OBJECTIVES FOR DISTRIBUTING
THIS DOCUMENT

Closing Comments
 The PowerPoint is somewhat  lengthy
 We wanted to provide you with Prototype details, not simply a
conceptual overview.
 The Prototype was implemented with very limited funding
and used proven technology.
 Demonstrating, in our opinion, a real potential for implementation.
 The Prototype can:
 Be demonstrated, hopefully providing ideas to others trying to address
the complex issue of response to food supply chain infection.
 Configured as a simulation training tool for use by multiple
Stakeholders.
 Only with private-sector, food commodity specific, industry
support could the Prototype be implemented as a Pilot.


Faster Response To Foodborne Incidents

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