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Whether you’re fast fashion, luxury or something in between, creating and distributing products to consumers demands robust data management.
Every product has a mountain of information, from design specifications to size measurements and material costs to quality control, that must be carefully maintained.
The real problem, however, comes in managing this data for hundreds, if not thousands, of SKUs every, single season.
It’s a nightmare.
Fortunately, there are tips and solutions that can help you master data management.
While your predecessors may have had the unfortunate task of manually entering product details and double-checking for errors, this burdensome process isn’t mandatory anymore.
Dedicated fashion solutions offer colour, size and fit matrices and wizards that allow you to create and manage items super quick.
It doesn’t matter whether you’re creating individual pieces or entire collections, the whole process can be completed in minutes rather than hours.
This means you can manage t-shirts, jeans, and sweaters – alongside all their associated colour, size, and fit variants – in a nifty matrix view rather than a boring spreadsheet.
It’s *so* much easier to handle.
Every product has its own set of characteristics that make it unique.
That’s cool and all but it’s a pain and a half to manually write these descriptive characteristics up to accompany your product images on eCommerce websites.
(We’re talking hundreds and hundreds of descriptions every season here…)
With the advent of AI though, this process can be automated almost entirely.
AI tools can analyse your images and characteristics to spin up product descriptions in seconds.
That’s right, reading and writing product details endlessly for websites is no more.
Now, we’re getting into the nitty gritty.
The end result of a fashion product is only as good as its materials, meaning your Bill of Materials (BOMs) is paramount to success.
However, most systems weren’t built to accommodate the nuances of fashion. For instance, they only allow BOM creation for a t-shirt, rather than BOMs for each t-shirt variant.
So, this tip is very much concerned with adopting a system that *actually* understands your process.
To give you a flavour of what we’re talking about, here are a few ways these systems support brands:
This might seem a bit obvious but you’d be surprised at just how many brands are unable to run quality control checks periodically throughout the production process.
In most cases, brands *do* want this capability, but their system doesn’t provide it. Oftentimes, quality control can only be run at the end of production.
So again, we recommend brands to adopt systems and processes that allow them to run frequent quality control checks starting at the very beginning.
This means you can test raw materials and fabrics so you don’t accidentally end up producing a bunch of products that are subpar or defective.
Our final tip is less a recommendation in isolation but more so a point that comes into its own when you combine all the previous suggestions together.
When your product data is properly managed, the benefits compound:
These benefits ultimately cascade across your entire organisation.
With all the different product data elements firing in unison, you don’t just solve individual problems, you create a foundation of excellence that’s greater than the sum of its parts.
If you’ve read this article, the chances are you’re having some issues with data management and could well need a new solution.
It probably doesn’t surprise you to know that we can offer exactly that and much, much more.
If you’d like to learn more, we’d be happy to have a chat. Feel free to contact us today.