case study reducing blackberry shrink in-transit...

CASE STUDY

Reducing Blackberry Shrink In-transit from Mexico to the USA Monetizing the Value of Pallet-level Temperature Monitoring

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Introduction

In the produce industry, everyone knows and deals with shrink – the loss of salable products

throughout the cold chain. Members of the cold chain, from growers to retailers, generally

consider shrink as quite „visible‟. What is often “invisible” is the cause of shrink because the

“actual cause” of shrink occurs in multiple places throughout the cold chain. Shrink itself only

becomes “visible” later – typically at the end of the supply chain when produce reaches the

retailer – well after it is too late to do anything about the problem. As a result, product is wasted,

and revenues and profits are lost for all segments of the supply chain.

Without good visibility into the cold chain it is difficult to determine the exact cause for any given

incident where loss of product occurs. In many cases, assigning responsibility becomes a

guessing game with no good data to justify the claim. The cause of shrink can occur at many

places within the supply chain, remaining invisible until after the product is sold to the unlucky

owner. Whether being received at a brand owner DC, retail DC or retail store, the Quality

Control (QC) staff are left to play a game of Three Card Monte as they do not have the tools to

see (or measure) “invisible” shelf life loss.

Recently, a world class tomato shipper

said that a major pain point is receiving a

claim from a retailer – along with

supporting photographs and inspection

reports – because the shipper‟s own QC

people inspected the product prior to

shipment and it was fine. The trailer-level

temperature monitoring for the transport

to the retailer was also fine. At the end of

the day, loads of tomatoes would end up

rejected because of „”invisible” loss of

shelf life – invisible aging of the produce

from the field to the retailer caused by

improper temperature control and inventory management. It is a common and costly problem,

regardless of the type of produce or product, the shipper, or the receiver.

Tracking the temperature of produce at the pallet-level from the field to retailer is critical. It can

help the grower, brand owner and retailer calculate the remaining shelf life, identify any potential

quality issues and help route produce effectively. Simply monitoring ambient temperature at the

trailer level is inadequate because the critical temperature is the core temperature of the

perishable goods themselves – not the surrounding ambient air temperature. And, the

transportation segment is just one segment in a complex supply chain. Unfortunately, if

temperature monitoring is only done during transit and at the trailer level, significant visibility into

the product‟s temperature condition – and its shelf life – is lost. It is most important to monitor

the temperature at the pallet level beginning at harvest to ensure visibility into critical segments

of the supply chain are not lost, including the cut-to-cool and pre-cooling segments.

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Temperature monitoring at the pallet level, beginning at harvest and at every step of the supply

chain, is what enables real-time decision making that can reduce or eliminate shrink, improve

product quality, increase profits and protect a brand for all segments of the supply chain.

The Value of Pallet-level Monitoring

The temperature and time from harvest-to-cool are common variables which are NOT monitored

on an individual pallet basis. Yet both temperature and time spent at the higher temperatures

affect each pallet differently. Throughout the cold chain, produce is processed, palletized and

shipped primarily on a First-In-First-Out (FIFO) basis, mixing variable shelf life product together,

causing pain later in the cold chain. The reality is that the normal QC visual inspection process

is not adequate to see the “invisible” shelf life loss introduced earlier in the supply chain due to

improper temperature controls. Simply put, you cannot see shrink when you look at it.

Consider the following example of a controlled study of the impact of pre-cooling delays on full

loads of strawberries, shipped from the west coast of the USA to the east coast.

In this study, prepared by the University of Florida, the only significant difference between each

truck load was pre-cooling. Things to note:

Every load passed QC at the retailer‟s distribution center because the shelf life loss was INVISIBLE at that point in the cold chain − the fruit looked fine by visual inspection.

The difference in remaining shelf life between fruit that was properly pre-cooled and fruit that was not properly pre-cooled was an astounding 81.7%! (91.7%-10%). This amounted to a net loss of $75,845!

There was no way for the store produce manager to determine if the loss was due to store operations, cold chain operations or poor quality fruit.

It gets worse: this data does not reveal what the consumer experienced with product actually sold – that is, what happened once the consumer took the product home?

