Tag Archives: artificial intelligence

FDA

FDA Begins Phase Two of Artificial Intelligence Imported Seafood Pilot Program

By Food Safety Tech Staff
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FDA

FDA is beginning phase two of its Artificial Intelligence Imported Seafood Pilot Program. The program, which is expected to run from February 1 through July 31, intends to improve FDA’s response in quickly and efficiently identifying potentially harmful imported seafood products.

Phase one of the pilot looked at using machine learning to find violative seafood shipments. “The pilot program will help the agency not only gain valuable experience with new powerful AI-enabled technology but also add to the tools used to determine compliance with regulatory requirements and speed up detection of public health threats,” FDA stated in a news release. “Following completion of the pilot, FDA will communicate on our findings to promote transparency and facilitate dialogue on how new and emerging technologies can be harnessed to solve complex public health challenges.”

The pilot program is part of the agency’s efforts that fall under the New Era of Smarter Food Safety.

FDA

In a Year of ‘Unprecedented Challenges’ FDA’s Food Program Achieved So Much

By Food Safety Tech Staff
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FDA

Earlier this week FSMA celebrated its 10-year anniversary, and FDA Deputy Commissioner for Food Policy and Response Frank Yiannas reflected on the progress and accomplishments as a result of this legislation, and the path forward. As we round out the first week of 2021, Yiannas is looking back at the achievements of 2020 in the face of the historic COVID-19 pandemic.

“I’m struck by how tirelessly our team members have worked together to help ensure the continuity of the food supply chain and to help keep food workers and consumers alike safe during the COVID-19 pandemic,” said Yiannas on the FDA Voices blog. “Their commitment has not wavered in a time when we’re all dealing personally with the impact of the pandemic on our families, schooling our children from home and taking care of elderly parents.”

  • Response to COVID-19. FDA addressed the concern of virus transmission, assuring consumers that COVID-19 cannot be transmitted via food or its packaging. The agency also worked with CDC and OSHA on resources to help promote worker safety and supply chain continuity.
  • Release of the New Era of Smarter Food Safety Blueprint
  • Release of the 2020 Leafy Greens STEC Action Plan with a focus on prevention, response and research gaps
  • Artificial Intelligence pilot program to strengthen the screening of imported foods
  • Proposed Food Traceability Rule issued in an effort to create more recordkeeping requirements for specific foods
  • New protocol for developing and registering antimicrobial treatments for pre-harvest agricultural water
  • Enhanced foodborne outbreak investigation processes and established the outbreak investigation table (via the CORE Network) to disseminate information about an outbreak right when the agency begins its investigation
Emily Newton, Revolutionized Magazine
FST Soapbox

How Can Preventive Maintenance Save Food Processors Money?

By Emily Newton
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Emily Newton, Revolutionized Magazine

The right preventive maintenance approach can improve food safety while saving money. With the right plan, food processing professionals can prevent serious machine failure, decrease maintenance costs and get a better sense of which machines may be more trouble than they’re worth.

However, not every preventive maintenance plan is guaranteed to help processors cut costs. Investing in the right strategy and tools will be necessary for a business that wants to save money with effective maintenance.

How an Effective Preventive Maintenance Approach Can Save Money

To start, the food safety benefits of a preventive maintenance program can help food processors avoid significant troubles down the line. Contamination and recalls will cost time and money.

They can also damage the professional relationships that businesses have with buyers. Recalls are extraordinarily expensive for food and beverage companies, costing an average of $10 million per recall, according to one joint study from the Food Marketing Institute and the Consumer Brands Association (formerly the Grocery Manufacturers Association).

Preventive maintenance can also extend machines’ life spans, giving a company more time before they’ll need to completely replace or rebuild a piece of equipment. Over time, this will help a business prevent machine failure or injuries resulting from improper machine behavior or function. In some cases, it can also mean cheaper repairs and less downtime.

Improving Records With the Right Plan

An effective preventive maintenance plan also generates a significant and detailed archive of maintenance records.

If a plan is implemented correctly, technicians will create a record every time they inspect, repair or otherwise maintain a particular machine. These records will be an invaluable asset in the event of an in-house or third-party audit, as they can help prove that machines have been properly lubricated, calibrated and otherwise maintained.

If a food processing business needs to resell a particular piece of equipment, they’ll also have a full service record that can help them establish the machine’s value.

Over time, the records will also give a highly accurate sense of how expensive the machines really are across an entire business. If the staff records repairs performed, tools used and resources and time spent, professionals can quickly tabulate each machine’s cost concerning man-hours or resources needed. These logs can help single out machinery that may be more trouble than it’s worth and plan future buying decisions.

