It’s 9:00 am on a Monday morning, and your new retail collection is about to launch. Meanwhile, the eCommerce Director is refreshing Slack for updates and Product Ops is reconciling two “final_v7” spreadsheets. A marketplace listing is missing size chart updates, the Canadian storefront doesn’t have the right locale images, and you have a last-minute spec change buried somewhere in your email. By mid-afternoon, the campaign is live—but the product listings aren’t clean, and everyone knows returns are coming.
No one on this team is at fault. They’re just outgrowing their system. When spreadsheets, shared drives, and Slack threads become the launch engine, every release turns into a firefight. Your brand hits the launch date, but the cost shows up later in rework, support tickets, and margin erosion. The absence of a repeatable product data operating system is slowing you down and impacting your bottom line.
Does this sound all too familiar? In this article, we’ll break down why this pattern keeps repeating and outline a practical 90-day plan to replace launch chaos with a system you can run again and again.
When product data lives across spreadsheets, commerce platforms, shared drives, and disconnected systems, complexity compounds faster than most teams expect. What begins as a practical workaround gradually turns into an operational constraint, particularly as SKU counts grow, channels multiply, and localization requirements increase.
Online retail return rates commonly sit in the mid-teens, and in categories like apparel they can climb far higher (up to 40%). If a brand processes 200,000 online orders annually and sees even a 20% return rate, that’s 40,000 returns. At an estimated $20 to $30 per return once shipping, handling, restocking, and customer service are factored in, that represents $800,000 to $1.2 million in annual operational costs tied to returns alone. Even a modest reduction in content-driven returns can materially affect margin.
About 22% of those returns trace back to product information issues: mismatched sizing, inconsistent specifications across channels, incomplete imagery, or outdated attributes that slipped through during a rushed launch. In fact, 54% of consumers have returned a product due to misrepresented product information. And when that happens, trust erodes, and customers take their business elsewhere.
Beyond returns, poor data quality carries a broader operational cost. Research from IBM has found that many organizations estimate millions of dollars in annual losses due to poor data quality, with some reporting losses exceeding $5 million. For growing brands, that loss appears as duplicated effort across spreadsheets, manual reconciliation after publishing, repeated corrections across multiple endpoints, and Product Ops teams spending more time fixing than improving.
What presents as “launch pressure” is often a deeper systems issue. As SKU counts grow and channels multiply, spreadsheet-led workflows introduce risk and inefficiency that scale faster than revenue.
As brands scale, product launches become less about coordination and more about control. Why? Because as the volume of SKUs increases, channels multiply, and localization, marketplace rules, and compliance requirements expand, complexity accumulates faster than teams can manage manually. A structured launch operating system brings order to that complexity.
At its core, a structured launch establishes three disciplines:
When these elements are in place, launches shift from reactive coordination to structured execution. Validation catches issues earlier in the process, reducing the volume of downstream fixes and post-publish corrections. Over time, rework declines, version confusion decreases, and teams redirect effort toward enrichment, optimization, and growth initiatives instead of reconciliation.
This is the foundation of the 90-day framework outlined below—a phased approach that helps growing brands introduce structure without a full replatform.
Improvement doesn’t always require a replatform, but it does require introducing structure in manageable stages. The 90-day framework below is designed to help growing brands move from reactive launches to controlled execution without disrupting their existing stack.
Phase 1 (Days 1 to 15): Define Outcomes and Scope
The first two weeks focus on clarity. Teams select three to five measurable outcomes, capture recent baselines, and choose a tightly scoped MVP—one category and one channel. A clear definition of launch readiness is documented, ownership is assigned, and the first publish window is scheduled. The goal here is alignment: one finish line, one owner, and a measurable starting point.
Phase 2 (Days 16 to 45): Establish Validation and Publish Rhythm
Next, the team publishes intentionally and learns from the process. Small SKU batches move through a defined workflow, validation issues are logged, and recurring problems are identified early. With each cycle, friction decreases and confidence increases. Launches begin to follow a rhythm.
Phase 3 (Days 46 to 90): Turn Fixes Into Rules and Scale
In the final phase, repeated errors become governance. Required fields are standardized, validation gates are formalized, and additional channels or locales are introduced using structured templates. What previously required reactive coordination becomes a controlled, repeatable system that supports growth.
This framework creates stability. For some brands, that structure alone meaningfully reduces delays and return-driven rework. For others, it clarifies something more important: the process is sound, but spreadsheets are no longer sufficient infrastructure.
The 90-day framework introduced above can begin creating structure and discipline. For many growing brands, that structure alone reduces delays and unnecessary rework. For others, it clarifies that although the process is sound, spreadsheets are no longer capable of supporting the brand’s scale.
If several of the statements below feel familiar, your team may already be operating at Product Information Management (PIM) scale:
If only one or two apply, running the 90-day plan may be enough to stabilize operations. If three or more apply, governance likely needs to move from documentation into infrastructure.
That is where a PIM platform becomes operationally necessary. A PIM centralizes product information, enforces validation automatically, manages workflow and approvals, and publishes consistently across endpoints without duplication or re-keying.
The 90-day framework introduced above is designed to help you regain control of your launch rhythm, reduce avoidable rework, and create measurable improvement in cycle time and content-driven returns. For many teams, that structure alone creates immediate clarity. For others, it becomes the foundation for a more permanent solution.
If you’re ready to turn launch chaos into a repeatable operating system, download The Product Data Playbook for Growing Brands here. It walks through the full 90-day plan in detail and gives you the tools to run it.
And if you’re already seeing signs that spreadsheets are limiting your scale, book a JasperX demo to see how a structured PIM platform can operationalize the system behind the playbook.