Ryan: Welcome in. So close your eyes for a second. Well, unless you’re driving, obviously.
Emma: Yeah. Please keep your eyes on the road if you’re driving.
Ryan: Right. But if you can picture a massive manufacturing facility, specifically I want you to picture a bustling pet food production facility. And down in Abilene, Texas.
Emma: That would be Primal Pet Group.
Ryan: Exactly. Primal Pet Group. And at first glance, making pet food might seem, you know, pretty straightforward.
Emma: Mix some ingredients, put in a bag, ship it out.
Ryan: Right. You mix raw ingredients, you package it, you load it onto a freight truck. Done. But behind those factory doors, it is actually this staggeringly complex ballet.
Emma: Oh, totally. People really underestimate it.
Ryan: They do. We are talking about a relentless high speed choreography. Raw materials coming in, continuous batch production, and finished goods constantly moving across all these different stages. And it’s all governed by incredibly strict compliance standards.
Emma: Which is really the kicker, right? The compliance.
Ryan: Exactly. So today we are pulling from a stack of technical case studies, some internal operational notes and a really detailed interview with Deepak Agrawal to do a deep dive into Primal Pet Group’s digital supply chain transformation.
Emma: Yeah. We’re going to explore how they took what was essentially this chaotic, completely paper based manufacturing process and turned it into a sleek, automated powerhouse.
Ryan: And they use Microsoft Dynamics 365 for that.
Emma: Right, Microsoft Dynamics 365. Plus a highly specialized suite of applications from an independent software vendor called insightworks.
Ryan: So whether you are managing an operational transition right now, or maybe you’re studying systems engineering or honestly, if you are just insanely curious about the hidden mechanics of how the stuff we buy actually makes it to our doorsteps efficiently, this deep dive is for you.
Emma: Because this case study is an absolute masterclass in eliminating friction. It’s really about conquering information overload in these intense manufacturing environments.
Ryan: Environments that basically have zero margin for error.
Emma: Right. I mean, in modern food manufacturing, the data footprint of a product is just as critical as its physical footprint. If you lose control of the data telemetry moving through your facility, you completely
Ryan: lose control of the factory floor.
Emma: Exactly. You’re flying blind.
Ryan: Okay, let’s unpack this. Because before we can really appreciate the shiny high tech digital ecosystem they built, we have to travel back to the before times.
Emma: The dark ages.
Ryan: The dark ages. We had to understand the sheer logistical headache of what Primal Pet Group was actually dealing with on a daily basis. They were stuck in what I like to call Paper based purgatory.
Emma: That is a perfect name for it. Because the core problem at Primal Pet Group was their total reliance on manual batch tracking and, you know, paper based
Ryan: reporting, which just sounds exhausting.
Emma: It is. In any kind of consumable manufacturing, including pet food, traceability is not some operational luxury. It is a strict non negotiable regulatory necessity.
Ryan: Right. You can’t just guess what went into the dog’s food.
Emma: No. You need perfectly clear, instantaneous visibility into exactly what was picked for every single production order. You need to isolate ingredients by type to prevent cross contamination.
Ryan: Oh, sure.
Emma: And you have to track the exact opposite origins, expiration dates and lot numbers of those ingredients as they move through every single routing stage on the floor.
Ryan: Because if there is an issue with a supplier’s raw ingredient, say like a specific delivery of protein, you can’t just assume which batches of finished pet food it went into.
Emma: Right. A recall situation.
Ryan: Exactly. You need to know the blast radius of that ingredient with absolute certainty. Tracking all of that with a pen and a clipboard reminds me of trying to bake a really complex recipe in a commercial kitchen.
Emma: Oh, that’s a good analogy.
Ryan: Like imagine you are baking a thousand tiered cakes, but you are legally required to track the exact farm origin of every single grain of flour and every single egg. Yes, every egg. With a pen, a clipboard and physical routing slips. While expediters are just yelling new orders at you across the room. The cognitive load on the worker is totally unsustainable.
Emma: What’s fascinating here is how that commercial kitchen analogy perfectly highlights one of their most specific, painful logistical hurdles.
Ryan: Which was what?
