From Excel Chaos to EPR Clarity: Lessons from Amazon Devices at Spec Summit 2026

Picture this: It’s 4 o’clock on a Friday. You’re staring at a spreadsheet — thousands of rows, color-coded columns, macros that may or may not work — and you’re responsible for every single gram of packaging data for products that ship worldwide to millions of customers. Get it wrong, and your company faces massive fines. Sound familiar?

That’s exactly where Joe Hunter, Sr. Sustainable Packaging Engineer at Amazon Devices, found himself not long ago. At Spec Summit 2026, Joe joined me for a fireside chat to share how the Amazon Devices team — responsible for Echo speakers, Kindles, Fire TV, Ring devices, and more — made the leap from spreadsheet chaos to scalable, EPR-ready data management using Specright.

What followed was one of the most candid, practical conversations of the event. Here’s what we covered.

The Breaking Point: When Excel Stops Working

Joe didn’t sugarcoat it. “I was Team G Drive,” he told the audience with a laugh. Like so many packaging professionals, the Amazon Devices team had been managing supplier data in Excel files stored on shared drives. It worked — until it didn’t.

The shift came when Extended Producer Responsibility (EPR) regulations entered the picture. Suddenly, those spec sheets that existed primarily as reference documents needed to become the foundation for regulatory reporting. Joe was sending spreadsheets to suppliers globally, getting files back corrupted, running macros, trying to aggregate data for reports — and hitting walls at every turn.

“It became very clear that this was not going to work going forward,” Joe said. “And I know this is probably surprising hearing this within Amazon, but that’s the reality.”

The wave of EPR regulations didn’t just reveal a data problem — it made it impossible to ignore. Amazon Devices needed a system that was flexible enough to adapt to new reporting requirements within weeks, not months.

The Decision to Act — and Act Fast

One of the standout themes of the session was Joe’s bias toward action over analysis paralysis. After about six to eight months of recognizing the problem, the team made the call: they needed a purpose-built Specification Data Management (SDM) platform.

“I wanted to at least put some good thought into where this data is going to be used and how to architect it,” Joe said. “But that’s a slippery slope. You can get into trying to perfect something. Progress over perfection — that could be a dangerous trap.”

That philosophy — progress over perfection — became a throughline for the entire conversation, and for good reason. With EPR deadlines looming and regulations evolving faster than ever, waiting for the perfect system means falling further behind.

Owning the System: The Accidental Admin

Due to shifting team dynamics, Joe stepped into the role of “Specright Admin” — despite having never written a SQL query in his life.

“I’m not an IT person, but I play one in real life,” he joked. What followed was a steep, self-directed learning curve: leveraging AI tools to write SQL queries, preparing user scripts from scratch, building validation rules with the support of the Specright team.

“I honestly would’ve needed a dedicated business intelligence expert or data scientist to do a lot of this stuff,” Joe reflected. “But I’m actually glad it happened — I understand our system in a way I wouldn’t otherwise.”

The lesson here for other teams: owning your system deeply pays dividends. When you understand the architecture, the validation logic, and the data flows, you can iterate faster and respond to new requirements with confidence.

The Supplier Portal: The Biggest Win

If there was one moment in the session where Joe’s enthusiasm was undeniable, it was when he talked about launching the Specright Supplier Portal.

“This was by far the biggest win of this whole thing — for sure,” he said.

Previously, the process was manual and painful: send spreadsheets to suppliers, chase responses, receive inconsistent data, and try to aggregate it. The suppliers — most of whom don’t speak English as a first language — were navigating complex, unstructured Excel files.

Once the portal launched, the team got a flood of data back quickly. But Joe noticed patterns of error: suppliers skipping fields, entering values that didn’t make sense (like indicating a corrugated shipping box had zero recycled content). Working with Specright’s team, they built approximately seven to eight core validation rules — binary logic that either blocked submission or required acknowledgment before proceeding.

The result? An 80% improvement in first-pass approval rates. Simple mistakes that were happening constantly were eliminated nearly overnight.

“We still are evolving it,” Joe noted, “but we’ve made a lot of progress.”

Data at Your Fingertips: From Collection to Reporting

Collecting clean data is only half the battle. The other half is making it useful for reporting — to regulators, to sustainability teams, to retailers, and internally.

Amazon Devices built a reporting workflow using Specright as the data backbone, integrating it with their internal Quick Suite dashboarding tool. By linking Specright data to sales data (units shipped, ASINs, destination countries) and PLM data, Joe’s team can now generate near-report-ready snapshots with a few clicks.

Filter by date range. Filter by country. Filter by sub-brand — Ring, Kindle, Echo, and more. Export a report that gets you very close to what you need for an EPR submission.

“I’m probably building a new dashboard or report every week,” Joe said, “whether it’s for regulatory reporting, EPR, internal sustainability reports, or our retail partners. There are endless places we need to report.”

The metrics they track now? 

Supplier data turnaround times, quarter-over-quarter increases in post-consumer recycled (PCR) content, material mix across shipped products, and more. These metrics feed directly into Quarterly Business Reviews with suppliers, creating accountability loops that didn’t exist before.

Four Lessons Learned (So Far)

Joe distilled the team’s journey into four key lessons — and they resonate well beyond Amazon Devices:

1. Don’t Get Paralyzed by Perfection. Focus on Progress. The perfect data architecture doesn’t exist on day one. Start, iterate, and improve. The risks of inaction outweigh the risks of imperfect implementation.
2. Align Data Fields for Scalability. Amazon Devices harmonized key data fields — component types, raw material types, taxonomies — across multiple packaging teams within Amazon. That alignment enabled cross-team rollup reporting and made it far easier to map to new regulatory requirements as they emerged.
3. Get User Feedback Early and Often. UAT revealed nuances specific to Amazon Devices’ workflows — shared components used across products, imported part numbers, filtered data loads. Early feedback from internal users shaped a system that actually works for the team using it.
4. Empower a System “Owner.” Whether it’s a dedicated admin or someone who grows into the role like Joe, having a person who owns the system deeply — who understands the validation rules, the workflow logic, the reporting outputs — is essential for long-term success.

The Takeaway

Joe’s final message to the Spec Summit audience was simple and direct:

“Think about what’s really critical. Get in there. Start learning quickly. You’ll be surprised — the benefits come very fast.”

EPR regulations are not slowing down. The companies that will navigate this landscape successfully are the ones investing now in clean, structured, supplier-connected packaging data. Not perfecting a system before they start — but starting, learning, and iterating.

Amazon Devices is proof that even in a complex, global, multi-brand supply chain, it’s possible to go from spreadsheet chaos to regulatory clarity. It just takes a commitment to moving forward.

Want to see how Specright helps brands like Amazon Devices manage packaging data and navigate EPR compliance? Watch the full Spec Summit session here or request a demo.