With a digital system, like a computerized maintenance management system (CMMS), managers can automate most of the administrative work that goes into a preventive maintenance plan.

Modern CMMS tech also provides a few additional benefits beyond streamlining recordkeeping. For example, if a business is up against a major maintenance backlog or trying to balance limited resources against necessary repairs and checkups, a CMMS can help optimize their use of resources. As a result, they can make the most of the time, money and tools they have.

Common Preventive Maintenance Pitfalls

Typically, an effective preventive maintenance plan starts with a catalog of facility equipment. This catalog includes basic information on every piece of equipment in the facility — such as location, name, serial number and vendor, as well as information on how frequently the machine should be inspected or maintained.

Keeping spotty or incomplete records can make a preventative maintenance plan both less effective and more expensive. For example, a partial service record may give an improper idea of how well-maintained certain equipment is. Missing machine information may also confuse service technicians, making it harder for them to properly inspect or maintain a machine.

Too-frequent maintenance checks can also become a problem over time. Every time a maintenance technician opens up a machine, they can potentially expose sensitive electronics to dust, humidity or facility contaminants, or risk damage to machine components.

A maintenance check also means some downtime, as it’s usually not safe or practical to inspect a running machine.

Using the wrong maintenance methods can also sometimes decrease a machine’s life span. For example, certain cleaning agents can damage door gaskets over time. This can eventually cause equipment like a freeze dryer to be unable to create a proper seal.

The equipment manufacturer and technicians can usually help a company know what kind of maintenance will work best and how often they should inspect or tune up a machine.

Going Beyond Preventive Maintenance

Preventive maintenance is the standard approach in most industries, but it’s no longer the cutting-edge of maintenance practices. New developments in the tech world, like new Industrial Internet of Things (IIoT) sensors and real-time artificial intelligence (AI) analysis, have enabled a new form of maintenance called predictive maintenance.

With predictive maintenance, a food processing plant can outfit their machines with an array of special sensors. These sensors track information like vibration, lubrication levels, temperature and even noise. A digital maintenance system will record that information, establishing baselines and data about normal operating levels.

Once the baseline is established, the predictive technology can use fluctuations or extreme variables to predict improper operation or machine failure. If some machine variable exceeds safe operating thresholds, the predictive maintenance system can alert facility supervisors — or, depending on what kind of control the system has, shut down a machine altogether.

The predictive approach can catch issues that may arise in-between checks in a preventive schedule. This can help reduce the frequency of maintenance checks — possibly preventing further machine damage and saving the business money on technician labor.

The data a predictive maintenance system collects can also help optimize equipment for maximum efficiency.

Implementing a predictive maintenance plan will require a bit of a tech investment, however.

Food Processors Can Save Money With the Right Maintenance Approach

Preventive maintenance isn’t just essential for food safety — done well, it can also be a major cost-saving measure for food processors.

Good recordkeeping, a regular maintenance schedule and new technology can all help a business decrease maintenance and equipment costs. For processors that want to invest more in their maintenance plans, a predictive approach can provide even better results.

Maria Fontanazza, Food Safety Tech
From the Editor’s Desk

Top 10 from the 2020 Food Safety Consortium Virtual Conference Series

By Maria Fontanazza
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Maria Fontanazza, Food Safety Tech

2020 has taken a lot away from us, but it has also taught us the importance of being able to quickly adapt (can you say…“pivot”?) to rapidly changing, dire circumstances. For Food Safety Tech, that meant shifting our in-person annual Food Safety Consortium to a virtual event. I really look forward to the Consortium each year, because we are a virtual company, and this is the one time of year that most of the Food Safety Tech and Innovative Publishing Company team are together. When we made the decision to move the event online, we really wanted to be considerate of our attendees, who more than likely were quickly developing webinar and Zoom fatigue. So we created a series of 14 Episodes that spanned from September until last week. I am not going to single out one episode or speaker/session in particular, because I think that all of our speakers and sponsors brought a tremendous amount of education to the food safety community. Thank you.

With that, the following are my top 10 takeaways from the 2020 Food Safety Consortium Virtual Conference Series—and this simply scratches the surface. Feel free to leave a comment on what you learned from our speakers and the discussions this fall.

