Your production data exists. It's just scattered across paper logs, spreadsheets, and WhatsApp threads.
When FDA asks for traceability records within 24 hours, how long does it actually take you to reconstruct a batch?
You know this process by heart
Avocados arrive. They get inspected, matured at controlled temperatures, checked daily for dry mass. Washed. Sliced—and now the 12-hour clock starts. Scooped by hand, rejections sent back. Mixed. Ingredients added. Vacuum sealed. Through the HPP machine. Flash frozen. Into storage.
Fourteen steps. Dozens of measurements. Temperatures, times, percentages, lot numbers.
And then someone updates SAP with the final inventory count.
Everything between receiving and that SAP entry? It lives on paper logs. In Excel files. In binders that get filed and rarely opened again. In WhatsApp messages asking "did you check the dry mass on lot 4?"
You have documentation. What you don't have is a system that knows who should capture what data, when, and what happens if they don't.
Small gaps compound fast
The 12-hour limit after slicing exists for a reason. Once an avocado is cut, microbial growth accelerates. Miss the window, and you're either discarding a batch or—worse—sending compromised product to customers.
But a spreadsheet doesn't know when the clock started. It doesn't alert anyone when hour 10 arrives. It just holds whatever gets typed into it, whenever someone gets around to typing it.
The daily dry mass checks during maturation? They're supposed to happen. Usually they do. But when someone forgets—or checks but forgets to log—the data gets backfilled later. Same handwriting. Same pen. Entered in a batch at the end of the shift.
Auditors know what backfilled records look like. More importantly: backfilled data isn't real data. It's a story told after the fact. And when that story is wrong, the consequences flow downstream.
One batch, not documented correctly. Sent to customers. Claims. People getting sick. A customer relationship that took years to build, damaged in days.
This isn't a failure of your team. Your team is trying to execute with tools that weren't built for how production actually works.
Your ERP tracks goods. It doesn't track how goods get made.
SAP knows that 500 cases of guacamole entered inventory on Tuesday. It doesn't know that the avocados came from three different suppliers with different rejection rates. It doesn't know that lot 7 sat at the scooping station for 11 hours and 45 minutes before moving to mixing. It doesn't know that the HPP machine ran at 580 MPa instead of the specified 600 MPa because someone adjusted a setting.
ERP systems were designed for financial flows and inventory movements—not for orchestrating the people and steps that make production happen.
So your team fills the gap with what they have: paper forms, Excel spreadsheets, WhatsApp groups, email threads. Each tool does one thing. None of them know how the pieces connect.
The result is tribal knowledge. How things actually get done lives in people's heads, not in your systems. When a key person takes a vacation—or leaves—part of your operation goes dark.
And when something goes wrong, the investigation becomes an archaeology project. Digging through binders. Searching chat histories. Trying to reconstruct what happened, when, and who was responsible.
This isn't a people problem. It's a structural problem.
What if production data captured itself—where the work happens, when it happens?
When avocados arrive, the receiving team logs the supplier and lot in one place. When those avocados move to maturation, the system knows. When QA needs to check dry mass, they get notified—not because someone remembered to send a message, but because the process requires it.
When the avocados are sliced, the 12-hour clock starts automatically. At hour 10, the mixing team sees that time is running. No one needs to chase. No one needs to remember.
At the scooping station, rejection percentages are captured in real time. You can see that Supplier A's avocados had 40% rejection while Supplier B had 8%—not in a report three weeks later, but today, while it still matters for tomorrow's orders.
Every HPP cycle logs its pressure and duration. Every flash-freeze records its temperature. Every step links to the lot it came from and the lot it becomes.
When the product is ready, the inventory update flows to SAP automatically—because all the upstream data already exists.
And when a customer calls with a claim, or an auditor asks for traceability records, or FDA requests documentation within 24 hours—you don't reconstruct. You retrieve.
This is what orchestrated operations look like
Palo Blanco, a food producer in Guatemala, used Navgar to transform how they handle customer claims. The results after one year:
59% reduction in total claims payouts 70% fewer total claims 10x faster execution 73% of claims closed on time with no payout
The difference wasn't better people or more training. It was giving their existing team a system that orchestrates who does what, when—with every conversation, decision, and data point captured where it happens.
Claims are downstream symptoms. Production documentation is upstream prevention.
FSMA 204 is here.
The FDA Food Traceability Rule requires manufacturers to maintain Key Data Elements for Critical Tracking Events—and provide them within 24 hours of a request. Fresh avocados and processed avocado products like guacamole are on the Food Traceability List.
If your traceability documentation lives in paper binders and disconnected spreadsheets, how confident are you in a 24-hour response?
Pick one process. Let's make it work by default.
You don't need to transform your entire operation at once. Start with one place where the pain is sharpest:
— Receiving and supplier quality tracking — Maturation monitoring and dry mass checks — The slicing-to-HPP time window — Customer claims and investigation workflows
We'll map your current process, configure Navgar to match how your team actually works, and show you results within 30 days.
No consultants. No six-month implementation. Your IT team can handle it.