쉐도잉 연습: Traceability 101: An Introduction to Food Supply Chain Traceability - 영상으로 영어 말하기 배우기

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Thank you, Mark.
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We truly appreciate the opportunity to join you
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and the entire AFTO community today to talk about a topic near and dear to our heart and to all of us.
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So Thomas and I are going to tag team today if we then move to the next slide.
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So first of all, we wanted to give you a sense of the scope of the topic
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that we'd like to talk to.
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First of all, we're going to give a little bit more background on Thomas and IA's role.
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We're going to talk about concepts, standards, where digital technology is today, spend quite a bit of time on interoperability, which is a key concept
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that we want to make all of you have a deep understanding on and what that means to the end-to-end supply chain.
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We also want to talk a little bit more about how this looks like in the future, specifically for your roles in your day-to-day life.
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And then we'll wrap up, hopefully, with 10 to 15 minutes of Q&A.
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so you can ask us any questions
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that you have on the top of your mind that's what
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we'd like to cover today I know we have a short one-hour timeframe
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but we'll try to get through as much as we can
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and give you a nice solid grounding or traceability conversation is today
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so next is you know webinars are always great to be able to put a name
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and a face together so there you see a picture myself.
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I come to the ISP about a year ago after a
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20-plus year career in the food CPG industry across Procter & Gamble
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and PepsiCo in various different roles of product process quality development type of roles commercializing new products
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and new technologies to the marketplace.
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Thomas how about you go ahead and introduce a little bit more about yourself.
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Thanks Brian.
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So here's my head shot so you have an idea of what I look like.
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I do wish I had taken my gotten a haircut before I took this picture but there's me.
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I have a background in microbiology and epidemiology and currently pursuing further education in food science.
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I kind of found this niche in food traceability research and early implementation and standardization.
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I was involved in trace back investigations
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while at the Georgia Department of Agriculture in their food safety division
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and I really saw a need for improving end-to-end traceability capabilities
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and I've at the moment now I lead interoperability work for the global dialogue CPU traceability
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which I'll kind of go into a little bit more detail how
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that applies more broadly to enabling better traceability systems but yeah
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so they're three file on me and I'm gonna head back off to Brian
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so you can start us off here sure
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so we thought we gave a little bit of background on IFT
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and how that fits into the traceability space
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so first of all a little bit about ifd so ift is a 15 000 member individual member community
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focused on the science of food delivering safe nutritious
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and sustainable food supplies to the world ift
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and traceability specifically has a you know 12-year history going back to partnerships between ift
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and the fda in preparation for the creation
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and rollout of fisma as you can see on the slide
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here multiple year engagements with contract work with the FDA convening
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experts across multiple stakeholder groups to conduct pilot traceback investigations and identifying some recommendations that ultimately were put into section 204 regulation.
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After we did that work, we transitioned somewhat into a partnership working specifically in the seafood traceability space.
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We chose seafood for multiple reasons that we'll get to in a little bit deeper into the later in the presentation.
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But the complexity, global scale, and the use cases
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that were of need there really sought us to choose seafood as a commodity of interest
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that we would put our focus on.
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Speaking of use cases, on the next slide, we'll try to summarize this in a couple different ways.
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Many of us think of traceability as focused on recall management and the food safety aspects of that.
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But ultimately, traceability systems and the backbone of information that they create have a lot of different use cases,
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including sustainability, fighting fraud, legality, provenance, and chain of custody.
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We believe that all of this ladders up to higher order consumer needs, such as trust and transparency, and having confidence in their food supply that they're getting the
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purchase and it's safe for them
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and their families to use just want to ground a little
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bit of you know everyone in the case of where we're traceability data can be used now
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that we're going to go in a little bit deeper into concepts
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and other areas I'll let you hand it off to Thomas
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to take you into the next layer of depth Thomas take it away thanks Brian
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so we're gonna first start talking traceability concepts I kind of
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want to preface this discussion with this is how we have seen traceability evolved
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and how businesses currently think about traceability
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when they're thinking about enabling better trace back mechanisms
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and also addressing those use cases that Brian had talked about there's been
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because of the spark and you know possibilities and digital technology
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There's been all sorts of use cases that have been played with
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and have been having early implementation that go beyond food safety.