  1. COVID-19 has served as the springboard for digital transformation, more of which we have seen in the past nine months than in the last several years or even decade. Tech advances are increasing efficiencies, adding the ability to be more predictive, giving more visibility and traceability in the supply chain and offering increased accessibility. These include: IoT; Advanced analytics; Artificial intelligence (FDA has been piloting AI technology); Graph technology used in supply chain visibility; blockchain; mixed reality; and remote monitoring.
  2. There are new responsibilities that come with being a part of America’s critical infrastructure and protecting essential frontline workers.
    • Companies must have a strong relationship (or work to build one) with local health departments and authorities
    • Name a COVID Czar at your company: This is a designated person, located both within a production facility as well as at the corporate location, who manages the bulk of the requirements and precautions that companies should be undertaking to address the pandemic.
  3. Every company should have an emergency risk management plan that centers around good communication.
  4. The COVID-19 pandemic is a reminder to us that the threat for viruses is always lurking beneath the surface. There is still work to be done on the food labs side regarding more rapid assays, leveling the playing field regarding conducting viral testing, and technology that enables labs to get safe, effective and consistent results.
  5. Lessons in sanitation: Investment in sanitation is critical, there are no shortcuts, and empower your sanitation employees, give them the tools they need to effectively do their jobs.
  6. The FDA’s FSMA Proposed Traceability rule is expected to be a “game changer”. It will lay the foundation for meaningful harmonization. FDA Deputy Commissioner for Food Policy and Response Frank Yiannas said the pandemic really put a spotlight on the fact that the U.S. food industry needs better tracking and tracing.
  7. Know your suppliers, know your suppliers, know your suppliers!
  8. Biofilms are ubiquitous, and the process of detecting and eliminating Listeria in your facility is a marathon with no finish line.
  9. Food Safety Culture is a profit center, not an overhead department.
  10. “If I’m not well, I can’t do well.” Making sure your needs are met personally and professionally plays an important role in being a better contributor to your company’s success.

As part of a special offering, we are making four episodes of the 2020 Food Safety Consortium Virtual Conference Series available on demand for free. Head to our Events & Webinars page to register to view the sessions on or after January 2021.

Are Traasdahl, Crisp
Retail Food Safety Forum

Is Programmatic Commerce the Next Wave in Supply Chain Tech?

By Are Traasdahl
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Are Traasdahl, Crisp

While COVID-19 exposed disconnects in the food supply chain, it also served as an overdue catalyst for rapid technology adoption. Food manufacturers, distributors and retailers were forced to grapple with consumer behaviors that—previously expected to occur over five years— changed within about five weeks. Faced with unprecedented demand, channel shifts and rapidly changing consumer purchasing behaviors, forward-looking brands and retailers have started to transform their business models to become highly responsive and agile.

A new approach called “programmatic commerce” may be the key to faster market insights and pivots. Taking cues from past attempts to digitize the supply chain from end-to-end, programmatic commerce uses artificial intelligence (AI) and machine learning (ML) to connect and unify critical business data across food manufacturers, distributors and retailers using common retail portals, BI and CRM tools as well as other data resources and platforms.

With a real-time unified view of channels and activity, programmatic commerce has the potential to create fully automated trade processes to optimize production, inventory management, logistics, promotions and more for both upstream and downstream supply chain activities.

To achieve the potential of programmatic commerce, real-time or near real-time data sources must be easily integrated, unified and displayed. This is in stark contrast to previous attempts to create end-to-end supply chain visibility, which often required custom or manual integrations, had costly and lengthy implementation requirements and necessitated custom reporting.

The programmatic approach is already gaining traction, enabling retailers to leverage AI and ML technology to optimize supply chains. But the real value is in taking it one step further—to tap into rich customer data, understand rapidly changing consumer behaviors and ultimately—to predict and personalize shopping experiences at scale.

Tracking and Adapting to Evolving Consumer Journeys

Consumers increasingly demand greater choice, control, personalization and transparency and companies must continuously create, track and manage a 360º view of customers’ shopping journeys to stay ahead of these trends. Fortunately, real-time data and analytical capabilities are available to supply the critical information they need to implement a programmatic commerce approach.

Among the shifts companies must track as a result of COVID-19 is the explosion in online grocery shopping. In November 2020, U.S. grocery delivery and pickup sales totaled $5.9 billion and a record high 83% of consumers intend to purchase groceries online again, signaling this trend continues as the pandemic lingers on.1 By 2025, online grocery sales are predicted to account for 21.5% of total grocery sales, representing more than a 60% increase over pre-pandemic estimates.2 A permanent shift toward online grocery shopping can be expected as consumers’ shopping and fulfillment experience continues to improve.

For consumers still shopping in stores, the pandemic also drove switches in primary physical store locations. In the United States, an estimated 17% of consumers shifted away from their primary store since the start of the pandemic.3 This was driven by increased work-from-home, which eliminated commuting routes and made different store locations more convenient, including ones closer to home.

