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

http://www.supplychainsustainability.com/

ABOUT THE DECISION SUPPORT TOOL Using Brand Distribution Patterns to Speed Incident Response

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


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. 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.



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. 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

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

ABOUT THE DATA AND THE STAKEHOLDERS

Linking and Data Population

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

Multiple sources of information were used in populating the 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

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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


KEY PROTOTYPE QUERIES/FEATURES Simulating Reality… Facilitating Collaboration

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

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Embedded Queries 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



Embedded Queries 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


BRAND-LINKAGE: PROCESSOR TO POS

By-Passing Supply Chain Distribution Complexity

For speed of mitigation Brand

Brand

A Linear View of the Food Supply Chain…

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Source

Commodity Movement from Source to Sale


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Source Processing



24

Source Processing Distribution



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Source Processing Distribution Sale


A Brand-Centric View of the Food Supply Chain…

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Source Processing Sale

Bypass the Problem of Distribution Complexity


A Brand-Centric View of the Food Supply Chain…

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Source Processing Sale

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

Distribution

Brand Distribution Patterns



Prototype View of the Spinach Food Supply Chain

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Growers & Importers

Processors

A High-Level Prototype View of Stakeholders and Linkages.

Sale/Purchase Agreements




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Growers & Importers

Processors

Points of Sale &

Consumption

A High-Level Prototype View of Stakeholders and Linkages


Branding/Purchase Agreements




Distribution


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Growers & Importers

Processors

Points of Sale &

Consumption

A High-Level Prototype View of Stakeholders and Linkages

Consumers








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

How it Works

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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.



Query the Prototype

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.



Query the Prototype

Receive the Results

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).



Query the Prototype

Receive the Results

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.


EXERCISING THE PROTOTYPE

A Simulation Scenario

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A Prototype Scenario

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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

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Query at Time 1

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Query 1: Inputs 5 Brands were identified as possible/known sources of consumer infection.

Aunt Mid’s

Dole

Earthbound Farms

Grateful Harvest

North Bay Spinach

4 Outlets were identified as possible/known points of consumer infection.

Kroger

Meijer

Casual Dining 1

Casual Dining 2

14 possible sources of infection were identified

Processors/Broker/Dealers

8

Growers

6


Query 1: Output

If the 6 GOWERS identified were contamination sources...

Baja Farm 02

Quebec Farm 01

Sonora Farm 3

Sonora Farm 112

Spinach Farm 27

Spinach Farm 120

And, if the 8 Processors/Brokers/Dealers identified were contamination sources...

Albert's & Aunt Mid’s

Fresh Express & Natural

Selections

New Star & North Bay

River Ranch and Mid-Michigan

The at-risk points of consumer purchase and consumption would be…

7,425 Outlets controlled by 18 Organizations

Across 49 States


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 at Time 2

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Dole

Earthbound Farms

Fresh Express

North Bay Spinach


Meijer

MI Supermarket Chain 3

Supermarket Chain 3

Casual Dining 3

Publix


Processors/Brokers/Dealers

9

Growers

7


Query 2: Output


Baja Farm 02

Quebec Farm 01

Sonora Farm 3

Sonora Farm 112

Spinach Farm 120

Spinach Farm 375

And, if the 9 Processors-Brokers identified were contamination sources...

Albert's & Aunt Mid’s

Fresh Express & Natural

Selections

New Star & North Bay

Nova & Mid-Michigan

Dole



Across 40 States




contaminated



8,620 points of purchase or consumption were identified as possible contamination points: Located in 40 States; Top 3 (38%) were Florida, North Carolina, Michigan





Query at Time 3

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Aunt Mid’s

Florida Fresh

North Bay Spinach


MI Supermarket Chain 3

Publix

Food Lion


Processors/Brokers/Dealers

6

Growers

5


Query 3: Output


Baja Farm 02

Quebec Farm 01

Sonora Farm 3

Spinach Farm 27

Spinach Farm 375

And, if the 6 Processors-Brokers identified were contamination sources...

Aunt Mid’s

Fresh Express

New Star

North Bay

Nova

Mid-Michigan



Across 45 States




contaminated



4,484 points of purchase or consumption were identified as possible contamination points: Located in 45 States; Top 3 (49%) were Florida, North Carolina, Michigan





Query at Time 4

Query 4: Input – Grower & Processor 1 Grower was identified as the most probable source of consumer infection.

Baja Farm 02 (Mexico)

1 Processor/Broker/Dealer was identified as potential source of consumer infection.

North Bay Produce, Inc.

The Prototype identified 1 other processor/broker dealer

Nova Products


Query 4: Input – Brands If the Grower is Baja Farm 02.

Baja Farm 02 (Mexico)

And if the Processor/Broker/Dealer are North Bay and Nova.

North Bay Produce, Inc.

Nova Products

The Prototype identified 3 Brands

Florida Fresh Spinach

North Bay Spinach

Southern Best


Query 4: Output

Combining the inputs…

Baja Farm 02

North Bay Produce

Nova Produce

Florida Fresh Spinach

North Bay Spinach

Southern Best

The results would be…

3,761 At-Risk Outlets

7 Organizations

• 98% in Top 5 Organizations

45 States

• 57 % in Fla., NC. Va.


Query 4: The Distribution of the 3,761Outlets


Query 4: End of Simulation

RTR provided the following “at-risk” information: In this query sequence, the inputs provided started upstream with a

single grower then, moving downstream to two processors/brokers/dealers.

3,761 points of purchase or consumption were identified as possible contamination points: Located in 45 States; Top 3 (57%) were Florida, 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.


Business

Faster Response To Foodborne Incidents