Trailer-level monitoring is insufficient to capture the necessary temperature information because

the temperature inside a trailer can vary significantly. Without creating pallet-level temperature

visibility throughout the supply chain, it is impossible to determine where the true cause of

shrink occurred, so it can‟t be addressed, fixed or avoided in the future. Everyone does their

best to reduce shrink, but when it happens – when the product deteriorates right in front of our

eyes – no one can determine where the problem occurred. This affects more than just the profit

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on any given load, it also affects quality, customer satisfaction, brand image, brand demand and

food safety.

Invisible shelf life loss can be introduced at any of the custody segments within a supply chain.

The most likely segments include:

Cut-to-Cool (Harvest to Pre-Cool)

Pre-Cooling

Cold Storage

In-transit

Customs Inspection

Cross Dock/Transfer points throughout routing between packing, DCs and retailers

Store Display & Display Rotation

Unfortunately, to date, the focus has been on temperature monitoring only for the simplest

trucking segments and even that has been limited to trailer-level monitoring.

What‟s important is cost-effectively monitoring every pallet from harvest onward, with an

“automated” data collection process that does not inhibit operations or slow down processing.

By doing so, several advantages can be realized:

Minimize the cut-to-cool time for each pallet.

Optimize the pre-cool process: eliminating freezing injury and optimizing product cooling while minimizing energy costs.

Route shipments using enhanced First Expired, First Out (FEFO+), not First In, First Out (FIFO), to match shelf life with routes ensuring that the pallets with the longer shelf life are sent on the longer routes and the pallets with the shorter shelf life are sent on the shorter routes.

Include special handling instructions for DC receiving when necessary, allowing the receiving party to rotate the product more efficiently to minimize loss.

Use the historical data to identify trends and the actual source of shrink: This provides the ability, when possible, to fix the true problems and assign the cost of shrink to the right entity.

Reduce waste and fuel costs: We can avoid shipping product with limited remaining shelf life on long shipments, only to dump it later when it is received by the retailer.

Improve food safety & quality: Proper temperature control not only improves quality but, by improving customer satisfaction, it enhances the brand and increases demand.

Case Study: Shipping Blackberries from Mexico to the USA

A recent Intelleflex project with a major grower and distributor of berries confirmed the

importance and value of monitoring the temperature of fresh fruit at the pallet level from harvest

to delivery. Working with ProWare Services, a software and services provider for the produce

industry, the project utilized Intelleflex XC3 Technology™ RFID readers and temperature tags

coupled with ProWare‟s FreshAware™ solution to track the pallet-level temperature of

blackberries from growers in Mexico to their distribution centers in California, Texas and

Pennsylvania. The results were compelling. There were a number of areas where the supply

chain process could be optimized that would result in immediate product quality and financial

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benefits. However, beyond that, the project demonstrated that shrink could be significantly

reduced without making modifications to the cold chain. By providing the growers, packers and

shippers with pallet-level information about remaining shelf life in-transit, they could dynamically

route product to destinations matched to that shelf life and avoid the shrink.

Project Overview

Intelleflex and ProWare worked with one of America‟s largest berry growers on a six week pilot

project in Mexico and the United States. The company has contracted producers and farms

located throughout Latin America. Because brand value and quality are critically important to the

company, it was eager to identify ways to further enhance the excellence of their products.

For the project, which spanned six weeks, Intelleflex and ProWare worked with one of the

company‟s blackberry production operations in central Mexico. The project studied two “loops”

in the supply chain:

From the growers to the packing house in Mexico.

From the packing house to the distribution centers (DC) in Southern California, Texas

and Pennsylvania.

It should be noted that, in the most optimal conditions, once harvested, blackberries

theoretically have at most 17 days of shelf life, depending on the harvest conditions. Once

harvested, the clock starts ticking and shelf life begins to deteriorate based on time and

temperature.

Approximately 150 growers in the area

harvest their blackberries and then

ship them, using a variety of vehicle

types, to the packing house and cold

storage facility in central Mexico. The

distance from the growing fields to the

packing house varies significantly,

from less than an hour to more than

four hours. The blackberries are

harvested at different temperatures

throughout the day. This variation in

temperature and time to pre-cool

results in a significant variation of shelf

life for each pallet.