Given the multitude of changes impacting consumer journeys during the pandemic, it is imperative that companies track relevant purchase drivers and considerations of each purchase occasion, while also taking into account their recent shopping experience. This creates the need for consistent, seamless and relevant experiences across both digital and physical channels that aligns all touchpoints with the consumer as part of their “total commerce experience.”

Multiple retailers are already pursuing this approach in the hope of retaining their “primary store” status across the totality of their consumers’ shopping experiences. Walmart recently launched a new store format to help achieve “seamless omni-shopping experiences” for its customers through a digitally enabled shopping environment. Customers can use the Walmart app to efficiently find what they’re looking for, discover new products, check pricing, and complete contactless checkout.4 Data tracked on these customers can eventually be used to create personalized recommendations and in-store activations and assistance based on their purchase history and in-store experience.

Conversely, the “digital store” is also being reimagined to align with consumers’ in-store experience to create a seamless shopping experience. For example, personalized meal planning service The Dinner Daily now offers the ability for its members to order recipe ingredients directly from Kroger and other Kroger-owned stores through The Dinner Daily app.5 Integrated data from multiple shopping platforms and consumer touchpoints can provide food manufacturers and retailers with shopper profiles, consumer experiences, and purchase history along with inventory status and other inputs to ultimately build personalized customer experiences and enhance shopper loyalty.

Applying Programmatic Commerce to Deliver Personalization to Consumers

Once armed with real-time data in a uniform format from sources ranging from consumer search analytics to retailer promotional pricing, a programmatic commerce approach can provide companies with predictive understanding of demand and supply to optimize decision making from raw materials through production through retail or direct-to-consumer.

Using online grocery shopping as an example, consumer personalization can be delivered through the accurate prediction and display of items relevant to each shopper based on shopping history, preferences, current cart selections, and other inputs such as real-time availability, marketing promotions and more.

Innovations are already in the market, including Halla, a data science company that developed a grocery-specific personalization algorithm that works with grocery retailer e-commerce platforms to create smart recommendations based on understanding of individual shoppers’ product usage and preferences.6 Another example is the Locai Solutions digital grocery platform, which applies AI to personalize recipe recommendations based on consumer preferences and purchase history and determines ingredients and quantities needed for easy incorporation into their shopping cart.7

The Path Ahead: Accelerating Technology Adoption in the Food Industry

AI and ML are already reducing waste across supply chains and enabling consumer personalization. However, currently only about 12% of retail decision-makers feel they are very effective at providing these experiences to customers and only 10% have access to the real-time data needed to achieve this goal.8

Modern programmatic commerce platforms (see Figure 1) can effectively bridge information gaps, improve inventory and distribution to prevent shortages or overages and help companies be data-ready to meet actual demand. Beyond this, a programmatic approach unlocks the next stage of customer satisfaction and loyalty, personalizing the experience during and after the pandemic.

Programmatic Commerce Platform visualization
Figure 1. Programmatic Commerce Platform visualization. (Courtesy of Crisp)

References

  1. Bishop, D. (2020). Tracking Online Grocery’s Growth. Brick Meets Click.
  2. Mercatus. (2020). The Evolution of the Grocery Customer.
  3.  Briedis, H., et al. (2020). Adapting to the next normal in retail: The customer experience imperative. McKinsey & Company.
  4. Whiteside, J. (2020). Reimagining Store Design to Help Customers Better Navigate the Omni-Shopping Experience. Walmart.
  5.  Corke, R. (2020). Our Online Ordering Connection for Kroger is Here. The Dinner Daily.
  6.  Halla. (2016). Halla Grocery Solutions.
  7. Locai. (2018). Locai Meal Planning.
  8. Bluecore. (2019). Align Technology, Data, And Your Organization to Deliver Customer Value.

 

Megan Nichols
FST Soapbox

Four Influential Technologies Changing Food Manufacturing

By Megan Ray Nichols
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Megan Nichols

Some impressive technologies are not only impacting the food industry right now but will also have a huge impact in the future. As their use grows to be more prevalent, the industry will change to be smarter and more efficient, with continued improvements across the board.

1. AI and Advanced Robotics

While artificial intelligence and advanced robotics are two distinct technologies, they are frequently paired together. AI, and the data it digests, is used to command robots, allowing them to be more precise, more intelligent and more aware.

Most robots on their own are capable of completing only repetitive and clearly defined tasks. Throw something unique into the mix and they’ll either fumble or fail. However, when governed by data-based intelligence solutions like AI or machine learning, those robots become something incredibly advanced.

In the food industry, machinery and robots are leveraged to improve operations, further maintaining quality and efficiency, at affordable costs. They often work alongside human laborers to augment or enhance processes. They come with several unexpected benefits as well, such as much-improved safety for workers, faster and higher product output and consistent, reliable quality.