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So I want to kind of center some of the concepts on what our business is thinking about
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when they're thinking about traceability and how that applies to traceback investigations
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and what you may be using in your familiarity with traceability.
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So here's kind of what the current paradigm is, is one up, one down traceability.
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It comes out of the 2002 Antibiotera Act where we needed to have a record keeping requirement
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so that there can be the ability to easily trace back
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or to facilitate trace back investigation in the event of a food emergency.
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So this is kind of displaying the kind of what the scenario is practically from a systems design point of view.
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So because you have basically the record keeping components of that you're keeping the records on your customers and on your suppliers,
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you end up having unique critical junctures where that you that are you have special relationships between them.
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You may have actually a different way of keeping that information depending on what your relationship is.
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So you end up having all of these types of relationships that you're managing just on the single supply chain node.
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This kind of works for internal traceability purposes, but when you are needing to connect the dots across the supply chain,
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especially if you need to have origin data, you have
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quite a bit of problems because you're actually having to connect this situation multiple times
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and in food supply chains that you can actually have quite a few different nodes you can have
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fragmented supply chains you can have very different ways of keeping this information
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and the way you keep the information especially from paper records
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maybe it's been on a particular person knowing where it is
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so it's it it isn't really effective for a lot of use cases
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and traceability that we had talked about earlier especially anything about traceback investigations where
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if you have a perishable food you need to be able to know
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when that you know you know where in the supply chain
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that potentially compromised product sits and as fast as possible so
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if you are even waiting a few hours at each of the supply chain junctions the critical tracking events,
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it still can end up being a prohibitive amount of time to be affected in a traceback
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and then subsequent trace forward investigation.
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So this is kind of the vision of what the future of traceability should be, is end-to-end traceability.
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This is really, there's some misconceptions about what end-to-end traceability really means, but what we're really entailing is a,
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you know, industry-wide
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or sector-wide approach to being able to enable the connection points to trace back products all the way to the source.
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So this is more than just requiring food companies to keep information on their customers and on their suppliers.
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It's also really kind of mandating a standardized way of housing this information
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and setting up interoperability and data query mechanisms so that you can facilitate this trace back even among disparate information systems.
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So, when you're designing, you know, a large-scale system like this, this is kind of like a system of systems, right?
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You're wanting to kind of hone in on the core components of what you need to know
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and what you need to design around.
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So there's a couple of different groups of concepts here that are combined into one slide.
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You have the key data elements and critical tracking events, and these are concepts
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that were created by the Global Food Traceability Center in understanding how to provide recommendations to the FDA
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when implementing FSMA's Section 204 provision.
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And then we also have three other concepts on that are really come from GS1 on product identity.
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So I'll actually now go into detail on all these.
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So key data elements these are the key pieces of information
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that need to be collected at each juncture of the supply chain so that you can address the use case.
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So for food safety, this may just be information on the who, what, where, when, and why of the product so you can do an effective recall.
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But if you're thinking about it also in terms of food quality or if you're thinking about it in terms of sustainability, you may be capturing other data elements.
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So So for instance, when we work in seafood, catch area is very important
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because companies are also concerned about potentially illegally caught product entering their supply chain and then being responsible for it.
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So they may have a catch area or they may have the gear type or something like that.
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So other key data elements can include temperature readings,
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humidity, that sort of thing that also be aiding a particular company's quality indexes.
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So critical tracking events are in work in conjunction with key data elements.
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So these are the critical junctures
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that I was talking about where you need to track the KDE's in order to address your use cases as well.
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So not every event that happens in a logistical supply chain may be necessary to be captured for traceability reasons.
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So and it depends on what your use case is that you are designing your traceability system around.
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For recall purposes it's really being able to know when
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and where the product is and
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so really it's kind of centered on chain of custody
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but for other use cases you may have you may have other CTEs.
