Bamboo Rose Blog | Backbone App

Size Specifications 101

At a Glance:

Initial Concept

Fit Revisions

Grading & Production

Size Spec Formats

Backbone’s Solution

One of the essential components of a complete tech pack for an apparel or accessory product is the size specification.  That being said, size specs can seem almost inscrutable for folks without a background in product development or technical design: they are large, intimidating-looking tables that match jargon-y Points of Measure with multiple sizes, defining specific target numbers for each.  It’s a lot of data to take in at once!

To make sense of the size spec, it’s helpful to examine where it comes into play throughout the development of a new product.

Initial Concept

A new style typically starts with sketches the designer renders to communicate the desired silhouette, style lines and features of the product.  The technical designer then interprets these sketches to lay out an initial size specification for the product, incorporating their tailoring expertise and knowledge about the size and shape of the intended customer.

A brand may have one customer profile, or they may have many – and they develop a point of view on the typical proportions of each.  For example, a brand that is marketed to young American men may conclude that the chest measurement of their typical size medium customer is 40”.  A garment must have a certain amount of ease built in to ensure the wearer is able to move and flex a bit, but the amount of ease varies depending on the design intent.  So if this brand’s designer wants a tailored, slim-fit shirt, the technical designer might set the target for the Chest Circumference Point of Measure at 42”.  If the designer wants a more relaxed silhouette, however, the TD might increase the POM target to 44”.

The initial size spec usually just lists target measurements for each POM in the sample size.  This spec and the design sketches are passed to a patternmaker, who drafts the first pattern to scale (although sometimes the technical designer and the patternmaker are the same person).  A prototype is cut and sewn using the pattern, and then measured.  For each Point of Measure, the technical designer will take note of how closely the product is aligned with the targets.

    Fit Revisions

    Once the sample is measured, it goes to a fitting – a collaborative working session between the product designer, technical designer and/or patternmaker, and a fit model who wears the size the sample was made in.  The fit model puts on the sample, and the group assesses how successfully the sample achieved the design intent.  They then determine what adjustments, if any, should be made for the next sample: adding more ease at the waist? Bringing up the hemline?  Increasing the width of a pocket opening?

    The technical designer will go through the size spec, POM by POM, and detail out revised targets for each.  The patternmaker reviews these callouts to understand what adjustments they must apply to the pattern.  A revised sample is produced with the revised pattern, and this process is repeated until the team is satisfied with the product’s fit. 

      Grading & Production

      At this point, the technical designer will detail out the grade rules – the incremental steps by which each POM target increases/decreases for sizes larger or smaller than the sample size.  The patternmaker can then grade the pattern, and if samples are needed in additional sizes, they can be made – or else the bulk order may go right into production.

      The size spec also plays a role in quality assurance at the end of production.  Typically, QA is performed on a set percentage of the bulk units; they are pulled from the line at random, inspected and measured.  QA technicians will record these measurements in comparison with the production targets so the brand can evaluate the factory’s compliance with specifications.

        Size Spec Formats

        The term size spec may sound like a single object, but generally refers to a set of tables containing interrelated data.  A lot of brands manage their size spec data in Excel spreadsheets, and the key formulas can be written in different ways which require different tables.

        For instance, one technical designer may maintain a table which lists only the grade rules for each POM across each size.  They’ll have a separate table where they enter target measurements for the sample size, and pair these with formulas referencing the grade rules (in the first table) in order to populate the targets for the graded sizes.  Below, you can see an example of this kind of setup.  Note how the formulas in the second tab are written to reference the grade rules in the first tab:

        Another technical designer may do without the grade rule table, and instead write formulas which incorporate the grade rules right into the table where the sample size targets are entered.  Here’s an example of what those formulas might look like:

        Excel is wonderfully flexible, and a savvy user can leverage it to solve a lot of different needs in different ways, but the DIY nature of the tool leads to inconsistencies – plus it’s a bit too easy to break a formula, or to overwrite swaths of data without meaning to.  PLM systems and product development platforms aim to standardize the management of spec data, and reduce the complexity of writing formulas and managing revisions.  These dedicated tools help technical designers keep their proprietary grade data organized, and make it easy to rinse and reuse consistent specs on related products.  And, importantly, PLMs create a system of record where size specs can be scalably managed alongside other product information like merchandising attributes, BOM data, images and more.

          Backbone’s Solution

          Backbone’s size spec hinges on formulas working off of sample size targets and grade rules like any other, but provides numerous format options which allow users to parse the data in different ways.  You can focus on just the sample size, or just the grade rules, or pull these and the graded measurements all into one view depending on what suits you.  You can also incorporate fields for different POM attributes to your preference, adjust your units of measure and seamlessly toggle between fraction and decimal format:

          Backbone provides libraries to store standard POMs and graded POM Blocks, which makes it easy to set and uphold consistent specs across products.  This consistency helps with factory communication and, ultimately, creates trust in your brand since your products will fit more reliably.  You can import core POMs and Blocks into different products seamlessly in Backbone, and in cases where these standards are too rigid, you also have the flexibility to import directly from a CSV, or from another Product Record in the system.

           When it comes time to measure samples, Backbone has built-in formulas with conditional formatting which allow you to quickly evaluate the adherence to spec, and to advise corrective actions.  The sample evaluation toolset also includes a Feedback and Revisions module where you can drop in fit photos, mark them up with comments, and write out more detailed notes on next steps.

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