For example, JBS, one of the world’s largest meatpacking firms, deployed robotic butchers within its plants. The robots were used to slice more challenging meats, which reduced workplace injuries.

2. Automation

Automation stands alongside AI and advanced robotics, even incorporating those technologies to create a streamlined system. As of 2017, 73% of surveyed companies in the food and beverage manufacturing industry either had or were in the process of establishing automation within their facilities.

Many systems are designed to replace or enhance repetitive tasks, boosting their speed and accuracy, to significantly improve output, without incurring a loss in quality. It’s not just about hardware, like swapping a human laborer for a robot. It’s also achieved through software. Think supply chain management solutions that help plan for various events and experiences without human input.

When many of these technologies are used side-by-side, it strengthens their application and usability. As is true of advanced robotics, for example, AI can also be used to create more intelligent automation platforms. Instead of carrying out rote or simple tasks, they can be programmed to react and engage through any number of parameters. The system might slow production, for instance, based on a decrease in product demand. Or, it might swap to an alternate component or ingredient because of a shortage somewhere.

With the right controls and support, automation technologies are game-changing. With the global population growing and demands increasing more with each year, food manufacturers will look to streamline their operations and boost output in any way possible, and automation will be a go-to.

3. Digital Twins

Digital twins in food manufacturing are essentially simulated copies or a virtual representation of a physical system. That definition might seem confusing, but think of it as a clone that can be manipulated for testing and analytics.In other words, it is a twin of the actual system and information, in every sense of the word, albeit one that is more versatile and less vulnerable. It allows manufacturers and distributors to run simulations by feeding specific information into the system to identify patterns, recognize outcomes and much more.

As the systems and controls supporting the field become smarter and more digitized, digital twins in food manufacturing will find their way into product development, testing, post-production, distribution and nearly every other facet of the industry. It will become an integral component to not only understand what’s happening in the market but also for keeping up with the ebb and flow of supply and demand.

4. Blockchain

Even well before the pandemic, people had become much more conscious about the foods they consume. They want to know the origin of their goods and whether they’ve been sourced using safe, healthy and environmentally friendly methods. The problem with such demands is that, until recently, there haven’t been many solutions for increased visibility within the food supply chain.

Growing concerns for health are now a priority, and visibility is an absolute must. Blockchain technology is the answer, providing precisely the kind of visibility, efficiency, controls and collaboration that consumers want.

With this food manufacturing technology in place, someone could trace a head of lettuce back to its initial seeding. They can see who grew the plants and where, and which methods they used to mature the crop. Then, they can follow its journey to the store shelf.

How is such a thing possible? It all has to do with the technology. In its simplest form, Blockchain is a digital ledger or complete and digitized record of a particular data set. The data that goes in is added to something called a block, and as more is added, it is tacked on to the end of that block to create a long, linked record. Every bit of information is visible across the entire chain, hence the name blockchain.

Walmart is using the technology to track potential food contamination outbreaks. It empowers them to not just find the source but also find the many branches involved — like where goods might have been shipped and who may have purchased them.

Food Manufacturing Technology for the Future

While each food manufacturing technology discussed here is incredibly influential and will have a direct impact on the future of the industry, they are not the only solutions making waves. Some additional examples include:

  • Drones and automated delivery vehicles
  • 3-D printing for edible goods
  • Smart or precision agriculture
  • High-tech packaging
  • Smarter waste disposal and recycling

The takeaway is that technology is vastly improving the operational efficiency of the food supply chain, from farmers and manufacturers to the retail stores featuring goods on their shelves. There’s no right or wrong buy-in, as any one of these technologies can be used to streamline separate processes. The biggest challenge will be deciding what to upgrade first, especially when it comes to delivering high-quality, fresh goods in a prompt manner.

Checklist

2020 FSC Episode 2 Wrap: Pest Management and How Technology Is Transforming Business

By Maria Fontanazza
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Checklist

Last week we were joined by experts in pest management for Episode 2 of the 2020 Food Safety Consortium Virtual Conference Series. Although pest management may not be seen as the most exciting topic, all food plants are required to have an integrated pest management program. In addition, the digital transformation fast-tracked by COVID-19 is also driving innovation in the remote monitoring of pests.

Barney Debnam, global agriculture strategy lead at Microsoft kicked off the conversation with some key themes driving change within the global food system, which have also been accelerated by COVID: Geopolitical forces, consumerization, democratized biology, sustainability, shifting economics and food security. As technology continues to evolve and is adopted at a faster pace (think artificial intelligence and how accessible it is now), businesses will be able to transform their outcomes by becoming more predictive. The key technology enablers in the process include:

  • Internet of Things and edge computing
  • Advanced analytics
  • Artificial intelligence and cognitive computing
  • Graph technology
  • Blockchain
  • Digital workplace
  • Mixed reality

The most significant benefit of implementing technology such as remote monitoring into an IPM program is its ability to provide visibility and the data to back up what is happening in a facility.

