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Home » IoT's Impact: What the Tech Promises in Logistics, Food, Pharma and Warehousing
Q&A

IoT's Impact: What the Tech Promises in Logistics, Food, Pharma and Warehousing

October 22, 2018
SupplyChainBrain

The internet of things is revolutionizing supply chains, but the value of some actions that connected devices can take may be questionable. 

For instance, knowing that the rubber is getting thin on long-haul truck tires is important; a tennis shoe that reports a worn spot in the sole, maybe not so much. The following are excerpts from conversations between SupplyChainBrain editors and industry experts about what IoT is accomplishing today in some vitally important verticals — and what the technology promises in the near future.

Pete Gilstrap, president, ASC Software: Based on years of experience and what we — as consumers — consume every single day, which is food and pharmaceutical goods, we want to make sure all the stuff we consume is good. How do we make sure of that? In the supply chain, from farm to fork, we have to make sure that the food is tracked well, that there's nothing wrong with it, that it goes through the cold chain properly, that it goes through quality control checks properly. 

And the same thing for pharmaceuticals. We want to make sure that the pharma-grade product that's given to patients in the hospital — for example, bags of saline solution, which have narcotics in them — we want to make sure that they have the correct percentage of narcotic, that it all went though quality checks, that all of the pharmacists have signed off on it, and that you're getting exactly and precisely what the doctor ordered. 

SCB: So how do you do that? Where's the assurance that all those I's have been dotted and T's crossed? 

Gilstrap: In the supply chain, primarily we have to make sure from start to finish there's complete traceability of the complete DNA of every component inside those products we consume.

Food and pharma are different from tracking automotive parts. If you have a problem there, you just replace it, but if it's consumable, for example, in pharma, you can't just immediately replace it if it's already been consumed. Therefore, it's important to make sure that the system of record actually provides the correct information upfront in proactive mode. And in case of a problem, it has to be able to respond in a reactive mode. 

SCB: We have track-and-trace tools and solutions. Are they not sufficient for the job?

Gilstrap: Yes, we have current standards, current consumer protection laws on food and pharmaceutical, but I see more of the action items occurring in the field, not necessarily in the lab. Over the past 20-odd years, we've seen desktop products [for traceability] but what if you're out in the field? What if you're a manager and need to be walking around your warehouse, do you have the right tools to ensure that you can effectively do a quality check on the spot, or do a cycle count on the spot of a contaminated product? Or if there's a reason for a recall while you're in that particular warehouse? 

So I see the future of being able to be anywhere on the planet, even with simple cell phone connection, being able to process a transaction. 

SCB: So how do we get to this future where one is on top of every development?

Gilstrap: The most important technology I see right now is IoT. What that basically means for the food and pharma industries is that they have information at their fingertips in real time. For example, in the food industry, you may have temperature-sensitive products. To get a product like that validated and tested, you have to have a device that is mobile with a worker. You need that to make sure that a cold-chain item is processed properly in real time and while in motion, not sitting idle. That's key: it has to be done in motion. And the same for pharmaceuticals. You need to have wearable technology. You need to be able to have devices that attach to machines, that are testing temperature or testing speed or testing various other things that manufacturers have to know instantaneously to be able to feed that information into the rest of the data that goes along with traceability.

SCB: The case for total connectivity is compelling, but what about the cost? Prohibitive or is this capability becoming affordable?

Paul Baboian, RFID enterprise solutions manager, Barcoding Inc.: I would say the overall the total cost of ownership of IoT and [associated] technologies has gone down tremendously. The cost of sensors now, is less than $20 apiece. They can be connected through gateways that offer more interoperability. There are many more vendors that make all of this possible. Now, with the innovation among cloud computing, blockchain and interoperability between sensors — all of that is a big difference maker for IoT and big data analytics. 

SCB: Let's talk about specific instances of applicability.

Baboian: In terms of the cold chain, we've seen two primary use cases. One is being able to verify the integrity of your product as it moves throughout the cold chain and, second, through third-party logistics providers. Now there is location tracking through multiple technologies — RFID, GPS — tracking temperatures en route and being able to leverage that data all the way from the growers through third-party logistics providers to the store and inevitably through to the consumers as well. So, track and trace is really important to the validity of temperature and other environmental conditions.

