Data Panda brings your Centric data together with the data from the rest of your brand. From one place, we turn it into dashboards, automations, AI workflows and custom apps your product, sourcing and finance teams use every day.
Centric Software, from Campbell, California and part of the Dassault Systèmes family, builds product lifecycle management software for fashion, retail, footwear, luxury, consumer goods, food and cosmetics brands. Its core product, Centric PLM, is where design, product development and sourcing teams manage styles, tech packs, bills of materials, material libraries, samples, suppliers and target costs, from first sketch to production handoff. Around it sit planning, pricing and visual-board products.
That means PLM holds the half of your product data your ERP never sees: what a style was supposed to cost, how many sample rounds it took, which milestones slipped and which supplier sat on an approval. In a warehouse, that development history lines up against purchase actuals and sell-through, and questions like margin against target or time-to-market per season get answered with data instead of recollection.
The product development KPIs that PLM collects but rarely shows across seasons.
Keep the systems around PLM fed without retyping tech-pack data.
Seasons of development history become a signal for cost and risk.
Views on PLM data for people who never open Centric.
A list of concrete reports, automations and AI features we have built on Centric Software data. Pick the one that matches your situation.
Which styles will miss the season calendar?
Milestone status per style against the season calendar, rolled up per product group and supplier. The style that slipped two milestones surfaces in week three of development, when there is still a supplier call to make, not when the delivery window is already gone.
How far off target cost did we land, and where?
BOM target cost from Centric against the purchase prices actually paid in the ERP, per style, material and supplier. It shows whether the gap comes from one renegotiated fabric or from a season-wide drift that belongs on the next costing meeting's agenda.
Which suppliers cost us the most sample rounds?
Fit and approval iterations per supplier and product type, across seasons. Two extra rounds per style is weeks of calendar and a courier budget; the scorecard makes that a number you can put on the table at the yearly supplier review.
Target cost against actual purchase cost per style, and development spend against the margin a style eventually earned. The costing conversation runs on booked numbers instead of on the tech pack's last saved version.
Merchandising sees adoption rate and sell-through next to development effort: which styles earned their place in the line and which ones consumed a season of sampling to sell two weeks. The next line plan starts from that.
Calendar adherence, supplier lead times and sample rounds in one scorecard. Sourcing decisions and the yearly supplier review run on measured behaviour across seasons, not on the loudest recent incident.
When a style reaches its production milestone in Centric, it lands in Odoo as an item with variants, supplier and cost data attached. Purchase orders start from the tech pack's own numbers, and nobody retypes a BOM into the ERP on a Friday afternoon.
Purchase order lines in NetSuite are matched to the style and BOM they belong to in Centric, so target cost against actual cost is a live report per style, supplier and season. The costing meeting discusses the gap, instead of spending an hour agreeing on what the gap is.
Styles and their development data from Centric are joined to Shopify sales per variant, so merchandising sees development effort and sell-through on the same line. The styles that took three sample rounds and sold out in a week, and the ones that did the opposite, both become visible per season.
Each morning the development channel gets the milestones due this week, the approvals waiting on a name and the styles that slipped, per season. Chasing status moves from walking the floor to reading one message, and the PLM data gets acted on the day it changes.
You keep the reporting tool you already have. We connect it to the warehouse where your Centric Software data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
The core development objects: styles with their specifications, bills of materials, material libraries, samples and their approval history, suppliers, target costs and calendar milestones. They arrive as related tables, so a question that spans objects, like sample rounds per supplier per season, is a join rather than a request to the PLM admin.
Everything from before the item existed in the ERP: target costs per BOM version, sample and approval iterations, milestone history and the suppliers considered rather than chosen. The ERP records what you bought; Centric records how you got there. Margin analysis and supplier reviews need both halves.
We review your Centric Software setup and the systems around it. Together we pick the first thing worth building.