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These are broadly grouped into commissioning events, the origin of a food product,
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the harvesting of the base ingredient, transformation, which takes inputs of particular logistical units
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and transforms them into an additional one
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so this is usually a processing step of some sort also aggregation events can take on this form
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or commingling events sorry not aggregation
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and then depletion is also the consumption of the product
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and then the other three concepts that are really core are identification capturing
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that identification and sharing that identification of that product identity
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so what is very important to end-to-end traceability is the ability to have a globally unique identification schema
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so for companies that work
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and the processor sector forward to to the retailer they tend to use
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and there's wide especially in the United States there's wide-scale adoption of GS1 standards for product identity this includes things like G10s,
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serialized G10s, SFCCs for containers, and then also having GLNs,
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the global location number for registering locations.
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And these are captured through a variety of mechanisms.
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These are the familiar barcodes that can take on the form of data bars or GS1-128 case labels,
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or they also can take the form of QR codes.
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And then also in the emerging spaces using RFIDs for capturing this information.
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There needs to be a way to basically link the digital and physical realms and that's what this capture segment really entails.
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And then the sharing platform and this is the sharing of business information across supply chain partners
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and ensuring that information is kept on a need-to-know basis but it is readily accessible
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in the cases of the need for traceability information.
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In data sharing there's a balance between what should be visible and what is business sensitive and that is
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is still being explored in what that proper balance is but
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and especially in end-to-end traceability schemas but it is yeah anyway
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so moving on this is kind of
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when we're conceptualizing traceability of the design elements we basically put KDE's
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and CTE's in a matrix where we have the who what where
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when and why along the rows
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and then columns of each of the critical tracking events
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that happen this has been very useful because it can help you figure out
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and conceptualize what needs to be captured at each of the CTE's
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and what the because odds are you're already collecting
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that each of the supply chain partners are capturing this information
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but it may not be complete on what they have available
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this also allows you to understand what format they may be
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so some of these records may be digitized some of these records may be paper-based
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and it allows you to devise a process flow for the products
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that you're trying to initiate a traceability information traceability system in
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and allows you kind of make strategic choices on technology adoption identifying identifiers
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and figuring out which KDE's needs to be collected
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so I'm gonna after talking about the the core concepts to traceability
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and the basic vocabulary words
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that we use in traceability space I want to kind of talk about how current traceability is a challenge um
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and what are some of the drivers towards what the current trends you may be seeing in government along disability.
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I kind of want to talk a little bit about, it's kind of in broad swaths, but about historical trends.
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But just in general we are you know seeing you know localization of production of various commodities
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and because of
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that we also have extensive distribution networks to being able to deliver those those goods to the consumer readily available and cheaply.
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So So there's been a lot of choices that we have made in order to make this possible.
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We end up having fairly complex supply chains.
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We have aggregation and co-mangling events that can make trace back to the source difficult.
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And we also, because of the way the industry sits and because of the various players on those stakeholders' needs,
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we have disparate information systems where some people may relying very
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much on paper records still some are looking at you know fully digitized blockchain based systems
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and so you have kind of a variability in adoption so
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that current landscape can be quite tricky to navigate because
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when you're designing a system-wide system you know you are having to anticipate
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and design around those those variability's of heterogeneity
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and then also I kind of wanted to speak to some of the scientific and outbreak trends.
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So methods in, you know, that often when we're thinking about traceback investigations, we're thinking about kind of three principal stools.
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So there's, or in food safety emergencies, we're thinking about three principal stool legs.
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We're thinking about lab results.
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We're thinking about the epidemiology linking lab results to the vehicle.
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And then we're also then doing the traceback
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investigation to identify the convergence point and to be able to trace forward
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and understand where the potentially contaminated product may be so
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that it can be removed from the shelves or removed from the supply chain to protect consumers.