Get access to the presentations and points discussed during this exclusive session by registering for the 2020 Food Safety Consortium Conference Virtual Series. Attendees will have access to upcoming sessions as well as the recordings of all sessions.

Summer of 2020: Hot Topics Include FDA Inspections, Records Retention, and New Technology Era

By Food Safety Tech Staff
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10

Is Food-Grade always Food-Safe?

9

Important Restaurant Food Storage Safety Tips You Need to Know

8

How a History of Slow Technology Adoption Across Food Supply Chains Nearly Broke Us

7

FDA Unveils Blueprint for New Era of Smarter Food Safety

6

FDA, CDC Investigating Multistate Cyclospora Outbreak Involving Bagged Salads

5

COVID-19 Leads Food Companies and Meat Processors to Explore AI and Robotics, Emphasize Sanitation, and Work from Home

4

FDA Announces Inspections Will Resume…Sort Of

3

Sustainability Strategies for the Food Industry

2

Top Three Visibility Challenges in Today’s Food Supply Chain

1

The COVID-19 Record Retention Conundrum

Pratik Soni, Omnichain
Retail Food Safety Forum

Top Three Visibility Challenges in Today’s Food Supply Chain

By Pratik Soni
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Pratik Soni, Omnichain

To say that COVID-19 has been disruptive would be putting it mildly. The pandemic’s sudden and seismic impact has brought major upheaval across industries—the food industry and its supply chain included.

There was the initial panic buying that drove upticks in consumer demand for which few manufacturers and grocers were prepared, resulting in widespread product shortages. With restaurants closed, distributors and suppliers were left with considerable excess inventory—most of which ended up as waste and losses. Inside production sites and plants, many had to try and maintain their output with a reduced workforce, even as demand continued to climb. Meanwhile, some plants unfortunately have had to shut down operations on account of employees testing positive for COVID-19.

In the time since the outbreak, the food supply chain has stabilized to an extent. Store shelves are continuously being replenished with products. Restaurants have started reopening with new health and safety measures. Yet even as the industry takes gradual steps toward recovery, the underlying problem that led to the magnitude of COVID-19’s impact persists: Lack of visibility. There was lack of visibility into supply and demand and what was happening upstream and downstream across the supply chain, which prevented timely, proactive action to optimize operations in face of disruption.

Looking ahead, participants across the food supply chain will need enhanced end-to-end visibility so that they can work together to get ahead of the curve. As part of gaining this visibility, they will need the transparent exchange of information and cohesive collaboration to adapt especially as the food industry continues to see shifts in consumer behavior and the marketplace in the wake of COVID-19—particularly in the following three key areas.

Food Distribution

While food producers have been working tirelessly to keep grocery store shelves and restaurant kitchens well stocked, there continues to be fluctuating availability on certain products, such as eggs, dairy, poultry and meat. This has led distributors and suppliers to increase their prices when selling these goods to stores and restaurants, who have had to then pass the additional costs on to consumers through their own price increases and surcharges, respectively. One report from CoBank, a cooperative bank part of the Farm Credit System, notes there could be as much as a 20% increase in the price of pork and beef this year due to supply issues.1 Many grocers have also implemented purchase limitations on consumers to combat shortages.

These downstream implications stem largely to uncertainty in the supply chain, with stores and restaurants unsure about available supply upstream and when they can expect to receive shipments. But if there was clearer visibility and transparency between production, distribution, transportation, food service and retail, then all parties could better anticipate and plan for supply shortages or delays. For instance, if a meat processing plant has to temporarily close due to cases of COVID-19, they can immediately communicate to the rest of the supply chain so that parties downstream can readily find alternative sources and minimize any necessary price inflations or other implications to consumers.

Consumer Demand

Even with the reopening of restaurants, people will likely choose to cook more of their meals at home. It was a trend that began with restaurant closures and will continue for the foreseeable future as consumers remain cautious of dining out. While this may bring tough times ahead for the food service industry, the grocery sector is seeing a huge lift in business. Research from restaurant management platform Crunchtime shows that, towards the end of June, restaurants were only seeing 64.5% of their pre-COVID-19 sales levels.2 At the same time, a study by Brick Meets Click and Mercatus reveals U.S. online grocery sales reached a record $7.2 billion in June, up nearly 10% over May.3

For food companies and brands, growth in the grocery sector has presented a challenge in the way of demand planning and forecasting. I’ve personally spoken with several company executives who have seen significant upticks in orders from their grocery channel partners—an increase for which they didn’t forecast—and are now struggling to adjust production levels accordingly to avoid the risk of excess production that would lead to unnecessary costs, wastes and losses. In such instances, real-time visibility into transactional activity and stock levels at the retail level would help production planners improve the accuracy of their forecasts and enable them to think steps ahead before orders come in and thereby optimally balance supply with demand. Stores would remain well stocked and the supply chain could flow in a more efficient and profitable way for all participants.