Emma: The leftover ingredients, or what we call in the industry, returning raw materials to inventory.
Ryan: Oh, because you don’t use everything you pull out of the warehouse.
Emma: Exactly. When a production run of pet food is finished, you rarely consume 100% of the raw materials you pulled from the staging area. You have these partial pallets of leftover ingredients.
Ryan: Okay, so what do they do with them in the paper based days?
Emma: Well, employees had to physically figure out how to accurately weigh those leftover materials. And they were often dealing with variable catch weights. Then they had to write down those new weights on a piece of paper, manually create labels for them, and then physically move them back to storage.
Ryan: And then what? Just leave a note?
Emma: Basically, they had to write down the new bin location on a routing slip so the ERP system could be manually updated later by a data entry clerk in an office.
Ryan: Wow. The margin for human error there is terrifying.
Emma: It’s massive.
Ryan: You are relying on a tired floor worker accurately reading a scale, writing it down legibly, not transposing any numbers, which
Emma: happens all the time.
Ryan: Right. And then a clerk in an office has to accurately read that handwriting and key it into a database without making a single typo.
Emma: What’s really fascinating here is the mathematical reality of compounding errors in that kind of environment.
Ryan: How so?
Emma: Let’s look at the actual mechanics of a transposition error. Say a worker writes down 45 pounds instead of 54 pounds for a return to lot of ingredients.
Ryan: Easy mistake to make.
Emma: Very easy. The next shift comes looking for £54. They can’t find it, so they assume it’s missing, and they adjust the inventory down.
Ryan: Oh, no.
Emma: Right. Then the Material requirements planning system, the mrp, sees a shortage and automatically triggers a rush reorder from a supplier.
Ryan: Even though they already have the ingredients.
Emma: Exactly. And a week later, someone finds the original 45 pounds sitting in the wrong aisle and adds it back to the system.
Ryan: So now your system thinks you have double the inventory.
Emma: Basically. Suddenly, your digital ledger says you have 99 pounds, but physical reality says you have 45. You now have this phantom inventory spiral.
Ryan: A phantom inventory spiral? That sounds like an absolute nightmare for an ops manager.
Emma: It is a pound off here, a mislabeled pallet there, and within a month, your digital system is completely divorced from physical reality. Your procurement team is rushing to buy ingredients you already have, while production lines
Ryan: are completely halted because you are missing ingredients. The system swears are sitting in aisle four.
Emma: Precisely.
Ryan: Okay, so when your paper system is actively destroying your inventory accuracy like that, you have no choice but to go digital. You have to replace the paper with pixels.
Emma: You really do.
Ryan: But replacing a physical workflow, especially one involving heavy pallets, raw organic materials, and wet factory floors, that requires highly specific digital tools. You can’t just hand a forklift driver an iPad and wish them luck.
Emma: No, an iPad would not survive an hour. They had to bring in an entirely new digital ecosystem. The foundation, the central nervous system, was Microsoft Dynamics 365 Business Central Cloud. But an ERP needs hands and eyes on the factory floor to collect the data in real time.
Ryan: And that is where they brought in InsightWorks.
Emma: Exactly. InsightWorks engineers add ons specifically for manufacturing and distribution environments.
Ryan: So they deployed a few specific modules. The first was called warehouse insight. And this is what transitioned the floor team to ruggedized handheld scanners.
Emma: Right. Effectively eliminating the routing slips and paper clipboards completely.
Ryan: They used these scanners for picking the raw materials, reporting what was actually consumed in the batch in real time and securely moving those tricky leftover quantities we just talked about.
Emma: They also deployed advanced inventory count.
Ryan: Which does what exactly?
Emma: It gave the inventory control staff the ability to execute accurate rolling bin counts and lot reconciliation directly on the floor.
Ryan: Okay, that makes sense. And then there’s this third module, license plating.
Emma: Ah, license plating is arguably the most crucial piece of architecture in this entire deployment.
Ryan: They use this to generate pallet and batch labels that structurally tie the production orders, the ingredients, the lots, and the picked quantities all together. Right?
Emma: Yes. All bundled into one.
Ryan: Okay, let me push back on this cloud deployment for a second, because if you are an ops manager listening to this, warning bells should be going off.