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So what we have seen in general is that you know lab techniques
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and epidemiology have generally continued to improve and and continue to be able to discover lower and lower case count outbreaks,
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we're able to, with whole genome sequencing, we're able to more easily link laboratory results with each other,
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previously with, with the pulsatile electrophoresis,
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we're matching up PFGE patterns, and we sometimes had false links sometimes missed links
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but with WGS we're much more able to identify outbreaks as they're occurring
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and long-term outfits as well and then epidemiology also continues to improve
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and so as data collection
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and also the clinical realities are changing too the physicians are
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much better able to test for a variety of potential pathogens and also increasing the detection.
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And then on kind of the more human side of this coin, we've seen, you know, social media really amplifying outbreak messages,
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people being very cognizant of it and being able to share information very rapidly,
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and this can have a greater reputational risk to companies.
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And then, you know, with those two identifications of outbreaks happening easier,
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much more robust and immediate data access is really necessary for an effective traceback response.
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So, I kind of want to do a little bit of time check yeah
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so i'm going to kind of quickly go through the romaine
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one of the romaine uh the outbreaks of e coli 0157
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and romaine last year this is the one
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that um came out of huma um this uh
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and just kind of illustrate how this is really showcasing why traceability is so important
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and we have such a um you know we have a
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challenge in front of us um as i said it was
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very widespread multi-state outbreak with very serious illnesses with 45 with
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HEUS the they could not pinpoint a single grower processor harvester
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distributor there was not as I show later here there was not a convergence point
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that they were able to identify in their various traceback investigation
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so they had to brought they were able to they didn't
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know what the you know what the pathogen was it didn't they did also know the vehicle, they knew that it was romaine lettuce,
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and they did know the growing region at least
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because of also I mean this is where romaine lettuce is produced at this time of year, but also in the Traceback Investigations,
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they could not readily pinpoint exactly where it was coming from
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and had to issue quite broad recommendations on not consuming any romaine coming from the Yuma region.
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And so it also took quite a bit of time in real time to do these traceback investigations
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and that was also very because of
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that they had to keep amending their the regular regulators had to keep amending their recommendations to consumers
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and their their their recall efforts which is also less than ideal.
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Again this is kind of just summarizing it
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and how it couldn't be resolved in real time
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and where end-to-end traceability
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and digitized standardized records could be a very it could be of extreme benefit in in aiding
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or aiding this process
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and one other thing that's touching why it's faceability is challenging
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as I did it kind of alluded to this earlier is
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that we have these really shiny objects that are occurring in digital technology
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that are very promising but they also are not silver solutions especially blockchain
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which I will talk about in depth a little bit later
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if we have time but also artificial intelligence and advanced analytical techniques
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and IOT devices all have these potential benefits to enabling indenture
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its ability of having much closer data monitoring of having unified methods of sharing data
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and decentralized approaches to data sharing but they are they do require certain elements
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and that's why I taught started this talk talking about what the core things
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that we need to know we need to know what those
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key data elements are we need to know what those critical critical junctures where the data needs to be collected
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and we need to have a unit we need to have an ability to have global uniqueness on the things
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that we're tracking and without those elements none of these you know technologies
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that are coming out are necessarily going to solve that
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but they can if you are having a standardized approach and
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if you are consider having a thoughtful approach to your design
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that these can be of benefit but it does cloud the conversation somewhat
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so that kind of leads me into really what GFTC brings to benefit for the global food industry
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which is really having the ability to bridge various stakeholders to arrive at unified standards
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and traceability and various good commodities and
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so I want to go over some of the existing standards
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that exist for product identity and traceability
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and just kind of pointing you guys to tools
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that you may be able or resources you may you may already be aware of them
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but that you can look at to learn more about what the current thinking of
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or what the current thinking is and traceability and what you can do to further your own education.
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Really, for product identity standards and linking supply chain nodes, the Global Standards 1, or GS1,
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has made significant strides in having a unified approach to global uniqueness on logistical units and product identity.
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They have various working groups and standards that they work on to facilitate this.
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So as you probably know they are known for the barcode
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and the G10 and informing other various identifiers through the purchasing of a company prefix.