Berries arrive at the packing house beginning early in the morning and continue to arrive well

into the afternoon. Intelleflex temperature monitoring tags were placed in the individual pallets of

blackberries at harvest in the field in order to monitor the temperature from harvest to the

packing house and then determine the remaining shelf life once the pallets reached the packing

house in Mexico.

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At the packing house, the berries were aggregated, visually inspected and loaded onto

refrigerated trucks and then shipped to one of the DCs in Southern California, Texas and

Pennsylvania.

Beyond the variable times it takes for the blackberries to travel from the field to the packing

house, there‟s also significant variation in the time it takes for the berries to travel to the US-

based distribution centers:

Texas: Takes 2 days by truck

o Requires 12 days of remaining shelf life for maximum routing requirements to the retailer (the

longest route)

Southern California: Takes 3-4 days by truck

o Requires 14 days of remaining shelf life to meet maximum routing requirements to the retailer

Pennsylvania: Takes 4-5 days by truck

o Requires 14 days of remaining shelf life to meet maximum routing requirements to the retailer

In other words, a pallet of berries sent from Mexico to Southern California may require up to 14

days of remaining shelf life to maximize quality for the retailer and consumer, depending on the

route and destination. If it leaves Mexico with less than 14 days, it may not arrive at the grocery

retailer with enough shelf life to sell and ensure quality to the consumer.

One of the goals of the project was to measure the temperature at the pallet level from harvest

all the way through to the distribution centers to quantify the temperature handling conditions for

the entire life of each pallet. Using data from Intelleflex temperature monitoring tags, each pallet

was graded using an algorithm that calculates the products‟ remaining shelf life based on the

temperature conditions it has experienced throughout its transit.

Using the shelf life information for each pallet, it is possible to estimate the savings that could be

obtained by shipping each pallet based on its unique remaining shelf life. For example, by

shipping a specific pallet to the most appropriate distribution center (e.g. Southern California,

Texas or Pennsylvania) based on the remaining shelf life for each pallet, the company can

reduce both its internal shrink (shrink experienced prior to delivery to the retail customer

distribution center) and external shrink (shrink experienced after the product is delivered to the

retail distribution center) and thereby improve the quality of the product delivered to consumers

as well as enhancing profitability.

The results from the pilot identified four areas where the temperature monitoring data can

improve operations which are further explored below:

1. Cut-To-Cool Shelf Life Variation

2. Pre-Cool Automation and Optimization

3. Inventory Rotation & Routing

4. In-Transit Visibility

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1. From Field to Pack House: Understanding Cut-To-Cool Shelf Life Variation

The Intelleflex temperature monitoring tags that were placed in the individual pallets in the field

provided the ability to monitor the pallet condition from harvest and determine the remaining

shelf life as the pallets reached the pack house in Mexico. It was found that the temperature

varied on a pallet-by-pallet basis due to the aforementioned differences in distances from the

field to the packing house and the types of vehicles used (e.g. refrigerated or flat bed trucks), as

well as the ambient temperature which, of course, varies by time of day and year. Any pallets

received at the pack house with less than 14 days of remaining shelf life (based on the

customer‟s supply chain routing profiles) required special handling because if they were shipped

to California or Pennsylvania, they may not meet the maximum routing profile requirements.

The table below shows the pallet shelf life distribution at QC in the pack house. Approximately

70% of the pallets were determined to have 14 or more days of remaining shelf life when they

arrived at the pack house and could therefore be safely shipped to any of the three distribution

centers using any route and still have sufficient shelf life upon arrival at the DC to ship to any

retailer. However, 30% of the pallets had less than 14 days of shelf life at arrival, indicating

these pallets require special routing to ensure their shelf life matches that required by the

routing profile.

This 30% of the product with less than 14 days of shelf life is “at-risk” product. Under current

FIFO inventory rotation, it is estimated that approximately 19% of this at-risk product will by-

chance be shipped out with enough shelf life to meet its required routing profile requirement.

