How AllWhere built a data platform it could trust — without hiring a data team
A fast-growing startup merged two and a half years of siloed data in two weeks, automated its reporting, and gave its supply chain lead his time back — with polyform.
The company
AllWhere is a fast-growing startup that runs a global supply chain: coordinating third-party logistics (3PL), OEM partners like Apple, Dell, and Lenovo, and distribution across the world. Two teams sit at the center of that operation: supply chain, led by Brayden Campbell, and asset management, led by Jadyn. Both run entirely on data: order flow, stock levels, escalation rates, SLA adherence, and the operational health of every vendor.
But for years, that data lived in a raw warehouse that forced every team member to become a part-time data architect just to answer basic questions. Polyform replaced that setup with a structured foundation and an external data team — and did it in weeks, not quarters.
“It was terrifying, quite frankly”
Before Polyform, answering a simple operational question meant fighting the tooling first, and trusting numbers no one could fully verify.
A raw warehouse
QuickSight sitting on raw data, with duplicated, differently-named endpoints. You had to know the entire territory to know whether the information coming out was even sound.
Two datasets, never merged
Order-level and asset-level data lived apart for two and a half years, making it nearly impossible to see when an order was truly complete.
Dashboards by hand, daily
Roughly an hour every morning: extract raw data, run it through spreadsheets, clean it, rebuild the dashboards before anyone could read the health of the operation.
AllWhere operated out of QuickSight on a raw data warehouse. Inexperienced users were forced to extract and manipulate their own data, navigating a warehouse where endpoints could be duplicated and named several different things. Getting a sound answer meant understanding the whole territory first.
That uncertainty landed squarely on Brayden. He had to keep immense oversight of what the team pulled, and usually be the one pulling it himself, just to be sure it was right. His team spent about an hour every morning extracting raw data, running it through spreadsheets, and rebuilding dashboards before they could even see how the operation was performing.
The deepest problem was structural. For two and a half years order-level and asset-level data had never been merged. Because the asset process continues after an order technically closes, AllWhere couldn’t see when an order was truly complete without joining two separate warehouses by hand. The hidden cost wasn’t only time; it was scale. As an early-stage startup building fast on legacy code, the mess compounded and left to their own devices, the team could clean up symptoms but never the structure.
Expertise they couldn’t hire quickly
AllWhere didn’t just need extra hands. It needed expertise it couldn’t build internally fast enough.
Just as important, Polyform showed up as thought leaders by challenging how the team framed a problem rather than only executing tickets.
The merge that changed everything
Rather than hand over features, Polyform rebuilt the foundation, and then taught the team to stand on it.
From spreadsheets to a structured, self-serve model
Not just cleaning the warehouse, but educating the team on how to structure data the right way, then building on top of it.
- ✓Order-level and asset-level data merged for the first time in 2.5 years
- ✓Manual dashboards rebuilt directly into the database
- ✓Auto-created, auto-emailed reports delivered to the team
- ✓A dedicated SLA adherence tab for cleaner, more accurate tracking
The turnaround was immediate. Within the first two weeks, Polyform merged the order and asset datasets that had lived apart for two and a half years, rebuilt the manual spreadsheet dashboards directly into the database, and stood up automated, auto-emailed reports. That single change removed Brayden from the equation faster than he expected.
The relationship is what makes it stick. Brayden can raise an issue and be on a call within 15 to 30 minutes, and complex problems that were not solvable in half an hour, routinely are with. For Jadyn’s asset-management team, the same structure produced a dedicated SLA adherence tab and dashboards that finally made the numbers clear.
“There was data all over the place that wasn’t clear or concise. Polyform built these dashboards for us — we have an entire SLA adherence tab now. They’re always on top of it, always making sure the teams here get what they need.”Jadyn · Asset Management Lead, AllWhere — inventory, stock levels, escalation & SLA adherence
Day and night
Two and a half years of siloed data was merged in two weeks. An hour of manual extraction every morning became automated, auto-emailed reporting. Response times that used to stretch to 72 hours collapsed to a 15-to-30-minute call. Most importantly, Brayden was removed as the bottleneck, his team is now self-serve with confidence and gets on calls with Polyform directly to build what they need next.
What other teams can learn
Making every team member a part-time data architect doesn’t scale. A correctly structured model does.
Order and asset data told the real story only once they were joined — dashboards built on unmerged data hid the truth.
The win wasn’t a dashboard — it was a team that no longer needs its lead in the loop.
A partner who can digest a half-formed problem and return a result keeps leaders out of the weeds.
You get elite data expertise without hiring — and without the legacy mess.