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They are are deeply involved in various traceability efforts
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and designing their standards around the ability to trace back various goods, including food.
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So they have a fresh foods and retail working group.
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They also have standards called the Global Traceability Standard, EPCAS, which stands for Electronic Product Code Information Services,
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and Digital Link, which a new a new initiative to have to really utilize
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the power of the internet to digitally link records together I will not really go into greater depth on this
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because I am trying to be cognizant of time the produce traceability initiative is a traceability initiative
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that relies heavily on GS1 standards evidenced by one of the major partners being GS1US.
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The impetus to this initiative was the 2006 E coli 0157H7 outbreak in spinach in 2006.
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So that kind of had this commodity killer effect where even companies that were not implicated in the outbreak had,
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you know, decreased consumption and decreased business for years.
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It took up to a decade really to get up to the same consumption that was at its peak.
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So this is a North American effort primarily focused on the US,
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Canada, and Mexico to have a unified approach to traceability so that they can trace back products to its to their source.
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really they focused on labeling and identification and how that
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and resolving real technical challenges that they have in the especially in the upstream
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which is where it's most challenging to start global uniqueness
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and identification and to have digitized records
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and then finally the I'll talk a little bit about the global dialogue
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and TV traceability this is the effort that we are currently working on.
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We are working with an industry collaboration of 67 or 70
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seafood companies across the world to develop a unified traceability standard and to address both food safety and illegal catch.
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Illegal fishing is an extremely large problem in the seafood industry.
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There, I think there's been some reports that up to a third of seafood is actually illegal or unregulated or unreported.
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That's globally traded.
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So, they had additional key data elements
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that needed to be collected in order to ascertain that product is legitimate and is not fraudulent.
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And we're seeking ways to enable interoperability between information systems.
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So we used our methodology, which I'll describe a little bit later,
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to leverage global standards that I previously talked about in order to have a unified approach.
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And then finally, I'll kind of speak a little bit more directly to the regulatory side of traceability at the moment.
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We do know with the Smarter Era Food Safety
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that there's going to be a movement forward at the FDA for their approach to traceability.
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And writing to that, when FSMA was put into law,
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the first provision of Section 204 went to effect where FDA
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contracted with IFT to facilitate an investigation basically of what is the landscape of traceability in the United States?
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What steps does the FDA and the industry as a whole need to take in order to get from a one-up,
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one-down system to a more connected and hopefully end-to-end system?
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How do we conceptualize that in a technology-agnostic way?
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And is there a way for us to move the needle a little bit in solutions to traceability?
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So this was an extensive trace, somewhat similar to a traceback investigation,
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understanding what the product flow from the source to the retailer was,
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and understanding also the data collection needs and the information psychology realities.
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Through this we produce a report
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which is still being used heavily by a variety of stakeholders to move forward in building traceability systems.
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So finally I want to go into the technology and applications
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and traceability which really connects a lot of those key concepts
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that I was talking about earlier and the standardization efforts that I was talking about as well.
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again think about those fundamental categories of capture or identity capture
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and sharing your identification you're thinking about any kind of unique identifiers digital identifiers capturing
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that can also be capturing that identity through physical means
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or through digital means also capturing additional key data elements that should be collected and then sharing are the
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various data sharing protocols that exist this can be anything from advanced blockchain
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or cloud-based systems to you know you know even mailed
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or emailed records so just really the idea of sharing traceability information
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and then also the use which is kind of newer in this space
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but it's the reality is that as information collects or digital as data collection increases
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we're going to be able to translate that into information and to analytics to
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to better supply chains better efficiencies
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and also better be able to respond to food safety incidents
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so here's a little bit more information on identification
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and what we really mean by that generally
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and what you may be mostly familiar with our GS1 identifiers
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it's usually the G10 plus lot to get down to the granularity needed for a recall response.
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So GTINs are made up of a company prefix that a company purchases,
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and then they form a unique class of identification for that product with the GTIN-14.
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And then there's an associated lot, which is an internal identifier to put it with a batch lot production.