Food Handling

Without question, public health is the number one priority right now. Participants at each point in the food supply chain today need to communicate with each other, as well as to consumers, that they’re following best practices for social distancing, disinfecting and other precautions. It’s not to prevent the possible transfer of the virus via actual products, as the FDA notes there is currently no evidence of transmission through food or packaging. But rather, it’s to build greater confidence in the food supply chain—that everyone is doing their part to support individual and collective health and safety, which in turn prevents possible facility closures or other case-related bottlenecks that would inhibit consistent supply to the market.

There also has to be confidence that, amid these countermeasures for COVID-19, companies are still upholding their commitments to food safety, integrity and proper handling. What can support that confidence is data—shared data from every point in a product’s journey from source to shelf. The data should be transparent and available to all supply chain participants as well as immutable so that it is tamperproof and fully traceable should there be any problem, such as mislabeling or a foodborne illness. The data ultimately holds everyone accountable for their role in ensuring a safe food supply chain.

To achieve the level of visibility outlined above, the food industry will have to break away from legacy processes involving the siloed management of operational systems and databases. Instead, the disruption seen during COVID-19 and ongoing shifts in the marketplace should encourage companies to consider digital transformation and technologies that can enable a more cohesive and nimble food supply chain. These are technologies like blockchain, which provides a decentralized, distributed ledger to publish and share data in real time. Moreover, artificial intelligence that can leverage incoming real-time data to guide next-best actions, even when the unexpected occurs. Personally, I always return to the notion that the supply chain is a team sport. You need visibility to know what each team member is doing on the field and how to align everyone on a gameplay. The digital solutions available today offer that visibility and insight, as well as the agility to pivot as needed to obstacles along the journey from source to shelf.

References

  1. Taylor, K. (May 6, 2020). “The American meat shortage is pushing prices to unprecedented heights — here’s how it could affect your grocery bill.” Business Insider.
  2. Maze, J. (July 7, 2020). “As the coronavirus resurges, restaurant sales start slowing again.” Restaurant Business.
  3. Perez, S. (July 6, 2020). “US online grocery sales hit record $7.2 billion in June.” TechCrunch.
Are Traasdahl, Crisp
FST Soapbox

How a History of Slow Technology Adoption Across Food Supply Chains Nearly Broke Us

By Are Traasdahl
1 Comment
Are Traasdahl, Crisp

The COVID-19 crisis has exacerbated existing disconnects between food supply and demand. While some may be noticing these issues on a broader scale for the first time, the reality is that there have been challenges in our food supply chains for decades. A lack of accurate data and information sharing is the core of the problem and had greater impact due to the pandemic. Outdated technologies are preventing advancements and efficiencies, resulting in the paradox of mounting food insecurity and food waste.

To bridge this disconnect, the food industry needs to implement innovative AI and machine learning technologies to prevent shortages, overages and waste as COVID-19 subsides. Solutions that enable data sharing and collaboration are essential to build more resilient food supply chains for the future.

Data-sharing technologies that can help alleviate these problems have been under development for decades, but food supply chains have been slow to innovate compared to other industries. By reviewing the top four data-sharing technologies used in food industry and the year they were introduced to food supply chains, it’s evident that the pace of technology innovation and adoption needs to accelerate to advance the industry.

A History of Technology Adoption in the Food Industry

The Barcode – 19741
We’re all familiar with the barcode—that assemblage of lines translated into numbers and letters conveying information about a product. When a cashier scans a barcode, the correct price pops up on the POS, and the sale data is recorded for inventory management. Barcodes are inexpensive and easy to implement. However, they only provide basic information, such as a product’s name, type, and price. Also, while you can glean information from a barcode, you can’t change it or add information to it. In addition, barcodes only group products by category—as opposed to radio-frequency identification (RFID), which provides a different code for every single item.

EDI First Multi-Industry Standards – 19812
Electronic data interchange (EDI) is just what it sounds like—the concept of sharing information electronically instead of on paper. Since EDI standardizes documents and the way they’re transferred, communication between business partners along the supply chain is easier, more efficient, and human error is reduced. To share information via EDI, however, software is required. This software can be challenging for businesses to implement and requires IT expertise to handle updates and maintenance.