Or, put another way, 19% of the at-risk product will, by-chance, not be sent on long routes and

have enough shelf life to make the trip to the consumer allowing at least 2 days to consume the

product. The remaining 11% of the at-risk product will not meet its required routing profile

requirement, providing the consumer with less than 2 days to consume the product or ending up

as shrink for the brand owner or retailer. Using smarter inventory rotation and routing with the

30% of at-risk product provides the opportunity to significantly reduce this 11%, resulting in

reduced shrink, increased quality, profits and consumer loyalty.

2. Pre-Cool Automation and Optimization

After arriving at the pack house in Mexico, the pallets go through a quality control (QC)

inspection. Once the remaining shelf life of each pallet was read from the tag at QC, the pallets

were marked with the shelf life and the temperature tag placed on the pallet at harvest was

removed.

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The existing process combines multiple pallets together to create

a full “export” pallet. Using the shelf life values marked on the

pallets, the export pallets can now be built combining product with

similar remaining shelf life. Once the export pallets are built, a new

temperature tag is started and associated with the new export

pallet and it‟s pallet bar-code label and then placed in the pallet.

The tag is placed in one of the flats (or cases) in between the

clamshells to more closely monitor the product temperature and

not the ambient air temperature outside of the pallet. The pallets

then proceed to pre-cooling where the temperature tags monitor

the pre-cooling process to optimize the pallet cooling and

eliminate possible freezing injury. A fixed RFID reader is located in

the pre-cooler and continuously monitors the temperature tags

contained in the pallets during the pre-cool process.

The temperature data read from the tags provides the visibility necessary for the software to

determine when each pallet has reached the optimum temperature. Operations personnel can

monitor the pre-cooling process remotely and be alerted when the pre-cooling is complete or if

there are risks of freezing injury. This real-time visibility optimizes the pre-cooling process,

improving the product quality while minimizing energy costs.

3. Inventory Rotation and Routing

With remaining shelf life information available for each export pallet, the “at-risk” pallets can be

prioritized when selected for shipping and routed to closer DCs (Texas) or sent to the other US

DCs with special handling instructions, (i.e. ship out first or ship to close retail DC). Simple color

coded labels on each pallet help to quickly and efficiently implement this inventory rotation and

routing process within the pack house. Matching the pallets shelf life to the correct ship-to

destination routing profile ensures each retail customer receives a pallet of product that has the

optimum shelf life, resulting in significantly less shrink, improved quality, increased consumer

satisfaction and increased demand – all resulting in higher revenue/case.

4. In-Transit Visibility to the US Distribution Centers

With each export pallet having a temperature monitoring tag, pallet level visibility continued

through distribution to the US DCs. Each trailer was also equipped with a traditional

temperature monitor to log the ambient temperature inside the trailer. Trailer-level (ambient)

temperature monitoring is considered normal practice and is assumed to provide adequate

information for determining if major cooling issues occur within the trailer during shipment. The

actual pallet-level temperature data, however, demonstrated that there was a wide variation in

pallet temperatures within the trailer – and therefore shelf life loss – while the pallets were in

route in the trailer. The chart below shows 21 pallets of blackberries on one single trailer on

the three day trip from the pack house in Mexico to the DC in Southern California. (Note: the left

axis represents temperature in degrees Fahrenheit. The bottom axis represents time.)

The Intelleflex

Temperature Monitoring Tag

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There are several points to note from the in-transit data. First, this trailer took approximately 5

days (4.94 days) for the trip to the US DC, almost 2 days longer than average. This means ALL

pallets on this truck have experienced two additional days of shelf life loss compared to pallets

on typical trips to this US DC and should be handled accordingly. Second, as a result of the

temperature variation inside the pallets in the trailer, 5 pallets experienced temperatures greater

than 40°F resulting in accelerated shelf life loss:

Pallet 10: lost 9.51 days of shelf life in-transit compared to the expected 4.94

days – for an accelerated shelf life loss of 4.57 days.









An important point to note is that the accelerated shelf life loss experienced by these pallets

does not stop once it arrives in the US DC. The refrigeration units in the trailers and cold

storage facilities are not intended to remove latent field heat. Instead they are designed to

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maintain the pre-cooled pallet temperature – as is shown by the ambient temperature in the

truck (shown by the thick black line at the bottom of the graph which shows an adequate

ambient temperature was maintained). These pallets will continue to lose shelf life at an

accelerated rate through the retailer‟s custody.