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That can actually be incorporated into what is called an LG 10 or G 10 plus lot, which can be put on a label such as a GS1-128.
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There are also non-GS1 ways of unique identification.
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We're running into this often in our traceability piloting activities and in our divisement of traceability system of traceability guidance,
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because the reality is that there's not a lot GS1 penetration upstream especially at the producer
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and even up to the primary producer level there can be
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a low amount of you know there may be internal identification
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but they may not be using they may not be using a GS1
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so where companies have made quite a bit of strides in
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doing end-to-end traceability such as a lot of blockchain companies other
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traceability companies they often will supply their own unique identifier
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and their own with basically their own company prefix to
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that particular supplier and then they use that internally but externally
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when you're wanting to if you wanted to have a unified way of identifying
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and ensuring that there's no collision between you know which basically means
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that people are sharing the same identifier you you IDs is also another way of doing
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that and then encoding that
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that identification should be on is generally done on optical through optical means namely barcodes again
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because of the amount of GS1 adoption and associated with that
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that means there's also a lot of readers a lot of automated ways of picking up that
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QR codes are also on the rise not as much especially in high throughput circumstances
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but QR codes can be generated
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and hold of more information than what a barcode can can hold
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and have a little bit more flexibility
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and are a little bit more durable there are also advances to using RFIDs
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which are radio frequency identifiers which have advantages in
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that you can read them at a distance you can also
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read multiple units at once you can basically you know pass you know pass product across an array
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and would automatically read it there's been some implementation challenges with
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the sorry my the light the automatic light my room just turned off anyway
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but but they are also there's being more adoption and that and then there's a couple of other experimental
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machine readable identification mechanisms that have not borne out yet
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but they're on the rise so data capture again
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so I was talking about earlier that there's associated KDE's that all need to also collect that information be and
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house it with and associate with that unique identification this is important to our efforts
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because these data need to be collected in a standardized
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and digitized way so that there can be interoperability between systems so
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if someone is a basic you know basic thinking around this
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is like how would you house you know temperature readings do how's it
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and you know generally at Celsius but you want to make sure
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that all supply chain partners are using Celsius you also would
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want to have a you know standardized the word I'm looking
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for have a standardized amount of digits to the specificity to the temperature things such as
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that so mostly like arriving at the unified syntax
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and semantics of the pieces of information and then having best collect best practices around that collection of information.
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So anything really can be considered in this segment, but mainly it's the capturing of the identity and then the associated KDE that needs to be collected.
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And then data sharing.
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And this is really important to business providers
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or solution providers and their corresponding food companies that they're working with for food safety regulators, it's important to kind of know these concepts,
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but it's not going to necessarily be part of your specific needs and traceback.
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But this is kind of where there's been a lot of excitement
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because there's classically been these ways of sharing business information especially along electronic data interchanges
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but you know with the enabling of the Internet's HTTP s API's are very popular
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and then blockchain also as a mechanism for sharing data
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across the fly chain nodes is also very popular and I won't go into that much detail with this.