Emma: I can hear them ringing from here.
Ryan: Right? In a commercial food manufacturing facility, you have dead zones, you have thick concrete walls, giant metal mixing vats, and massive amounts of RF interference.
Emma: Aw, it’s an IT nightmare to get good signal in those places.
Ryan: Exactly. So if you put your entire operational brain in the cloud, and you require workers to use three different scanner apps simultaneously, what happens when the WI fi drops while a worker is scanning a license plate?
Emma: That’s the big question.
Ryan: Doesn’t the whole production line just lock up? You are asking workers who are used to analog clipboards to suddenly troubleshoot latency issues while operating heavy machinery.
Emma: This raises a really important point, and it is the exact reason why so many digital transformations fail. If these were fragile web based apps constantly pinging a server to function, you would absolutely have total operational paralysis.
Ryan: The second a forklift drove behind a steel vat, everything would freeze.
Emma: Exactly. But they aren’t disconnected. They are a deeply integrated ecosystem utilizing asynchronous data syncing.
Ryan: Asynchronous data syncing. Okay, so what does that mean for the worker on the floor?
Emma: It means the handheld scanners cache the operational state locally. If a worker drops connection, they can continue scanning, picking, and moving. Yeah, the second the device catches a signal again, it handshakes with the business central and updates the central database in milliseconds.
Ryan: So the worker never even notices the drop?
Emma: Nope. And that concept you just brought up, license plating. That is the perfect example of how this technology actually eliminates cognitive load rather than adding to it.
Ryan: Walk me through the actual systems engineering of license plating in a warehouse context. How does it actually work?
Emma: So license plating in modern warehouse technology is essentially data virtualization. In a legacy system, a worker interacting with a pallet of mixed goods has to parse a dozen distinct data fields.
Ryan: Right? They have to read the labels.
Emma: Yeah. They have to scan a barcode for the item number, manually key in the lot number, type in the tare weight, verify the expiration date, and then scan a destination bin location.
Ryan: Which is incredibly tedious and leaves so much room for typos.
Emma: Exactly. License plating assigns a single serialized barcode to that physical pallet. It acts as a master record.
Ryan: Okay.
Emma: Scanning that one barcode triggers an API call that instantly queries the relational database in Dynamics 365 and pulls all of those fields simultaneously.
Ryan: Wait, so it’s just one scan?
Emma: Just one scan. The system already knows the lot, the weight, the origin and the routing destination because all of that data is bound to that serialized plate in the database.
Ryan: So the worker doesn’t have to parse anything?
Emma: Not at all. They point, they scan one time and they move the palette. The systemic complexity is handled entirely invisibly by the database architecture.
Ryan: You are basically hiding a massive database query behind a single beep of a scanner.
Emma: Exactly.
Ryan: The worker just does their job and the data telemetry handles itself. Okay, so Primal Pet Group gets the warehouse in order. They’ve got the scanner’s offline, syncing the license plates, virtualizing the data, the cloud brain tracking it all.
Emma: It finally had a solid foundation.
Ryan: But just as they were getting their house in order, they introduced a massive new variable to the operational physics of the building. In early 2025, they launched direct consumer E Commerce fulfillment.
Emma: Which is a completely different logistical universe.
Ryan: It’s a massive shock to the system. It is one thing to ship a massive shrink wrapped pallet of dog food to a B2B retail distributor.
Emma: Right. You load it on an LTL freight truck, wave goodbye and you’re done.
Ryan: Yeah, but it is a completely different operational reality to pick, pack and ship a single bag of kibble directly to a customer’s front porch. The physics completely change.
Emma: You shift from low volume high line count orders to incredibly high volume low line count orders.
Ryan: Exactly. You have to completely minimize manual touch points. You need instant visibility into your inventory allocation so you don’t sell something on your website that you don’t physically have in the warehouse.
Emma: That’s the worst case scenario in E Commerce.
Ryan: It is. And you have to integrate with parcel free providers through APIs. And you need discrete pick pack and ship workflows.
Emma: And this is where the pristine data foundation they built with those warehouse scanners became absolutely mandatory.
