Product Ops

Make product data reliable enough for design, merch, production and ecommerce to move at the same pace.

Product operations is where most growing brands start to feel the drag. Not because the team is weak. Because the business is asking for more than the current tools, spreadsheets and handovers can support.

Design has one version of the product. Production has another. Merchandising is working from a buy file. Ecommerce is waiting for enriched data, imagery, copy, attributes, pricing and launch information. ERP, Shopify and PLM do not quite agree. The critical path exists, but nobody fully trusts it. This is exactly the pattern we see in product data work: fragmented spreadsheets, mismatched PLM, ERP and Shopify data, and product launch processes that are not effective enough for scale.

Commerce Thinking helps fashion, lifestyle and consumer product brands fix the operating model around product data, product development, merchandising and go-to-market readiness.

That might mean PLM, PIM, a merchandise planning tool, or none of those yet.

The point is not to buy another system. The point is to make product operations accurate, governed and usable enough that every downstream team can do their job.

When product ops starts to matter

Most teams come to us when one or more of these things is true:

• Product data lives across PLM, ERP, Shopify, Excel, Airtable, Monday, Miro and people’s heads.
• Design, production, buying, merchandising, wholesale and ecommerce are all asking which information is current.
• Products are late to launch because attributes, imagery, copy, pricing, barcodes, SKUs or supplier data are incomplete.
• Teams are debating PLM, PIM or merchandise planning without a clear view of which problem each system should solve.
• Merchandising is still making buy, allocation, size curve and range decisions in spreadsheets because no planning tool exists yet.
• Ecommerce is the last team to find out that product information has changed.
• The business has implemented a system, but the process around it is still unclear.
• Nobody owns product data governance across the full journey from concept to purchase order.

This work is cross-functional by nature. A product going to market touches design, product development, buying, merchandising, marketing, PR, creative, ecommerce, wholesale, supply chain and fulfilment. If the data, milestones and ownership are not clear, every team downstream loses time.

How we help

We start by mapping the real product journey.

Not the version in the systems diagram. The version your teams actually live with: where data is created, where it is duplicated, where it changes, where spreadsheets still matter, where decisions are made, and where handovers break.

Then we help you decide what needs to change.

The right answer depends on what is creating the drag. It might be a PLM project. It might be PIM. It might be merchandise planning. It might be stabilising the product master before adding another layer. We are careful about sequencing because doing everything at once is usually how brands create more noise, not less. In client work, we have specifically challenged whether a PLM overhaul and merchandise planning implementation should happen in the same year, because planning tools rely on the quality and stability of the underlying product master.

If a system is needed, we support vendor selection, requirements, process design, data model decisions, integration thinking, testing, training and adoption. We sit brand-side, between your internal teams and the vendor or implementation partner, so the project stays connected to the way the business actually works. That means less theatre, fewer generic workshops, and more useful decisions.

We also build the operating rhythm around product data: weekly product data squads, ownership models, task lists, roadmaps, data completeness tracking, governance rules and clear escalation routes. In one project, a PLM implementation evolved into a product data squad covering not just PLM, but issues across NetSuite, Shopify and other connected systems. In another, the team used a red, amber and green tracker to show whether key data was complete for wholesale, purchase orders and launch milestones, with clear owners across merchandising, buying, product development and design.

That is the level product operations needs. Not just fields in a system. Ownership, cadence and consequences.