An equally critical point is that this loss of shelf life cannot be easily determined by visual

inspection. As a result, product that is shipped on a FIFO methodology increases the risk of

product experiencing accelerated shelf life loss being shipped to distant retailer DCs. Armed

with this information, US DC inventory managers can make more informed decisions to

maximize shelf life (including pre-cooling pallets in the US and intelligent routing of at-risk

pallets), increase revenues and improve freshness and customer satisfaction.

The value of this data can be extended to trading partners and retailers further down the supply

chain. The data from the tags can provide the QC staff at the retail DC with another tool to

enhance or augment physical QC inspections to improve inventory management and forward

each pallet to appropriate retail stores. Each retail store would receive product with adequate

remaining shelf life, reducing waste and enhancing the quality of the product sold to the

consumer.

Quantifying the Results and Calculating the ROI

The project confirmed significant savings and ROI resulting in a single-season payback. The

cost savings used in calculating the ROI included:

Reduced internal shrink by using shelf life data from the harvest-to-precool segment in

the Mexico pack house to intelligently route at-risk pallets (30% of all pallets) to

acceptable destinations,

Reduced internal shrink by improved handling of pallets (13.2% of all pallets) at the US

DCs that incurred accelerated shelf life loss during the trip from Mexico to the US,

The ROI calculation did NOT include the following:

Savings from reduced freezing injury in monitoring the pre-cool process

Savings from reduced re-grading and re-packing costs at US distribution centers

Savings from reduced labor, improved efficiency and increased accuracy for QC and

field personnel

Reduced shrink and increased revenue for retailers due improved product quality and

longer product shelf life resulting in increased/repeat business by retailers and

consumers as well as new retail customers

Increased revenue/case due to improved quality and demand

Savings from continuous operational and systemic process improvements by analyzing

historical data and time efficiency studies

Value of attracting new growers from increased revenue/case and stronger brand,

leading to higher volumes

Value for marketing and sales in differentiating brand within the market

Value of brand protection and brand building

Value of inherent traceability and food safety

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Summary of Key Findings

It has been presumed that trailer-level temperature monitoring is adequate to ensure proper

temperature control within the cold chain and that there is not significant temperature variation

within the trailer to affect the aging (and remaining shelf life) of the produce. This pilot study

proved that this is not the case and that, in fact, monitoring only this segment of the supply

chain and only ambient temperatures in this segment provides little value in controlling the

quality of your produce.

The cost of invisible shrink within the cold chain is significant, both in terms of actual spoilage in

the supply chain and in terms of its effect on quality and salability after the product is delivered

to the retailer (and the consumer). Other key pilot findings include:

30% of pallets received from the field at the pack house in Mexico required special handling

due to in-transit temperature conditions during delivery prior to distribution to the USA.

There is the potential for damage due to over chilling if there are attempts to rapidly cool the

product to achieve proper temperature once it was received from the field.

Significant temperature variation occurs in trailers during transportation from Mexico to the

US distribution centers. 13.2% of all pallets monitored during the Mexico to US segment

experienced temperatures that negatively impacted their shelf life. These temperatures can

vary significantly from pallet-to-pallet to the point of having some pallets lose twice the

expected shelf life in-transit.

Visual inspection at the US DCs could benefit significantly by having the additional pallet

shelf life data.

Additional savings can be achieved (shrinkage avoided) by pallet-level temperature

monitoring and by prioritizing/routing the affected pallets based on the calculated remaining

shelf life when they reach the US distribution centers.

The temperature data collected at the pallet level from harvest provides the visibility

necessary to identify pallets requiring special handling and enables actionable decisions and

supports FEFO+ inventory management to prioritize and route the pallets accordingly. This

can result in a significant reduction in internal (pre-ship) and external (post-ship) shrink,

improved product quality, brand protection and happier customers.

For more information on Intelleflex solutions, please contact us at:

North America Toll-Free: 1-877-694-3539 International/Direct: +1 408-200-6500

[email protected]

Or visit us at:

www.intelleflex.com

WP-16-1011

© 2011 by Intelleflex Corp.

All Rights Reserved

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case study reducing blackberry shrink in-transit...

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