Ryan: They couldn’t have done it without them.
Emma: No way to handle this E Commerce pivot. They deployed two additional modules into their Microsoft Dynamics environment. The order Fulfillment Worksheet and Dynamics Ship.
Ryan: Here’s where it gets really interesting to me. The order fulfillment worksheet acts like a hyper intelligent air traffic controller for the warehouse.
Emma: That’s a great way to put it.
Ryan: Imagine you have hundreds of customer orders dropping into the system every hour. In a legacy setup, a human planner would have to look at the incoming order queue, cross reference it with the warehouse inventory shelves, and manually allocate inventory to decide if they even had enough to release the order to the floor. The order fulfillment worksheet does this programmatically.
Emma: Right. It looks at the incoming E Commerce orders, pings the real time inventory levels generated by those handheld scanners, and instantly grounds the orders with shortages.
Ryan: It just parks them.
Emma: Exactly. Then it soft allocates the inventory for the orders that are ready. And with a single click, the planning team can release only the fully shippable orders to the warehouse pickers.
Ryan: If we connect this to the bigger picture, E Commerce profitability is entirely dictated by velocity and the complete removal of manual decision making.
Emma: Oh, 100%. If a human being has to stop and manually verify if an order can be shipped, you have already bled your margin.
Ryan: You’re losing money on that order.
Emma: Basically, yeah. The order fulfillment worksheet automates that triage. And once that order is physically picked and packed, the shipping station uses the Dynamic Ship module.
Ryan: And what does Dynamic Ship do?
Emma: It makes split second API calls to various shipping carriers to automatically perform rate shopping based on the parcel’s dimensions and weight.
Ryan: So it finds the cheapest or fastest option.
Emma: Right. It selects the optimal carrier and prints the shipping label directly from within the business central interface.
Ryan: There’s no switching screens. You aren’t alt tabbing to a FedEx portal, typing in an address and hoping you don’t make a mistake. The data just flows natively.
Emma: The native flow is vital. But here is the critical systems engineering insight.
Ryan: Let’s hear it.
Emma: Tools like Dynamic Ship and automated Rate Shopping are completely useless if you don’t have the foundation of accurate data we discussed in the first phase because the
Ryan: system is blind otherwise.
Emma: Exactly. You cannot accurately rate, shop or allocate inventory that you don’t actually possess. If your base warehouse data is corrupted by compounding paper errors, your E Commerce platform will aggressively make promises to customers that your supply chain cannot fit physically keep.
Ryan: It’s just a house of cards. At that point.
Emma: It is the entire seamless E commerce experience. You know, the quick shipping, the accurate stock levels on the website. It is entirely mathematically dependent on that floor worker accurately scanning the license plate Of a leftover ingredients.
Ryan: The choreography is completely interconnected. The ballet is all one piece.
Emma: Every step matters.
Ryan: So we understand the initial problem, right? The compounding errors of paper based tracking. We understand the solution. The digital ecosystem with asynchronous scanners, data virtualization and automated order triage.
Emma: Yep.
Ryan: The final piece of the puzzle is the execution. How do you actually pull off an IT overhaul of this magnitude without shutting down your entire production line?
Emma: It’s the million dollar question.
Ryan: Because if you’ve been in this industry long enough, you’ve seen companies spend two years trying to implement a simple ERP upgrade or let alone a factory wide warehouse management system. But Primal Pet Group executed this rollout in roughly three months.
Emma: Three months for a digital supply chain transformation that touches the physical factory floor is blistering speed. I mean, it is genuinely rare in enterprise IT implementations.
Ryan: So what does this all mean for other businesses? How do they manage to deploy a cloud erp, handheld scanners, license plating and an automated shipping suite in just 90 days?
Emma: The secret to their velocity wasn’t just the software itself. It was their strict discipline regarding implementation methodology. Okay, first, it was a largely self managed deployment. Their internal team already had some familiarity with the architecture of InsightWorks applications from previous projects, which definitely mitigated the learning curve.
Ryan: Sure, they weren’t starting from scratch, right?
Emma: But more importantly, they treated the applications as strictly plug and play.
Ryan: Meaning they didn’t try to heavily customize the source code to match their old broken physical workflows.