RFID in the Food Supply Chain – 20033
RFID and RFID tags are encoded with information that can be transmitted to a reader device via radio waves, allowing businesses to identify and track products and assets. The reader device translates the radio waves into usable data, which then lands in a database for tracking and analysis.

RFID tags hold a lot more data than barcodes—and data is accessible in remote locations and easily shared along the supply chain to boost transparency and trust. Unlike barcode scanners, which need a direct line of sight to a code, RFID readers can read multiple tags at once from any direction. Businesses can use RFID to track products from producer to supplier to retailer in real time.

In 2003, Walmart rolled out a pilot program requiring 100 of its suppliers to use RFID technology by 2005.3 However, the retail giant wasn’t able to scale up the program. While prices have dropped from 35–40 cents during Walmart’s pilot to just 5 cents each as of 2018, RFID tags are still more expensive than barcodes.4 They can also be harder to implement and configure. Since active tags have such a long reach, businesses also need to ensure that scammers can’t intercept sensitive data.

Blockchain – 20175
A blockchain is a digital ledger of blocks (records) used to record data across multiple transactions. Changes are recorded in real-time, making the history unfalsifiable and transparent. Along the food supply chain, users can tag food, materials, compliance certificates and more with a set of information that’s recorded on the blockchain. Partners can easily follow the item through the physical supply chain, and new information is recorded in real-time.

Blockchain is more secure and transparent, less vulnerable to fraud, and more scalable than technologies like RFID. When paired with embedded sensors and RFID tags, the tech offers easier record-keeping and better provenance tracking, so it can address and help solve traceability problems. Blockchain boosts trust by reducing food falsification and decreasing delays in the supply chain.6

On the negative side, the cost of transaction processing with blockchain is high. Not to mention, the technology is confusing to many, which hinders adoption. Finally, while more transparency is good news, there’s such a thing as too much transparency; there needs to be a balance, so competitors don’t have too much access to sensitive data.

Cloud-Based Demand Forecasting – 2019 to present7
Cloud-based demand forecasting uses machine learning and AI to predict demand for various products at different points in the food supply chain. This technology leverages other technologies on this list to enhance communication across supply chain partners and improve the accuracy of demand forecasting, resulting in less waste and more profit for the food industry. It enables huge volumes of data to be used to predict demand, including past buying patterns, market changes, weather, events and holidays, social media input and more to create a more accurate picture of demand.

The alternative to cloud-based demand forecasting that is still in use today involves Excel or manual spreadsheets and lots of number crunching, which are time-intensive and prone to human error. This manual approach is not a sustainable process, but AI, machine learning and automation can step in to resolve these issues.

Obtaining real-time insights from a centralized, accurate and accessible data source enables food suppliers, brokers, distributors, brands and retailers to share information and be nimble, improving their ability to adjust supply in response to factors influencing demand.8 This, in turn, reduces cost, time and food waste, since brands can accurately predict how much to produce down to the individual SKU level, where to send it and even what factors might impact it along the way.

Speeding Up Adoption

As illustrated in Figure 1, the pace of technology change in the food industry has been slow compared to other industries, such as music and telecommunications. But we now have the tools, the data and the brainpower to create more resilient food supply chains.

Technology adoption, food industry
Figure 1. The pace of technology change in the food industry has been slow compared to other industries. Figure courtesy of Crisp.

Given the inherent connectivity of partners in the food supply chain, we now need to work together to connect information systems in ways that give us the insights needed to deliver exactly the rights foods to the right places, at the right time. This will not only improve consumer satisfaction but will also protect revenue and margins up and down food supply chains and reduce global waste.

References

  1. Weightman, G. (2015). The History of the Bar Code. Smithsonian Magazine.
  2. Locken, S. (2012). History of EDI Technology. EDI Alliance.
  3. Markoff, R, Seifert, R. (2019). RFID: Yesterday’s blockchain. International Institute for Management Development.
  4. Wollenhaupt, G. (2018). What’s next for RFID? Supply Chain Dive.
  5. Tran, S. (2019). IBM Food Trust: Cutting Through the Complexity of the World’s Food Supply with Blockchain. Blockchain News.
  6. Galvez, J, Mejuto, J.C., Simal-Gandara, J. (2018). Future Challenge on the use of blockchain for food traceability analysis. Science Direct.
  7. (2019). Crisp launches with $14.2 million to cut food waste using big data. Venture Beat.
  8. Dixie, G. (2005). The Impact of Supply and Demand. Marketing Extension Guide.