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So this is just kind of a it's kind of a
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nifty graph it's I know it's a little bit cumbersome
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and a lot of words but what I really want to center this focus on is
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that standardization really especially in the food traceability space really centers on this this line of sharing
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and capturing really in the EPCIS capture interface that's really the
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EPCIS is just a file format for encoding logistics information
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and standardizing that approach for the use case of the industry is really important
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so that you can really use other standards
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and protocols you know at the data capture level
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and at the data sharing level to leverage and enable
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and then traceability and then finally I kind of talked about this in the introduction
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but there's you know the actual use of the traceability information how should it be housed
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and shared so that we can have these affected
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so we can actually use information for what we want it for
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so in food safety
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and trace back investigations you this may be the principal data
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use is going to be you know rapid query ability in the event
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that needs to be so for sustainability maybe being able to do audit checks
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or be able to perform a mass balance to ensure
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that there's the allocation
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that all of the weight of the product is accounted for throughout each supply chain network
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and also though once you have an you know information
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and aggregator along the supply chain no matter you know
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if you have more
419
and more information about further upstream of your supply chain you
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may also be able to make better decisions about your purchasing
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or how you do inventory or and also
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that can feed into your your food safety considerations as well
423
and then again there's the kind of this balance between accountability
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with business sensitivity we have seen a shift oh from businesses
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being extremely sensitive about what is shared to a little bit more of a nuanced approach to
426
that they realize that transparency in supply chains is going to rise just from happenstance
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and the advancing of technology and these advances in these standardization efforts etc
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but that does need to be balanced with the particular information
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that may be critical to what gives them a market advantage
430
um just a kind of a take-home point is
431
that you know we have found that standardization to data elements
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and IT architectures is critically important to enabling indent traceability
433
and enabling solutions to to arise
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so what we really see standardization as is kind of common rules the road where technology providers can come in
435
and use those common rules the road to really basically compete
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on user interfaces on their ability their you know data security
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you know all these kind of technical considerations rather than you
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know trying to garner market share in using their proprietary data format or their proprietary way of labeling or
439
or issuing identification the future technology may change may change the the realities of traceability
440
but at the moment this is the what we have seen
441
and it will be the reality for some time especially as producers become more
442
and more digitized but that's still um that's still on the on the right
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so I just kind of want to talk specifically about blockchain you guys may have heard about it
444
and I kind of wanted to spell kind of some myths
445
some of the mythology behind it um I want to kind of
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and I'm going to keep this pretty short um
447
but it has been kind of of tatted as this ultimate ledger
448
and data sharing arrangement where everybody has a decentralized copy of the ledger
449
that sensitive information can be cryptologically you know hidden
450
that there can be variable you know levels of access using smart contracts etc etc
451
because of the way of its architecture
452
it's um it's uh uses time stamping and encryption
453
and linked records to to ensure that there's this immutability um
454
and uh so because it has this kind of decentralized approach
455
and because it you know just is a very promising technology in general
456
and has certain attributes um
457
that has seen have been seen as a very attractive technology to be used in food traceability
458
I will preface this with the caveat being that blockchain is a technology that's born out of the financial technology space.
459
So it works very, very well in Bitcoin and Ethereum and trading digital assets.
460
When you're trading assets on a blockchain that only sit on the blockchain, it works very, very well and but when you are tying
461
that to a physical asset is still a lot of these problems that I was talking about earlier about standardization about
462
digitization about you know interoperability still still occur
463
and are still meaningful additionally you know with the technology still
464
in its infancy there are issues with latency you know a long period of time between posting a transaction
465
or posting a data upload and it actually being appended on the blockchain
466
because it has to be resolved among all the nodes.
467
Error correction can be a problem because it's immutable it's not really it's not something
468
that you can actually go in and delete or amend it.
469
You basically would have to and
470
then there's also level visibility at the moment a lot of blockchains are mostly set up for fairly radical transparency
471
and then you still also have some regulatory considerations such as GDPR
472
or our gas requirements are requiring the use of cryptocurrency to
473
upload something onto a public blockchain those are a little bit less relevant to us
474
because we're in the United States and we're not necessarily thinking about GDPR
475
and the gas requirements is a consideration for Southeast Asia but it's also as important to note that it's
476
some cryptocurrency is still being explored by various regulatory entities not just food safety
477
but and financial assets as well
478
so I kind of want to give you guys some food for thought on how to on what some tools
479
and techniques would be useful for you you know really centering on familiarizing yourself with data standards is really something
480
that could be really useful to you.
481
The global traceability standard for instance at GS1, but looking at also the produce traceability initiative
482
and their approach to standardizing case labeling
483
and also looking at the IFT FSMA report may also be very useful in and thinking about a system-wide approach to traceability.
484
And then also kind of investigating some of the digital aspects of it.
485
Really, I don't think these are necessarily skills that are required, but in the future,
486
having a little more digital slaviness is going to be going to be essential to being effective in traceback investigations,
487
being familiar with SQL queries,
488
being familiar with various file formats and how they're transmitted may be useful to you,
489
and also kind of understanding where the industry is and what their current, what their next steps are in designing traceability systems.