Emma: That is the exact trap where most enterprise implementations go to die.
Ryan: Oh, I’ve seen it. Companies spend millions of dollars and years of development time customizing new software to perfectly mimic their old operational inefficiencies.
Emma: It’s wild. But Primal Pet Group refused to do that. They relied on insightworks for only a handful of minor, absolutely necessary workflow adjustments.
Ryan: So what did they spend those three months doing then?
Emma: Instead of getting bogged down in endless software configuration and featuregreep, they dedicated the vast majority of those three months to process design and rigorous scenario testing.
Ryan: They practiced the ballet. They ran user acceptance testing right on the floor.
Emma: Yes, they ruthlessly tested the out of the box software against real world edge cases. What happens when a label printer jams midway through a run? What happens when a pallet is dropped and needs to be written off?
Ryan: They figured out the physical reality of the software.
Emma: They validated every physical workflow before opening nights, and they executed the launch in strict phases.
Ryan: Which phases went first?
Emma: They rolled out the core warehouse data collection apps first. So Warehouse insight, license plating and advanced inventory count. They ensured that the base data telemetry
Ryan: was rock solid before complicating it further.
Emma: Exactly. Only after that foundation was proven in production did they extend the system to the e commerce tools like Dynamic Ship and the order fulfillment worksheet.
Ryan: And the operational results are undeniable. They achieved vastly improved picking consistency. They reached totally paperless consumption reporting on the manufacturing floor, which is a huge win. Massive. They instituted immediate serialized labeling of finished goods, meaning full regulatory traceability was structurally locked in the very second a product was palletized.
Emma: No more guessing where the protein came from.
Ryan: Right. Those dreaded compounding inventory adjustments, you know, the phantom inventory spirals. They started trending aggressively downward and their bin accuracy improves steadily across the board.
Emma: It represents a complete operational paradigm shift for the people actually doing the work.
Ryan: There is a great quote from Deepak Agrawal from Primal Pet Group that summarized the victory incredibly well. He noted, using handheld scanners with license plating and warehouse Insight gave us real time visibility into production and inventory movements that we simply did not have before. The workflows reduced manual effort and helped improve our overall inventory accuracy.
Emma: Real time visibility without added manual effort. That’s the dream.
Ryan: It really is. So to step back and look at the entirety of the journey we’ve mapped out today. Primal Pet Group took a tangled paper based tracking nightmare where human error wasn’t a bug, but basically a feature of the process.
Emma: Yeah. And expectations.
Ryan: They introduced highly targeted asynchronous digital tools to completely virtualize their data collection. They used that pristine telemetry to successfully layer on a highly demanding high velocity and E commerce fulfillment system.
Emma: All in 90 days.
Ryan: Exactly.
Emma: Yeah.
Ryan: And they executed the entire pivot without breaking the company utilizing a highly disciplined, testing focused 90 day sprint. It is just a phenomenal blueprint.
Emma: It is a blueprint that leaves us with a rather profound question to consider. Really?
Ryan: I’m listening.
Emma: If a mid sized pet food manufacturer in Abilene, Texas can achieve this level of granular real time systems architecture, knowing
Ryan: the exact origin and lot number.
Emma: Right. Knowing the location of every raw material down to the ounce and tracking it seamlessly through a complex physical ballet of production right to a customer’s front door via an automated API, what is the excuse for the countless other modern industries that still rely on guesswork, siloed legacy databases and paper routing slips to manage their most critical assets?
Ryan: Wow. That’s a fair point.
Emma: If we can engineer this level of frictionless traceability for pet food, why are we accepting anything less? In aerospace manufacturing or pharmaceuticals or our critical infrastructure.
Ryan: The technology stack is clearly available right now. The only thing missing in those other sectors is the operational willingness to completely rethink the choreography.
Emma: You have to be willing to change
Ryan: the dance you do. Well, thank you so much for joining us on this custom deep dive today. We hope you found some concrete systems engineering insights to take back to your own projects. Whether you’re scaling a warehouse or just trying to understand the complex logistics of the modern world, keep questioning the process, keep looking for those better systems and we will catch you on the next one.