SCB: IoT's role in that?

Baboian: IoT is all about enhanced visibility. Besides leveraging traditional sensors, being able to leverage sensors at the end customer site, whether that's a factory or another type of end customer site — if we can leverage load cells, for example, and we know when bins are depleted, or if we can leverage an electronic transaction as it moves through our RFID technology and then replenish through those intermediary sites, we can gain value. 

So, literally, from producer to third-party logistics warehousing to the factory, we can basically pull upstream, we can gain those electronic pulls upstream and certainly monitor accurately and more timely knowing when inventory transactions take place. We can gain more inventory turns, and the total cost of ownership becomes less.

SCB: So how do we leverage these new signals to drive more efficiency in the supply chain? 

Fred Baumann, vice president of global industries and solutions, JDA: It's really being driven by three things, the first being physical assets that now have embedded technology in them. We're talking everything from a refrigerator to a sneaker; these things have chips in them. We're talking about 20 billion connected devices by 2020. 

Second, you've got Big Data generating enormous amounts of information. And the third thing driving the digitization trend is software and systems becoming more intelligent. It's what I call the self-learning element of the supply chain. 

SCB: Well, let's drill down on digitization and self-learning supply chains.

Baumann: We see four key stages of maturity in this whole supply chain digitization journey. The biggest focus right now is in end-to-end visibility. So I've got all these sensors that are on containers or on trucks, supplementing other types of data. This is Big Data we're talking about. People just starting out of the gate want an end-to-end view, not only within their enterprise but with upstream suppliers and with the downstream customer. So the first phase of maturity is visibility. 

The next area is what we call the predictive element. So I have visibility, but how do I leverage this framework to have predictability in my supply chain? Algorithms may say there is a weather pattern that will cause my ship to be late, perhaps by three or four days. Or I have port or traffic congestion. So, now we have signals that are digitally connected to the cloud and other elements that can give us a predictive point of view on what things may go wrong. 

The next maturity level is the prescriptive side, which basically takes the predictive elements and says, now with this insight, this weather or traffic insight, what's the predictive time frame that's going to impact my supply chain? Moving to a prescriptive view means knowing that it's going to happen, so you need to have a solution tell what you should do to mitigate that risk.

And then the last element is really around self-learning. That means enabling the software systems to become somewhat autonomous, having less human touch on the parameters. So, within certain guardrails, the solution is allowed to execute on the predicted elements, to expedite where necessary, to move inventory to the right place, all without human touch.

SCB: Does that mean we're going to throw away some of the core elements that supply chain professionals have been around and are used to?

Baumann: We still have to move molecules at the end of the day from point A to point B. So we don't want to do away with demand planning or supply planning or supply chain execution within the DCs and transportation. What we are going to do is enhance all of that with new data, so that we have a view to sense demand much further out than ever before. We used to have to wait on a POS signal, but now we can get social media insight, we can get product-likes insight, so from a frontier perspective, we will be more effective and agile than planning and execution processes were ever before.

SCB: Your view is that IoT is revolutionizing the warehouse. Walk us through that as you see it.

Kevin Reader, director of business development and marketing, Knapp: IoT is very important. When we think of today's technology — a WCS, for example — that's feeding much of the information up to a warehouse management system while a control tower takes feeds from it as well, including feeds from other devices like a palletizer or a conveyor system or from motors.

SCB: Elaborate on motors being a link in IoT connectivity.

Reader: A motor might transmit information about vibration or heat, for example. It could indicate it needs potential maintenance services, and that's important because that would be predictive maintenance as opposed to breakdown maintenance, which is much more costly and can severely impact service levels.

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Logistics Transportation & Distribution Data Management (Big Data/IoT/Blockchain) Supply Chain Visibility Technology Global Supply Chain Management Quality & Metrics Supply Chain Security & Risk Mgmt All Warehouse Services Order Fulfillment Food & Beverage Pharmaceutical/Biotech
KEYWORDS All Warehouse Services Big Data/IOT Food and Beverage Global Supply Chain Management Logistics order fulfillment Pharmaceutical/Biotech Quality & Metrics RFID & Barcode SC Security & Risk Mgmt Supply Chain Analysis & Consulting Supply Chain Visibility Technology Transportation & Distribution
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