490
And I can share some of those some of those resources as well in a post-meeting email.
491
So with that, that's kind of a rapid look at traceability,
492
what we've seen in our effort as a convener of global industry players
493
and where that interplay is between what the industry needs are, what the regulatory needs are,
494
and what various interest groups such as sustainability NGOs or food safety advocates,
495
and converging those into having a unified standards process.
496
I think we have about 10 minutes available, and I will leave it to Randy to help us, lead us through the questions that have arisen.
497
Thank you.
498
I think we have a question here from James.
499
And the question is, what is the most critical component of traceability in produce safety?
500
So, what we've seen in the most critical component is really the identification
501
and the integration between that identification at the harvest level and at the commingling level. been there
502
because of the business realities at the harvest level it is not easy to implement a new process
503
or to implement a new labeling requirement that can uniquely identify products
504
and there's also challenges once it can get to the pack house where coming events may occur
505
so that's still really the biggest challenge
506
that we see is you know uptake of identification schemas
507
and in compliance to a standard so
508
that there can be better better trace back to the source I don't know Brian if you have any additional thoughts
509
no I think that's appropriate you know the the protus industry has been on quite a journey
510
and they've been learning a lot.
511
Thomas highlighted a couple areas that they continue to work through and try to drive industry level type of alignment.
512
One of the challenges in this space is getting to a common language
513
and a common set of tools that can be used by everyone in a pre-competitive type of environment.
514
Certainly the produce industry has been on that journey and continues to be on that journey.
515
I'd like to go ahead and thank Brian and Thomas for making the time to present today, and I'd like to thank everyone else for attending.
516
And that will conclude today's webinar on traceability.
517
Thank you, everyone, and have a great day.
518
Thank you.
519
Thank you.

이 레슨에서 배울 것

이 비디오는 식품 공급망 추적성에 대한 소개로, 전문가 간 대화를 통해 실제 업무에서 사용되는 영어 표현과 발음을 연습할 수 있습니다. 특히 업무 회의에서 자주 등장하는 소개, 주제 개요, 역할 설명 등의 구문을 익히고, 자연스러운 말하기 속도와 어조를 연습할 수 있어요. 영어 쉐도잉을 통해 듣고 바로 따라말하는 능력을 키우면, 실제 회의 상황에서도 자신감 있게 의사소통할 수 있을 거예요!

핵심 어휘 & 구문

  • Traceability: 추적성 (식품 공급망에서 제품의 이동 경로를 추적하는 능력)
  • Interoperability: 상호운용성 (서로 다른 시스템이 데이터를 공유하고 작동하는 능력)
  • End-to-end supply chain: 종단 간 공급망 (제품 생산부터 소비자에게 도달할 때까지의 전 과정)
  • Stakeholder groups: 이해관계자 그룹 (사업에 영향을 받거나 영향을 미치는 집단)
  • Traceback investigations: 역추적 조사 (문제가 발생한 제품의 원천을 찾는 조사)

연습 팁: 쉐도잉을 잘하는 방법

이 비디오는 전문가 간 대화로, 말하는 속도가 중간 정도이며 명확한 발음을 특징으로 해요. 영어 쉐도잉을 할 때는 다음과 같이 연습해 보세요. 먼저 비디오를 2-3초 뒤에 따라말하며, 발음과 강세, 어조를 정확히 모방해 보세요. 특히 "we're going to talk about", "I come to"와 같은 흔한 구문은 빠르게 연결되는 것을 주의하세요. shadowspeak 또는 shadowing site를 이용해 반복 연습하면, 발음 교정과 동시에 말하기 속도를 자연스럽게 따라갈 수 있습니다. 매일 10분씩 연습하면, 1주일 만에도 분명한 진전을 느낄 수 있을 거예요. 포기하지 마세요, 꾸준히 하면 실력이 늘어나요!

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.